Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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use crate::{
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archetype::{Archetype, ArchetypeComponentId},
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2023-01-11 15:41:54 +00:00
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change_detection::{Ticks, TicksMut},
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2022-11-21 12:59:09 +00:00
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component::{Component, ComponentId, ComponentStorage, ComponentTicks, StorageType, Tick},
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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|
|
entity::Entity,
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Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
|
|
|
query::{Access, DebugCheckedUnwrap, FilteredAccess},
|
2022-12-06 01:38:21 +00:00
|
|
|
storage::{ComponentSparseSet, Table, TableRow},
|
2023-01-11 15:41:54 +00:00
|
|
|
world::{Mut, Ref, World},
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
};
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
pub use bevy_ecs_macros::WorldQuery;
|
2022-05-04 19:16:10 +00:00
|
|
|
use bevy_ptr::{ThinSlicePtr, UnsafeCellDeref};
|
2023-02-16 17:09:44 +00:00
|
|
|
use bevy_utils::all_tuples;
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
use std::{cell::UnsafeCell, marker::PhantomData};
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-09-02 12:35:24 +00:00
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/// Types that can be fetched from a [`World`] using a [`Query`].
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///
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/// There are many types that natively implement this trait:
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///
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/// - **Component references.**
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/// Fetches a component by reference (immutably or mutably).
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/// - **`WorldQuery` tuples.**
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/// If every element of a tuple implements `WorldQuery`, then the tuple itself also implements the same trait.
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/// This enables a single `Query` to access multiple components and filter over multiple conditions.
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/// Due to the current lack of variadic generics in Rust, the trait has been implemented for tuples from 0 to 15 elements,
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/// but nesting of tuples allows infinite `WorldQuery`s.
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/// - **Component filters.**
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/// [`With`] and [`Without`] filters can be applied to check if the queried entity contains or not a particular component.
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/// - **Change detection filters.**
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/// [`Added`] and [`Changed`] filters can be applied to detect component changes to an entity.
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/// - **Filter disjunction operator.**
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/// By default, tuples compose query filters in such a way that all conditions must be satisfied to generate a query item for a given entity.
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/// Wrapping a tuple inside an [`Or`] operator will relax the requirement to just one condition.
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/// - **[`Entity`].**
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/// Gets the identifier of the queried entity.
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/// - **[`Option`].**
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/// By default, a world query only tests entities that have the matching component types.
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/// Wrapping it into an `Option` will increase the query search space, and it will return `None` if an entity doesn't satisfy the `WorldQuery`.
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/// - **[`AnyOf`].**
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/// Equivalent to wrapping each world query inside it into an `Option`.
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/// - **[`ChangeTrackers`].**
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/// Similar to change detection filters but it is used as a query fetch parameter.
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/// It exposes methods to check for changes to the wrapped component.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
|
|
|
/// Implementing the trait manually can allow for a fundamentally new type of behaviour.
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// # Trait derivation
|
|
|
|
///
|
|
|
|
/// Query design can be easily structured by deriving `WorldQuery` for custom types.
|
|
|
|
/// Despite the added complexity, this approach has several advantages over using `WorldQuery` tuples.
|
|
|
|
/// The most relevant improvements are:
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// - Reusability across multiple systems.
|
|
|
|
/// - There is no need to destructure a tuple since all fields are named.
|
|
|
|
/// - Subqueries can be composed together to create a more complex query.
|
|
|
|
/// - Methods can be implemented for the query items.
|
|
|
|
/// - There is no hardcoded limit on the number of elements.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
2022-11-01 03:15:34 +00:00
|
|
|
/// This trait can only be derived if each field either
|
|
|
|
///
|
|
|
|
/// * also implements `WorldQuery`, or
|
|
|
|
/// * is marked with `#[world_query(ignore)]`. Fields decorated with this attribute
|
|
|
|
/// must implement [`Default`] and will be initialized to the default value as defined
|
|
|
|
/// by the trait.
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// The derive macro only supports regular structs (structs with named fields).
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
|
|
|
/// ```
|
|
|
|
/// # use bevy_ecs::prelude::*;
|
|
|
|
/// use bevy_ecs::query::WorldQuery;
|
2022-09-02 12:35:24 +00:00
|
|
|
/// #
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentA;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentB;
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
|
|
|
/// #[derive(WorldQuery)]
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
/// struct MyQuery {
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// entity: Entity,
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // It is required that all reference lifetimes are explicitly annotated, just like in any
|
|
|
|
/// // struct. Each lifetime should be 'static.
|
|
|
|
/// component_a: &'static ComponentA,
|
|
|
|
/// component_b: &'static ComponentB,
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
///
|
|
|
|
/// fn my_system(query: Query<MyQuery>) {
|
2022-07-11 15:28:50 +00:00
|
|
|
/// for q in &query {
|
2022-09-02 12:35:24 +00:00
|
|
|
/// q.component_a;
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
/// }
|
|
|
|
/// # bevy_ecs::system::assert_is_system(my_system);
|
|
|
|
/// ```
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// ## Macro expansion
|
|
|
|
///
|
|
|
|
/// Expanding the macro will declare three or six additional structs, depending on whether or not the struct is marked as mutable.
|
|
|
|
/// For a struct named `X`, the additional structs will be:
|
|
|
|
///
|
|
|
|
/// |Struct name|`mutable` only|Description|
|
|
|
|
/// |:---:|:---:|---|
|
|
|
|
/// |`XState`|---|Used as the [`State`] type for `X` and `XReadOnly`|
|
|
|
|
/// |`XItem`|---|The type of the query item for `X`|
|
|
|
|
/// |`XFetch`|---|Used as the [`Fetch`] type for `X`|
|
|
|
|
/// |`XReadOnlyItem`|✓|The type of the query item for `XReadOnly`|
|
|
|
|
/// |`XReadOnlyFetch`|✓|Used as the [`Fetch`] type for `XReadOnly`|
|
|
|
|
/// |`XReadOnly`|✓|[`ReadOnly`] variant of `X`|
|
|
|
|
///
|
|
|
|
/// ## Adding mutable references
|
|
|
|
///
|
|
|
|
/// Simply adding mutable references to a derived `WorldQuery` will result in a compilation error:
|
|
|
|
///
|
|
|
|
/// ```compile_fail
|
|
|
|
/// # use bevy_ecs::prelude::*;
|
|
|
|
/// # use bevy_ecs::query::WorldQuery;
|
|
|
|
/// #
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentA;
|
|
|
|
/// #
|
|
|
|
/// #[derive(WorldQuery)]
|
|
|
|
/// struct CustomQuery {
|
|
|
|
/// component_a: &'static mut ComponentA,
|
|
|
|
/// }
|
|
|
|
/// ```
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// To grant mutable access to components, the struct must be marked with the `#[world_query(mutable)]` attribute.
|
|
|
|
/// This will also create three more structs that will be used for accessing the query immutably (see table above).
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
|
|
|
/// ```
|
|
|
|
/// # use bevy_ecs::prelude::*;
|
2022-09-02 12:35:24 +00:00
|
|
|
/// # use bevy_ecs::query::WorldQuery;
|
|
|
|
/// #
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentA;
|
|
|
|
/// #
|
|
|
|
/// #[derive(WorldQuery)]
|
|
|
|
/// #[world_query(mutable)]
|
|
|
|
/// struct CustomQuery {
|
|
|
|
/// component_a: &'static mut ComponentA,
|
|
|
|
/// }
|
|
|
|
/// ```
|
|
|
|
///
|
|
|
|
/// ## Adding methods to query items
|
|
|
|
///
|
|
|
|
/// It is possible to add methods to query items in order to write reusable logic about related components.
|
|
|
|
/// This will often make systems more readable because low level logic is moved out from them.
|
|
|
|
/// It is done by adding `impl` blocks with methods for the `-Item` or `-ReadOnlyItem` generated structs.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// ```
|
|
|
|
/// # use bevy_ecs::prelude::*;
|
|
|
|
/// # use bevy_ecs::query::WorldQuery;
|
|
|
|
/// #
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// #[derive(Component)]
|
|
|
|
/// struct Health(f32);
|
2022-09-02 12:35:24 +00:00
|
|
|
///
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// #[derive(Component)]
|
|
|
|
/// struct Buff(f32);
|
|
|
|
///
|
|
|
|
/// #[derive(WorldQuery)]
|
|
|
|
/// #[world_query(mutable)]
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
/// struct HealthQuery {
|
|
|
|
/// health: &'static mut Health,
|
|
|
|
/// buff: Option<&'static mut Buff>,
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // `HealthQueryItem` is only available when accessing the query with mutable methods.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// impl<'w> HealthQueryItem<'w> {
|
|
|
|
/// fn damage(&mut self, value: f32) {
|
|
|
|
/// self.health.0 -= value;
|
|
|
|
/// }
|
|
|
|
///
|
|
|
|
/// fn total(&self) -> f32 {
|
|
|
|
/// self.health.0 + self.buff.as_deref().map_or(0.0, |Buff(buff)| *buff)
|
|
|
|
/// }
|
|
|
|
/// }
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // `HealthQueryReadOnlyItem` is only available when accessing the query with immutable methods.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// impl<'w> HealthQueryReadOnlyItem<'w> {
|
|
|
|
/// fn total(&self) -> f32 {
|
|
|
|
/// self.health.0 + self.buff.map_or(0.0, |Buff(buff)| *buff)
|
|
|
|
/// }
|
|
|
|
/// }
|
|
|
|
///
|
|
|
|
/// fn my_system(mut health_query: Query<HealthQuery>) {
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // The item returned by the iterator is of type `HealthQueryReadOnlyItem`.
|
|
|
|
/// for health in health_query.iter() {
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// println!("Total: {}", health.total());
|
|
|
|
/// }
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // The item returned by the iterator is of type `HealthQueryItem`.
|
2022-07-11 15:28:50 +00:00
|
|
|
/// for mut health in &mut health_query {
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// health.damage(1.0);
|
|
|
|
/// println!("Total (mut): {}", health.total());
|
|
|
|
/// }
|
|
|
|
/// }
|
|
|
|
/// # bevy_ecs::system::assert_is_system(my_system);
|
|
|
|
/// ```
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// ## Deriving traits for query items
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// The `WorldQuery` derive macro does not automatically implement the traits of the struct to the query item types.
|
|
|
|
/// Something similar can be done by using the `#[world_query(derive(...))]` attribute.
|
|
|
|
/// This will apply the listed derivable traits to the query item structs.
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
///
|
|
|
|
/// ```
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// # use bevy_ecs::prelude::*;
|
2022-09-02 12:35:24 +00:00
|
|
|
/// # use bevy_ecs::query::WorldQuery;
|
|
|
|
/// #
|
|
|
|
/// # #[derive(Component, Debug)]
|
|
|
|
/// # struct ComponentA;
|
|
|
|
/// #
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// #[derive(WorldQuery)]
|
|
|
|
/// #[world_query(mutable, derive(Debug))]
|
2022-09-02 12:35:24 +00:00
|
|
|
/// struct CustomQuery {
|
|
|
|
/// component_a: &'static ComponentA,
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // This function statically checks that `T` implements `Debug`.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// fn assert_debug<T: std::fmt::Debug>() {}
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// assert_debug::<CustomQueryItem>();
|
|
|
|
/// assert_debug::<CustomQueryReadOnlyItem>();
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// ```
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// ## Query composition
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// It is possible to use any `WorldQuery` as a field of another one.
|
|
|
|
/// This means that a `WorldQuery` can also be used as a subquery, potentially in multiple places.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
|
|
|
/// ```
|
|
|
|
/// # use bevy_ecs::prelude::*;
|
2022-09-02 12:35:24 +00:00
|
|
|
/// # use bevy_ecs::query::WorldQuery;
|
|
|
|
/// #
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentA;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentB;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentC;
|
|
|
|
/// #
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// #[derive(WorldQuery)]
|
2022-09-02 12:35:24 +00:00
|
|
|
/// struct SubQuery {
|
|
|
|
/// component_a: &'static ComponentA,
|
|
|
|
/// component_b: &'static ComponentB,
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
///
|
|
|
|
/// #[derive(WorldQuery)]
|
2022-09-02 12:35:24 +00:00
|
|
|
/// struct MyQuery {
|
|
|
|
/// subquery: SubQuery,
|
|
|
|
/// component_c: &'static ComponentC,
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
/// ```
|
|
|
|
///
|
|
|
|
/// ## Filters
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// Since the query filter type parameter is `WorldQuery`, it is also possible to use this macro to create filters.
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
///
|
|
|
|
/// ```
|
|
|
|
/// # use bevy_ecs::prelude::*;
|
2022-09-02 12:35:24 +00:00
|
|
|
/// # use bevy_ecs::{query::WorldQuery, component::Component};
|
|
|
|
/// #
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentA;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentB;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentC;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentD;
|
|
|
|
/// # #[derive(Component)]
|
|
|
|
/// # struct ComponentE;
|
|
|
|
/// #
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// #[derive(WorldQuery)]
|
|
|
|
/// struct MyFilter<T: Component, P: Component> {
|
2022-09-02 12:35:24 +00:00
|
|
|
/// // Field names are not relevant, since they are never manually accessed.
|
|
|
|
/// with_a: With<ComponentA>,
|
|
|
|
/// or_filter: Or<(With<ComponentC>, Added<ComponentB>)>,
|
|
|
|
/// generic_tuple: (With<T>, Without<P>),
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
///
|
2022-09-02 12:35:24 +00:00
|
|
|
/// fn my_system(query: Query<Entity, MyFilter<ComponentD, ComponentE>>) {
|
|
|
|
/// // ...
|
Implement `WorldQuery` derive macro (#2713)
# Objective
- Closes #786
- Closes #2252
- Closes #2588
This PR implements a derive macro that allows users to define their queries as structs with named fields.
## Example
```rust
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct NumQuery<'w, T: Component, P: Component> {
entity: Entity,
u: UNumQuery<'w>,
generic: GenericQuery<'w, T, P>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct UNumQuery<'w> {
u_16: &'w u16,
u_32_opt: Option<&'w u32>,
}
#[derive(WorldQuery)]
#[world_query(derive(Debug))]
struct GenericQuery<'w, T: Component, P: Component> {
generic: (&'w T, &'w P),
}
#[derive(WorldQuery)]
#[world_query(filter)]
struct NumQueryFilter<T: Component, P: Component> {
_u_16: With<u16>,
_u_32: With<u32>,
_or: Or<(With<i16>, Changed<u16>, Added<u32>)>,
_generic_tuple: (With<T>, With<P>),
_without: Without<Option<u16>>,
_tp: PhantomData<(T, P)>,
}
fn print_nums_readonly(query: Query<NumQuery<u64, i64>, NumQueryFilter<u64, i64>>) {
for num in query.iter() {
println!("{:#?}", num);
}
}
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct MutNumQuery<'w, T: Component, P: Component> {
i_16: &'w mut i16,
i_32_opt: Option<&'w mut i32>,
}
fn print_nums(mut query: Query<MutNumQuery, NumQueryFilter<u64, i64>>) {
for num in query.iter_mut() {
println!("{:#?}", num);
}
}
```
## TODOs:
- [x] Add support for `&T` and `&mut T`
- [x] Test
- [x] Add support for optional types
- [x] Test
- [x] Add support for `Entity`
- [x] Test
- [x] Add support for nested `WorldQuery`
- [x] Test
- [x] Add support for tuples
- [x] Test
- [x] Add support for generics
- [x] Test
- [x] Add support for query filters
- [x] Test
- [x] Add support for `PhantomData`
- [x] Test
- [x] Refactor `read_world_query_field_type_info`
- [x] Properly document `readonly` attribute for nested queries and the static assertions that guarantee safety
- [x] Test that we never implement `ReadOnlyFetch` for types that need mutable access
- [x] Test that we insert static assertions for nested `WorldQuery` that a user marked as readonly
2022-02-24 00:19:49 +00:00
|
|
|
/// }
|
|
|
|
/// # bevy_ecs::system::assert_is_system(my_system);
|
|
|
|
/// ```
|
2022-09-02 12:35:24 +00:00
|
|
|
///
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
/// # Safety
|
|
|
|
///
|
2022-11-03 16:33:05 +00:00
|
|
|
/// Component access of `Self::ReadOnly` must be a subset of `Self`
|
|
|
|
/// and `Self::ReadOnly` must match exactly the same archetypes/tables as `Self`
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
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///
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2022-09-02 12:35:24 +00:00
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/// Implementor must ensure that
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/// [`update_component_access`] and [`update_archetype_component_access`]
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/// exactly reflects the results of the following methods:
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///
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/// - [`matches_component_set`]
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2022-10-28 09:25:50 +00:00
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/// - [`fetch`]
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2022-09-02 12:35:24 +00:00
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///
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/// [`Added`]: crate::query::Added
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2022-10-28 09:25:50 +00:00
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/// [`fetch`]: Self::fetch
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2022-09-02 12:35:24 +00:00
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/// [`Changed`]: crate::query::Changed
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2022-11-03 16:33:05 +00:00
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/// [`Fetch`]: crate::query::WorldQuery::Fetch
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2022-09-02 12:35:24 +00:00
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/// [`matches_component_set`]: Self::matches_component_set
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/// [`Or`]: crate::query::Or
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/// [`Query`]: crate::system::Query
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/// [`ReadOnly`]: Self::ReadOnly
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/// [`State`]: Self::State
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/// [`update_archetype_component_access`]: Self::update_archetype_component_access
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/// [`update_component_access`]: Self::update_component_access
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/// [`With`]: crate::query::With
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/// [`Without`]: crate::query::Without
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2022-11-03 16:33:05 +00:00
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pub unsafe trait WorldQuery {
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/// The item returned by this [`WorldQuery`]
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type Item<'a>;
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/// Per archetype/table state used by this [`WorldQuery`] to fetch [`Self::Item`](crate::query::WorldQuery::Item)
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type Fetch<'a>;
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2022-08-04 21:51:02 +00:00
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/// The read-only variant of this [`WorldQuery`], which satisfies the [`ReadOnlyWorldQuery`] trait.
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type ReadOnly: ReadOnlyWorldQuery<State = Self::State>;
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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/// State used to construct a [`Self::Fetch`](crate::query::WorldQuery::Fetch). This will be cached inside [`QueryState`](crate::query::QueryState),
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/// so it is best to move as much data / computation here as possible to reduce the cost of
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/// constructing [`Self::Fetch`](crate::query::WorldQuery::Fetch).
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type State: Send + Sync + Sized;
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Modular Rendering (#2831)
This changes how render logic is composed to make it much more modular. Previously, all extraction logic was centralized for a given "type" of rendered thing. For example, we extracted meshes into a vector of ExtractedMesh, which contained the mesh and material asset handles, the transform, etc. We looked up bindings for "drawn things" using their index in the `Vec<ExtractedMesh>`. This worked fine for built in rendering, but made it hard to reuse logic for "custom" rendering. It also prevented us from reusing things like "extracted transforms" across contexts.
To make rendering more modular, I made a number of changes:
* Entities now drive rendering:
* We extract "render components" from "app components" and store them _on_ entities. No more centralized uber lists! We now have true "ECS-driven rendering"
* To make this perform well, I implemented #2673 in upstream Bevy for fast batch insertions into specific entities. This was merged into the `pipelined-rendering` branch here: #2815
* Reworked the `Draw` abstraction:
* Generic `PhaseItems`: each draw phase can define its own type of "rendered thing", which can define its own "sort key"
* Ported the 2d, 3d, and shadow phases to the new PhaseItem impl (currently Transparent2d, Transparent3d, and Shadow PhaseItems)
* `Draw` trait and and `DrawFunctions` are now generic on PhaseItem
* Modular / Ergonomic `DrawFunctions` via `RenderCommands`
* RenderCommand is a trait that runs an ECS query and produces one or more RenderPass calls. Types implementing this trait can be composed to create a final DrawFunction. For example the DrawPbr DrawFunction is created from the following DrawCommand tuple. Const generics are used to set specific bind group locations:
```rust
pub type DrawPbr = (
SetPbrPipeline,
SetMeshViewBindGroup<0>,
SetStandardMaterialBindGroup<1>,
SetTransformBindGroup<2>,
DrawMesh,
);
```
* The new `custom_shader_pipelined` example illustrates how the commands above can be reused to create a custom draw function:
```rust
type DrawCustom = (
SetCustomMaterialPipeline,
SetMeshViewBindGroup<0>,
SetTransformBindGroup<2>,
DrawMesh,
);
```
* ExtractComponentPlugin and UniformComponentPlugin:
* Simple, standardized ways to easily extract individual components and write them to GPU buffers
* Ported PBR and Sprite rendering to the new primitives above.
* Removed staging buffer from UniformVec in favor of direct Queue usage
* Makes UniformVec much easier to use and more ergonomic. Completely removes the need for custom render graph nodes in these contexts (see the PbrNode and view Node removals and the much simpler call patterns in the relevant Prepare systems).
* Added a many_cubes_pipelined example to benchmark baseline 3d rendering performance and ensure there were no major regressions during this port. Avoiding regressions was challenging given that the old approach of extracting into centralized vectors is basically the "optimal" approach. However thanks to a various ECS optimizations and render logic rephrasing, we pretty much break even on this benchmark!
* Lifetimeless SystemParams: this will be a bit divisive, but as we continue to embrace "trait driven systems" (ex: ExtractComponentPlugin, UniformComponentPlugin, DrawCommand), the ergonomics of `(Query<'static, 'static, (&'static A, &'static B, &'static)>, Res<'static, C>)` were getting very hard to bear. As a compromise, I added "static type aliases" for the relevant SystemParams. The previous example can now be expressed like this: `(SQuery<(Read<A>, Read<B>)>, SRes<C>)`. If anyone has better ideas / conflicting opinions, please let me know!
* RunSystem trait: a way to define Systems via a trait with a SystemParam associated type. This is used to implement the various plugins mentioned above. I also added SystemParamItem and QueryItem type aliases to make "trait stye" ecs interactions nicer on the eyes (and fingers).
* RenderAsset retrying: ensures that render assets are only created when they are "ready" and allows us to create bind groups directly inside render assets (which significantly simplified the StandardMaterial code). I think ultimately we should swap this out on "asset dependency" events to wait for dependencies to load, but this will require significant asset system changes.
* Updated some built in shaders to account for missing MeshUniform fields
2021-09-23 06:16:11 +00:00
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2022-08-04 21:51:02 +00:00
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/// This function manually implements subtyping for the query items.
|
2022-11-03 16:33:05 +00:00
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fn shrink<'wlong: 'wshort, 'wshort>(item: Self::Item<'wlong>) -> Self::Item<'wshort>;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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/// Creates a new instance of this fetch.
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2021-03-11 00:27:30 +00:00
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///
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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/// # Safety
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2021-04-22 19:09:09 +00:00
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///
|
2022-08-04 21:51:02 +00:00
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/// `state` must have been initialized (via [`WorldQuery::init_state`]) using the same `world` passed
|
2022-01-06 00:43:37 +00:00
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/// in to this function.
|
2022-08-04 21:51:02 +00:00
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unsafe fn init_fetch<'w>(
|
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world: &'w World,
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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state: &Self::State,
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last_change_tick: u32,
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change_tick: u32,
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2022-11-03 16:33:05 +00:00
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) -> Self::Fetch<'w>;
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-10-26 13:16:25 +00:00
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/// While this function can be called for any query, it is always safe to call if `Self: ReadOnlyWorldQuery` holds.
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///
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/// # Safety
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/// While calling this method on its own cannot cause UB it is marked `unsafe` as the caller must ensure
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/// that the returned value is not used in any way that would cause two `QueryItem<Self>` for the same
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2022-12-06 01:38:21 +00:00
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/// `archetype_row` or `table_row` to be alive at the same time.
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2022-11-03 16:33:05 +00:00
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unsafe fn clone_fetch<'w>(fetch: &Self::Fetch<'w>) -> Self::Fetch<'w>;
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2022-10-26 13:16:25 +00:00
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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/// Returns true if (and only if) every table of every archetype matched by this fetch contains
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2021-03-11 00:27:30 +00:00
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/// all of the matched components. This is used to select a more efficient "table iterator"
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2022-10-28 09:25:50 +00:00
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/// for "dense" queries. If this returns true, [`WorldQuery::set_table`] must be used before
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/// [`WorldQuery::fetch`] can be called for iterators. If this returns false,
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/// [`WorldQuery::set_archetype`] must be used before [`WorldQuery::fetch`] can be called for
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/// iterators.
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2021-10-03 19:23:44 +00:00
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const IS_DENSE: bool;
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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/// Returns true if (and only if) this Fetch relies strictly on archetypes to limit which
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/// components are accessed by the Query.
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///
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/// This enables optimizations for [`crate::query::QueryIter`] that rely on knowing exactly how
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/// many elements are being iterated (such as `Iterator::collect()`).
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const IS_ARCHETYPAL: bool;
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/// Adjusts internal state to account for the next [`Archetype`]. This will always be called on
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/// archetypes that match this [`WorldQuery`].
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///
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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/// # Safety
|
2021-04-22 19:09:09 +00:00
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///
|
2022-08-04 21:51:02 +00:00
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/// `archetype` and `tables` must be from the [`World`] [`WorldQuery::init_state`] was called on. `state` must
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
/// be the [`Self::State`] this was initialized with.
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe fn set_archetype<'w>(
|
2022-11-03 16:33:05 +00:00
|
|
|
fetch: &mut Self::Fetch<'w>,
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
state: &Self::State,
|
2022-08-04 21:51:02 +00:00
|
|
|
archetype: &'w Archetype,
|
2022-10-28 09:25:50 +00:00
|
|
|
table: &'w Table,
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2021-04-22 19:09:09 +00:00
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/// Adjusts internal state to account for the next [`Table`]. This will always be called on tables
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2022-08-04 21:51:02 +00:00
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/// that match this [`WorldQuery`].
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///
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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/// # Safety
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2021-04-22 19:09:09 +00:00
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///
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2022-08-04 21:51:02 +00:00
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/// `table` must be from the [`World`] [`WorldQuery::init_state`] was called on. `state` must be the
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2022-01-06 00:43:37 +00:00
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/// [`Self::State`] this was initialized with.
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2022-11-03 16:33:05 +00:00
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unsafe fn set_table<'w>(fetch: &mut Self::Fetch<'w>, state: &Self::State, table: &'w Table);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
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|
2022-11-03 16:33:05 +00:00
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/// Fetch [`Self::Item`](`WorldQuery::Item`) for either the given `entity` in the current [`Table`],
|
2022-10-28 09:25:50 +00:00
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|
/// or for the given `entity` in the current [`Archetype`]. This must always be called after
|
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/// [`WorldQuery::set_table`] with a `table_row` in the range of the current [`Table`] or after
|
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/// [`WorldQuery::set_archetype`] with a `entity` in the current archetype.
|
2021-03-11 00:27:30 +00:00
|
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///
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
/// # Safety
|
2021-04-22 19:09:09 +00:00
|
|
|
///
|
2022-10-28 09:25:50 +00:00
|
|
|
/// Must always be called _after_ [`WorldQuery::set_table`] or [`WorldQuery::set_archetype`]. `entity` and
|
|
|
|
/// `table_row` must be in the range of the current table and archetype.
|
|
|
|
unsafe fn fetch<'w>(
|
2022-11-03 16:33:05 +00:00
|
|
|
fetch: &mut Self::Fetch<'w>,
|
2022-10-28 09:25:50 +00:00
|
|
|
entity: Entity,
|
2022-12-06 01:38:21 +00:00
|
|
|
table_row: TableRow,
|
2022-11-03 16:33:05 +00:00
|
|
|
) -> Self::Item<'w>;
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
|
|
|
|
/// # Safety
|
|
|
|
///
|
2022-10-28 09:25:50 +00:00
|
|
|
/// Must always be called _after_ [`WorldQuery::set_table`] or [`WorldQuery::set_archetype`]. `entity` and
|
|
|
|
/// `table_row` must be in the range of the current table and archetype.
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
#[allow(unused_variables)]
|
2022-10-28 09:25:50 +00:00
|
|
|
#[inline(always)]
|
2022-12-06 01:38:21 +00:00
|
|
|
unsafe fn filter_fetch(
|
|
|
|
fetch: &mut Self::Fetch<'_>,
|
|
|
|
entity: Entity,
|
|
|
|
table_row: TableRow,
|
|
|
|
) -> bool {
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
true
|
|
|
|
}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
|
|
|
// This does not have a default body of `{}` because 99% of cases need to add accesses
|
|
|
|
// and forgetting to do so would be unsound.
|
|
|
|
fn update_component_access(state: &Self::State, access: &mut FilteredAccess<ComponentId>);
|
2023-01-06 00:43:30 +00:00
|
|
|
// This does not have a default body of `{}` because 99% of cases need to add accesses
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
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// and forgetting to do so would be unsound.
|
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fn update_archetype_component_access(
|
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state: &Self::State,
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archetype: &Archetype,
|
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access: &mut Access<ArchetypeComponentId>,
|
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);
|
2022-08-04 21:51:02 +00:00
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fn init_state(world: &mut World) -> Self::State;
|
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fn matches_component_set(
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state: &Self::State,
|
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set_contains_id: &impl Fn(ComponentId) -> bool,
|
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) -> bool;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-08-04 21:51:02 +00:00
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/// A world query that is read only.
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///
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/// # Safety
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///
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/// This must only be implemented for read-only [`WorldQuery`]'s.
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pub unsafe trait ReadOnlyWorldQuery: WorldQuery<ReadOnly = Self> {}
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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2022-08-04 21:51:02 +00:00
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/// The `Fetch` of a [`WorldQuery`], which is used to store state for each archetype/table.
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2022-11-03 16:33:05 +00:00
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pub type QueryFetch<'w, Q> = <Q as WorldQuery>::Fetch<'w>;
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2022-08-04 21:51:02 +00:00
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/// The item type returned when a [`WorldQuery`] is iterated over
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2022-11-03 16:33:05 +00:00
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pub type QueryItem<'w, Q> = <Q as WorldQuery>::Item<'w>;
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2022-08-04 21:51:02 +00:00
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/// The read-only `Fetch` of a [`WorldQuery`], which is used to store state for each archetype/table.
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pub type ROQueryFetch<'w, Q> = QueryFetch<'w, <Q as WorldQuery>::ReadOnly>;
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/// The read-only variant of the item type returned when a [`WorldQuery`] is iterated over immutably
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pub type ROQueryItem<'w, Q> = QueryItem<'w, <Q as WorldQuery>::ReadOnly>;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-08-04 21:51:02 +00:00
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/// SAFETY: no component or archetype access
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unsafe impl WorldQuery for Entity {
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2022-11-03 16:33:05 +00:00
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type Fetch<'w> = ();
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type Item<'w> = Entity;
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2022-08-04 21:51:02 +00:00
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type ReadOnly = Self;
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type State = ();
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2021-10-03 19:23:44 +00:00
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const IS_DENSE: bool = true;
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-04-27 18:02:06 +00:00
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const IS_ARCHETYPAL: bool = true;
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2022-08-04 21:51:02 +00:00
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unsafe fn init_fetch<'w>(
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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_world: &'w World,
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2022-10-28 09:25:50 +00:00
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_state: &Self::State,
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Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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_last_change_tick: u32,
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_change_tick: u32,
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2022-11-03 16:33:05 +00:00
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) -> Self::Fetch<'w> {
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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#[inline]
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2022-08-04 21:51:02 +00:00
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unsafe fn set_archetype<'w>(
|
2022-11-03 16:33:05 +00:00
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_fetch: &mut Self::Fetch<'w>,
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2022-10-28 09:25:50 +00:00
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_state: &Self::State,
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_archetype: &'w Archetype,
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_table: &Table,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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unsafe fn set_table<'w>(_fetch: &mut Self::Fetch<'w>, _state: &Self::State, _table: &'w Table) {
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
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|
fn update_component_access(_state: &Self::State, _access: &mut FilteredAccess<ComponentId>) {}
|
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|
fn update_archetype_component_access(
|
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|
_state: &Self::State,
|
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|
_archetype: &Archetype,
|
|
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|
_access: &mut Access<ArchetypeComponentId>,
|
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) {
|
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}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
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|
2022-08-04 21:51:02 +00:00
|
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|
fn init_state(_world: &mut World) {}
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn matches_component_set(
|
|
|
|
_state: &Self::State,
|
|
|
|
_set_contains_id: &impl Fn(ComponentId) -> bool,
|
|
|
|
) -> bool {
|
|
|
|
true
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-08-04 21:51:02 +00:00
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/// SAFETY: access is read only
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unsafe impl ReadOnlyWorldQuery for Entity {}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-03-21 05:23:36 +00:00
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#[doc(hidden)]
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
pub struct ReadFetch<'w, T> {
|
|
|
|
// T::Storage = TableStorage
|
|
|
|
table_components: Option<ThinSlicePtr<'w, UnsafeCell<T>>>,
|
|
|
|
// T::Storage = SparseStorage
|
|
|
|
sparse_set: Option<&'w ComponentSparseSet>,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
}
|
|
|
|
|
2022-11-03 16:33:05 +00:00
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|
/// SAFETY: `Self` is the same as `Self::ReadOnly`
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe impl<T: Component> WorldQuery for &T {
|
2022-11-03 16:33:05 +00:00
|
|
|
type Fetch<'w> = ReadFetch<'w, T>;
|
|
|
|
type Item<'w> = &'w T;
|
2022-08-04 21:51:02 +00:00
|
|
|
type ReadOnly = Self;
|
|
|
|
type State = ComponentId;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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const IS_DENSE: bool = {
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match T::Storage::STORAGE_TYPE {
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
StorageType::Table => true,
|
|
|
|
StorageType::SparseSet => false,
|
|
|
|
}
|
2021-10-03 19:23:44 +00:00
|
|
|
};
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-04-27 18:02:06 +00:00
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const IS_ARCHETYPAL: bool = true;
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2022-08-04 21:51:02 +00:00
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unsafe fn init_fetch<'w>(
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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world: &'w World,
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2022-08-04 21:51:02 +00:00
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&component_id: &ComponentId,
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Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
|
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_last_change_tick: u32,
|
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_change_tick: u32,
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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) -> ReadFetch<'w, T> {
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ReadFetch {
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table_components: None,
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2022-10-28 09:25:50 +00:00
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sparse_set: (T::Storage::STORAGE_TYPE == StorageType::SparseSet).then(|| {
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world
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.storages()
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.sparse_sets
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.get(component_id)
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Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
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.debug_checked_unwrap()
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2022-10-28 09:25:50 +00:00
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}),
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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2022-11-03 16:33:05 +00:00
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unsafe fn clone_fetch<'w>(fetch: &Self::Fetch<'w>) -> Self::Fetch<'w> {
|
2022-10-26 13:16:25 +00:00
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ReadFetch {
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table_components: fetch.table_components,
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sparse_set: fetch.sparse_set,
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}
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
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#[inline]
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe fn set_archetype<'w>(
|
|
|
|
fetch: &mut ReadFetch<'w, T>,
|
2022-10-28 09:25:50 +00:00
|
|
|
component_id: &ComponentId,
|
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_archetype: &'w Archetype,
|
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table: &'w Table,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
) {
|
2022-10-28 09:25:50 +00:00
|
|
|
if Self::IS_DENSE {
|
|
|
|
Self::set_table(fetch, component_id, table);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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#[inline]
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2022-10-28 09:25:50 +00:00
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unsafe fn set_table<'w>(
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fetch: &mut ReadFetch<'w, T>,
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&component_id: &ComponentId,
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table: &'w Table,
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) {
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fetch.table_components = Some(
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table
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.get_column(component_id)
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Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
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2022-10-28 09:25:50 +00:00
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-10-28 09:25:50 +00:00
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#[inline(always)]
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unsafe fn fetch<'w>(
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2022-11-03 16:33:05 +00:00
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fetch: &mut Self::Fetch<'w>,
|
2022-10-28 09:25:50 +00:00
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entity: Entity,
|
2022-12-06 01:38:21 +00:00
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table_row: TableRow,
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2022-11-03 16:33:05 +00:00
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) -> Self::Item<'w> {
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2021-10-03 19:23:44 +00:00
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match T::Storage::STORAGE_TYPE {
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2022-10-28 09:25:50 +00:00
|
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StorageType::Table => fetch
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.table_components
|
Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
|
|
|
.debug_checked_unwrap()
|
2022-12-06 01:38:21 +00:00
|
|
|
.get(table_row.index())
|
2022-10-28 09:25:50 +00:00
|
|
|
.deref(),
|
|
|
|
StorageType::SparseSet => fetch
|
|
|
|
.sparse_set
|
Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
|
|
|
.debug_checked_unwrap()
|
2022-10-28 09:25:50 +00:00
|
|
|
.get(entity)
|
Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
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2022-10-28 09:25:50 +00:00
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn update_component_access(
|
|
|
|
&component_id: &ComponentId,
|
|
|
|
access: &mut FilteredAccess<ComponentId>,
|
|
|
|
) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
assert!(
|
2022-08-04 21:51:02 +00:00
|
|
|
!access.access().has_write(component_id),
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
"&{} conflicts with a previous access in this query. Shared access cannot coincide with exclusive access.",
|
|
|
|
std::any::type_name::<T>(),
|
|
|
|
);
|
2022-08-04 21:51:02 +00:00
|
|
|
access.add_read(component_id);
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
fn update_archetype_component_access(
|
2022-08-04 21:51:02 +00:00
|
|
|
&component_id: &ComponentId,
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
archetype: &Archetype,
|
|
|
|
access: &mut Access<ArchetypeComponentId>,
|
|
|
|
) {
|
2022-08-04 21:51:02 +00:00
|
|
|
if let Some(archetype_component_id) = archetype.get_archetype_component_id(component_id) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
access.add_read(archetype_component_id);
|
|
|
|
}
|
|
|
|
}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-08-04 21:51:02 +00:00
|
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fn init_state(world: &mut World) -> ComponentId {
|
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world.init_component::<T>()
|
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|
}
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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2022-08-04 21:51:02 +00:00
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fn matches_component_set(
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&state: &ComponentId,
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|
|
set_contains_id: &impl Fn(ComponentId) -> bool,
|
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|
) -> bool {
|
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set_contains_id(state)
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
}
|
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
/// SAFETY: access is read only
|
|
|
|
unsafe impl<T: Component> ReadOnlyWorldQuery for &T {}
|
|
|
|
|
2023-01-11 15:41:54 +00:00
|
|
|
#[doc(hidden)]
|
|
|
|
pub struct RefFetch<'w, T> {
|
|
|
|
// T::Storage = TableStorage
|
|
|
|
table_data: Option<(
|
|
|
|
ThinSlicePtr<'w, UnsafeCell<T>>,
|
|
|
|
ThinSlicePtr<'w, UnsafeCell<Tick>>,
|
|
|
|
ThinSlicePtr<'w, UnsafeCell<Tick>>,
|
|
|
|
)>,
|
|
|
|
// T::Storage = SparseStorage
|
|
|
|
sparse_set: Option<&'w ComponentSparseSet>,
|
|
|
|
|
|
|
|
last_change_tick: u32,
|
|
|
|
change_tick: u32,
|
|
|
|
}
|
|
|
|
|
|
|
|
/// SAFETY: `Self` is the same as `Self::ReadOnly`
|
|
|
|
unsafe impl<'__w, T: Component> WorldQuery for Ref<'__w, T> {
|
|
|
|
type Fetch<'w> = RefFetch<'w, T>;
|
|
|
|
type Item<'w> = Ref<'w, T>;
|
|
|
|
type ReadOnly = Self;
|
|
|
|
type State = ComponentId;
|
|
|
|
|
|
|
|
fn shrink<'wlong: 'wshort, 'wshort>(item: Ref<'wlong, T>) -> Ref<'wshort, T> {
|
|
|
|
item
|
|
|
|
}
|
|
|
|
|
|
|
|
const IS_DENSE: bool = {
|
|
|
|
match T::Storage::STORAGE_TYPE {
|
|
|
|
StorageType::Table => true,
|
|
|
|
StorageType::SparseSet => false,
|
|
|
|
}
|
|
|
|
};
|
|
|
|
|
|
|
|
const IS_ARCHETYPAL: bool = true;
|
|
|
|
|
|
|
|
unsafe fn init_fetch<'w>(
|
|
|
|
world: &'w World,
|
|
|
|
&component_id: &ComponentId,
|
|
|
|
last_change_tick: u32,
|
|
|
|
change_tick: u32,
|
|
|
|
) -> RefFetch<'w, T> {
|
|
|
|
RefFetch {
|
|
|
|
table_data: None,
|
|
|
|
sparse_set: (T::Storage::STORAGE_TYPE == StorageType::SparseSet).then(|| {
|
|
|
|
world
|
|
|
|
.storages()
|
|
|
|
.sparse_sets
|
|
|
|
.get(component_id)
|
|
|
|
.debug_checked_unwrap()
|
|
|
|
}),
|
|
|
|
last_change_tick,
|
|
|
|
change_tick,
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
unsafe fn clone_fetch<'w>(fetch: &Self::Fetch<'w>) -> Self::Fetch<'w> {
|
|
|
|
RefFetch {
|
|
|
|
table_data: fetch.table_data,
|
|
|
|
sparse_set: fetch.sparse_set,
|
|
|
|
last_change_tick: fetch.last_change_tick,
|
|
|
|
change_tick: fetch.change_tick,
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
#[inline]
|
|
|
|
unsafe fn set_archetype<'w>(
|
|
|
|
fetch: &mut RefFetch<'w, T>,
|
|
|
|
component_id: &ComponentId,
|
|
|
|
_archetype: &'w Archetype,
|
|
|
|
table: &'w Table,
|
|
|
|
) {
|
|
|
|
if Self::IS_DENSE {
|
|
|
|
Self::set_table(fetch, component_id, table);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
#[inline]
|
|
|
|
unsafe fn set_table<'w>(
|
|
|
|
fetch: &mut RefFetch<'w, T>,
|
|
|
|
&component_id: &ComponentId,
|
|
|
|
table: &'w Table,
|
|
|
|
) {
|
|
|
|
let column = table.get_column(component_id).debug_checked_unwrap();
|
|
|
|
fetch.table_data = Some((
|
|
|
|
column.get_data_slice().into(),
|
|
|
|
column.get_added_ticks_slice().into(),
|
|
|
|
column.get_changed_ticks_slice().into(),
|
|
|
|
));
|
|
|
|
}
|
|
|
|
|
|
|
|
#[inline(always)]
|
|
|
|
unsafe fn fetch<'w>(
|
|
|
|
fetch: &mut Self::Fetch<'w>,
|
|
|
|
entity: Entity,
|
|
|
|
table_row: TableRow,
|
|
|
|
) -> Self::Item<'w> {
|
|
|
|
match T::Storage::STORAGE_TYPE {
|
|
|
|
StorageType::Table => {
|
|
|
|
let (table_components, added_ticks, changed_ticks) =
|
|
|
|
fetch.table_data.debug_checked_unwrap();
|
|
|
|
Ref {
|
|
|
|
value: table_components.get(table_row.index()).deref(),
|
|
|
|
ticks: Ticks {
|
|
|
|
added: added_ticks.get(table_row.index()).deref(),
|
|
|
|
changed: changed_ticks.get(table_row.index()).deref(),
|
|
|
|
change_tick: fetch.change_tick,
|
|
|
|
last_change_tick: fetch.last_change_tick,
|
|
|
|
},
|
|
|
|
}
|
|
|
|
}
|
|
|
|
StorageType::SparseSet => {
|
|
|
|
let (component, ticks) = fetch
|
|
|
|
.sparse_set
|
|
|
|
.debug_checked_unwrap()
|
|
|
|
.get_with_ticks(entity)
|
|
|
|
.debug_checked_unwrap();
|
|
|
|
Ref {
|
|
|
|
value: component.deref(),
|
|
|
|
ticks: Ticks::from_tick_cells(ticks, fetch.last_change_tick, fetch.change_tick),
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
fn update_component_access(
|
|
|
|
&component_id: &ComponentId,
|
|
|
|
access: &mut FilteredAccess<ComponentId>,
|
|
|
|
) {
|
|
|
|
assert!(
|
|
|
|
!access.access().has_write(component_id),
|
|
|
|
"&{} conflicts with a previous access in this query. Shared access cannot coincide with exclusive access.",
|
|
|
|
std::any::type_name::<T>(),
|
|
|
|
);
|
|
|
|
access.add_read(component_id);
|
|
|
|
}
|
|
|
|
|
|
|
|
fn update_archetype_component_access(
|
|
|
|
&component_id: &ComponentId,
|
|
|
|
archetype: &Archetype,
|
|
|
|
access: &mut Access<ArchetypeComponentId>,
|
|
|
|
) {
|
|
|
|
if let Some(archetype_component_id) = archetype.get_archetype_component_id(component_id) {
|
|
|
|
access.add_read(archetype_component_id);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
fn init_state(world: &mut World) -> ComponentId {
|
|
|
|
world.init_component::<T>()
|
|
|
|
}
|
|
|
|
|
|
|
|
fn matches_component_set(
|
|
|
|
&state: &ComponentId,
|
|
|
|
set_contains_id: &impl Fn(ComponentId) -> bool,
|
|
|
|
) -> bool {
|
|
|
|
set_contains_id(state)
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
/// SAFETY: access is read only
|
|
|
|
unsafe impl<'__w, T: Component> ReadOnlyWorldQuery for Ref<'__w, T> {}
|
|
|
|
|
2022-03-21 05:23:36 +00:00
|
|
|
#[doc(hidden)]
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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pub struct WriteFetch<'w, T> {
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// T::Storage = TableStorage
|
2022-10-28 09:25:50 +00:00
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table_data: Option<(
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ThinSlicePtr<'w, UnsafeCell<T>>,
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2022-11-21 12:59:09 +00:00
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ThinSlicePtr<'w, UnsafeCell<Tick>>,
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ThinSlicePtr<'w, UnsafeCell<Tick>>,
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2022-10-28 09:25:50 +00:00
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)>,
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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// T::Storage = SparseStorage
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sparse_set: Option<&'w ComponentSparseSet>,
|
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|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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last_change_tick: u32,
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change_tick: u32,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-08-04 21:51:02 +00:00
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/// SAFETY: access of `&T` is a subset of `&mut T`
|
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unsafe impl<'__w, T: Component> WorldQuery for &'__w mut T {
|
2022-11-03 16:33:05 +00:00
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type Fetch<'w> = WriteFetch<'w, T>;
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type Item<'w> = Mut<'w, T>;
|
2022-08-04 21:51:02 +00:00
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type ReadOnly = &'__w T;
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type State = ComponentId;
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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2022-08-04 21:51:02 +00:00
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fn shrink<'wlong: 'wshort, 'wshort>(item: Mut<'wlong, T>) -> Mut<'wshort, T> {
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item
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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const IS_DENSE: bool = {
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match T::Storage::STORAGE_TYPE {
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
StorageType::Table => true,
|
|
|
|
StorageType::SparseSet => false,
|
|
|
|
}
|
2021-10-03 19:23:44 +00:00
|
|
|
};
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-04-27 18:02:06 +00:00
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const IS_ARCHETYPAL: bool = true;
|
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2022-08-04 21:51:02 +00:00
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unsafe fn init_fetch<'w>(
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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world: &'w World,
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2022-08-04 21:51:02 +00:00
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&component_id: &ComponentId,
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Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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last_change_tick: u32,
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change_tick: u32,
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2022-08-04 21:51:02 +00:00
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) -> WriteFetch<'w, T> {
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WriteFetch {
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2022-10-28 09:25:50 +00:00
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table_data: None,
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sparse_set: (T::Storage::STORAGE_TYPE == StorageType::SparseSet).then(|| {
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world
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.storages()
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.sparse_sets
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.get(component_id)
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Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
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.debug_checked_unwrap()
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2022-10-28 09:25:50 +00:00
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}),
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Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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change_tick,
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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2022-11-03 16:33:05 +00:00
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unsafe fn clone_fetch<'w>(fetch: &Self::Fetch<'w>) -> Self::Fetch<'w> {
|
2022-10-26 13:16:25 +00:00
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WriteFetch {
|
2022-10-28 09:25:50 +00:00
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table_data: fetch.table_data,
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2022-10-26 13:16:25 +00:00
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sparse_set: fetch.sparse_set,
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last_change_tick: fetch.last_change_tick,
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change_tick: fetch.change_tick,
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}
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
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|
#[inline]
|
2022-08-04 21:51:02 +00:00
|
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|
unsafe fn set_archetype<'w>(
|
|
|
|
fetch: &mut WriteFetch<'w, T>,
|
2022-10-28 09:25:50 +00:00
|
|
|
component_id: &ComponentId,
|
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|
_archetype: &'w Archetype,
|
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|
table: &'w Table,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
) {
|
2022-10-28 09:25:50 +00:00
|
|
|
if Self::IS_DENSE {
|
|
|
|
Self::set_table(fetch, component_id, table);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
#[inline]
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe fn set_table<'w>(
|
|
|
|
fetch: &mut WriteFetch<'w, T>,
|
|
|
|
&component_id: &ComponentId,
|
|
|
|
table: &'w Table,
|
|
|
|
) {
|
Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
|
|
|
let column = table.get_column(component_id).debug_checked_unwrap();
|
2022-10-28 09:25:50 +00:00
|
|
|
fetch.table_data = Some((
|
|
|
|
column.get_data_slice().into(),
|
2022-11-21 12:59:09 +00:00
|
|
|
column.get_added_ticks_slice().into(),
|
|
|
|
column.get_changed_ticks_slice().into(),
|
2022-10-28 09:25:50 +00:00
|
|
|
));
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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#[inline(always)]
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unsafe fn fetch<'w>(
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fetch: &mut Self::Fetch<'w>,
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entity: Entity,
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table_row: TableRow,
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) -> Self::Item<'w> {
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match T::Storage::STORAGE_TYPE {
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
StorageType::Table => {
|
2022-11-21 12:59:09 +00:00
|
|
|
let (table_components, added_ticks, changed_ticks) =
|
|
|
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fetch.table_data.debug_checked_unwrap();
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
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Mut {
|
2022-12-06 01:38:21 +00:00
|
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value: table_components.get(table_row.index()).deref_mut(),
|
2023-01-11 15:41:54 +00:00
|
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ticks: TicksMut {
|
2022-12-06 01:38:21 +00:00
|
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added: added_ticks.get(table_row.index()).deref_mut(),
|
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changed: changed_ticks.get(table_row.index()).deref_mut(),
|
2022-08-04 21:51:02 +00:00
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change_tick: fetch.change_tick,
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last_change_tick: fetch.last_change_tick,
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2021-05-30 19:29:31 +00:00
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},
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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StorageType::SparseSet => {
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2022-11-21 12:59:09 +00:00
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let (component, ticks) = fetch
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2022-10-28 09:25:50 +00:00
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.sparse_set
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Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
|
|
|
.debug_checked_unwrap()
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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.get_with_ticks(entity)
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Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
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.debug_checked_unwrap();
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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Mut {
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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value: component.assert_unique().deref_mut(),
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2023-01-11 15:41:54 +00:00
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ticks: TicksMut::from_tick_cells(
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ticks,
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fetch.last_change_tick,
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fetch.change_tick,
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),
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-08-04 21:51:02 +00:00
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fn update_component_access(
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&component_id: &ComponentId,
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access: &mut FilteredAccess<ComponentId>,
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Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
assert!(
|
2022-08-04 21:51:02 +00:00
|
|
|
!access.access().has_read(component_id),
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
"&mut {} conflicts with a previous access in this query. Mutable component access must be unique.",
|
|
|
|
std::any::type_name::<T>(),
|
|
|
|
);
|
2022-08-04 21:51:02 +00:00
|
|
|
access.add_write(component_id);
|
2021-12-01 23:28:10 +00:00
|
|
|
}
|
|
|
|
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
fn update_archetype_component_access(
|
2022-08-04 21:51:02 +00:00
|
|
|
&component_id: &ComponentId,
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
archetype: &Archetype,
|
|
|
|
access: &mut Access<ArchetypeComponentId>,
|
2021-12-01 23:28:10 +00:00
|
|
|
) {
|
2022-08-04 21:51:02 +00:00
|
|
|
if let Some(archetype_component_id) = archetype.get_archetype_component_id(component_id) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
access.add_write(archetype_component_id);
|
2021-12-01 23:28:10 +00:00
|
|
|
}
|
|
|
|
}
|
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn init_state(world: &mut World) -> ComponentId {
|
|
|
|
world.init_component::<T>()
|
|
|
|
}
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn matches_component_set(
|
|
|
|
&state: &ComponentId,
|
|
|
|
set_contains_id: &impl Fn(ComponentId) -> bool,
|
|
|
|
) -> bool {
|
|
|
|
set_contains_id(state)
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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#[doc(hidden)]
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pub struct OptionFetch<'w, T: WorldQuery> {
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fetch: T::Fetch<'w>,
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matches: bool,
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-08-04 21:51:02 +00:00
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// SAFETY: defers to soundness of `T: WorldQuery` impl
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unsafe impl<T: WorldQuery> WorldQuery for Option<T> {
|
2022-11-03 16:33:05 +00:00
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type Fetch<'w> = OptionFetch<'w, T>;
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type Item<'w> = Option<T::Item<'w>>;
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2022-08-04 21:51:02 +00:00
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type ReadOnly = Option<T::ReadOnly>;
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type State = T::State;
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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2022-11-03 16:33:05 +00:00
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fn shrink<'wlong: 'wshort, 'wshort>(item: Self::Item<'wlong>) -> Self::Item<'wshort> {
|
2022-08-04 21:51:02 +00:00
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item.map(T::shrink)
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
|
2021-10-03 19:23:44 +00:00
|
|
|
const IS_DENSE: bool = T::IS_DENSE;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-04-27 18:02:06 +00:00
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const IS_ARCHETYPAL: bool = T::IS_ARCHETYPAL;
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2022-08-04 21:51:02 +00:00
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unsafe fn init_fetch<'w>(
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
world: &'w World,
|
2022-08-04 21:51:02 +00:00
|
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state: &T::State,
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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last_change_tick: u32,
|
|
|
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change_tick: u32,
|
2022-08-04 21:51:02 +00:00
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) -> OptionFetch<'w, T> {
|
|
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OptionFetch {
|
|
|
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fetch: T::init_fetch(world, state, last_change_tick, change_tick),
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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matches: false,
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}
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}
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2022-11-03 16:33:05 +00:00
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unsafe fn clone_fetch<'w>(fetch: &Self::Fetch<'w>) -> Self::Fetch<'w> {
|
2022-10-26 13:16:25 +00:00
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OptionFetch {
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fetch: T::clone_fetch(&fetch.fetch),
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matches: fetch.matches,
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}
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
#[inline]
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe fn set_archetype<'w>(
|
|
|
|
fetch: &mut OptionFetch<'w, T>,
|
|
|
|
state: &T::State,
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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archetype: &'w Archetype,
|
2022-10-28 09:25:50 +00:00
|
|
|
table: &'w Table,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
) {
|
2022-08-04 21:51:02 +00:00
|
|
|
fetch.matches = T::matches_component_set(state, &|id| archetype.contains(id));
|
|
|
|
if fetch.matches {
|
2022-10-28 09:25:50 +00:00
|
|
|
T::set_archetype(&mut fetch.fetch, state, archetype, table);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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#[inline]
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2022-08-04 21:51:02 +00:00
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unsafe fn set_table<'w>(fetch: &mut OptionFetch<'w, T>, state: &T::State, table: &'w Table) {
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fetch.matches = T::matches_component_set(state, &|id| table.has_column(id));
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if fetch.matches {
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T::set_table(&mut fetch.fetch, state, table);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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unsafe fn fetch<'w>(
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entity: Entity,
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fetch
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.then(|| T::fetch(&mut fetch.fetch, entity, table_row))
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn update_component_access(state: &T::State, access: &mut FilteredAccess<ComponentId>) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
// We don't want to add the `with`/`without` of `T` as `Option<T>` will match things regardless of
|
|
|
|
// `T`'s filters. for example `Query<(Option<&U>, &mut V)>` will match every entity with a `V` component
|
2023-01-06 00:43:30 +00:00
|
|
|
// regardless of whether it has a `U` component. If we don't do this the query will not conflict with
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
// `Query<&mut V, Without<U>>` which would be unsound.
|
|
|
|
let mut intermediate = access.clone();
|
2022-08-04 21:51:02 +00:00
|
|
|
T::update_component_access(state, &mut intermediate);
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
access.extend_access(&intermediate);
|
|
|
|
}
|
|
|
|
|
|
|
|
fn update_archetype_component_access(
|
2022-08-04 21:51:02 +00:00
|
|
|
state: &T::State,
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
archetype: &Archetype,
|
|
|
|
access: &mut Access<ArchetypeComponentId>,
|
|
|
|
) {
|
2022-08-04 21:51:02 +00:00
|
|
|
if T::matches_component_set(state, &|id| archetype.contains(id)) {
|
|
|
|
T::update_archetype_component_access(state, archetype, access);
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
}
|
|
|
|
}
|
2022-08-04 21:51:02 +00:00
|
|
|
|
|
|
|
fn init_state(world: &mut World) -> T::State {
|
|
|
|
T::init_state(world)
|
|
|
|
}
|
|
|
|
|
|
|
|
fn matches_component_set(
|
|
|
|
_state: &T::State,
|
|
|
|
_set_contains_id: &impl Fn(ComponentId) -> bool,
|
|
|
|
) -> bool {
|
|
|
|
true
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
/// SAFETY: [`OptionFetch`] is read only because `T` is read only
|
|
|
|
unsafe impl<T: ReadOnlyWorldQuery> ReadOnlyWorldQuery for Option<T> {}
|
|
|
|
|
2021-04-22 19:09:09 +00:00
|
|
|
/// [`WorldQuery`] that tracks changes and additions for component `T`.
|
|
|
|
///
|
|
|
|
/// Wraps a [`Component`] to track whether the component changed for the corresponding entities in
|
|
|
|
/// a query since the last time the system that includes these queries ran.
|
|
|
|
///
|
|
|
|
/// If you only care about entities that changed or that got added use the
|
|
|
|
/// [`Changed`](crate::query::Changed) and [`Added`](crate::query::Added) filters instead.
|
|
|
|
///
|
|
|
|
/// # Examples
|
|
|
|
///
|
|
|
|
/// ```
|
2021-10-03 19:23:44 +00:00
|
|
|
/// # use bevy_ecs::component::Component;
|
2021-04-22 19:09:09 +00:00
|
|
|
/// # use bevy_ecs::query::ChangeTrackers;
|
|
|
|
/// # use bevy_ecs::system::IntoSystem;
|
2021-10-03 19:23:44 +00:00
|
|
|
/// # use bevy_ecs::system::Query;
|
2021-04-22 19:09:09 +00:00
|
|
|
/// #
|
2021-10-03 19:23:44 +00:00
|
|
|
/// # #[derive(Component, Debug)]
|
2021-04-22 19:09:09 +00:00
|
|
|
/// # struct Name {};
|
2021-10-03 19:23:44 +00:00
|
|
|
/// # #[derive(Component)]
|
2021-04-22 19:09:09 +00:00
|
|
|
/// # struct Transform {};
|
|
|
|
/// #
|
|
|
|
/// fn print_moving_objects_system(query: Query<(&Name, ChangeTrackers<Transform>)>) {
|
2022-07-11 15:28:50 +00:00
|
|
|
/// for (name, tracker) in &query {
|
2021-04-22 19:09:09 +00:00
|
|
|
/// if tracker.is_changed() {
|
|
|
|
/// println!("Entity moved: {:?}", name);
|
|
|
|
/// } else {
|
|
|
|
/// println!("Entity stood still: {:?}", name);
|
|
|
|
/// }
|
|
|
|
/// }
|
|
|
|
/// }
|
2022-02-08 04:00:58 +00:00
|
|
|
/// # bevy_ecs::system::assert_is_system(print_moving_objects_system);
|
2021-04-22 19:09:09 +00:00
|
|
|
/// ```
|
2023-02-19 16:19:56 +00:00
|
|
|
#[deprecated = "`ChangeTrackers<T>` will be removed in bevy 0.11. Use `bevy_ecs::prelude::Ref<T>` instead."]
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
|
|
|
pub struct ChangeTrackers<T: Component> {
|
|
|
|
pub(crate) component_ticks: ComponentTicks,
|
|
|
|
pub(crate) last_change_tick: u32,
|
|
|
|
pub(crate) change_tick: u32,
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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marker: PhantomData<T>,
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}
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#[allow(deprecated)]
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impl<T: Component> Clone for ChangeTrackers<T> {
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fn clone(&self) -> Self {
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*self
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impl<T: Component> Copy for ChangeTrackers<T> {}
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#[allow(deprecated)]
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Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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impl<T: Component> std::fmt::Debug for ChangeTrackers<T> {
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
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Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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f.debug_struct("ChangeTrackers")
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.field("component_ticks", &self.component_ticks)
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.field("last_change_tick", &self.last_change_tick)
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.field("change_tick", &self.change_tick)
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
.finish()
|
|
|
|
}
|
|
|
|
}
|
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|
|
|
2023-02-19 16:19:56 +00:00
|
|
|
#[allow(deprecated)]
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
|
|
|
impl<T: Component> ChangeTrackers<T> {
|
2021-04-22 19:09:09 +00:00
|
|
|
/// Returns true if this component has been added since the last execution of this system.
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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pub fn is_added(&self) -> bool {
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self.component_ticks
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.is_added(self.last_change_tick, self.change_tick)
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2021-04-22 19:09:09 +00:00
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/// Returns true if this component has been changed since the last execution of this system.
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
|
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|
pub fn is_changed(&self) -> bool {
|
|
|
|
self.component_ticks
|
|
|
|
.is_changed(self.last_change_tick, self.change_tick)
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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2022-03-21 05:23:36 +00:00
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#[doc(hidden)]
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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pub struct ChangeTrackersFetch<'w, T> {
|
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// T::Storage = TableStorage
|
2022-11-21 12:59:09 +00:00
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table_added: Option<ThinSlicePtr<'w, UnsafeCell<Tick>>>,
|
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|
table_changed: Option<ThinSlicePtr<'w, UnsafeCell<Tick>>>,
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
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// T::Storage = SparseStorage
|
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|
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sparse_set: Option<&'w ComponentSparseSet>,
|
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|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
marker: PhantomData<T>,
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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change_tick: u32,
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
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}
|
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2023-02-19 16:19:56 +00:00
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|
#[allow(deprecated)]
|
2022-08-04 21:51:02 +00:00
|
|
|
// SAFETY: `ROQueryFetch<Self>` is the same as `QueryFetch<Self>`
|
|
|
|
unsafe impl<T: Component> WorldQuery for ChangeTrackers<T> {
|
2022-11-03 16:33:05 +00:00
|
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|
type Fetch<'w> = ChangeTrackersFetch<'w, T>;
|
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type Item<'w> = ChangeTrackers<T>;
|
2022-08-04 21:51:02 +00:00
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type ReadOnly = Self;
|
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|
type State = ComponentId;
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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2022-11-03 16:33:05 +00:00
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fn shrink<'wlong: 'wshort, 'wshort>(item: Self::Item<'wlong>) -> Self::Item<'wshort> {
|
2022-08-04 21:51:02 +00:00
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item
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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const IS_DENSE: bool = {
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match T::Storage::STORAGE_TYPE {
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
StorageType::Table => true,
|
|
|
|
StorageType::SparseSet => false,
|
|
|
|
}
|
2021-10-03 19:23:44 +00:00
|
|
|
};
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-04-27 18:02:06 +00:00
|
|
|
const IS_ARCHETYPAL: bool = true;
|
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe fn init_fetch<'w>(
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
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world: &'w World,
|
2022-10-28 09:25:50 +00:00
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|
|
&component_id: &ComponentId,
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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last_change_tick: u32,
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change_tick: u32,
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
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) -> ChangeTrackersFetch<'w, T> {
|
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|
ChangeTrackersFetch {
|
2022-11-21 12:59:09 +00:00
|
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table_added: None,
|
|
|
|
table_changed: None,
|
2022-10-28 09:25:50 +00:00
|
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sparse_set: (T::Storage::STORAGE_TYPE == StorageType::SparseSet).then(|| {
|
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world
|
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.storages()
|
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.sparse_sets
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.get(component_id)
|
Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
|
|
|
.debug_checked_unwrap()
|
2022-10-28 09:25:50 +00:00
|
|
|
}),
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
marker: PhantomData,
|
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
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last_change_tick,
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change_tick,
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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2022-11-03 16:33:05 +00:00
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unsafe fn clone_fetch<'w>(fetch: &Self::Fetch<'w>) -> Self::Fetch<'w> {
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2022-10-26 13:16:25 +00:00
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ChangeTrackersFetch {
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2022-11-21 12:59:09 +00:00
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table_added: fetch.table_added,
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table_changed: fetch.table_changed,
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2022-10-26 13:16:25 +00:00
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sparse_set: fetch.sparse_set,
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marker: fetch.marker,
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last_change_tick: fetch.last_change_tick,
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change_tick: fetch.change_tick,
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}
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}
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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#[inline]
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2022-08-04 21:51:02 +00:00
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unsafe fn set_archetype<'w>(
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fetch: &mut ChangeTrackersFetch<'w, T>,
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2022-10-28 09:25:50 +00:00
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component_id: &ComponentId,
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_archetype: &'w Archetype,
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table: &'w Table,
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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) {
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2022-10-28 09:25:50 +00:00
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if Self::IS_DENSE {
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Self::set_table(fetch, component_id, table);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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}
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#[inline]
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2022-08-04 21:51:02 +00:00
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unsafe fn set_table<'w>(
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fetch: &mut ChangeTrackersFetch<'w, T>,
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&id: &ComponentId,
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table: &'w Table,
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) {
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2022-11-21 12:59:09 +00:00
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let column = table.get_column(id).debug_checked_unwrap();
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fetch.table_added = Some(column.get_added_ticks_slice().into());
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fetch.table_changed = Some(column.get_changed_ticks_slice().into());
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-10-28 09:25:50 +00:00
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#[inline(always)]
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unsafe fn fetch<'w>(
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fetch: &mut Self::Fetch<'w>,
|
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entity: Entity,
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table_row: TableRow,
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2022-11-03 16:33:05 +00:00
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) -> Self::Item<'w> {
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2022-10-28 09:25:50 +00:00
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match T::Storage::STORAGE_TYPE {
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StorageType::Table => ChangeTrackers {
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component_ticks: {
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2022-11-21 12:59:09 +00:00
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ComponentTicks {
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added: fetch
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.table_added
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.debug_checked_unwrap()
|
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.get(table_row.index())
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.read(),
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changed: fetch
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.table_changed
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.debug_checked_unwrap()
|
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.get(table_row.index())
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.read(),
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}
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},
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marker: PhantomData,
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last_change_tick: fetch.last_change_tick,
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change_tick: fetch.change_tick,
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},
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StorageType::SparseSet => ChangeTrackers {
|
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|
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|
component_ticks: fetch
|
2022-10-28 09:25:50 +00:00
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.sparse_set
|
Remove unnecesary branches/panics from Query accesses (#6461)
# Objective
Supercedes #6452. Upon inspection of the [generated assembly](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-original-s) of a [simple Bevy binary](https://gist.github.com/james7132/c2740c6941b80d7912f1e8888e223cbb#file-source-rs) compiled with `cargo rustc --release -- --emit asm`, it's apparent that there are multiple unnecessary branches in the generated assembly:
```assembly
.LBB5_5:
cmpq %r10, %r11
je .LBB5_15
movq (%r11), %rcx
movq 328(%r15), %rdx
cmpq %rdx, %rcx
jae .LBB5_14
movq 312(%r15), %rdi
leaq (%rcx,%rcx,2), %rcx
shlq $5, %rcx
movq 336(%r12), %rdx
movq 64(%rdi,%rcx), %rax
cmpq %rdx, %rax
jbe .LBB5_4
leaq (%rdi,%rcx), %rsi
movq 48(%rsi), %rbp
shlq $4, %rdx
cmpq $0, (%rbp,%rdx)
je .LBB5_4
movq 344(%r12), %rbx
cmpq %rbx, %rax
jbe .LBB5_4
shlq $4, %rbx
cmpq $0, (%rbp,%rbx)
je .LBB5_4
addq $8, %r11
movq 88(%rdi,%rcx), %rcx
testq %rcx, %rcx
je .LBB5_5
movq (%rsi), %rax
movq 8(%rbp,%rdx), %rdx
leaq (%rdx,%rdx,4), %rdi
shlq $4, %rdi
movq 32(%rax,%rdi), %rdx
movq 56(%rax,%rdi), %r8
movq 8(%rbp,%rbx), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rax,%rbp), %r9
xorl %ebp, %ebp
jmp .LBB5_13
.p2align 4, 0x90
```
Almost every one of the instructions starting with `j` is a potential branch, which can significantly slow down accesses. Of these, two labels are both common and never used:
```asm
.LBB5_14:
leaq __unnamed_2(%rip), %r8
callq _ZN4core9panicking18panic_bounds_check17h70367088e72af65aE
ud2
.LBB5_4:
callq _ZN8bevy_ecs5query25debug_checked_unreachable17h0855ff520ceaea77E
ud2
.seh_endproc
```
These correpsond to subprocedure calls to panicking due to out of bounds from indexing `Tables` and `debug_checked_unreadable`. Both of which should be inlined and optimized out, but are not.
## Solution
Make `debug_checked_unreachable` a macro to forcibly inline either `unreachable!()` in debug builds, and `std::hint::unreachable_unchecked()` in release mode. Replace the `Tables` and `Archetype` index access with `get(id).unwrap_or_else(|| debug_checked_unreachable!())` to assume that the table or archetype provided exists.
This has no external breaking change of any kind.
The equivalent section of code with these changes removes most of the conditional jump instructions:
```asm
.LBB5_5:
movss (%rbx,%rbp,4), %xmm0
movl %r14d, 4(%r8,%rbp,8)
addss (%rdi,%rbp,4), %xmm0
movss %xmm0, (%rdi,%rbp,4)
incq %rbp
.LBB5_1:
cmpq %rdx, %rbp
jne .LBB5_5
.p2align 4, 0x90
.LBB5_2:
cmpq %rcx, %rax
je .LBB5_6
movq (%rax), %rdx
addq $8, %rax
movq 312(%rsi), %rbp
leaq (%rdx,%rdx,2), %rbx
shlq $5, %rbx
movq 88(%rbp,%rbx), %rdx
testq %rdx, %rdx
je .LBB5_2
leaq (%rbx,%rbp), %r8
movq 336(%r15), %rdi
movq 344(%r15), %r9
movq 48(%rbp,%rbx), %r10
shlq $4, %rdi
movq (%r8), %rbx
movq 8(%r10,%rdi), %rdi
leaq (%rdi,%rdi,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rdi
movq 56(%rbx,%rbp), %r8
shlq $4, %r9
movq 8(%r10,%r9), %rbp
leaq (%rbp,%rbp,4), %rbp
shlq $4, %rbp
movq 32(%rbx,%rbp), %rbx
xorl %ebp, %ebp
jmp .LBB5_5
.LBB5_6:
addq $40, %rsp
popq %rbx
popq %rbp
popq %rdi
popq %rsi
popq %r14
popq %r15
retq
.seh_endproc
```
## Performance
Microbenchmarks results:
<details>
```
group main no-panic-query
----- ---- --------------
busy_systems/01x_entities_03_systems 1.20 42.4±2.66µs ? ?/sec 1.00 35.3±1.68µs ? ?/sec
busy_systems/01x_entities_06_systems 1.32 83.8±3.50µs ? ?/sec 1.00 63.6±1.72µs ? ?/sec
busy_systems/01x_entities_09_systems 1.15 113.3±8.90µs ? ?/sec 1.00 98.2±6.15µs ? ?/sec
busy_systems/01x_entities_12_systems 1.27 160.8±32.44µs ? ?/sec 1.00 126.6±4.70µs ? ?/sec
busy_systems/01x_entities_15_systems 1.12 179.6±3.71µs ? ?/sec 1.00 160.3±11.03µs ? ?/sec
busy_systems/02x_entities_03_systems 1.18 76.8±3.14µs ? ?/sec 1.00 65.2±3.17µs ? ?/sec
busy_systems/02x_entities_06_systems 1.16 144.6±6.10µs ? ?/sec 1.00 124.5±5.14µs ? ?/sec
busy_systems/02x_entities_09_systems 1.19 215.3±9.18µs ? ?/sec 1.00 181.5±5.67µs ? ?/sec
busy_systems/02x_entities_12_systems 1.20 266.7±8.33µs ? ?/sec 1.00 222.0±9.53µs ? ?/sec
busy_systems/02x_entities_15_systems 1.23 338.8±10.53µs ? ?/sec 1.00 276.3±6.94µs ? ?/sec
busy_systems/03x_entities_03_systems 1.43 113.5±5.06µs ? ?/sec 1.00 79.6±1.49µs ? ?/sec
busy_systems/03x_entities_06_systems 1.38 217.3±12.67µs ? ?/sec 1.00 157.5±3.07µs ? ?/sec
busy_systems/03x_entities_09_systems 1.23 308.8±24.75µs ? ?/sec 1.00 251.6±8.93µs ? ?/sec
busy_systems/03x_entities_12_systems 1.05 347.7±12.43µs ? ?/sec 1.00 330.6±11.43µs ? ?/sec
busy_systems/03x_entities_15_systems 1.13 455.5±13.88µs ? ?/sec 1.00 401.7±17.29µs ? ?/sec
busy_systems/04x_entities_03_systems 1.24 144.7±5.89µs ? ?/sec 1.00 116.9±6.29µs ? ?/sec
busy_systems/04x_entities_06_systems 1.24 282.8±21.40µs ? ?/sec 1.00 228.6±21.31µs ? ?/sec
busy_systems/04x_entities_09_systems 1.35 431.8±14.10µs ? ?/sec 1.00 319.6±9.83µs ? ?/sec
busy_systems/04x_entities_12_systems 1.16 493.8±22.87µs ? ?/sec 1.00 424.9±15.24µs ? ?/sec
busy_systems/04x_entities_15_systems 1.10 587.5±23.25µs ? ?/sec 1.00 531.7±16.32µs ? ?/sec
busy_systems/05x_entities_03_systems 1.14 148.2±9.61µs ? ?/sec 1.00 129.5±4.32µs ? ?/sec
busy_systems/05x_entities_06_systems 1.31 359.7±17.46µs ? ?/sec 1.00 273.6±10.55µs ? ?/sec
busy_systems/05x_entities_09_systems 1.22 473.5±23.11µs ? ?/sec 1.00 389.3±13.62µs ? ?/sec
busy_systems/05x_entities_12_systems 1.05 562.9±20.76µs ? ?/sec 1.00 536.5±24.35µs ? ?/sec
busy_systems/05x_entities_15_systems 1.23 818.5±28.70µs ? ?/sec 1.00 666.6±45.87µs ? ?/sec
contrived/01x_entities_03_systems 1.27 27.5±0.49µs ? ?/sec 1.00 21.6±1.71µs ? ?/sec
contrived/01x_entities_06_systems 1.22 49.9±1.18µs ? ?/sec 1.00 40.7±2.62µs ? ?/sec
contrived/01x_entities_09_systems 1.30 72.3±2.39µs ? ?/sec 1.00 55.4±2.60µs ? ?/sec
contrived/01x_entities_12_systems 1.28 94.3±9.44µs ? ?/sec 1.00 73.7±3.62µs ? ?/sec
contrived/01x_entities_15_systems 1.25 118.0±2.43µs ? ?/sec 1.00 94.1±3.99µs ? ?/sec
contrived/02x_entities_03_systems 1.23 41.6±1.71µs ? ?/sec 1.00 33.7±2.30µs ? ?/sec
contrived/02x_entities_06_systems 1.19 78.6±2.63µs ? ?/sec 1.00 65.9±2.35µs ? ?/sec
contrived/02x_entities_09_systems 1.28 113.6±3.60µs ? ?/sec 1.00 88.6±3.60µs ? ?/sec
contrived/02x_entities_12_systems 1.20 146.4±5.75µs ? ?/sec 1.00 121.7±3.35µs ? ?/sec
contrived/02x_entities_15_systems 1.23 178.5±4.86µs ? ?/sec 1.00 145.7±4.00µs ? ?/sec
contrived/03x_entities_03_systems 1.42 58.3±2.77µs ? ?/sec 1.00 41.1±1.54µs ? ?/sec
contrived/03x_entities_06_systems 1.32 108.5±7.30µs ? ?/sec 1.00 82.4±4.86µs ? ?/sec
contrived/03x_entities_09_systems 1.23 153.7±4.61µs ? ?/sec 1.00 125.0±4.76µs ? ?/sec
contrived/03x_entities_12_systems 1.18 197.5±5.12µs ? ?/sec 1.00 166.8±8.14µs ? ?/sec
contrived/03x_entities_15_systems 1.23 238.8±6.38µs ? ?/sec 1.00 194.6±4.55µs ? ?/sec
contrived/04x_entities_03_systems 1.34 66.4±3.42µs ? ?/sec 1.00 49.5±1.98µs ? ?/sec
contrived/04x_entities_06_systems 1.27 134.3±4.86µs ? ?/sec 1.00 105.8±3.58µs ? ?/sec
contrived/04x_entities_09_systems 1.26 193.2±3.83µs ? ?/sec 1.00 153.0±5.60µs ? ?/sec
contrived/04x_entities_12_systems 1.16 237.1±5.78µs ? ?/sec 1.00 204.9±18.77µs ? ?/sec
contrived/04x_entities_15_systems 1.17 289.2±4.76µs ? ?/sec 1.00 246.3±8.57µs ? ?/sec
contrived/05x_entities_03_systems 1.26 80.4±2.90µs ? ?/sec 1.00 63.7±3.07µs ? ?/sec
contrived/05x_entities_06_systems 1.27 161.6±13.47µs ? ?/sec 1.00 127.2±5.59µs ? ?/sec
contrived/05x_entities_09_systems 1.22 228.0±7.76µs ? ?/sec 1.00 186.2±7.68µs ? ?/sec
contrived/05x_entities_12_systems 1.20 289.5±6.21µs ? ?/sec 1.00 241.8±7.52µs ? ?/sec
contrived/05x_entities_15_systems 1.18 357.3±11.24µs ? ?/sec 1.00 302.7±7.21µs ? ?/sec
heavy_compute/base 1.01 302.4±3.52µs ? ?/sec 1.00 300.2±3.40µs ? ?/sec
iter_fragmented/base 1.00 348.1±7.51ns ? ?/sec 1.01 351.9±8.32ns ? ?/sec
iter_fragmented/foreach 1.03 239.8±23.78ns ? ?/sec 1.00 233.8±18.12ns ? ?/sec
iter_fragmented/foreach_wide 1.00 3.9±0.13µs ? ?/sec 1.02 4.0±0.22µs ? ?/sec
iter_fragmented/wide 1.18 4.6±0.15µs ? ?/sec 1.00 3.9±0.10µs ? ?/sec
iter_fragmented_sparse/base 1.02 8.1±0.15ns ? ?/sec 1.00 7.9±0.56ns ? ?/sec
iter_fragmented_sparse/foreach 1.00 7.8±0.22ns ? ?/sec 1.01 7.9±0.62ns ? ?/sec
iter_fragmented_sparse/foreach_wide 1.00 37.2±1.17ns ? ?/sec 1.10 40.9±0.95ns ? ?/sec
iter_fragmented_sparse/wide 1.09 48.4±2.13ns ? ?/sec 1.00 44.5±18.34ns ? ?/sec
iter_simple/base 1.02 8.4±0.10µs ? ?/sec 1.00 8.2±0.14µs ? ?/sec
iter_simple/foreach 1.01 8.3±0.07µs ? ?/sec 1.00 8.2±0.09µs ? ?/sec
iter_simple/foreach_sparse_set 1.00 25.3±0.32µs ? ?/sec 1.02 25.7±0.42µs ? ?/sec
iter_simple/foreach_wide 1.03 41.1±0.94µs ? ?/sec 1.00 39.9±0.41µs ? ?/sec
iter_simple/foreach_wide_sparse_set 1.05 123.6±2.05µs ? ?/sec 1.00 118.1±2.78µs ? ?/sec
iter_simple/sparse_set 1.14 30.5±1.40µs ? ?/sec 1.00 26.9±0.64µs ? ?/sec
iter_simple/system 1.01 8.4±0.25µs ? ?/sec 1.00 8.4±0.11µs ? ?/sec
iter_simple/wide 1.18 48.2±0.62µs ? ?/sec 1.00 40.7±0.38µs ? ?/sec
iter_simple/wide_sparse_set 1.12 140.8±21.56µs ? ?/sec 1.00 126.0±2.30µs ? ?/sec
query_get/50000_entities_sparse 1.17 378.6±7.60µs ? ?/sec 1.00 324.1±23.17µs ? ?/sec
query_get/50000_entities_table 1.08 330.9±10.90µs ? ?/sec 1.00 306.8±4.98µs ? ?/sec
query_get_component/50000_entities_sparse 1.00 976.7±19.55µs ? ?/sec 1.00 979.8±35.87µs ? ?/sec
query_get_component/50000_entities_table 1.00 1029.0±15.11µs ? ?/sec 1.05 1080.0±59.18µs ? ?/sec
query_get_component_simple/system 1.13 839.7±14.18µs ? ?/sec 1.00 742.8±10.72µs ? ?/sec
query_get_component_simple/unchecked 1.01 909.0±15.17µs ? ?/sec 1.00 898.0±13.56µs ? ?/sec
query_get_many_10/50000_calls_sparse 1.04 5.5±0.54ms ? ?/sec 1.00 5.3±0.67ms ? ?/sec
query_get_many_10/50000_calls_table 1.01 4.9±0.49ms ? ?/sec 1.00 4.8±0.45ms ? ?/sec
query_get_many_2/50000_calls_sparse 1.28 848.4±210.89µs ? ?/sec 1.00 664.8±47.69µs ? ?/sec
query_get_many_2/50000_calls_table 1.05 779.0±73.85µs ? ?/sec 1.00 739.2±83.02µs ? ?/sec
query_get_many_5/50000_calls_sparse 1.05 2.4±0.37ms ? ?/sec 1.00 2.3±0.33ms ? ?/sec
query_get_many_5/50000_calls_table 1.00 1939.9±75.22µs ? ?/sec 1.04 2.0±0.19ms ? ?/sec
run_criteria/yes_using_query/001_systems 1.00 3.7±0.38µs ? ?/sec 1.30 4.9±0.14µs ? ?/sec
run_criteria/yes_using_query/006_systems 1.00 8.9±0.40µs ? ?/sec 1.17 10.3±0.57µs ? ?/sec
run_criteria/yes_using_query/011_systems 1.00 13.9±0.49µs ? ?/sec 1.08 15.0±0.89µs ? ?/sec
run_criteria/yes_using_query/016_systems 1.00 18.8±0.74µs ? ?/sec 1.00 18.8±1.43µs ? ?/sec
run_criteria/yes_using_query/021_systems 1.07 24.1±0.87µs ? ?/sec 1.00 22.6±1.58µs ? ?/sec
run_criteria/yes_using_query/026_systems 1.04 27.9±0.62µs ? ?/sec 1.00 26.8±1.71µs ? ?/sec
run_criteria/yes_using_query/031_systems 1.09 33.3±1.03µs ? ?/sec 1.00 30.5±2.18µs ? ?/sec
run_criteria/yes_using_query/036_systems 1.14 38.7±0.80µs ? ?/sec 1.00 33.9±1.75µs ? ?/sec
run_criteria/yes_using_query/041_systems 1.18 43.7±1.07µs ? ?/sec 1.00 37.0±2.39µs ? ?/sec
run_criteria/yes_using_query/046_systems 1.14 47.6±1.16µs ? ?/sec 1.00 41.9±2.09µs ? ?/sec
run_criteria/yes_using_query/051_systems 1.17 52.9±2.04µs ? ?/sec 1.00 45.3±1.75µs ? ?/sec
run_criteria/yes_using_query/056_systems 1.25 59.2±2.38µs ? ?/sec 1.00 47.2±2.01µs ? ?/sec
run_criteria/yes_using_query/061_systems 1.28 66.1±15.84µs ? ?/sec 1.00 51.5±2.47µs ? ?/sec
run_criteria/yes_using_query/066_systems 1.28 70.2±2.57µs ? ?/sec 1.00 54.7±2.58µs ? ?/sec
run_criteria/yes_using_query/071_systems 1.30 75.5±2.27µs ? ?/sec 1.00 58.2±3.31µs ? ?/sec
run_criteria/yes_using_query/076_systems 1.26 81.5±2.66µs ? ?/sec 1.00 64.5±3.13µs ? ?/sec
run_criteria/yes_using_query/081_systems 1.29 89.7±2.58µs ? ?/sec 1.00 69.3±3.47µs ? ?/sec
run_criteria/yes_using_query/086_systems 1.33 95.6±3.39µs ? ?/sec 1.00 71.8±3.48µs ? ?/sec
run_criteria/yes_using_query/091_systems 1.25 102.0±3.67µs ? ?/sec 1.00 81.4±4.82µs ? ?/sec
run_criteria/yes_using_query/096_systems 1.33 111.7±3.29µs ? ?/sec 1.00 83.8±4.15µs ? ?/sec
run_criteria/yes_using_query/101_systems 1.29 113.2±12.04µs ? ?/sec 1.00 87.7±5.15µs ? ?/sec
world_query_for_each/50000_entities_sparse 1.00 47.4±0.51µs ? ?/sec 1.00 47.3±0.33µs ? ?/sec
world_query_for_each/50000_entities_table 1.00 27.2±0.50µs ? ?/sec 1.00 27.2±0.17µs ? ?/sec
world_query_get/50000_entities_sparse_wide 1.09 210.5±1.78µs ? ?/sec 1.00 192.5±2.61µs ? ?/sec
world_query_get/50000_entities_table 1.00 127.7±2.09µs ? ?/sec 1.07 136.2±5.95µs ? ?/sec
world_query_get/50000_entities_table_wide 1.00 209.8±2.37µs ? ?/sec 1.15 240.6±2.04µs ? ?/sec
world_query_iter/50000_entities_sparse 1.00 54.2±0.36µs ? ?/sec 1.01 54.7±0.61µs ? ?/sec
world_query_iter/50000_entities_table 1.00 27.2±0.31µs ? ?/sec 1.00 27.3±0.64µs ? ?/sec
```
</details>
NOTE: This PR includes a change to enable LTO on our benchmarks to get a "fully optimized" baseline for our benchmarks. Both the main and the current PR's results were with LTO enabled.
2022-11-04 06:04:55 +00:00
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.debug_checked_unwrap()
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2022-10-28 09:25:50 +00:00
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.get_ticks(entity)
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2022-11-21 12:59:09 +00:00
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.debug_checked_unwrap(),
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2022-10-28 09:25:50 +00:00
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marker: PhantomData,
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last_change_tick: fetch.last_change_tick,
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change_tick: fetch.change_tick,
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
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},
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
}
|
|
|
|
}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn update_component_access(&id: &ComponentId, access: &mut FilteredAccess<ComponentId>) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
assert!(
|
2022-08-04 21:51:02 +00:00
|
|
|
!access.access().has_write(id),
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
"ChangeTrackers<{}> conflicts with a previous access in this query. Shared access cannot coincide with exclusive access.",
|
|
|
|
std::any::type_name::<T>()
|
|
|
|
);
|
2022-08-04 21:51:02 +00:00
|
|
|
access.add_read(id);
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
fn update_archetype_component_access(
|
2022-08-04 21:51:02 +00:00
|
|
|
&id: &ComponentId,
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
archetype: &Archetype,
|
|
|
|
access: &mut Access<ArchetypeComponentId>,
|
|
|
|
) {
|
2022-08-04 21:51:02 +00:00
|
|
|
if let Some(archetype_component_id) = archetype.get_archetype_component_id(id) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
access.add_read(archetype_component_id);
|
|
|
|
}
|
|
|
|
}
|
2022-08-04 21:51:02 +00:00
|
|
|
|
|
|
|
fn init_state(world: &mut World) -> ComponentId {
|
|
|
|
world.init_component::<T>()
|
|
|
|
}
|
|
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|
|
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fn matches_component_set(
|
|
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|
&id: &ComponentId,
|
|
|
|
set_contains_id: &impl Fn(ComponentId) -> bool,
|
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|
|
) -> bool {
|
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|
|
set_contains_id(id)
|
|
|
|
}
|
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|
}
|
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2023-02-19 16:19:56 +00:00
|
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#[allow(deprecated)]
|
2022-08-04 21:51:02 +00:00
|
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|
/// SAFETY: access is read only
|
|
|
|
unsafe impl<T: Component> ReadOnlyWorldQuery for ChangeTrackers<T> {}
|
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|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
macro_rules! impl_tuple_fetch {
|
|
|
|
($(($name: ident, $state: ident)),*) => {
|
|
|
|
#[allow(non_snake_case)]
|
2022-08-04 21:51:02 +00:00
|
|
|
#[allow(clippy::unused_unit)]
|
|
|
|
// SAFETY: defers to soundness `$name: WorldQuery` impl
|
|
|
|
unsafe impl<$($name: WorldQuery),*> WorldQuery for ($($name,)*) {
|
2022-11-03 16:33:05 +00:00
|
|
|
type Fetch<'w> = ($($name::Fetch<'w>,)*);
|
|
|
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type Item<'w> = ($($name::Item<'w>,)*);
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2022-08-04 21:51:02 +00:00
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type ReadOnly = ($($name::ReadOnly,)*);
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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type State = ($($name::State,)*);
|
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|
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2022-11-03 16:33:05 +00:00
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fn shrink<'wlong: 'wshort, 'wshort>(item: Self::Item<'wlong>) -> Self::Item<'wshort> {
|
2022-08-04 21:51:02 +00:00
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let ($($name,)*) = item;
|
|
|
|
($(
|
|
|
|
$name::shrink($name),
|
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|
|
)*)
|
|
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|
}
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2021-07-29 20:52:15 +00:00
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#[allow(clippy::unused_unit)]
|
2022-11-03 16:33:05 +00:00
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unsafe fn init_fetch<'w>(_world: &'w World, state: &Self::State, _last_change_tick: u32, _change_tick: u32) -> Self::Fetch<'w> {
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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let ($($name,)*) = state;
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2022-08-04 21:51:02 +00:00
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($($name::init_fetch(_world, $name, _last_change_tick, _change_tick),)*)
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2022-10-26 13:16:25 +00:00
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unsafe fn clone_fetch<'w>(
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2022-11-03 16:33:05 +00:00
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fetch: &Self::Fetch<'w>,
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) -> Self::Fetch<'w> {
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let ($($name,)*) = &fetch;
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($($name::clone_fetch($name),)*)
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}
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2021-10-03 19:23:44 +00:00
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const IS_DENSE: bool = true $(&& $name::IS_DENSE)*;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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const IS_ARCHETYPAL: bool = true $(&& $name::IS_ARCHETYPAL)*;
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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#[inline]
|
2022-10-28 09:25:50 +00:00
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unsafe fn set_archetype<'w>(
|
2022-11-03 16:33:05 +00:00
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|
_fetch: &mut Self::Fetch<'w>,
|
2022-10-28 09:25:50 +00:00
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_state: &Self::State,
|
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_archetype: &'w Archetype,
|
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|
_table: &'w Table
|
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|
) {
|
2022-08-04 21:51:02 +00:00
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let ($($name,)*) = _fetch;
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
let ($($state,)*) = _state;
|
2022-10-28 09:25:50 +00:00
|
|
|
$($name::set_archetype($name, $state, _archetype, _table);)*
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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#[inline]
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2022-11-03 16:33:05 +00:00
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unsafe fn set_table<'w>(_fetch: &mut Self::Fetch<'w>, _state: &Self::State, _table: &'w Table) {
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let ($($name,)*) = _fetch;
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
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|
let ($($state,)*) = _state;
|
2022-08-04 21:51:02 +00:00
|
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$($name::set_table($name, $state, _table);)*
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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#[inline(always)]
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#[allow(clippy::unused_unit)]
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unsafe fn fetch<'w>(
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_fetch: &mut Self::Fetch<'w>,
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_entity: Entity,
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_table_row: TableRow
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) -> Self::Item<'w> {
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let ($($name,)*) = _fetch;
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($($name::fetch($name, _entity, _table_row),)*)
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Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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#[inline(always)]
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unsafe fn filter_fetch<'w>(
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_fetch: &mut Self::Fetch<'w>,
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_entity: Entity,
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_table_row: TableRow
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) -> bool {
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let ($($name,)*) = _fetch;
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true $(&& $name::filter_fetch($name, _entity, _table_row))*
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
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}
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Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
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|
|
fn update_component_access(state: &Self::State, _access: &mut FilteredAccess<ComponentId>) {
|
|
|
|
let ($($name,)*) = state;
|
|
|
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$($name::update_component_access($name, _access);)*
|
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|
}
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|
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|
|
|
|
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fn update_archetype_component_access(state: &Self::State, _archetype: &Archetype, _access: &mut Access<ArchetypeComponentId>) {
|
|
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|
let ($($name,)*) = state;
|
|
|
|
$($name::update_archetype_component_access($name, _archetype, _access);)*
|
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}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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2022-08-04 21:51:02 +00:00
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fn init_state(_world: &mut World) -> Self::State {
|
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|
|
($($name::init_state(_world),)*)
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn matches_component_set(state: &Self::State, _set_contains_id: &impl Fn(ComponentId) -> bool) -> bool {
|
|
|
|
let ($($name,)*) = state;
|
|
|
|
true $(&& $name::matches_component_set($name, _set_contains_id))*
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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}
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2021-04-22 19:09:09 +00:00
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/// SAFETY: each item in the tuple is read only
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
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unsafe impl<$($name: ReadOnlyWorldQuery),*> ReadOnlyWorldQuery for ($($name,)*) {}
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
|
|
|
|
|
|
|
};
|
|
|
|
}
|
|
|
|
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
/// The `AnyOf` query parameter fetches entities with any of the component types included in T.
|
|
|
|
///
|
2022-08-25 20:31:51 +00:00
|
|
|
/// `Query<AnyOf<(&A, &B, &mut C)>>` is equivalent to `Query<(Option<&A>, Option<&B>, Option<&mut C>), Or<(With<A>, With<B>, With<C>)>>`.
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
/// Each of the components in `T` is returned as an `Option`, as with `Option<A>` queries.
|
|
|
|
/// Entities are guaranteed to have at least one of the components in `T`.
|
2022-08-04 21:51:02 +00:00
|
|
|
pub struct AnyOf<T>(PhantomData<T>);
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
|
|
|
|
macro_rules! impl_anytuple_fetch {
|
|
|
|
($(($name: ident, $state: ident)),*) => {
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
#[allow(non_snake_case)]
|
2022-08-04 21:51:02 +00:00
|
|
|
#[allow(clippy::unused_unit)]
|
|
|
|
// SAFETY: defers to soundness of `$name: WorldQuery` impl
|
|
|
|
unsafe impl<$($name: WorldQuery),*> WorldQuery for AnyOf<($($name,)*)> {
|
2022-11-03 16:33:05 +00:00
|
|
|
type Fetch<'w> = ($(($name::Fetch<'w>, bool),)*);
|
|
|
|
type Item<'w> = ($(Option<$name::Item<'w>>,)*);
|
2022-08-04 21:51:02 +00:00
|
|
|
type ReadOnly = AnyOf<($($name::ReadOnly,)*)>;
|
|
|
|
type State = ($($name::State,)*);
|
|
|
|
|
2022-11-03 16:33:05 +00:00
|
|
|
fn shrink<'wlong: 'wshort, 'wshort>(item: Self::Item<'wlong>) -> Self::Item<'wshort> {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = item;
|
|
|
|
($(
|
|
|
|
$name.map($name::shrink),
|
|
|
|
)*)
|
|
|
|
}
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
|
|
|
|
#[allow(clippy::unused_unit)]
|
2022-11-03 16:33:05 +00:00
|
|
|
unsafe fn init_fetch<'w>(_world: &'w World, state: &Self::State, _last_change_tick: u32, _change_tick: u32) -> Self::Fetch<'w> {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = state;
|
|
|
|
($(($name::init_fetch(_world, $name, _last_change_tick, _change_tick), false),)*)
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
|
|
|
|
2022-10-26 13:16:25 +00:00
|
|
|
unsafe fn clone_fetch<'w>(
|
2022-11-03 16:33:05 +00:00
|
|
|
fetch: &Self::Fetch<'w>,
|
|
|
|
) -> Self::Fetch<'w> {
|
2022-10-26 13:16:25 +00:00
|
|
|
let ($($name,)*) = &fetch;
|
|
|
|
($(($name::clone_fetch(& $name.0), $name.1),)*)
|
|
|
|
}
|
|
|
|
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
const IS_DENSE: bool = true $(&& $name::IS_DENSE)*;
|
|
|
|
|
2022-04-27 18:02:06 +00:00
|
|
|
const IS_ARCHETYPAL: bool = true $(&& $name::IS_ARCHETYPAL)*;
|
|
|
|
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
#[inline]
|
2022-10-28 09:25:50 +00:00
|
|
|
unsafe fn set_archetype<'w>(
|
2022-11-03 16:33:05 +00:00
|
|
|
_fetch: &mut Self::Fetch<'w>,
|
2022-10-28 09:25:50 +00:00
|
|
|
_state: &Self::State,
|
|
|
|
_archetype: &'w Archetype,
|
|
|
|
_table: &'w Table
|
|
|
|
) {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = _fetch;
|
|
|
|
let ($($state,)*) = _state;
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
$(
|
2022-08-04 21:51:02 +00:00
|
|
|
$name.1 = $name::matches_component_set($state, &|id| _archetype.contains(id));
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
if $name.1 {
|
2022-10-28 09:25:50 +00:00
|
|
|
$name::set_archetype(&mut $name.0, $state, _archetype, _table);
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
|
|
|
)*
|
|
|
|
}
|
|
|
|
|
|
|
|
#[inline]
|
2022-11-03 16:33:05 +00:00
|
|
|
unsafe fn set_table<'w>(_fetch: &mut Self::Fetch<'w>, _state: &Self::State, _table: &'w Table) {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = _fetch;
|
|
|
|
let ($($state,)*) = _state;
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
$(
|
2022-08-04 21:51:02 +00:00
|
|
|
$name.1 = $name::matches_component_set($state, &|id| _table.has_column(id));
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
if $name.1 {
|
2022-08-04 21:51:02 +00:00
|
|
|
$name::set_table(&mut $name.0, $state, _table);
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
|
|
|
)*
|
|
|
|
}
|
|
|
|
|
2022-10-28 09:25:50 +00:00
|
|
|
#[inline(always)]
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
#[allow(clippy::unused_unit)]
|
2022-10-28 09:25:50 +00:00
|
|
|
unsafe fn fetch<'w>(
|
2022-11-03 16:33:05 +00:00
|
|
|
_fetch: &mut Self::Fetch<'w>,
|
2022-10-28 09:25:50 +00:00
|
|
|
_entity: Entity,
|
2022-12-06 01:38:21 +00:00
|
|
|
_table_row: TableRow
|
2022-11-03 16:33:05 +00:00
|
|
|
) -> Self::Item<'w> {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = _fetch;
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
($(
|
2022-10-28 09:25:50 +00:00
|
|
|
$name.1.then(|| $name::fetch(&mut $name.0, _entity, _table_row)),
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
)*)
|
|
|
|
}
|
|
|
|
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
fn update_component_access(state: &Self::State, _access: &mut FilteredAccess<ComponentId>) {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = state;
|
Fix unsoundness with `Or`/`AnyOf`/`Option` component access' (#4659)
# Objective
Fixes #4657
Example code that wasnt panic'ing before this PR (and so was unsound):
```rust
#[test]
#[should_panic = "error[B0001]"]
fn option_has_no_filter_with() {
fn sys(_1: Query<(Option<&A>, &mut B)>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
#[test]
#[should_panic = "error[B0001]"]
fn any_of_has_no_filter_with() {
fn sys(_1: Query<(AnyOf<(&A, ())>, &mut B)>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
#[test]
#[should_panic = "error[B0001]"]
fn or_has_no_filter_with() {
fn sys(_1: Query<&mut B, Or<(With<A>, With<B>)>>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
```
## Solution
- Only add the intersection of `with`/`without` accesses of all the elements in `Or/AnyOf` to the world query's `FilteredAccess<ComponentId>` instead of the union.
- `Option`'s fix can be thought of the same way since its basically `AnyOf<T, ()>` but its impl is just simpler as `()` has no `with`/`without` accesses
---
## Changelog
- `Or`/`AnyOf`/`Option` will now report more query conflicts in order to fix unsoundness
## Migration Guide
- If you are now getting query conflicts from `Or`/`AnyOf`/`Option` rip to you and ur welcome for it now being caught
2022-05-18 20:57:24 +00:00
|
|
|
|
|
|
|
// We do not unconditionally add `$name`'s `with`/`without` accesses to `_access`
|
|
|
|
// as this would be unsound. For example the following two queries should conflict:
|
|
|
|
// - Query<(AnyOf<(&A, ())>, &mut B)>
|
|
|
|
// - Query<&mut B, Without<A>>
|
|
|
|
//
|
|
|
|
// If we were to unconditionally add `$name`'s `with`/`without` accesses then `AnyOf<(&A, ())>`
|
|
|
|
// would have a `With<A>` access which is incorrect as this `WorldQuery` will match entities that
|
|
|
|
// do not have the `A` component. This is the same logic as the `Or<...>: WorldQuery` impl.
|
|
|
|
//
|
|
|
|
// The correct thing to do here is to only add a `with`/`without` access to `_access` if all
|
|
|
|
// `$name` params have that `with`/`without` access. More jargony put- we add the intersection
|
|
|
|
// of all `with`/`without` accesses of the `$name` params to `_access`.
|
|
|
|
let mut _intersected_access = _access.clone();
|
|
|
|
let mut _not_first = false;
|
|
|
|
$(
|
|
|
|
if _not_first {
|
|
|
|
let mut intermediate = _access.clone();
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
$name::update_component_access($name, &mut intermediate);
|
Fix unsoundness with `Or`/`AnyOf`/`Option` component access' (#4659)
# Objective
Fixes #4657
Example code that wasnt panic'ing before this PR (and so was unsound):
```rust
#[test]
#[should_panic = "error[B0001]"]
fn option_has_no_filter_with() {
fn sys(_1: Query<(Option<&A>, &mut B)>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
#[test]
#[should_panic = "error[B0001]"]
fn any_of_has_no_filter_with() {
fn sys(_1: Query<(AnyOf<(&A, ())>, &mut B)>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
#[test]
#[should_panic = "error[B0001]"]
fn or_has_no_filter_with() {
fn sys(_1: Query<&mut B, Or<(With<A>, With<B>)>>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
```
## Solution
- Only add the intersection of `with`/`without` accesses of all the elements in `Or/AnyOf` to the world query's `FilteredAccess<ComponentId>` instead of the union.
- `Option`'s fix can be thought of the same way since its basically `AnyOf<T, ()>` but its impl is just simpler as `()` has no `with`/`without` accesses
---
## Changelog
- `Or`/`AnyOf`/`Option` will now report more query conflicts in order to fix unsoundness
## Migration Guide
- If you are now getting query conflicts from `Or`/`AnyOf`/`Option` rip to you and ur welcome for it now being caught
2022-05-18 20:57:24 +00:00
|
|
|
_intersected_access.extend_intersect_filter(&intermediate);
|
|
|
|
_intersected_access.extend_access(&intermediate);
|
|
|
|
} else {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
|
|
|
$name::update_component_access($name, &mut _intersected_access);
|
Fix unsoundness with `Or`/`AnyOf`/`Option` component access' (#4659)
# Objective
Fixes #4657
Example code that wasnt panic'ing before this PR (and so was unsound):
```rust
#[test]
#[should_panic = "error[B0001]"]
fn option_has_no_filter_with() {
fn sys(_1: Query<(Option<&A>, &mut B)>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
#[test]
#[should_panic = "error[B0001]"]
fn any_of_has_no_filter_with() {
fn sys(_1: Query<(AnyOf<(&A, ())>, &mut B)>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
#[test]
#[should_panic = "error[B0001]"]
fn or_has_no_filter_with() {
fn sys(_1: Query<&mut B, Or<(With<A>, With<B>)>>, _2: Query<&mut B, Without<A>>) {}
let mut world = World::default();
run_system(&mut world, sys);
}
```
## Solution
- Only add the intersection of `with`/`without` accesses of all the elements in `Or/AnyOf` to the world query's `FilteredAccess<ComponentId>` instead of the union.
- `Option`'s fix can be thought of the same way since its basically `AnyOf<T, ()>` but its impl is just simpler as `()` has no `with`/`without` accesses
---
## Changelog
- `Or`/`AnyOf`/`Option` will now report more query conflicts in order to fix unsoundness
## Migration Guide
- If you are now getting query conflicts from `Or`/`AnyOf`/`Option` rip to you and ur welcome for it now being caught
2022-05-18 20:57:24 +00:00
|
|
|
_not_first = true;
|
|
|
|
}
|
|
|
|
)*
|
|
|
|
|
|
|
|
*_access = _intersected_access;
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
|
|
|
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
fn update_archetype_component_access(state: &Self::State, _archetype: &Archetype, _access: &mut Access<ArchetypeComponentId>) {
|
2022-08-04 21:51:02 +00:00
|
|
|
let ($($name,)*) = state;
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
$(
|
2022-08-04 21:51:02 +00:00
|
|
|
if $name::matches_component_set($name, &|id| _archetype.contains(id)) {
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
$name::update_archetype_component_access($name, _archetype, _access);
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
|
|
|
)*
|
|
|
|
}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn init_state(_world: &mut World) -> Self::State {
|
|
|
|
($($name::init_state(_world),)*)
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn matches_component_set(_state: &Self::State, _set_contains_id: &impl Fn(ComponentId) -> bool) -> bool {
|
|
|
|
let ($($name,)*) = _state;
|
|
|
|
false $(|| $name::matches_component_set($name, _set_contains_id))*
|
Use lifetimed, type erased pointers in bevy_ecs (#3001)
# Objective
`bevy_ecs` has large amounts of unsafe code which is hard to get right and makes it difficult to audit for soundness.
## Solution
Introduce lifetimed, type-erased pointers: `Ptr<'a>` `PtrMut<'a>` `OwningPtr<'a>'` and `ThinSlicePtr<'a, T>` which are newtypes around a raw pointer with a lifetime and conceptually representing strong invariants about the pointee and validity of the pointer.
The process of converting bevy_ecs to use these has already caught multiple cases of unsound behavior.
## Changelog
TL;DR for release notes: `bevy_ecs` now uses lifetimed, type-erased pointers internally, significantly improving safety and legibility without sacrificing performance. This should have approximately no end user impact, unless you were meddling with the (unfortunately public) internals of `bevy_ecs`.
- `Fetch`, `FilterFetch` and `ReadOnlyFetch` trait no longer have a `'state` lifetime
- this was unneeded
- `ReadOnly/Fetch` associated types on `WorldQuery` are now on a new `WorldQueryGats<'world>` trait
- was required to work around lack of Generic Associated Types (we wish to express `type Fetch<'a>: Fetch<'a>`)
- `derive(WorldQuery)` no longer requires `'w` lifetime on struct
- this was unneeded, and improves the end user experience
- `EntityMut::get_unchecked_mut` returns `&'_ mut T` not `&'w mut T`
- allows easier use of unsafe API with less footguns, and can be worked around via lifetime transmutery as a user
- `Bundle::from_components` now takes a `ctx` parameter to pass to the `FnMut` closure
- required because closure return types can't borrow from captures
- `Fetch::init` takes `&'world World`, `Fetch::set_archetype` takes `&'world Archetype` and `&'world Tables`, `Fetch::set_table` takes `&'world Table`
- allows types implementing `Fetch` to store borrows into world
- `WorldQuery` trait now has a `shrink` fn to shorten the lifetime in `Fetch::<'a>::Item`
- this works around lack of subtyping of assoc types, rust doesnt allow you to turn `<T as Fetch<'static>>::Item'` into `<T as Fetch<'a>>::Item'`
- `QueryCombinationsIter` requires this
- Most types implementing `Fetch` now have a lifetime `'w`
- allows the fetches to store borrows of world data instead of using raw pointers
## Migration guide
- `EntityMut::get_unchecked_mut` returns a more restricted lifetime, there is no general way to migrate this as it depends on your code
- `Bundle::from_components` implementations must pass the `ctx` arg to `func`
- `Bundle::from_components` callers have to use a fn arg instead of closure captures for borrowing from world
- Remove lifetime args on `derive(WorldQuery)` structs as it is nonsensical
- `<Q as WorldQuery>::ReadOnly/Fetch` should be changed to either `RO/QueryFetch<'world>` or `<Q as WorldQueryGats<'world>>::ReadOnly/Fetch`
- `<F as Fetch<'w, 's>>` should be changed to `<F as Fetch<'w>>`
- Change the fn sigs of `Fetch::init/set_archetype/set_table` to match respective trait fn sigs
- Implement the required `fn shrink` on any `WorldQuery` implementations
- Move assoc types `Fetch` and `ReadOnlyFetch` on `WorldQuery` impls to `WorldQueryGats` impls
- Pass an appropriate `'world` lifetime to whatever fetch struct you are for some reason using
### Type inference regression
in some cases rustc may give spurrious errors when attempting to infer the `F` parameter on a query/querystate this can be fixed by manually specifying the type, i.e. `QueryState::new::<_, ()>(world)`. The error is rather confusing:
```rust=
error[E0271]: type mismatch resolving `<() as Fetch<'_>>::Item == bool`
--> crates/bevy_pbr/src/render/light.rs:1413:30
|
1413 | main_view_query: QueryState::new(world),
| ^^^^^^^^^^^^^^^ expected `bool`, found `()`
|
= note: required because of the requirements on the impl of `for<'x> FilterFetch<'x>` for `<() as WorldQueryGats<'x>>::Fetch`
note: required by a bound in `bevy_ecs::query::QueryState::<Q, F>::new`
--> crates/bevy_ecs/src/query/state.rs:49:32
|
49 | for<'x> QueryFetch<'x, F>: FilterFetch<'x>,
| ^^^^^^^^^^^^^^^ required by this bound in `bevy_ecs::query::QueryState::<Q, F>::new`
```
---
Made with help from @BoxyUwU and @alice-i-cecile
Co-authored-by: Boxy <supbscripter@gmail.com>
2022-04-27 23:44:06 +00:00
|
|
|
}
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
/// SAFETY: each item in the tuple is read only
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
unsafe impl<$($name: ReadOnlyWorldQuery),*> ReadOnlyWorldQuery for AnyOf<($($name,)*)> {}
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
|
|
|
|
|
|
|
};
|
|
|
|
}
|
|
|
|
|
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
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all_tuples!(impl_tuple_fetch, 0, 15, F, S);
|
Implement AnyOf queries (#2889)
Implements a new Queryable called AnyOf, which will return an item as long as at least one of it's requested Queryables returns something. For example, a `Query<AnyOf<(&A, &B, &C)>>` will return items with type `(Option<&A>, Option<&B>, Option<&C>)`, and will guarantee that for every element at least one of the option s is Some. This is a shorthand for queries like `Query<(Option<&A>, Option<&B>, Option<&C>), Or<(With<A>, With<B>, With&C>)>>`.
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-02-06 00:52:47 +00:00
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all_tuples!(impl_anytuple_fetch, 0, 15, F, S);
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2021-12-01 23:28:10 +00:00
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remove QF generics from all `Query/State` methods and types (#5170)
# Objective
remove `QF` generics from a bunch of types and methods on query related items. this has a few benefits:
- simplifies type signatures `fn iter(&self) -> QueryIter<'_, 's, Q::ReadOnly, F::ReadOnly>` is (imo) conceptually simpler than `fn iter(&self) -> QueryIter<'_, 's, Q, ROQueryFetch<'_, Q>, F>`
- `Fetch` is mostly an implementation detail but previously we had to expose it on every `iter` `get` etc method
- Allows us to potentially in the future simplify the `WorldQuery` trait hierarchy by removing the `Fetch` trait
## Solution
remove the `QF` generic and add a way to (unsafely) turn `&QueryState<Q1, F1>` into `&QueryState<Q2, F2>`
---
## Changelog/Migration Guide
The `QF` generic was removed from various `Query` iterator types and some methods, you should update your code to use the type of the corresponding worldquery of the fetch type that was being used, or call `as_readonly`/`as_nop` to convert a querystate to the appropriate type. For example:
`.get_single_unchecked_manual::<ROQueryFetch<Q>>(..)` -> `.as_readonly().get_single_unchecked_manual(..)`
`my_field: QueryIter<'w, 's, Q, ROQueryFetch<'w, Q>, F>` -> `my_field: QueryIter<'w, 's, Q::ReadOnly, F::ReadOnly>`
2022-07-19 00:45:00 +00:00
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/// [`WorldQuery`] used to nullify queries by turning `Query<Q>` into `Query<NopWorldQuery<Q>>`
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///
|
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|
/// This will rarely be useful to consumers of `bevy_ecs`.
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pub struct NopWorldQuery<Q: WorldQuery>(PhantomData<Q>);
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/// SAFETY: `Self::ReadOnly` is `Self`
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unsafe impl<Q: WorldQuery> WorldQuery for NopWorldQuery<Q> {
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2022-11-03 16:33:05 +00:00
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type Fetch<'w> = ();
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type Item<'w> = ();
|
remove QF generics from all `Query/State` methods and types (#5170)
# Objective
remove `QF` generics from a bunch of types and methods on query related items. this has a few benefits:
- simplifies type signatures `fn iter(&self) -> QueryIter<'_, 's, Q::ReadOnly, F::ReadOnly>` is (imo) conceptually simpler than `fn iter(&self) -> QueryIter<'_, 's, Q, ROQueryFetch<'_, Q>, F>`
- `Fetch` is mostly an implementation detail but previously we had to expose it on every `iter` `get` etc method
- Allows us to potentially in the future simplify the `WorldQuery` trait hierarchy by removing the `Fetch` trait
## Solution
remove the `QF` generic and add a way to (unsafely) turn `&QueryState<Q1, F1>` into `&QueryState<Q2, F2>`
---
## Changelog/Migration Guide
The `QF` generic was removed from various `Query` iterator types and some methods, you should update your code to use the type of the corresponding worldquery of the fetch type that was being used, or call `as_readonly`/`as_nop` to convert a querystate to the appropriate type. For example:
`.get_single_unchecked_manual::<ROQueryFetch<Q>>(..)` -> `.as_readonly().get_single_unchecked_manual(..)`
`my_field: QueryIter<'w, 's, Q, ROQueryFetch<'w, Q>, F>` -> `my_field: QueryIter<'w, 's, Q::ReadOnly, F::ReadOnly>`
2022-07-19 00:45:00 +00:00
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type ReadOnly = Self;
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type State = Q::State;
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fn shrink<'wlong: 'wshort, 'wshort>(_: ()) {}
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2021-12-01 23:28:10 +00:00
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2022-08-04 21:51:02 +00:00
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const IS_DENSE: bool = Q::IS_DENSE;
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2021-12-01 23:28:10 +00:00
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2022-04-27 18:02:06 +00:00
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const IS_ARCHETYPAL: bool = true;
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2021-12-01 23:28:10 +00:00
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#[inline(always)]
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2022-08-04 21:51:02 +00:00
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unsafe fn init_fetch(
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_world: &World,
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_state: &Q::State,
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2021-12-01 23:28:10 +00:00
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_last_change_tick: u32,
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_change_tick: u32,
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2022-08-04 21:51:02 +00:00
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) {
|
2021-12-01 23:28:10 +00:00
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|
|
}
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|
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2022-11-03 16:33:05 +00:00
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unsafe fn clone_fetch<'w>(_fetch: &Self::Fetch<'w>) -> Self::Fetch<'w> {}
|
2022-10-26 13:16:25 +00:00
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2021-12-01 23:28:10 +00:00
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#[inline(always)]
|
|
|
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unsafe fn set_archetype(
|
2022-08-04 21:51:02 +00:00
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|
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_fetch: &mut (),
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_state: &Q::State,
|
2021-12-01 23:28:10 +00:00
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_archetype: &Archetype,
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2022-10-28 09:25:50 +00:00
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_tables: &Table,
|
2021-12-01 23:28:10 +00:00
|
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) {
|
|
|
|
}
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|
|
|
#[inline(always)]
|
2022-08-04 21:51:02 +00:00
|
|
|
unsafe fn set_table<'w>(_fetch: &mut (), _state: &Q::State, _table: &Table) {}
|
2021-12-01 23:28:10 +00:00
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|
|
|
|
#[inline(always)]
|
2022-10-28 09:25:50 +00:00
|
|
|
unsafe fn fetch<'w>(
|
2022-11-03 16:33:05 +00:00
|
|
|
_fetch: &mut Self::Fetch<'w>,
|
2022-10-28 09:25:50 +00:00
|
|
|
_entity: Entity,
|
2022-12-06 01:38:21 +00:00
|
|
|
_table_row: TableRow,
|
2022-11-03 16:33:05 +00:00
|
|
|
) -> Self::Item<'w> {
|
2022-08-04 21:51:02 +00:00
|
|
|
}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
2022-08-04 21:51:02 +00:00
|
|
|
fn update_component_access(_state: &Q::State, _access: &mut FilteredAccess<ComponentId>) {}
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
|
|
|
|
fn update_archetype_component_access(
|
2022-08-04 21:51:02 +00:00
|
|
|
_state: &Q::State,
|
Replace `ReadOnlyFetch` with `ReadOnlyWorldQuery` (#4626)
# Objective
- Fix a type inference regression introduced by #3001
- Make read only bounds on world queries more user friendly
ptrification required you to write `Q::Fetch: ReadOnlyFetch` as `for<'w> QueryFetch<'w, Q>: ReadOnlyFetch` which has the same type inference problem as `for<'w> QueryFetch<'w, Q>: FilterFetch<'w>` had, i.e. the following code would error:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: WorldQuery>(a: Query<Q, ()>)
where
for<'w> QueryFetch<'w, Q>: ReadOnlyFetch,
{
}
```
`for<..>` bounds are also rather user unfriendly..
## Solution
Remove the `ReadOnlyFetch` trait in favour of a `ReadOnlyWorldQuery` trait, and remove `WorldQueryGats::ReadOnlyFetch` in favor of `WorldQuery::ReadOnly` allowing the previous code snippet to be written as:
```rust
#[derive(Component)]
struct Foo;
fn bar(a: Query<(&Foo, Without<Foo>)>) {
foo(a);
}
fn foo<Q: ReadOnlyWorldQuery>(a: Query<Q, ()>) {}
```
This avoids the `for<...>` bound which makes the code simpler and also fixes the type inference issue.
The reason for moving the two functions out of `FetchState` and into `WorldQuery` is to allow the world query `&mut T` to share a `State` with the `&T` world query so that it can have `type ReadOnly = &T`. Presumably it would be possible to instead have a `ReadOnlyRefMut<T>` world query and then do `type ReadOnly = ReadOnlyRefMut<T>` much like how (before this PR) we had a `ReadOnlyWriteFetch<T>`. A side benefit of the current solution in this PR is that it will likely make it easier in the future to support an API such as `Query<&mut T> -> Query<&T>`. The primary benefit IMO is just that `ReadOnlyRefMut<T>` and its associated fetch would have to reimplement all of the logic that the `&T` world query impl does but this solution avoids that :)
---
## Changelog/Migration Guide
The trait `ReadOnlyFetch` has been replaced with `ReadOnlyWorldQuery` along with the `WorldQueryGats::ReadOnlyFetch` assoc type which has been replaced with `<WorldQuery::ReadOnly as WorldQueryGats>::Fetch`
- Any where clauses such as `QueryFetch<Q>: ReadOnlyFetch` should be replaced with `Q: ReadOnlyWorldQuery`.
- Any custom world query impls should implement `ReadOnlyWorldQuery` insead of `ReadOnlyFetch`
Functions `update_component_access` and `update_archetype_component_access` have been moved from the `FetchState` trait to `WorldQuery`
- Any callers should now call `Q::update_component_access(state` instead of `state.update_component_access` (and `update_archetype_component_access` respectively)
- Any custom world query impls should move the functions from the `FetchState` impl to `WorldQuery` impl
`WorldQuery` has been made an `unsafe trait`, `FetchState` has been made a safe `trait`. (I think this is how it should have always been, but regardless this is _definitely_ necessary now that the two functions have been moved to `WorldQuery`)
- If you have a custom `FetchState` impl make it a normal `impl` instead of `unsafe impl`
- If you have a custom `WorldQuery` impl make it an `unsafe impl`, if your code was sound before it is going to still be sound
2022-06-13 23:35:54 +00:00
|
|
|
_archetype: &Archetype,
|
|
|
|
_access: &mut Access<ArchetypeComponentId>,
|
|
|
|
) {
|
|
|
|
}
|
2022-08-04 21:51:02 +00:00
|
|
|
|
|
|
|
fn init_state(world: &mut World) -> Self::State {
|
|
|
|
Q::init_state(world)
|
|
|
|
}
|
|
|
|
|
|
|
|
fn matches_component_set(
|
|
|
|
state: &Self::State,
|
|
|
|
set_contains_id: &impl Fn(ComponentId) -> bool,
|
|
|
|
) -> bool {
|
|
|
|
Q::matches_component_set(state, set_contains_id)
|
|
|
|
}
|
2021-12-01 23:28:10 +00:00
|
|
|
}
|
2022-08-04 21:51:02 +00:00
|
|
|
|
|
|
|
/// SAFETY: `NopFetch` never accesses any data
|
|
|
|
unsafe impl<Q: WorldQuery> ReadOnlyWorldQuery for NopWorldQuery<Q> {}
|