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
use crate ::{
2024-04-22 16:37:42 +00:00
batching ::BatchingStrategy ,
2024-02-19 19:04:47 +00:00
component ::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
entity ::Entity ,
query ::{
2024-04-22 16:37:42 +00:00
QueryCombinationIter , QueryData , QueryEntityError , QueryFilter , QueryIter , QueryManyIter ,
QueryParIter , QuerySingleError , QueryState , ROQueryItem , ReadOnlyQueryData ,
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
} ,
2024-02-19 19:04:47 +00:00
world ::unsafe_world_cell ::UnsafeWorldCell ,
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
} ;
2024-09-28 19:35:27 +00:00
use core ::{
borrow ::Borrow ,
marker ::PhantomData ,
ops ::{ Deref , DerefMut } ,
} ;
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
2022-09-02 12:57:39 +00:00
/// [System parameter] that provides selective access to the [`Component`] data stored in a [`World`].
2021-04-22 19:09:09 +00:00
///
2022-09-02 12:57:39 +00:00
/// Enables access to [entity identifiers] and [components] from a system, without the need to directly access the world.
/// Its iterators and getter methods return *query items*.
/// Each query item is a type containing data relative to an entity.
2021-04-22 19:09:09 +00:00
///
Split WorldQuery into WorldQueryData and WorldQueryFilter (#9918)
# Objective
- Fixes #7680
- This is an updated for https://github.com/bevyengine/bevy/pull/8899
which had the same objective but fell a long way behind the latest
changes
## Solution
The traits `WorldQueryData : WorldQuery` and `WorldQueryFilter :
WorldQuery` have been added and some of the types and functions from
`WorldQuery` has been moved into them.
`ReadOnlyWorldQuery` has been replaced with `ReadOnlyWorldQueryData`.
`WorldQueryFilter` is safe (as long as `WorldQuery` is implemented
safely).
`WorldQueryData` is unsafe - safely implementing it requires that
`Self::ReadOnly` is a readonly version of `Self` (this used to be a
safety requirement of `WorldQuery`)
The type parameters `Q` and `F` of `Query` must now implement
`WorldQueryData` and `WorldQueryFilter` respectively.
This makes it impossible to accidentally use a filter in the data
position or vice versa which was something that could lead to bugs.
~~Compile failure tests have been added to check this.~~
It was previously sometimes useful to use `Option<With<T>>` in the data
position. Use `Has<T>` instead in these cases.
The `WorldQuery` derive macro has been split into separate derive macros
for `WorldQueryData` and `WorldQueryFilter`.
Previously it was possible to derive both `WorldQuery` for a struct that
had a mixture of data and filter items. This would not work correctly in
some cases but could be a useful pattern in others. *This is no longer
possible.*
---
## Notes
- The changes outside of `bevy_ecs` are all changing type parameters to
the new types, updating the macro use, or replacing `Option<With<T>>`
with `Has<T>`.
- All `WorldQueryData` types always returned `true` for `IS_ARCHETYPAL`
so I moved it to `WorldQueryFilter` and
replaced all calls to it with `true`. That should be the only logic
change outside of the macro generation code.
- `Changed<T>` and `Added<T>` were being generated by a macro that I
have expanded. Happy to revert that if desired.
- The two derive macros share some functions for implementing
`WorldQuery` but the tidiest way I could find to implement them was to
give them a ton of arguments and ask clippy to ignore that.
## Changelog
### Changed
- Split `WorldQuery` into `WorldQueryData` and `WorldQueryFilter` which
now have separate derive macros. It is not possible to derive both for
the same type.
- `Query` now requires that the first type argument implements
`WorldQueryData` and the second implements `WorldQueryFilter`
## Migration Guide
- Update derives
```rust
// old
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct CustomQuery {
entity: Entity,
a: &'static mut ComponentA
}
#[derive(WorldQuery)]
struct QueryFilter {
_c: With<ComponentC>
}
// new
#[derive(WorldQueryData)]
#[world_query_data(mutable, derive(Debug))]
struct CustomQuery {
entity: Entity,
a: &'static mut ComponentA,
}
#[derive(WorldQueryFilter)]
struct QueryFilter {
_c: With<ComponentC>
}
```
- Replace `Option<With<T>>` with `Has<T>`
```rust
/// old
fn my_system(query: Query<(Entity, Option<With<ComponentA>>)>)
{
for (entity, has_a_option) in query.iter(){
let has_a:bool = has_a_option.is_some();
//todo!()
}
}
/// new
fn my_system(query: Query<(Entity, Has<ComponentA>)>)
{
for (entity, has_a) in query.iter(){
//todo!()
}
}
```
- Fix queries which had filters in the data position or vice versa.
```rust
// old
fn my_system(query: Query<(Entity, With<ComponentA>)>)
{
for (entity, _) in query.iter(){
//todo!()
}
}
// new
fn my_system(query: Query<Entity, With<ComponentA>>)
{
for entity in query.iter(){
//todo!()
}
}
// old
fn my_system(query: Query<AnyOf<(&ComponentA, With<ComponentB>)>>)
{
for (entity, _) in query.iter(){
//todo!()
}
}
// new
fn my_system(query: Query<Option<&ComponentA>, Or<(With<ComponentA>, With<ComponentB>)>>)
{
for entity in query.iter(){
//todo!()
}
}
```
---------
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
2023-11-28 03:56:07 +00:00
/// `Query` is a generic data structure that accepts two type parameters:
2021-04-22 19:09:09 +00:00
///
2023-12-13 18:50:46 +00:00
/// - **`D` (query data).**
2022-09-02 12:57:39 +00:00
/// The type of data contained in the query item.
/// Only entities that match the requested data will generate an item.
Rename `WorldQueryData` & `WorldQueryFilter` to `QueryData` & `QueryFilter` (#10779)
# Rename `WorldQueryData` & `WorldQueryFilter` to `QueryData` &
`QueryFilter`
Fixes #10776
## Solution
Traits `WorldQueryData` & `WorldQueryFilter` were renamed to `QueryData`
and `QueryFilter`, respectively. Related Trait types were also renamed.
---
## Changelog
- Trait `WorldQueryData` has been renamed to `QueryData`. Derive macro's
`QueryData` attribute `world_query_data` has been renamed to
`query_data`.
- Trait `WorldQueryFilter` has been renamed to `QueryFilter`. Derive
macro's `QueryFilter` attribute `world_query_filter` has been renamed to
`query_filter`.
- Trait's `ExtractComponent` type `Query` has been renamed to `Data`.
- Trait's `GetBatchData` types `Query` & `QueryFilter` has been renamed
to `Data` & `Filter`, respectively.
- Trait's `ExtractInstance` type `Query` has been renamed to `Data`.
- Trait's `ViewNode` type `ViewQuery` has been renamed to `ViewData`.
- Trait's `RenderCommand` types `ViewWorldQuery` & `ItemWorldQuery` has
been renamed to `ViewData` & `ItemData`, respectively.
## Migration Guide
Note: if merged before 0.13 is released, this should instead modify the
migration guide of #10776 with the updated names.
- Rename `WorldQueryData` & `WorldQueryFilter` trait usages to
`QueryData` & `QueryFilter` and their respective derive macro attributes
`world_query_data` & `world_query_filter` to `query_data` &
`query_filter`.
- Rename the following trait type usages:
- Trait's `ExtractComponent` type `Query` to `Data`.
- Trait's `GetBatchData` type `Query` to `Data`.
- Trait's `ExtractInstance` type `Query` to `Data`.
- Trait's `ViewNode` type `ViewQuery` to `ViewData`'
- Trait's `RenderCommand` types `ViewWolrdQuery` & `ItemWorldQuery` to
`ViewData` & `ItemData`, respectively.
```rust
// Before
#[derive(WorldQueryData)]
#[world_query_data(derive(Debug))]
struct EmptyQuery {
empty: (),
}
// After
#[derive(QueryData)]
#[query_data(derive(Debug))]
struct EmptyQuery {
empty: (),
}
// Before
#[derive(WorldQueryFilter)]
struct CustomQueryFilter<T: Component, P: Component> {
_c: With<ComponentC>,
_d: With<ComponentD>,
_or: Or<(Added<ComponentC>, Changed<ComponentD>, Without<ComponentZ>)>,
_generic_tuple: (With<T>, With<P>),
}
// After
#[derive(QueryFilter)]
struct CustomQueryFilter<T: Component, P: Component> {
_c: With<ComponentC>,
_d: With<ComponentD>,
_or: Or<(Added<ComponentC>, Changed<ComponentD>, Without<ComponentZ>)>,
_generic_tuple: (With<T>, With<P>),
}
// Before
impl ExtractComponent for ContrastAdaptiveSharpeningSettings {
type Query = &'static Self;
type Filter = With<Camera>;
type Out = (DenoiseCAS, CASUniform);
fn extract_component(item: QueryItem<Self::Query>) -> Option<Self::Out> {
//...
}
}
// After
impl ExtractComponent for ContrastAdaptiveSharpeningSettings {
type Data = &'static Self;
type Filter = With<Camera>;
type Out = (DenoiseCAS, CASUniform);
fn extract_component(item: QueryItem<Self::Data>) -> Option<Self::Out> {
//...
}
}
// Before
impl GetBatchData for MeshPipeline {
type Param = SRes<RenderMeshInstances>;
type Query = Entity;
type QueryFilter = With<Mesh3d>;
type CompareData = (MaterialBindGroupId, AssetId<Mesh>);
type BufferData = MeshUniform;
fn get_batch_data(
mesh_instances: &SystemParamItem<Self::Param>,
entity: &QueryItem<Self::Query>,
) -> (Self::BufferData, Option<Self::CompareData>) {
// ....
}
}
// After
impl GetBatchData for MeshPipeline {
type Param = SRes<RenderMeshInstances>;
type Data = Entity;
type Filter = With<Mesh3d>;
type CompareData = (MaterialBindGroupId, AssetId<Mesh>);
type BufferData = MeshUniform;
fn get_batch_data(
mesh_instances: &SystemParamItem<Self::Param>,
entity: &QueryItem<Self::Data>,
) -> (Self::BufferData, Option<Self::CompareData>) {
// ....
}
}
// Before
impl<A> ExtractInstance for AssetId<A>
where
A: Asset,
{
type Query = Read<Handle<A>>;
type Filter = ();
fn extract(item: QueryItem<'_, Self::Query>) -> Option<Self> {
Some(item.id())
}
}
// After
impl<A> ExtractInstance for AssetId<A>
where
A: Asset,
{
type Data = Read<Handle<A>>;
type Filter = ();
fn extract(item: QueryItem<'_, Self::Data>) -> Option<Self> {
Some(item.id())
}
}
// Before
impl ViewNode for PostProcessNode {
type ViewQuery = (
&'static ViewTarget,
&'static PostProcessSettings,
);
fn run(
&self,
_graph: &mut RenderGraphContext,
render_context: &mut RenderContext,
(view_target, _post_process_settings): QueryItem<Self::ViewQuery>,
world: &World,
) -> Result<(), NodeRunError> {
// ...
}
}
// After
impl ViewNode for PostProcessNode {
type ViewData = (
&'static ViewTarget,
&'static PostProcessSettings,
);
fn run(
&self,
_graph: &mut RenderGraphContext,
render_context: &mut RenderContext,
(view_target, _post_process_settings): QueryItem<Self::ViewData>,
world: &World,
) -> Result<(), NodeRunError> {
// ...
}
}
// Before
impl<P: CachedRenderPipelinePhaseItem> RenderCommand<P> for SetItemPipeline {
type Param = SRes<PipelineCache>;
type ViewWorldQuery = ();
type ItemWorldQuery = ();
#[inline]
fn render<'w>(
item: &P,
_view: (),
_entity: (),
pipeline_cache: SystemParamItem<'w, '_, Self::Param>,
pass: &mut TrackedRenderPass<'w>,
) -> RenderCommandResult {
// ...
}
}
// After
impl<P: CachedRenderPipelinePhaseItem> RenderCommand<P> for SetItemPipeline {
type Param = SRes<PipelineCache>;
type ViewData = ();
type ItemData = ();
#[inline]
fn render<'w>(
item: &P,
_view: (),
_entity: (),
pipeline_cache: SystemParamItem<'w, '_, Self::Param>,
pass: &mut TrackedRenderPass<'w>,
) -> RenderCommandResult {
// ...
}
}
```
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/// Must implement the [`QueryData`] trait.
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/// - **`F` (query filter).**
/// A set of conditions that determines whether query items should be kept or discarded.
Rename `WorldQueryData` & `WorldQueryFilter` to `QueryData` & `QueryFilter` (#10779)
# Rename `WorldQueryData` & `WorldQueryFilter` to `QueryData` &
`QueryFilter`
Fixes #10776
## Solution
Traits `WorldQueryData` & `WorldQueryFilter` were renamed to `QueryData`
and `QueryFilter`, respectively. Related Trait types were also renamed.
---
## Changelog
- Trait `WorldQueryData` has been renamed to `QueryData`. Derive macro's
`QueryData` attribute `world_query_data` has been renamed to
`query_data`.
- Trait `WorldQueryFilter` has been renamed to `QueryFilter`. Derive
macro's `QueryFilter` attribute `world_query_filter` has been renamed to
`query_filter`.
- Trait's `ExtractComponent` type `Query` has been renamed to `Data`.
- Trait's `GetBatchData` types `Query` & `QueryFilter` has been renamed
to `Data` & `Filter`, respectively.
- Trait's `ExtractInstance` type `Query` has been renamed to `Data`.
- Trait's `ViewNode` type `ViewQuery` has been renamed to `ViewData`.
- Trait's `RenderCommand` types `ViewWorldQuery` & `ItemWorldQuery` has
been renamed to `ViewData` & `ItemData`, respectively.
## Migration Guide
Note: if merged before 0.13 is released, this should instead modify the
migration guide of #10776 with the updated names.
- Rename `WorldQueryData` & `WorldQueryFilter` trait usages to
`QueryData` & `QueryFilter` and their respective derive macro attributes
`world_query_data` & `world_query_filter` to `query_data` &
`query_filter`.
- Rename the following trait type usages:
- Trait's `ExtractComponent` type `Query` to `Data`.
- Trait's `GetBatchData` type `Query` to `Data`.
- Trait's `ExtractInstance` type `Query` to `Data`.
- Trait's `ViewNode` type `ViewQuery` to `ViewData`'
- Trait's `RenderCommand` types `ViewWolrdQuery` & `ItemWorldQuery` to
`ViewData` & `ItemData`, respectively.
```rust
// Before
#[derive(WorldQueryData)]
#[world_query_data(derive(Debug))]
struct EmptyQuery {
empty: (),
}
// After
#[derive(QueryData)]
#[query_data(derive(Debug))]
struct EmptyQuery {
empty: (),
}
// Before
#[derive(WorldQueryFilter)]
struct CustomQueryFilter<T: Component, P: Component> {
_c: With<ComponentC>,
_d: With<ComponentD>,
_or: Or<(Added<ComponentC>, Changed<ComponentD>, Without<ComponentZ>)>,
_generic_tuple: (With<T>, With<P>),
}
// After
#[derive(QueryFilter)]
struct CustomQueryFilter<T: Component, P: Component> {
_c: With<ComponentC>,
_d: With<ComponentD>,
_or: Or<(Added<ComponentC>, Changed<ComponentD>, Without<ComponentZ>)>,
_generic_tuple: (With<T>, With<P>),
}
// Before
impl ExtractComponent for ContrastAdaptiveSharpeningSettings {
type Query = &'static Self;
type Filter = With<Camera>;
type Out = (DenoiseCAS, CASUniform);
fn extract_component(item: QueryItem<Self::Query>) -> Option<Self::Out> {
//...
}
}
// After
impl ExtractComponent for ContrastAdaptiveSharpeningSettings {
type Data = &'static Self;
type Filter = With<Camera>;
type Out = (DenoiseCAS, CASUniform);
fn extract_component(item: QueryItem<Self::Data>) -> Option<Self::Out> {
//...
}
}
// Before
impl GetBatchData for MeshPipeline {
type Param = SRes<RenderMeshInstances>;
type Query = Entity;
type QueryFilter = With<Mesh3d>;
type CompareData = (MaterialBindGroupId, AssetId<Mesh>);
type BufferData = MeshUniform;
fn get_batch_data(
mesh_instances: &SystemParamItem<Self::Param>,
entity: &QueryItem<Self::Query>,
) -> (Self::BufferData, Option<Self::CompareData>) {
// ....
}
}
// After
impl GetBatchData for MeshPipeline {
type Param = SRes<RenderMeshInstances>;
type Data = Entity;
type Filter = With<Mesh3d>;
type CompareData = (MaterialBindGroupId, AssetId<Mesh>);
type BufferData = MeshUniform;
fn get_batch_data(
mesh_instances: &SystemParamItem<Self::Param>,
entity: &QueryItem<Self::Data>,
) -> (Self::BufferData, Option<Self::CompareData>) {
// ....
}
}
// Before
impl<A> ExtractInstance for AssetId<A>
where
A: Asset,
{
type Query = Read<Handle<A>>;
type Filter = ();
fn extract(item: QueryItem<'_, Self::Query>) -> Option<Self> {
Some(item.id())
}
}
// After
impl<A> ExtractInstance for AssetId<A>
where
A: Asset,
{
type Data = Read<Handle<A>>;
type Filter = ();
fn extract(item: QueryItem<'_, Self::Data>) -> Option<Self> {
Some(item.id())
}
}
// Before
impl ViewNode for PostProcessNode {
type ViewQuery = (
&'static ViewTarget,
&'static PostProcessSettings,
);
fn run(
&self,
_graph: &mut RenderGraphContext,
render_context: &mut RenderContext,
(view_target, _post_process_settings): QueryItem<Self::ViewQuery>,
world: &World,
) -> Result<(), NodeRunError> {
// ...
}
}
// After
impl ViewNode for PostProcessNode {
type ViewData = (
&'static ViewTarget,
&'static PostProcessSettings,
);
fn run(
&self,
_graph: &mut RenderGraphContext,
render_context: &mut RenderContext,
(view_target, _post_process_settings): QueryItem<Self::ViewData>,
world: &World,
) -> Result<(), NodeRunError> {
// ...
}
}
// Before
impl<P: CachedRenderPipelinePhaseItem> RenderCommand<P> for SetItemPipeline {
type Param = SRes<PipelineCache>;
type ViewWorldQuery = ();
type ItemWorldQuery = ();
#[inline]
fn render<'w>(
item: &P,
_view: (),
_entity: (),
pipeline_cache: SystemParamItem<'w, '_, Self::Param>,
pass: &mut TrackedRenderPass<'w>,
) -> RenderCommandResult {
// ...
}
}
// After
impl<P: CachedRenderPipelinePhaseItem> RenderCommand<P> for SetItemPipeline {
type Param = SRes<PipelineCache>;
type ViewData = ();
type ItemData = ();
#[inline]
fn render<'w>(
item: &P,
_view: (),
_entity: (),
pipeline_cache: SystemParamItem<'w, '_, Self::Param>,
pass: &mut TrackedRenderPass<'w>,
) -> RenderCommandResult {
// ...
}
}
```
2023-12-12 19:45:50 +00:00
/// Must implement the [`QueryFilter`] trait.
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/// This type parameter is optional.
2021-04-22 19:09:09 +00:00
///
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
/// [`World`]: crate::world::World
///
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/// # Similar parameters
///
/// [`Query`] has few sibling [`SystemParam`](crate::system::system_param::SystemParam)s, which perform additional validation:
/// - [`Single`] - Exactly one matching query item.
/// - [`Option<Single>`] - Zero or one matching query item.
/// - [`Populated`] - At least one matching query item.
///
/// Those parameters will prevent systems from running if their requirements aren't met.
///
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/// # System parameter declaration
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///
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/// A query should always be declared as a system parameter.
Split WorldQuery into WorldQueryData and WorldQueryFilter (#9918)
# Objective
- Fixes #7680
- This is an updated for https://github.com/bevyengine/bevy/pull/8899
which had the same objective but fell a long way behind the latest
changes
## Solution
The traits `WorldQueryData : WorldQuery` and `WorldQueryFilter :
WorldQuery` have been added and some of the types and functions from
`WorldQuery` has been moved into them.
`ReadOnlyWorldQuery` has been replaced with `ReadOnlyWorldQueryData`.
`WorldQueryFilter` is safe (as long as `WorldQuery` is implemented
safely).
`WorldQueryData` is unsafe - safely implementing it requires that
`Self::ReadOnly` is a readonly version of `Self` (this used to be a
safety requirement of `WorldQuery`)
The type parameters `Q` and `F` of `Query` must now implement
`WorldQueryData` and `WorldQueryFilter` respectively.
This makes it impossible to accidentally use a filter in the data
position or vice versa which was something that could lead to bugs.
~~Compile failure tests have been added to check this.~~
It was previously sometimes useful to use `Option<With<T>>` in the data
position. Use `Has<T>` instead in these cases.
The `WorldQuery` derive macro has been split into separate derive macros
for `WorldQueryData` and `WorldQueryFilter`.
Previously it was possible to derive both `WorldQuery` for a struct that
had a mixture of data and filter items. This would not work correctly in
some cases but could be a useful pattern in others. *This is no longer
possible.*
---
## Notes
- The changes outside of `bevy_ecs` are all changing type parameters to
the new types, updating the macro use, or replacing `Option<With<T>>`
with `Has<T>`.
- All `WorldQueryData` types always returned `true` for `IS_ARCHETYPAL`
so I moved it to `WorldQueryFilter` and
replaced all calls to it with `true`. That should be the only logic
change outside of the macro generation code.
- `Changed<T>` and `Added<T>` were being generated by a macro that I
have expanded. Happy to revert that if desired.
- The two derive macros share some functions for implementing
`WorldQuery` but the tidiest way I could find to implement them was to
give them a ton of arguments and ask clippy to ignore that.
## Changelog
### Changed
- Split `WorldQuery` into `WorldQueryData` and `WorldQueryFilter` which
now have separate derive macros. It is not possible to derive both for
the same type.
- `Query` now requires that the first type argument implements
`WorldQueryData` and the second implements `WorldQueryFilter`
## Migration Guide
- Update derives
```rust
// old
#[derive(WorldQuery)]
#[world_query(mutable, derive(Debug))]
struct CustomQuery {
entity: Entity,
a: &'static mut ComponentA
}
#[derive(WorldQuery)]
struct QueryFilter {
_c: With<ComponentC>
}
// new
#[derive(WorldQueryData)]
#[world_query_data(mutable, derive(Debug))]
struct CustomQuery {
entity: Entity,
a: &'static mut ComponentA,
}
#[derive(WorldQueryFilter)]
struct QueryFilter {
_c: With<ComponentC>
}
```
- Replace `Option<With<T>>` with `Has<T>`
```rust
/// old
fn my_system(query: Query<(Entity, Option<With<ComponentA>>)>)
{
for (entity, has_a_option) in query.iter(){
let has_a:bool = has_a_option.is_some();
//todo!()
}
}
/// new
fn my_system(query: Query<(Entity, Has<ComponentA>)>)
{
for (entity, has_a) in query.iter(){
//todo!()
}
}
```
- Fix queries which had filters in the data position or vice versa.
```rust
// old
fn my_system(query: Query<(Entity, With<ComponentA>)>)
{
for (entity, _) in query.iter(){
//todo!()
}
}
// new
fn my_system(query: Query<Entity, With<ComponentA>>)
{
for entity in query.iter(){
//todo!()
}
}
// old
fn my_system(query: Query<AnyOf<(&ComponentA, With<ComponentB>)>>)
{
for (entity, _) in query.iter(){
//todo!()
}
}
// new
fn my_system(query: Query<Option<&ComponentA>, Or<(With<ComponentA>, With<ComponentB>)>>)
{
for entity in query.iter(){
//todo!()
}
}
```
---------
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
2023-11-28 03:56:07 +00:00
/// This section shows the most common idioms involving the declaration of `Query`.
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///
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/// ## Component access
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///
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/// A query defined with a reference to a component as the query fetch type parameter can be used to generate items that refer to the data of said component.
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///
/// ```
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/// # use bevy_ecs::prelude::*;
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/// # #[derive(Component)]
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/// # struct ComponentA;
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/// # fn immutable_ref(
/// // A component can be accessed by shared reference...
/// query: Query<&ComponentA>
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/// # ) {}
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/// # bevy_ecs::system::assert_is_system(immutable_ref);
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///
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/// # fn mutable_ref(
/// // ... or by mutable reference.
/// query: Query<&mut ComponentA>
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/// # ) {}
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/// # bevy_ecs::system::assert_is_system(mutable_ref);
2021-04-22 19:09:09 +00:00
/// ```
///
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/// ## Query filtering
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///
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/// Setting the query filter type parameter will ensure that each query item satisfies the given condition.
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///
/// ```
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct ComponentA;
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/// # #[derive(Component)]
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/// # struct ComponentB;
/// # fn system(
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/// // Just `ComponentA` data will be accessed, but only for entities that also contain
/// // `ComponentB`.
/// query: Query<&ComponentA, With<ComponentB>>
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/// # ) {}
2022-02-08 04:00:58 +00:00
/// # bevy_ecs::system::assert_is_system(system);
2021-09-17 18:00:29 +00:00
/// ```
///
Rename `WorldQueryData` & `WorldQueryFilter` to `QueryData` & `QueryFilter` (#10779)
# Rename `WorldQueryData` & `WorldQueryFilter` to `QueryData` &
`QueryFilter`
Fixes #10776
## Solution
Traits `WorldQueryData` & `WorldQueryFilter` were renamed to `QueryData`
and `QueryFilter`, respectively. Related Trait types were also renamed.
---
## Changelog
- Trait `WorldQueryData` has been renamed to `QueryData`. Derive macro's
`QueryData` attribute `world_query_data` has been renamed to
`query_data`.
- Trait `WorldQueryFilter` has been renamed to `QueryFilter`. Derive
macro's `QueryFilter` attribute `world_query_filter` has been renamed to
`query_filter`.
- Trait's `ExtractComponent` type `Query` has been renamed to `Data`.
- Trait's `GetBatchData` types `Query` & `QueryFilter` has been renamed
to `Data` & `Filter`, respectively.
- Trait's `ExtractInstance` type `Query` has been renamed to `Data`.
- Trait's `ViewNode` type `ViewQuery` has been renamed to `ViewData`.
- Trait's `RenderCommand` types `ViewWorldQuery` & `ItemWorldQuery` has
been renamed to `ViewData` & `ItemData`, respectively.
## Migration Guide
Note: if merged before 0.13 is released, this should instead modify the
migration guide of #10776 with the updated names.
- Rename `WorldQueryData` & `WorldQueryFilter` trait usages to
`QueryData` & `QueryFilter` and their respective derive macro attributes
`world_query_data` & `world_query_filter` to `query_data` &
`query_filter`.
- Rename the following trait type usages:
- Trait's `ExtractComponent` type `Query` to `Data`.
- Trait's `GetBatchData` type `Query` to `Data`.
- Trait's `ExtractInstance` type `Query` to `Data`.
- Trait's `ViewNode` type `ViewQuery` to `ViewData`'
- Trait's `RenderCommand` types `ViewWolrdQuery` & `ItemWorldQuery` to
`ViewData` & `ItemData`, respectively.
```rust
// Before
#[derive(WorldQueryData)]
#[world_query_data(derive(Debug))]
struct EmptyQuery {
empty: (),
}
// After
#[derive(QueryData)]
#[query_data(derive(Debug))]
struct EmptyQuery {
empty: (),
}
// Before
#[derive(WorldQueryFilter)]
struct CustomQueryFilter<T: Component, P: Component> {
_c: With<ComponentC>,
_d: With<ComponentD>,
_or: Or<(Added<ComponentC>, Changed<ComponentD>, Without<ComponentZ>)>,
_generic_tuple: (With<T>, With<P>),
}
// After
#[derive(QueryFilter)]
struct CustomQueryFilter<T: Component, P: Component> {
_c: With<ComponentC>,
_d: With<ComponentD>,
_or: Or<(Added<ComponentC>, Changed<ComponentD>, Without<ComponentZ>)>,
_generic_tuple: (With<T>, With<P>),
}
// Before
impl ExtractComponent for ContrastAdaptiveSharpeningSettings {
type Query = &'static Self;
type Filter = With<Camera>;
type Out = (DenoiseCAS, CASUniform);
fn extract_component(item: QueryItem<Self::Query>) -> Option<Self::Out> {
//...
}
}
// After
impl ExtractComponent for ContrastAdaptiveSharpeningSettings {
type Data = &'static Self;
type Filter = With<Camera>;
type Out = (DenoiseCAS, CASUniform);
fn extract_component(item: QueryItem<Self::Data>) -> Option<Self::Out> {
//...
}
}
// Before
impl GetBatchData for MeshPipeline {
type Param = SRes<RenderMeshInstances>;
type Query = Entity;
type QueryFilter = With<Mesh3d>;
type CompareData = (MaterialBindGroupId, AssetId<Mesh>);
type BufferData = MeshUniform;
fn get_batch_data(
mesh_instances: &SystemParamItem<Self::Param>,
entity: &QueryItem<Self::Query>,
) -> (Self::BufferData, Option<Self::CompareData>) {
// ....
}
}
// After
impl GetBatchData for MeshPipeline {
type Param = SRes<RenderMeshInstances>;
type Data = Entity;
type Filter = With<Mesh3d>;
type CompareData = (MaterialBindGroupId, AssetId<Mesh>);
type BufferData = MeshUniform;
fn get_batch_data(
mesh_instances: &SystemParamItem<Self::Param>,
entity: &QueryItem<Self::Data>,
) -> (Self::BufferData, Option<Self::CompareData>) {
// ....
}
}
// Before
impl<A> ExtractInstance for AssetId<A>
where
A: Asset,
{
type Query = Read<Handle<A>>;
type Filter = ();
fn extract(item: QueryItem<'_, Self::Query>) -> Option<Self> {
Some(item.id())
}
}
// After
impl<A> ExtractInstance for AssetId<A>
where
A: Asset,
{
type Data = Read<Handle<A>>;
type Filter = ();
fn extract(item: QueryItem<'_, Self::Data>) -> Option<Self> {
Some(item.id())
}
}
// Before
impl ViewNode for PostProcessNode {
type ViewQuery = (
&'static ViewTarget,
&'static PostProcessSettings,
);
fn run(
&self,
_graph: &mut RenderGraphContext,
render_context: &mut RenderContext,
(view_target, _post_process_settings): QueryItem<Self::ViewQuery>,
world: &World,
) -> Result<(), NodeRunError> {
// ...
}
}
// After
impl ViewNode for PostProcessNode {
type ViewData = (
&'static ViewTarget,
&'static PostProcessSettings,
);
fn run(
&self,
_graph: &mut RenderGraphContext,
render_context: &mut RenderContext,
(view_target, _post_process_settings): QueryItem<Self::ViewData>,
world: &World,
) -> Result<(), NodeRunError> {
// ...
}
}
// Before
impl<P: CachedRenderPipelinePhaseItem> RenderCommand<P> for SetItemPipeline {
type Param = SRes<PipelineCache>;
type ViewWorldQuery = ();
type ItemWorldQuery = ();
#[inline]
fn render<'w>(
item: &P,
_view: (),
_entity: (),
pipeline_cache: SystemParamItem<'w, '_, Self::Param>,
pass: &mut TrackedRenderPass<'w>,
) -> RenderCommandResult {
// ...
}
}
// After
impl<P: CachedRenderPipelinePhaseItem> RenderCommand<P> for SetItemPipeline {
type Param = SRes<PipelineCache>;
type ViewData = ();
type ItemData = ();
#[inline]
fn render<'w>(
item: &P,
_view: (),
_entity: (),
pipeline_cache: SystemParamItem<'w, '_, Self::Param>,
pass: &mut TrackedRenderPass<'w>,
) -> RenderCommandResult {
// ...
}
}
```
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/// ## `QueryData` or `QueryFilter` tuples
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///
/// Using tuples, each `Query` type parameter can contain multiple elements.
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///
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/// In the following example, two components are accessed simultaneously, and the query items are filtered on two conditions.
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///
/// ```
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct ComponentA;
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/// # #[derive(Component)]
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/// # struct ComponentB;
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/// # #[derive(Component)]
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/// # struct ComponentC;
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/// # #[derive(Component)]
/// # struct ComponentD;
/// # fn immutable_ref(
/// query: Query<(&ComponentA, &ComponentB), (With<ComponentC>, Without<ComponentD>)>
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/// # ) {}
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/// # bevy_ecs::system::assert_is_system(immutable_ref);
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/// ```
///
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/// ## Entity identifier access
///
/// The identifier of an entity can be made available inside the query item by including [`Entity`] in the query fetch type parameter.
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///
/// ```
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct ComponentA;
/// # fn system(
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/// query: Query<(Entity, &ComponentA)>
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/// # ) {}
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/// # bevy_ecs::system::assert_is_system(system);
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/// ```
///
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/// ## Optional component access
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///
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/// A component can be made optional in a query by wrapping it into an [`Option`].
/// In this way, a query item can still be generated even if the queried entity does not contain the wrapped component.
/// In this case, its corresponding value will be `None`.
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///
/// ```
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct ComponentA;
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/// # #[derive(Component)]
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/// # struct ComponentB;
/// # fn system(
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/// // Generates items for entities that contain `ComponentA`, and optionally `ComponentB`.
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/// query: Query<(&ComponentA, Option<&ComponentB>)>
/// # ) {}
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/// # bevy_ecs::system::assert_is_system(system);
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/// ```
///
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/// See the documentation for [`AnyOf`] to idiomatically declare many optional components.
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///
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/// See the [performance] section to learn more about the impact of optional components.
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///
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/// ## Disjoint queries
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///
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/// A system cannot contain two queries that break Rust's mutability rules.
/// In this case, the [`Without`] filter can be used to disjoint them.
///
/// In the following example, two queries mutably access the same component.
/// Executing this system will panic, since an entity could potentially match the two queries at the same time by having both `Player` and `Enemy` components.
/// This would violate mutability rules.
///
/// ```should_panic
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct Health;
/// # #[derive(Component)]
/// # struct Player;
/// # #[derive(Component)]
/// # struct Enemy;
/// #
/// fn randomize_health(
/// player_query: Query<&mut Health, With<Player>>,
/// enemy_query: Query<&mut Health, With<Enemy>>,
/// )
/// # {}
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/// # let mut randomize_health_system = IntoSystem::into_system(randomize_health);
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/// # let mut world = World::new();
/// # randomize_health_system.initialize(&mut world);
/// # randomize_health_system.run((), &mut world);
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/// ```
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///
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/// Adding a `Without` filter will disjoint the queries.
/// In this way, any entity that has both `Player` and `Enemy` components is excluded from both queries.
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///
/// ```
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct Health;
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/// # #[derive(Component)]
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/// # struct Player;
/// # #[derive(Component)]
/// # struct Enemy;
/// #
/// fn randomize_health(
/// player_query: Query<&mut Health, (With<Player>, Without<Enemy>)>,
/// enemy_query: Query<&mut Health, (With<Enemy>, Without<Player>)>,
/// )
/// # {}
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/// # let mut randomize_health_system = IntoSystem::into_system(randomize_health);
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/// # let mut world = World::new();
/// # randomize_health_system.initialize(&mut world);
/// # randomize_health_system.run((), &mut world);
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/// ```
///
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/// An alternative to this idiom is to wrap the conflicting queries into a [`ParamSet`](super::ParamSet).
///
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/// ## Whole Entity Access
///
/// [`EntityRef`]s can be fetched from a query. This will give read-only access to any component on the entity,
/// and can be use to dynamically fetch any component without baking it into the query type. Due to this global
/// access to the entity, this will block any other system from parallelizing with it. As such these queries
/// should be sparingly used.
///
/// ```
/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
/// # struct ComponentA;
/// # fn system(
/// query: Query<(EntityRef, &ComponentA)>
/// # ) {}
/// # bevy_ecs::system::assert_is_system(system);
/// ```
///
/// As `EntityRef` can read any component on an entity, a query using it will conflict with *any* mutable
/// access. It is strongly advised to couple `EntityRef` queries with the use of either `With`/`Without`
/// filters or `ParamSets`. This also limits the scope of the query, which will improve iteration performance
/// and also allows it to parallelize with other non-conflicting systems.
///
/// ```should_panic
/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
/// # struct ComponentA;
/// # fn system(
/// // This will panic!
/// query: Query<(EntityRef, &mut ComponentA)>
/// # ) {}
/// # bevy_ecs::system::assert_system_does_not_conflict(system);
/// ```
/// ```
/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
/// # struct ComponentA;
/// # #[derive(Component)]
/// # struct ComponentB;
/// # fn system(
/// // This will not panic.
/// query_a: Query<EntityRef, With<ComponentA>>,
/// query_b: Query<&mut ComponentB, Without<ComponentA>>,
/// # ) {}
/// # bevy_ecs::system::assert_system_does_not_conflict(system);
/// ```
///
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/// # Accessing query items
///
/// The following table summarizes the behavior of the safe methods that can be used to get query items.
///
/// |Query methods|Effect|
/// |:---:|---|
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/// |[`iter`]\[[`_mut`][`iter_mut`]]|Returns an iterator over all query items.|
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/// |[[`iter().for_each()`][`for_each`]\[[`iter_mut().for_each()`][`for_each`]],<br>[`par_iter`]\[[`_mut`][`par_iter_mut`]]|Runs a specified function for each query item.|
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/// |[`iter_many`]\[[`_mut`][`iter_many_mut`]]|Iterates or runs a specified function over query items generated by a list of entities.|
/// |[`iter_combinations`]\[[`_mut`][`iter_combinations_mut`]]|Returns an iterator over all combinations of a specified number of query items.|
/// |[`get`]\[[`_mut`][`get_mut`]]|Returns the query item for the specified entity.|
/// |[`many`]\[[`_mut`][`many_mut`]],<br>[`get_many`]\[[`_mut`][`get_many_mut`]]|Returns the query items for the specified entities.|
/// |[`single`]\[[`_mut`][`single_mut`]],<br>[`get_single`]\[[`_mut`][`get_single_mut`]]|Returns the query item while verifying that there aren't others.|
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///
/// There are two methods for each type of query operation: immutable and mutable (ending with `_mut`).
/// When using immutable methods, the query items returned are of type [`ROQueryItem`], a read-only version of the query item.
/// In this circumstance, every mutable reference in the query fetch type parameter is substituted by a shared reference.
///
/// # Performance
///
/// Creating a `Query` is a low-cost constant operation.
/// Iterating it, on the other hand, fetches data from the world and generates items, which can have a significant computational cost.
///
/// [`Table`] component storage type is much more optimized for query iteration than [`SparseSet`].
///
/// Two systems cannot be executed in parallel if both access the same component type where at least one of the accesses is mutable.
/// This happens unless the executor can verify that no entity could be found in both queries.
///
/// Optional components increase the number of entities a query has to match against.
/// This can hurt iteration performance, especially if the query solely consists of only optional components, since the query would iterate over each entity in the world.
///
/// The following table compares the computational complexity of the various methods and operations, where:
///
/// - **n** is the number of entities that match the query,
/// - **r** is the number of elements in a combination,
/// - **k** is the number of involved entities in the operation,
/// - **a** is the number of archetypes in the world,
/// - **C** is the [binomial coefficient], used to count combinations.
/// <sub>n</sub>C<sub>r</sub> is read as "*n* choose *r*" and is equivalent to the number of distinct unordered subsets of *r* elements that can be taken from a set of *n* elements.
///
/// |Query operation|Computational complexity|
/// |:---:|:---:|
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/// |[`iter`]\[[`_mut`][`iter_mut`]]|O(n)|
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/// |[[`iter().for_each()`][`for_each`]\[[`iter_mut().for_each()`][`for_each`]],<br>[`par_iter`]\[[`_mut`][`par_iter_mut`]]|O(n)|
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/// |[`iter_many`]\[[`_mut`][`iter_many_mut`]]|O(k)|
/// |[`iter_combinations`]\[[`_mut`][`iter_combinations_mut`]]|O(<sub>n</sub>C<sub>r</sub>)|
/// |[`get`]\[[`_mut`][`get_mut`]]|O(1)|
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/// |([`get_`][`get_many`])[`many`]|O(k)|
/// |([`get_`][`get_many_mut`])[`many_mut`]|O(k<sup>2</sup>)|
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/// |[`single`]\[[`_mut`][`single_mut`]],<br>[`get_single`]\[[`_mut`][`get_single_mut`]]|O(a)|
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/// |Archetype based filtering ([`With`], [`Without`], [`Or`])|O(a)|
/// |Change detection filtering ([`Added`], [`Changed`])|O(a + n)|
///
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/// # `Iterator::for_each`
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///
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/// `for_each` methods are seen to be generally faster than directly iterating through `iter` on worlds with high archetype
/// fragmentation, and may enable additional optimizations like [autovectorization]. It is strongly advised to only use
/// [`Iterator::for_each`] if it tangibly improves performance. *Always* be sure profile or benchmark both before and
/// after the change!
///
/// ```rust
/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
/// # struct ComponentA;
/// # fn system(
/// # query: Query<&ComponentA>,
/// # ) {
/// // This might be result in better performance...
/// query.iter().for_each(|component| {
/// // do things with the component
/// });
/// // ...than this. Always be sure to benchmark to validate the difference!
/// for component in query.iter() {
/// // do things with the component
/// }
/// # }
/// # bevy_ecs::system::assert_system_does_not_conflict(system);
/// ```
///
/// [`Component`]: crate::component::Component
/// [autovectorization]: https://en.wikipedia.org/wiki/Automatic_vectorization
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/// [`Added`]: crate::query::Added
/// [`AnyOf`]: crate::query::AnyOf
/// [binomial coefficient]: https://en.wikipedia.org/wiki/Binomial_coefficient
/// [`Changed`]: crate::query::Changed
/// [components]: crate::component::Component
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/// [entity identifiers]: Entity
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/// [`EntityRef`]: crate::world::EntityRef
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/// [`for_each`]: #iterator-for-each
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/// [`get`]: Self::get
/// [`get_many`]: Self::get_many
/// [`get_many_mut`]: Self::get_many_mut
/// [`get_mut`]: Self::get_mut
/// [`get_single`]: Self::get_single
/// [`get_single_mut`]: Self::get_single_mut
/// [`iter`]: Self::iter
/// [`iter_combinations`]: Self::iter_combinations
/// [`iter_combinations_mut`]: Self::iter_combinations_mut
/// [`iter_many`]: Self::iter_many
/// [`iter_many_mut`]: Self::iter_many_mut
/// [`iter_mut`]: Self::iter_mut
/// [`many`]: Self::many
/// [`many_mut`]: Self::many_mut
/// [`Or`]: crate::query::Or
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/// [`par_iter`]: Self::par_iter
/// [`par_iter_mut`]: Self::par_iter_mut
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/// [performance]: #performance
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/// [`Single`]: Single
/// [`Option<Single>`]: Single
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/// [`single`]: Self::single
/// [`single_mut`]: Self::single_mut
/// [`SparseSet`]: crate::storage::SparseSet
/// [System parameter]: crate::system::SystemParam
/// [`Table`]: crate::storage::Table
/// [`With`]: crate::query::With
/// [`Without`]: crate::query::Without
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pub struct Query < ' world , ' state , D : QueryData , F : QueryFilter = ( ) > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
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// SAFETY: Must have access to the components registered in `state`.
world : UnsafeWorldCell < ' world > ,
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state : & ' state QueryState < D , F > ,
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last_run : Tick ,
this_run : 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
}
2024-09-27 00:59:59 +00:00
impl < D : QueryData , F : QueryFilter > core ::fmt ::Debug for Query < '_ , '_ , D , F > {
fn fmt ( & self , f : & mut core ::fmt ::Formatter ) -> core ::fmt ::Result {
2023-08-20 22:00:12 +00:00
f . debug_struct ( " Query " )
. field ( " matched_entities " , & self . iter ( ) . count ( ) )
. field ( " state " , & self . state )
. field ( " last_run " , & self . last_run )
. field ( " this_run " , & self . this_run )
. field ( " world " , & self . world )
. finish ( )
Adding Debug implementations for App, Stage, Schedule, Query, QueryState, etc. (#6214)
# Objective
- Adding Debug implementations for App, Stage, Schedule, Query, QueryState.
- Fixes #1130.
## Solution
- Implemented std::fmt::Debug for a number of structures.
---
## Changelog
Also added Debug implementations for ParallelSystemExecutor, SingleThreadedExecutor, various RunCriteria structures, SystemContainer, and SystemDescriptor.
Opinions are sure to differ as to what information to provide in a Debug implementation. Best guess was taken for this initial version for these structures.
Co-authored-by: targrub <62773321+targrub@users.noreply.github.com>
2022-10-10 20:59:38 +00:00
}
}
2023-12-13 18:50:46 +00:00
impl < ' w , ' s , D : QueryData , F : QueryFilter > Query < ' w , ' s , D , F > {
2021-04-15 20:36:16 +00:00
/// Creates a new query.
///
2023-01-10 17:25:45 +00:00
/// # Panics
///
/// This will panic if the world used to create `state` is not `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
/// # Safety
2021-04-15 20:36:16 +00:00
///
/// This will create a query that could violate memory safety rules. Make sure that this is only
/// called in ways that ensure the queries have unique mutable access.
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 ]
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 ( crate ) unsafe fn new (
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
world : UnsafeWorldCell < ' w > ,
2023-12-13 18:50:46 +00:00
state : & ' s QueryState < D , F > ,
2023-03-09 17:17:02 +00:00
last_run : Tick ,
this_run : Tick ,
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
) -> Self {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
state . validate_world ( world . id ( ) ) ;
2023-01-10 17:25:45 +00:00
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
Self {
world ,
state ,
2023-03-09 17:17:02 +00:00
last_run ,
this_run ,
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
}
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)
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}
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/// Returns another `Query` from this that fetches the read-only version of the query items.
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///
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/// For example, `Query<(&mut D1, &D2, &mut D3), With<F>>` will become `Query<(&D1, &D2, &D3), With<F>>`.
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/// This can be useful when working around the borrow checker,
/// or reusing functionality between systems via functions that accept query types.
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pub fn to_readonly ( & self ) -> Query < '_ , ' s , D ::ReadOnly , F > {
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let new_state = self . state . as_readonly ( ) ;
// SAFETY: This is memory safe because it turns the query immutable.
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unsafe { Query ::new ( self . world , new_state , self . last_run , self . this_run ) }
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}
Add query reborrowing (#14690)
# Objective
- Sometimes some method or function takes an owned `Query`, but we don't
want to give up ours;
- transmuting it technically a solution, but it more costly than
necessary.
- Make query iterators more flexible
- this would allow the equivalent of
`slice::split_first`/`slice::split_first_mut` for query iterators
- helps with requests like #14685
## Solution
- Add a way for reborrowing queries, that is going from a `&'a mut
Query<'w, 's, D, F>` to a `Query<'a, 's, D, F>`:
- this is safe because the original query will be borrowed while the new
query exists and thus no aliased access can happen;
- it's basically the equivalent of going from `&'short mut &'long mut T`
to `&'short mut T` the the compiler automatically implements.
- Add a way for getting the remainder of a query iterator:
- this is interesting also because the original iterator keeps its
position, which was not possible before;
- this in turn requires a way to reborrow query fetches, which I had to
add to `WorldQuery`.
## Showcase
- You can now reborrow a `Query`, getting an equivalent `Query` with a
shorter lifetime. Previously this was possible for read-only queries by
using `Query::to_readonly`, now it's possible for mutable queries too;
- You can now separately iterate over the remainder of `QueryIter`.
## Migration Guide
- `WorldQuery` now has an additional `shrink_fetch` method you have to
implement if you were implementing `WorldQuery` manually.
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/// Returns a new `Query` reborrowing the access from this one. The current query will be unusable
/// while the new one exists.
///
/// # Example
///
/// For example this allows to call other methods or other systems that require an owned `Query` without
/// completely giving up ownership of it.
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
/// # #[derive(Component)]
/// # struct ComponentA;
///
/// fn helper_system(query: Query<&ComponentA>) { /* ... */}
///
/// fn system(mut query: Query<&ComponentA>) {
/// helper_system(query.reborrow());
/// // Can still use query here:
/// for component in &query {
/// // ...
/// }
/// }
/// ```
pub fn reborrow ( & mut self ) -> Query < '_ , ' s , D , F > {
// SAFETY: this query is exclusively borrowed while the new one exists, so
// no overlapping access can occur.
unsafe { Query ::new ( self . world , self . state , self . last_run , self . this_run ) }
}
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/// Returns an [`Iterator`] over the read-only query items.
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///
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/// This iterator is always guaranteed to return results from each matching entity once and only once.
/// Iteration order is not guaranteed.
///
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/// # Example
///
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/// Here, the `report_names_system` iterates over the `Player` component of every entity that contains it:
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///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
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/// # #[derive(Component)]
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/// # struct Player { name: String }
/// #
/// fn report_names_system(query: Query<&Player>) {
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/// for player in &query {
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/// println!("Say hello to {}!", player.name);
/// }
/// }
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/// # bevy_ecs::system::assert_is_system(report_names_system);
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/// ```
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///
/// # See also
///
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/// [`iter_mut`](Self::iter_mut) for mutable query items.
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 ]
2023-12-13 18:50:46 +00:00
pub fn iter ( & self ) -> QueryIter < '_ , ' s , D ::ReadOnly , F > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY:
// - `self.world` has permission to access the required components.
2023-07-10 00:11:51 +00:00
// - The query is read-only, so it can be aliased even if it was originally mutable.
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
unsafe {
2023-03-09 17:17:02 +00:00
self . state
. as_readonly ( )
. iter_unchecked_manual ( self . world , self . last_run , self . this_run )
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
}
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)
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}
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/// Returns an [`Iterator`] over the query items.
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///
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/// This iterator is always guaranteed to return results from each matching entity once and only once.
/// Iteration order is not guaranteed.
///
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/// # Example
///
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/// Here, the `gravity_system` updates the `Velocity` component of every entity that contains it:
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///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
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/// # #[derive(Component)]
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/// # struct Velocity { x: f32, y: f32, z: f32 }
/// fn gravity_system(mut query: Query<&mut Velocity>) {
/// const DELTA: f32 = 1.0 / 60.0;
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/// for mut velocity in &mut query {
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/// velocity.y -= 9.8 * DELTA;
/// }
/// }
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/// # bevy_ecs::system::assert_is_system(gravity_system);
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/// ```
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///
/// # See also
///
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/// [`iter`](Self::iter) for read-only query items.
System Param Lifetime Split (#2605)
# Objective
Enable using exact World lifetimes during read-only access . This is motivated by the new renderer's need to allow read-only world-only queries to outlive the query itself (but still be constrained by the world lifetime).
For example:
https://github.com/bevyengine/bevy/blob/115b170d1f11a91146bb6d6e9684dceb8b21f786/pipelined/bevy_pbr2/src/render/mod.rs#L774
## Solution
Split out SystemParam state and world lifetimes and pipe those lifetimes up to read-only Query ops (and add into_inner for Res). According to every safety test I've run so far (except one), this is safe (see the temporary safety test commit). Note that changing the mutable variants to the new lifetimes would allow aliased mutable pointers (try doing that to see how it affects the temporary safety tests).
The new state lifetime on SystemParam does make `#[derive(SystemParam)]` more cumbersome (the current impl requires PhantomData if you don't use both lifetimes). We can make this better by detecting whether or not a lifetime is used in the derive and adjusting accordingly, but that should probably be done in its own pr.
## Why is this a draft?
The new lifetimes break QuerySet safety in one very specific case (see the query_set system in system_safety_test). We need to solve this before we can use the lifetimes given.
This is due to the fact that QuerySet is just a wrapper over Query, which now relies on world lifetimes instead of `&self` lifetimes to prevent aliasing (but in systems, each Query has its own implied lifetime, not a centralized world lifetime). I believe the fix is to rewrite QuerySet to have its own World lifetime (and own the internal reference). This will complicate the impl a bit, but I think it is doable. I'm curious if anyone else has better ideas.
Personally, I think these new lifetimes need to happen. We've gotta have a way to directly tie read-only World queries to the World lifetime. The new renderer is the first place this has come up, but I doubt it will be the last. Worst case scenario we can come up with a second `WorldLifetimeQuery<Q, F = ()>` parameter to enable these read-only scenarios, but I'd rather not add another type to the type zoo.
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#[ inline ]
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pub fn iter_mut ( & mut self ) -> QueryIter < '_ , ' s , D , F > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY: `self.world` has permission to access the required components.
System Param Lifetime Split (#2605)
# Objective
Enable using exact World lifetimes during read-only access . This is motivated by the new renderer's need to allow read-only world-only queries to outlive the query itself (but still be constrained by the world lifetime).
For example:
https://github.com/bevyengine/bevy/blob/115b170d1f11a91146bb6d6e9684dceb8b21f786/pipelined/bevy_pbr2/src/render/mod.rs#L774
## Solution
Split out SystemParam state and world lifetimes and pipe those lifetimes up to read-only Query ops (and add into_inner for Res). According to every safety test I've run so far (except one), this is safe (see the temporary safety test commit). Note that changing the mutable variants to the new lifetimes would allow aliased mutable pointers (try doing that to see how it affects the temporary safety tests).
The new state lifetime on SystemParam does make `#[derive(SystemParam)]` more cumbersome (the current impl requires PhantomData if you don't use both lifetimes). We can make this better by detecting whether or not a lifetime is used in the derive and adjusting accordingly, but that should probably be done in its own pr.
## Why is this a draft?
The new lifetimes break QuerySet safety in one very specific case (see the query_set system in system_safety_test). We need to solve this before we can use the lifetimes given.
This is due to the fact that QuerySet is just a wrapper over Query, which now relies on world lifetimes instead of `&self` lifetimes to prevent aliasing (but in systems, each Query has its own implied lifetime, not a centralized world lifetime). I believe the fix is to rewrite QuerySet to have its own World lifetime (and own the internal reference). This will complicate the impl a bit, but I think it is doable. I'm curious if anyone else has better ideas.
Personally, I think these new lifetimes need to happen. We've gotta have a way to directly tie read-only World queries to the World lifetime. The new renderer is the first place this has come up, but I doubt it will be the last. Worst case scenario we can come up with a second `WorldLifetimeQuery<Q, F = ()>` parameter to enable these read-only scenarios, but I'd rather not add another type to the type zoo.
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unsafe {
self . state
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. iter_unchecked_manual ( self . world , self . last_run , self . this_run )
System Param Lifetime Split (#2605)
# Objective
Enable using exact World lifetimes during read-only access . This is motivated by the new renderer's need to allow read-only world-only queries to outlive the query itself (but still be constrained by the world lifetime).
For example:
https://github.com/bevyengine/bevy/blob/115b170d1f11a91146bb6d6e9684dceb8b21f786/pipelined/bevy_pbr2/src/render/mod.rs#L774
## Solution
Split out SystemParam state and world lifetimes and pipe those lifetimes up to read-only Query ops (and add into_inner for Res). According to every safety test I've run so far (except one), this is safe (see the temporary safety test commit). Note that changing the mutable variants to the new lifetimes would allow aliased mutable pointers (try doing that to see how it affects the temporary safety tests).
The new state lifetime on SystemParam does make `#[derive(SystemParam)]` more cumbersome (the current impl requires PhantomData if you don't use both lifetimes). We can make this better by detecting whether or not a lifetime is used in the derive and adjusting accordingly, but that should probably be done in its own pr.
## Why is this a draft?
The new lifetimes break QuerySet safety in one very specific case (see the query_set system in system_safety_test). We need to solve this before we can use the lifetimes given.
This is due to the fact that QuerySet is just a wrapper over Query, which now relies on world lifetimes instead of `&self` lifetimes to prevent aliasing (but in systems, each Query has its own implied lifetime, not a centralized world lifetime). I believe the fix is to rewrite QuerySet to have its own World lifetime (and own the internal reference). This will complicate the impl a bit, but I think it is doable. I'm curious if anyone else has better ideas.
Personally, I think these new lifetimes need to happen. We've gotta have a way to directly tie read-only World queries to the World lifetime. The new renderer is the first place this has come up, but I doubt it will be the last. Worst case scenario we can come up with a second `WorldLifetimeQuery<Q, F = ()>` parameter to enable these read-only scenarios, but I'd rather not add another type to the type zoo.
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}
}
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/// Returns a [`QueryCombinationIter`] over all combinations of `K` read-only query items without repetition.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
///
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/// This iterator is always guaranteed to return results from each unique pair of matching entities.
/// Iteration order is not guaranteed.
///
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/// # Example
///
/// ```
/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
/// # struct ComponentA;
/// #
/// fn some_system(query: Query<&ComponentA>) {
/// for [a1, a2] in query.iter_combinations() {
/// // ...
/// }
/// }
/// ```
///
/// # See also
///
/// - [`iter_combinations_mut`](Self::iter_combinations_mut) for mutable query item combinations.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
#[ inline ]
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>`
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pub fn iter_combinations < const K : usize > (
& self ,
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) -> QueryCombinationIter < '_ , ' s , D ::ReadOnly , F , K > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY:
// - `self.world` has permission to access the required components.
2023-07-10 00:11:51 +00:00
// - The query is read-only, so it can be aliased even if it was originally mutable.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
unsafe {
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
self . state . as_readonly ( ) . iter_combinations_unchecked_manual (
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
self . world ,
2023-03-09 17:17:02 +00:00
self . last_run ,
self . this_run ,
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
)
}
}
2022-09-02 16:33:19 +00:00
/// Returns a [`QueryCombinationIter`] over all combinations of `K` query items without repetition.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
///
2024-03-11 18:17:46 +00:00
/// This iterator is always guaranteed to return results from each unique pair of matching entities.
/// Iteration order is not guaranteed.
///
2022-09-02 16:33:19 +00:00
/// # Example
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
///
/// ```
/// # use bevy_ecs::prelude::*;
2022-09-02 16:33:19 +00:00
/// # #[derive(Component)]
/// # struct ComponentA;
/// fn some_system(mut query: Query<&mut ComponentA>) {
/// let mut combinations = query.iter_combinations_mut();
/// while let Some([mut a1, mut a2]) = combinations.fetch_next() {
/// // mutably access components data
/// }
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
/// }
/// ```
///
2022-09-02 16:33:19 +00:00
/// # See also
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
///
2022-09-02 16:33:19 +00:00
/// - [`iter_combinations`](Self::iter_combinations) for read-only query item combinations.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
#[ inline ]
pub fn iter_combinations_mut < const K : usize > (
& mut self ,
2023-12-13 18:50:46 +00:00
) -> QueryCombinationIter < '_ , ' s , D , F , K > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY: `self.world` has permission to access the required components.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
unsafe {
2023-03-09 17:17:02 +00:00
self . state
. iter_combinations_unchecked_manual ( self . world , self . last_run , self . this_run )
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
}
}
2022-09-02 16:33:19 +00:00
/// Returns an [`Iterator`] over the read-only query items generated from an [`Entity`] list.
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
///
2024-03-11 18:17:46 +00:00
/// Items are returned in the order of the list of entities, and may not be unique if the input
2024-03-22 13:28:41 +00:00
/// doesn't guarantee uniqueness. Entities that don't match the query are skipped.
2022-10-24 13:46:38 +00:00
///
2022-09-02 16:33:19 +00:00
/// # Example
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
///
/// ```
/// # use bevy_ecs::prelude::*;
2022-09-02 16:33:19 +00:00
/// # #[derive(Component)]
/// # struct Counter {
/// # value: i32
/// # }
/// #
/// // A component containing an entity list.
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
/// #[derive(Component)]
/// struct Friends {
/// list: Vec<Entity>,
/// }
///
/// fn system(
/// friends_query: Query<&Friends>,
/// counter_query: Query<&Counter>,
/// ) {
/// for friends in &friends_query {
/// for counter in counter_query.iter_many(&friends.list) {
/// println!("Friend's counter: {:?}", counter.value);
/// }
/// }
/// }
/// # bevy_ecs::system::assert_is_system(system);
/// ```
2022-09-02 16:33:19 +00:00
///
/// # See also
///
/// - [`iter_many_mut`](Self::iter_many_mut) to get mutable query items.
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
#[ inline ]
2024-09-09 16:24:39 +00:00
pub fn iter_many < EntityList : IntoIterator < Item : Borrow < Entity > > > (
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
& self ,
entities : EntityList ,
2024-09-09 16:24:39 +00:00
) -> QueryManyIter < '_ , ' s , D ::ReadOnly , F , EntityList ::IntoIter > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY:
// - `self.world` has permission to access the required components.
2023-07-10 00:11:51 +00:00
// - The query is read-only, so it can be aliased even if it was originally mutable.
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
unsafe {
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
self . state . as_readonly ( ) . iter_many_unchecked_manual (
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
entities ,
self . world ,
2023-03-09 17:17:02 +00:00
self . last_run ,
self . this_run ,
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
)
}
}
2022-10-24 13:46:38 +00:00
/// Returns an iterator over the query items generated from an [`Entity`] list.
///
2024-03-11 18:17:46 +00:00
/// Items are returned in the order of the list of entities, and may not be unique if the input
2024-11-21 14:42:56 +00:00
/// doesn't guarantee uniqueness. Entities that don't match the query are skipped.
2022-09-02 16:33:19 +00:00
///
2022-07-30 01:38:13 +00:00
/// # Examples
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #[derive(Component)]
/// struct Counter {
/// value: i32
/// }
///
/// #[derive(Component)]
/// struct Friends {
/// list: Vec<Entity>,
/// }
///
/// fn system(
/// friends_query: Query<&Friends>,
/// mut counter_query: Query<&mut Counter>,
/// ) {
/// for friends in &friends_query {
/// let mut iter = counter_query.iter_many_mut(&friends.list);
/// while let Some(mut counter) = iter.fetch_next() {
/// println!("Friend's counter: {:?}", counter.value);
/// counter.value += 1;
/// }
/// }
/// }
/// # bevy_ecs::system::assert_is_system(system);
/// ```
#[ inline ]
2024-09-09 16:24:39 +00:00
pub fn iter_many_mut < EntityList : IntoIterator < Item : Borrow < Entity > > > (
2022-07-30 01:38:13 +00:00
& mut self ,
entities : EntityList ,
2024-09-09 16:24:39 +00:00
) -> QueryManyIter < '_ , ' s , D , F , EntityList ::IntoIter > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY: `self.world` has permission to access the required components.
2022-07-30 01:38:13 +00:00
unsafe {
self . state . iter_many_unchecked_manual (
entities ,
self . world ,
2023-03-09 17:17:02 +00:00
self . last_run ,
self . this_run ,
2022-07-30 01:38:13 +00:00
)
}
}
2022-09-02 16:33:19 +00:00
/// Returns an [`Iterator`] over the query items.
2021-03-11 00:27:30 +00:00
///
2024-03-11 18:17:46 +00:00
/// This iterator is always guaranteed to return results from each matching entity once and only once.
/// Iteration order is not guaranteed.
///
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
2021-04-15 20:36:16 +00:00
///
2022-09-02 16:33:19 +00:00
/// This function makes it possible to violate Rust's aliasing guarantees.
/// You must make sure this call does not result in multiple mutable references to the same component.
///
/// # See also
///
/// - [`iter`](Self::iter) and [`iter_mut`](Self::iter_mut) for the safe versions.
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 ]
2023-12-13 18:50:46 +00:00
pub unsafe fn iter_unsafe ( & self ) -> QueryIter < '_ , ' s , D , F > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY:
// - `self.world` has permission to access the required components.
// - The caller ensures that this operation will not result in any aliased mutable accesses.
2024-02-22 00:04:38 +00:00
unsafe {
self . state
. iter_unchecked_manual ( self . world , self . last_run , self . this_run )
}
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
}
2022-09-02 16:33:19 +00:00
/// Iterates over all possible combinations of `K` query items without repetition.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
///
2024-03-11 18:17:46 +00:00
/// This iterator is always guaranteed to return results from each unique pair of matching entities.
/// Iteration order is not guaranteed.
///
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
/// # Safety
2022-09-02 16:33:19 +00:00
///
/// This allows aliased mutability.
/// You must make sure this call does not result in multiple mutable references to the same component.
///
/// # See also
///
/// - [`iter_combinations`](Self::iter_combinations) and [`iter_combinations_mut`](Self::iter_combinations_mut) for the safe versions.
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
#[ inline ]
pub unsafe fn iter_combinations_unsafe < const K : usize > (
& self ,
2023-12-13 18:50:46 +00:00
) -> QueryCombinationIter < '_ , ' s , D , F , K > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY:
// - `self.world` has permission to access the required components.
// - The caller ensures that this operation will not result in any aliased mutable accesses.
2024-02-22 00:04:38 +00:00
unsafe {
self . state
. iter_combinations_unchecked_manual ( self . world , self . last_run , self . this_run )
}
Add a method `iter_combinations` on query to iterate over combinations of query results (#1763)
Related to [discussion on discord](https://discord.com/channels/691052431525675048/742569353878437978/824731187724681289)
With const generics, it is now possible to write generic iterator over multiple entities at once.
This enables patterns of query iterations like
```rust
for [e1, e2, e3] in query.iter_combinations() {
// do something with relation of all three entities
}
```
The compiler is able to infer the correct iterator for given size of array, so either of those work
```rust
for [e1, e2] in query.iter_combinations() { ... }
for [e1, e2, e3] in query.iter_combinations() { ... }
```
This feature can be very useful for systems like collision detection.
When you ask for permutations of size K of N entities:
- if K == N, you get one result of all entities
- if K < N, you get all possible subsets of N with size K, without repetition
- if K > N, the result set is empty (no permutation of size K exist)
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-05-17 23:33:47 +00:00
}
2022-09-02 16:33:19 +00:00
/// Returns an [`Iterator`] over the query items generated from an [`Entity`] list.
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
///
2024-03-11 18:17:46 +00:00
/// Items are returned in the order of the list of entities, and may not be unique if the input
/// doesnn't guarantee uniqueness. Entities that don't match the query are skipped.
///
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
/// # Safety
2022-09-02 16:33:19 +00:00
///
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
/// This allows aliased mutability and does not check for entity uniqueness.
/// You must make sure this call does not result in multiple mutable references to the same component.
2022-09-02 16:33:19 +00:00
/// Particular care must be taken when collecting the data (rather than iterating over it one item at a time) such as via [`Iterator::collect`].
///
/// # See also
///
/// - [`iter_many_mut`](Self::iter_many_mut) to safely access the query items.
2024-09-09 16:24:39 +00:00
pub unsafe fn iter_many_unsafe < EntityList : IntoIterator < Item : Borrow < Entity > > > (
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
& self ,
entities : EntityList ,
2024-09-09 16:24:39 +00:00
) -> QueryManyIter < '_ , ' s , D , F , EntityList ::IntoIter > {
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
// SAFETY:
// - `self.world` has permission to access the required components.
// - The caller ensures that this operation will not result in any aliased mutable accesses.
2024-02-22 00:04:38 +00:00
unsafe {
self . state . iter_many_unchecked_manual (
entities ,
self . world ,
self . last_run ,
self . this_run ,
)
}
Add methods for querying lists of entities. (#4879)
# Objective
Improve querying ergonomics around collections and iterators of entities.
Example how queries over Children might be done currently.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for child in children.iter() {
if let Ok((bar, children)) = bar_query.get(*child) {
for child in children.iter() {
if let Ok((foo, children)) = foo_query.get(*child) {
// D:
}
}
}
}
}
}
```
Answers #4868
Partially addresses #4864
Fixes #1470
## Solution
Based on the great work by @deontologician in #2563
Added `iter_many` and `many_for_each_mut` to `Query`.
These take a list of entities (Anything that implements `IntoIterator<Item: Borrow<Entity>>`).
`iter_many` returns a `QueryManyIter` iterator over immutable results of a query (mutable data will be cast to an immutable form).
`many_for_each_mut` calls a closure for every result of the query, ensuring not aliased mutability.
This iterator goes over the list of entities in order and returns the result from the query for it. Skipping over any entities that don't match the query.
Also added `unsafe fn iter_many_unsafe`.
### Examples
```rust
#[derive(Component)]
struct Counter {
value: i32
}
#[derive(Component)]
struct Friends {
list: Vec<Entity>,
}
fn system(
friends_query: Query<&Friends>,
mut counter_query: Query<&mut Counter>,
) {
for friends in &friends_query {
for counter in counter_query.iter_many(&friends.list) {
println!("Friend's counter: {:?}", counter.value);
}
counter_query.many_for_each_mut(&friends.list, |mut counter| {
counter.value += 1;
println!("Friend's counter: {:?}", counter.value);
});
}
}
```
Here's how example in the Objective section can be written with this PR.
```rust
fn system(foo_query: Query<(&Foo, &Children)>, bar_query: Query<(&Bar, &Children)>) {
for (foo, children) in &foo_query {
for (bar, children) in bar_query.iter_many(children) {
for (foo, children) in foo_query.iter_many(children) {
// :D
}
}
}
}
```
## Additional changes
Implemented `IntoIterator` for `&Children` because why not.
## Todo
- Bikeshed!
Co-authored-by: deontologician <deontologician@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
2022-06-06 16:09:16 +00:00
}
2023-01-20 08:47:20 +00:00
/// Returns a parallel iterator over the query results for the given [`World`].
2021-04-15 20:36:16 +00:00
///
2024-03-11 18:17:46 +00:00
/// This parallel iterator is always guaranteed to return results from each matching entity once and
/// only once. Iteration order and thread assignment is not guaranteed.
///
/// If the `multithreaded` feature is disabled, iterating with this operates identically to [`Iterator::for_each`]
/// on [`QueryIter`].
///
2023-01-20 08:47:20 +00:00
/// This can only be called for read-only queries, see [`par_iter_mut`] for write-queries.
2022-02-25 23:57:01 +00:00
///
2024-01-28 02:13:03 +00:00
/// Note that you must use the `for_each` method to iterate over the
/// results, see [`par_iter_mut`] for an example.
///
2023-01-20 08:47:20 +00:00
/// [`par_iter_mut`]: Self::par_iter_mut
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
/// [`World`]: crate::world::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
#[ inline ]
2023-12-13 18:50:46 +00:00
pub fn par_iter ( & self ) -> QueryParIter < '_ , '_ , D ::ReadOnly , F > {
2023-01-20 08:47:20 +00:00
QueryParIter {
world : self . world ,
state : self . state . as_readonly ( ) ,
2023-03-13 22:06:16 +00:00
last_run : self . last_run ,
this_run : self . this_run ,
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batching_strategy : BatchingStrategy ::new ( ) ,
}
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
}
2023-01-20 08:47:20 +00:00
/// Returns a parallel iterator over the query results for the given [`World`].
2022-05-30 16:59:38 +00:00
///
2024-03-11 18:17:46 +00:00
/// This parallel iterator is always guaranteed to return results from each matching entity once and
/// only once. Iteration order and thread assignment is not guaranteed.
///
/// If the `multithreaded` feature is disabled, iterating with this operates identically to [`Iterator::for_each`]
/// on [`QueryIter`].
///
2023-01-20 08:47:20 +00:00
/// This can only be called for mutable queries, see [`par_iter`] for read-only-queries.
2022-09-02 16:33:19 +00:00
///
2024-01-28 02:13:03 +00:00
/// # Example
///
/// Here, the `gravity_system` updates the `Velocity` component of every entity that contains it:
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
/// # #[derive(Component)]
/// # struct Velocity { x: f32, y: f32, z: f32 }
/// fn gravity_system(mut query: Query<&mut Velocity>) {
/// const DELTA: f32 = 1.0 / 60.0;
/// query.par_iter_mut().for_each(|mut velocity| {
/// velocity.y -= 9.8 * DELTA;
/// });
/// }
/// # bevy_ecs::system::assert_is_system(gravity_system);
/// ```
///
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/// [`par_iter`]: Self::par_iter
Migrate the rest of the engine to `UnsafeWorldCell` (#8833)
# Objective
Follow-up to #6404 and #8292.
Mutating the world through a shared reference is surprising, and it
makes the meaning of `&World` unclear: sometimes it gives read-only
access to the entire world, and sometimes it gives interior mutable
access to only part of it.
This is an up-to-date version of #6972.
## Solution
Use `UnsafeWorldCell` for all interior mutability. Now, `&World`
*always* gives you read-only access to the entire world.
---
## Changelog
TODO - do we still care about changelogs?
## Migration Guide
Mutating any world data using `&World` is now considered unsound -- the
type `UnsafeWorldCell` must be used to achieve interior mutability. The
following methods now accept `UnsafeWorldCell` instead of `&World`:
- `QueryState`: `get_unchecked`, `iter_unchecked`,
`iter_combinations_unchecked`, `for_each_unchecked`,
`get_single_unchecked`, `get_single_unchecked_manual`.
- `SystemState`: `get_unchecked_manual`
```rust
let mut world = World::new();
let mut query = world.query::<&mut T>();
// Before:
let t1 = query.get_unchecked(&world, entity_1);
let t2 = query.get_unchecked(&world, entity_2);
// After:
let world_cell = world.as_unsafe_world_cell();
let t1 = query.get_unchecked(world_cell, entity_1);
let t2 = query.get_unchecked(world_cell, entity_2);
```
The methods `QueryState::validate_world` and
`SystemState::matches_world` now take a `WorldId` instead of `&World`:
```rust
// Before:
query_state.validate_world(&world);
// After:
query_state.validate_world(world.id());
```
The methods `QueryState::update_archetypes` and
`SystemState::update_archetypes` now take `UnsafeWorldCell` instead of
`&World`:
```rust
// Before:
query_state.update_archetypes(&world);
// After:
query_state.update_archetypes(world.as_unsafe_world_cell_readonly());
```
2023-06-15 01:31:56 +00:00
/// [`World`]: crate::world::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
#[ inline ]
2023-12-13 18:50:46 +00:00
pub fn par_iter_mut ( & mut self ) -> QueryParIter < '_ , '_ , D , F > {
2023-01-20 08:47:20 +00:00
QueryParIter {
world : self . world ,
state : self . state ,
2023-03-13 22:06:16 +00:00
last_run : self . last_run ,
this_run : self . this_run ,
2023-01-20 08:47:20 +00:00
batching_strategy : BatchingStrategy ::new ( ) ,
}
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)
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}
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/// Returns the read-only query item for the given [`Entity`].
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///
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/// In case of a nonexisting entity or mismatched component, a [`QueryEntityError`] is returned instead.
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///
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/// This is always guaranteed to run in `O(1)` time.
///
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/// # Example
///
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/// Here, `get` is used to retrieve the exact query item of the entity specified by the `SelectedCharacter` resource.
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///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
Make `Resource` trait opt-in, requiring `#[derive(Resource)]` V2 (#5577)
*This PR description is an edited copy of #5007, written by @alice-i-cecile.*
# Objective
Follow-up to https://github.com/bevyengine/bevy/pull/2254. The `Resource` trait currently has a blanket implementation for all types that meet its bounds.
While ergonomic, this results in several drawbacks:
* it is possible to make confusing, silent mistakes such as inserting a function pointer (Foo) rather than a value (Foo::Bar) as a resource
* it is challenging to discover if a type is intended to be used as a resource
* we cannot later add customization options (see the [RFC](https://github.com/bevyengine/rfcs/blob/main/rfcs/27-derive-component.md) for the equivalent choice for Component).
* dependencies can use the same Rust type as a resource in invisibly conflicting ways
* raw Rust types used as resources cannot preserve privacy appropriately, as anyone able to access that type can read and write to internal values
* we cannot capture a definitive list of possible resources to display to users in an editor
## Notes to reviewers
* Review this commit-by-commit; there's effectively no back-tracking and there's a lot of churn in some of these commits.
*ira: My commits are not as well organized :')*
* I've relaxed the bound on Local to Send + Sync + 'static: I don't think these concerns apply there, so this can keep things simple. Storing e.g. a u32 in a Local is fine, because there's a variable name attached explaining what it does.
* I think this is a bad place for the Resource trait to live, but I've left it in place to make reviewing easier. IMO that's best tackled with https://github.com/bevyengine/bevy/issues/4981.
## Changelog
`Resource` is no longer automatically implemented for all matching types. Instead, use the new `#[derive(Resource)]` macro.
## Migration Guide
Add `#[derive(Resource)]` to all types you are using as a resource.
If you are using a third party type as a resource, wrap it in a tuple struct to bypass orphan rules. Consider deriving `Deref` and `DerefMut` to improve ergonomics.
`ClearColor` no longer implements `Component`. Using `ClearColor` as a component in 0.8 did nothing.
Use the `ClearColorConfig` in the `Camera3d` and `Camera2d` components instead.
Co-authored-by: Alice <alice.i.cecile@gmail.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
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/// # #[derive(Resource)]
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/// # struct SelectedCharacter { entity: Entity }
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/// # #[derive(Component)]
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/// # struct Character { name: String }
/// #
/// fn print_selected_character_name_system(
/// query: Query<&Character>,
/// selection: Res<SelectedCharacter>
/// )
/// {
/// if let Ok(selected_character) = query.get(selection.entity) {
/// println!("{}", selected_character.name);
/// }
/// }
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/// # bevy_ecs::system::assert_is_system(print_selected_character_name_system);
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/// ```
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///
/// # See also
///
/// - [`get_mut`](Self::get_mut) to get a mutable query item.
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 ]
2023-12-13 18:50:46 +00:00
pub fn get ( & self , entity : Entity ) -> Result < ROQueryItem < '_ , D > , QueryEntityError > {
2022-07-04 14:44:24 +00:00
// SAFETY: system runs without conflicts with other systems.
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
// same-system queries have runtime borrow checks when they conflict
unsafe {
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
self . state . as_readonly ( ) . get_unchecked_manual (
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
self . world ,
entity ,
2023-03-09 17:17:02 +00:00
self . last_run ,
self . this_run ,
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
)
}
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)
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}
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/// Returns the read-only query items for the given array of [`Entity`].
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///
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/// The returned query items are in the same order as the input.
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/// In case of a nonexisting entity or mismatched component, a [`QueryEntityError`] is returned instead.
/// The elements of the array do not need to be unique, unlike `get_many_mut`.
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///
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/// # See also
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///
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/// - [`get_many_mut`](Self::get_many_mut) to get mutable query items.
/// - [`many`](Self::many) for the panicking version.
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#[ inline ]
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pub fn get_many < const N : usize > (
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& self ,
entities : [ Entity ; N ] ,
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) -> Result < [ ROQueryItem < '_ , D > ; N ] , QueryEntityError > {
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// SAFETY:
// - `&self` ensures there is no mutable access to any components accessible to this query.
// - `self.world` matches `self.state`.
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unsafe {
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self . state
. get_many_read_only_manual ( self . world , entities , self . last_run , self . this_run )
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}
}
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/// Returns the read-only query items for the given array of [`Entity`].
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///
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/// # Panics
///
/// This method panics if there is a query mismatch or a non-existing entity.
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///
/// # Examples
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/// ``` no_run
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/// use bevy_ecs::prelude::*;
///
/// #[derive(Component)]
/// struct Targets([Entity; 3]);
///
/// #[derive(Component)]
/// struct Position{
/// x: i8,
/// y: i8
/// };
///
/// impl Position {
/// fn distance(&self, other: &Position) -> i8 {
/// // Manhattan distance is way easier to compute!
/// (self.x - other.x).abs() + (self.y - other.y).abs()
/// }
/// }
///
/// fn check_all_targets_in_range(targeting_query: Query<(Entity, &Targets, &Position)>, targets_query: Query<&Position>){
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/// for (targeting_entity, targets, origin) in &targeting_query {
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/// // We can use "destructuring" to unpack the results nicely
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/// let [target_1, target_2, target_3] = targets_query.many(targets.0);
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///
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/// assert!(target_1.distance(origin) <= 5);
/// assert!(target_2.distance(origin) <= 5);
/// assert!(target_3.distance(origin) <= 5);
/// }
/// }
/// ```
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///
/// # See also
///
/// - [`get_many`](Self::get_many) for the non-panicking version.
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#[ inline ]
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#[ track_caller ]
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pub fn many < const N : usize > ( & self , entities : [ Entity ; N ] ) -> [ ROQueryItem < '_ , D > ; N ] {
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match self . get_many ( entities ) {
Ok ( items ) = > items ,
Err ( error ) = > panic! ( " Cannot get query results: {error} " ) ,
}
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}
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/// Returns the query item for the given [`Entity`].
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///
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/// In case of a nonexisting entity or mismatched component, a [`QueryEntityError`] is returned instead.
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///
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/// This is always guaranteed to run in `O(1)` time.
///
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/// # Example
///
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/// Here, `get_mut` is used to retrieve the exact query item of the entity specified by the `PoisonedCharacter` resource.
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///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
Make `Resource` trait opt-in, requiring `#[derive(Resource)]` V2 (#5577)
*This PR description is an edited copy of #5007, written by @alice-i-cecile.*
# Objective
Follow-up to https://github.com/bevyengine/bevy/pull/2254. The `Resource` trait currently has a blanket implementation for all types that meet its bounds.
While ergonomic, this results in several drawbacks:
* it is possible to make confusing, silent mistakes such as inserting a function pointer (Foo) rather than a value (Foo::Bar) as a resource
* it is challenging to discover if a type is intended to be used as a resource
* we cannot later add customization options (see the [RFC](https://github.com/bevyengine/rfcs/blob/main/rfcs/27-derive-component.md) for the equivalent choice for Component).
* dependencies can use the same Rust type as a resource in invisibly conflicting ways
* raw Rust types used as resources cannot preserve privacy appropriately, as anyone able to access that type can read and write to internal values
* we cannot capture a definitive list of possible resources to display to users in an editor
## Notes to reviewers
* Review this commit-by-commit; there's effectively no back-tracking and there's a lot of churn in some of these commits.
*ira: My commits are not as well organized :')*
* I've relaxed the bound on Local to Send + Sync + 'static: I don't think these concerns apply there, so this can keep things simple. Storing e.g. a u32 in a Local is fine, because there's a variable name attached explaining what it does.
* I think this is a bad place for the Resource trait to live, but I've left it in place to make reviewing easier. IMO that's best tackled with https://github.com/bevyengine/bevy/issues/4981.
## Changelog
`Resource` is no longer automatically implemented for all matching types. Instead, use the new `#[derive(Resource)]` macro.
## Migration Guide
Add `#[derive(Resource)]` to all types you are using as a resource.
If you are using a third party type as a resource, wrap it in a tuple struct to bypass orphan rules. Consider deriving `Deref` and `DerefMut` to improve ergonomics.
`ClearColor` no longer implements `Component`. Using `ClearColor` as a component in 0.8 did nothing.
Use the `ClearColorConfig` in the `Camera3d` and `Camera2d` components instead.
Co-authored-by: Alice <alice.i.cecile@gmail.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
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/// # #[derive(Resource)]
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/// # struct PoisonedCharacter { character_id: Entity }
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/// # #[derive(Component)]
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/// # struct Health(u32);
/// #
/// fn poison_system(mut query: Query<&mut Health>, poisoned: Res<PoisonedCharacter>) {
/// if let Ok(mut health) = query.get_mut(poisoned.character_id) {
/// health.0 -= 1;
/// }
/// }
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/// # bevy_ecs::system::assert_is_system(poison_system);
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/// ```
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///
/// # See also
///
/// - [`get`](Self::get) to get a read-only query item.
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 ]
2023-12-13 18:50:46 +00:00
pub fn get_mut ( & mut self , entity : Entity ) -> Result < D ::Item < '_ > , QueryEntityError > {
2022-07-04 14:44:24 +00:00
// SAFETY: system runs without conflicts with other systems.
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
// same-system queries have runtime borrow checks when they conflict
unsafe {
2023-03-09 17:17:02 +00:00
self . state
. get_unchecked_manual ( self . world , entity , self . last_run , self . this_run )
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
}
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)
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}
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/// Returns the query items for the given array of [`Entity`].
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///
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/// The returned query items are in the same order as the input.
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/// In case of a nonexisting entity, duplicate entities or mismatched component, a [`QueryEntityError`] is returned instead.
///
/// # See also
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///
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/// - [`get_many`](Self::get_many) to get read-only query items.
/// - [`many_mut`](Self::many_mut) for the panicking version.
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#[ inline ]
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pub fn get_many_mut < const N : usize > (
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& mut self ,
entities : [ Entity ; N ] ,
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) -> Result < [ D ::Item < '_ > ; N ] , QueryEntityError > {
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// SAFETY: scheduler ensures safe Query world access
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unsafe {
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self . state
. get_many_unchecked_manual ( self . world , entities , self . last_run , self . this_run )
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}
}
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/// Returns the query items for the given array of [`Entity`].
///
/// # Panics
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///
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/// This method panics if there is a query mismatch, a non-existing entity, or the same `Entity` is included more than once in the array.
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///
/// # Examples
///
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/// ``` no_run
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/// use bevy_ecs::prelude::*;
///
/// #[derive(Component)]
/// struct Spring{
/// connected_entities: [Entity; 2],
/// strength: f32,
/// }
///
/// #[derive(Component)]
/// struct Position {
/// x: f32,
/// y: f32,
/// }
///
/// #[derive(Component)]
/// struct Force {
/// x: f32,
/// y: f32,
/// }
///
/// fn spring_forces(spring_query: Query<&Spring>, mut mass_query: Query<(&Position, &mut Force)>){
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/// for spring in &spring_query {
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/// // We can use "destructuring" to unpack our query items nicely
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/// let [(position_1, mut force_1), (position_2, mut force_2)] = mass_query.many_mut(spring.connected_entities);
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///
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/// force_1.x += spring.strength * (position_1.x - position_2.x);
/// force_1.y += spring.strength * (position_1.y - position_2.y);
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///
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/// // Silence borrow-checker: I have split your mutable borrow!
/// force_2.x += spring.strength * (position_2.x - position_1.x);
/// force_2.y += spring.strength * (position_2.y - position_1.y);
/// }
/// }
/// ```
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///
/// # See also
///
/// - [`get_many_mut`](Self::get_many_mut) for the non panicking version.
/// - [`many`](Self::many) to get read-only query items.
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#[ inline ]
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#[ track_caller ]
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pub fn many_mut < const N : usize > ( & mut self , entities : [ Entity ; N ] ) -> [ D ::Item < '_ > ; N ] {
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match self . get_many_mut ( entities ) {
Ok ( items ) = > items ,
Err ( error ) = > panic! ( " Cannot get query result: {error} " ) ,
}
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}
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/// Returns the query item for the given [`Entity`].
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///
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/// In case of a nonexisting entity or mismatched component, a [`QueryEntityError`] is returned instead.
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///
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/// This is always guaranteed to run in `O(1)` time.
///
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
2021-04-15 20:36:16 +00:00
///
2022-09-02 16:33:19 +00:00
/// This function makes it possible to violate Rust's aliasing guarantees.
/// You must make sure this call does not result in multiple mutable references to the same component.
///
/// # See also
///
/// - [`get_mut`](Self::get_mut) for the safe version.
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 ]
2023-12-13 18:50:46 +00:00
pub unsafe fn get_unchecked ( & self , entity : Entity ) -> Result < D ::Item < '_ > , QueryEntityError > {
2022-07-04 14:44:24 +00:00
// SEMI-SAFETY: system runs without conflicts with other systems.
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
// same-system queries have runtime borrow checks when they conflict
2024-02-22 00:04:38 +00:00
unsafe {
self . state
. get_unchecked_manual ( self . world , entity , self . last_run , self . this_run )
}
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)
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}
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/// Returns a single read-only query item when there is exactly one entity matching the query.
///
/// # Panics
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///
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/// This method panics if the number of query items is **not** exactly one.
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///
/// # Example
///
/// ```
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/// # use bevy_ecs::prelude::*;
/// # #[derive(Component)]
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/// # struct Player;
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/// # #[derive(Component)]
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/// # struct Position(f32, f32);
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/// fn player_system(query: Query<&Position, With<Player>>) {
/// let player_position = query.single();
/// // do something with player_position
/// }
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/// # bevy_ecs::system::assert_is_system(player_system);
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/// ```
///
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/// # See also
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///
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/// - [`get_single`](Self::get_single) for the non-panicking version.
/// - [`single_mut`](Self::single_mut) to get the mutable query item.
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#[ track_caller ]
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pub fn single ( & self ) -> ROQueryItem < '_ , D > {
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self . get_single ( ) . unwrap ( )
}
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/// Returns a single read-only query item when there is exactly one entity matching the query.
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///
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/// If the number of query items is not exactly one, a [`QuerySingleError`] is returned instead.
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///
/// # Example
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///
/// ```
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/// # use bevy_ecs::prelude::*;
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/// # use bevy_ecs::query::QuerySingleError;
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/// # #[derive(Component)]
/// # struct PlayerScore(i32);
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/// fn player_scoring_system(query: Query<&PlayerScore>) {
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/// match query.get_single() {
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/// Ok(PlayerScore(score)) => {
/// println!("Score: {}", score);
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/// }
/// Err(QuerySingleError::NoEntities(_)) => {
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/// println!("Error: There is no player!");
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/// }
/// Err(QuerySingleError::MultipleEntities(_)) => {
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/// println!("Error: There is more than one player!");
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/// }
/// }
/// }
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/// # bevy_ecs::system::assert_is_system(player_scoring_system);
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/// ```
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///
/// # See also
///
/// - [`get_single_mut`](Self::get_single_mut) to get the mutable query item.
/// - [`single`](Self::single) for the panicking version.
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#[ inline ]
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pub fn get_single ( & self ) -> Result < ROQueryItem < '_ , D > , QuerySingleError > {
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// SAFETY:
// the query ensures that the components it accesses are not mutably accessible somewhere else
// and the query is read only.
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unsafe {
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>`
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self . state . as_readonly ( ) . get_single_unchecked_manual (
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self . world ,
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self . last_run ,
self . this_run ,
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)
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}
}
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/// Returns a single query item when there is exactly one entity matching the query.
///
/// # Panics
///
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/// This method panics if the number of query items is **not** exactly one.
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///
/// # Example
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
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/// # #[derive(Component)]
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/// # struct Player;
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/// # #[derive(Component)]
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/// # struct Health(u32);
/// #
/// fn regenerate_player_health_system(mut query: Query<&mut Health, With<Player>>) {
/// let mut health = query.single_mut();
/// health.0 += 1;
/// }
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/// # bevy_ecs::system::assert_is_system(regenerate_player_health_system);
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/// ```
///
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/// # See also
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///
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/// - [`get_single_mut`](Self::get_single_mut) for the non-panicking version.
/// - [`single`](Self::single) to get the read-only query item.
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#[ track_caller ]
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pub fn single_mut ( & mut self ) -> D ::Item < '_ > {
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self . get_single_mut ( ) . unwrap ( )
}
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/// Returns a single query item when there is exactly one entity matching the query.
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///
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/// If the number of query items is not exactly one, a [`QuerySingleError`] is returned instead.
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///
/// # Example
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
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/// # #[derive(Component)]
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/// # struct Player;
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/// # #[derive(Component)]
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/// # struct Health(u32);
/// #
/// fn regenerate_player_health_system(mut query: Query<&mut Health, With<Player>>) {
/// let mut health = query.get_single_mut().expect("Error: Could not find a single player.");
/// health.0 += 1;
/// }
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/// # bevy_ecs::system::assert_is_system(regenerate_player_health_system);
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/// ```
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///
/// # See also
///
/// - [`get_single`](Self::get_single) to get the read-only query item.
/// - [`single_mut`](Self::single_mut) for the panicking version.
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#[ inline ]
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pub fn get_single_mut ( & mut self ) -> Result < D ::Item < '_ > , QuerySingleError > {
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// SAFETY:
// the query ensures mutable access to the components it accesses, and the query
// is uniquely borrowed
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unsafe {
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self . state
. get_single_unchecked_manual ( self . world , self . last_run , self . this_run )
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}
}
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/// Returns `true` if there are no query items.
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///
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/// This is equivalent to `self.iter().next().is_none()`, and thus the worst case runtime will be `O(n)`
/// where `n` is the number of *potential* matches. This can be notably expensive for queries that rely
/// on non-archetypal filters such as [`Added`] or [`Changed`] which must individually check each query
/// result for a match.
///
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/// # Example
///
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/// Here, the score is increased only if an entity with a `Player` component is present in the world:
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///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
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/// # #[derive(Component)]
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/// # struct Player;
Make `Resource` trait opt-in, requiring `#[derive(Resource)]` V2 (#5577)
*This PR description is an edited copy of #5007, written by @alice-i-cecile.*
# Objective
Follow-up to https://github.com/bevyengine/bevy/pull/2254. The `Resource` trait currently has a blanket implementation for all types that meet its bounds.
While ergonomic, this results in several drawbacks:
* it is possible to make confusing, silent mistakes such as inserting a function pointer (Foo) rather than a value (Foo::Bar) as a resource
* it is challenging to discover if a type is intended to be used as a resource
* we cannot later add customization options (see the [RFC](https://github.com/bevyengine/rfcs/blob/main/rfcs/27-derive-component.md) for the equivalent choice for Component).
* dependencies can use the same Rust type as a resource in invisibly conflicting ways
* raw Rust types used as resources cannot preserve privacy appropriately, as anyone able to access that type can read and write to internal values
* we cannot capture a definitive list of possible resources to display to users in an editor
## Notes to reviewers
* Review this commit-by-commit; there's effectively no back-tracking and there's a lot of churn in some of these commits.
*ira: My commits are not as well organized :')*
* I've relaxed the bound on Local to Send + Sync + 'static: I don't think these concerns apply there, so this can keep things simple. Storing e.g. a u32 in a Local is fine, because there's a variable name attached explaining what it does.
* I think this is a bad place for the Resource trait to live, but I've left it in place to make reviewing easier. IMO that's best tackled with https://github.com/bevyengine/bevy/issues/4981.
## Changelog
`Resource` is no longer automatically implemented for all matching types. Instead, use the new `#[derive(Resource)]` macro.
## Migration Guide
Add `#[derive(Resource)]` to all types you are using as a resource.
If you are using a third party type as a resource, wrap it in a tuple struct to bypass orphan rules. Consider deriving `Deref` and `DerefMut` to improve ergonomics.
`ClearColor` no longer implements `Component`. Using `ClearColor` as a component in 0.8 did nothing.
Use the `ClearColorConfig` in the `Camera3d` and `Camera2d` components instead.
Co-authored-by: Alice <alice.i.cecile@gmail.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-08-08 21:36:35 +00:00
/// # #[derive(Resource)]
2021-09-17 18:00:29 +00:00
/// # struct Score(u32);
/// fn update_score_system(query: Query<(), With<Player>>, mut score: ResMut<Score>) {
/// if !query.is_empty() {
/// score.0 += 1;
/// }
/// }
2022-02-08 04:00:58 +00:00
/// # bevy_ecs::system::assert_is_system(update_score_system);
2021-09-17 18:00:29 +00:00
/// ```
2024-03-14 01:36:03 +00:00
///
/// [`Added`]: crate::query::Added
/// [`Changed`]: crate::query::Changed
2021-06-02 20:50:06 +00:00
#[ inline ]
pub fn is_empty ( & self ) -> bool {
2023-09-02 23:43:22 +00:00
// SAFETY:
// - `self.world` has permission to read any data required by the WorldQuery.
// - `&self` ensures that no one currently has write access.
// - `self.world` matches `self.state`.
unsafe {
self . state
. is_empty_unsafe_world_cell ( self . world , self . last_run , self . this_run )
}
2021-06-02 20:50:06 +00:00
}
2022-02-08 03:37:34 +00:00
/// Returns `true` if the given [`Entity`] matches the query.
///
2024-03-29 14:49:43 +00:00
/// This is always guaranteed to run in `O(1)` time.
///
2022-02-08 03:37:34 +00:00
/// # Example
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
/// # #[derive(Component)]
/// # struct InRange;
/// #
Make `Resource` trait opt-in, requiring `#[derive(Resource)]` V2 (#5577)
*This PR description is an edited copy of #5007, written by @alice-i-cecile.*
# Objective
Follow-up to https://github.com/bevyengine/bevy/pull/2254. The `Resource` trait currently has a blanket implementation for all types that meet its bounds.
While ergonomic, this results in several drawbacks:
* it is possible to make confusing, silent mistakes such as inserting a function pointer (Foo) rather than a value (Foo::Bar) as a resource
* it is challenging to discover if a type is intended to be used as a resource
* we cannot later add customization options (see the [RFC](https://github.com/bevyengine/rfcs/blob/main/rfcs/27-derive-component.md) for the equivalent choice for Component).
* dependencies can use the same Rust type as a resource in invisibly conflicting ways
* raw Rust types used as resources cannot preserve privacy appropriately, as anyone able to access that type can read and write to internal values
* we cannot capture a definitive list of possible resources to display to users in an editor
## Notes to reviewers
* Review this commit-by-commit; there's effectively no back-tracking and there's a lot of churn in some of these commits.
*ira: My commits are not as well organized :')*
* I've relaxed the bound on Local to Send + Sync + 'static: I don't think these concerns apply there, so this can keep things simple. Storing e.g. a u32 in a Local is fine, because there's a variable name attached explaining what it does.
* I think this is a bad place for the Resource trait to live, but I've left it in place to make reviewing easier. IMO that's best tackled with https://github.com/bevyengine/bevy/issues/4981.
## Changelog
`Resource` is no longer automatically implemented for all matching types. Instead, use the new `#[derive(Resource)]` macro.
## Migration Guide
Add `#[derive(Resource)]` to all types you are using as a resource.
If you are using a third party type as a resource, wrap it in a tuple struct to bypass orphan rules. Consider deriving `Deref` and `DerefMut` to improve ergonomics.
`ClearColor` no longer implements `Component`. Using `ClearColor` as a component in 0.8 did nothing.
Use the `ClearColorConfig` in the `Camera3d` and `Camera2d` components instead.
Co-authored-by: Alice <alice.i.cecile@gmail.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-08-08 21:36:35 +00:00
/// # #[derive(Resource)]
2022-02-08 03:37:34 +00:00
/// # struct Target {
/// # entity: Entity,
/// # }
/// #
/// fn targeting_system(in_range_query: Query<&InRange>, target: Res<Target>) {
/// if in_range_query.contains(target.entity) {
/// println!("Bam!")
/// }
/// }
2022-04-16 21:33:51 +00:00
/// # bevy_ecs::system::assert_is_system(targeting_system);
2022-02-08 03:37:34 +00:00
/// ```
#[ inline ]
pub fn contains ( & self , entity : Entity ) -> bool {
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// SAFETY: NopFetch does not access any members while &self ensures no one has exclusive access
2022-02-08 03:37:34 +00:00
unsafe {
self . state
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
. as_nop ( )
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. get_unchecked_manual ( self . world , entity , self . last_run , self . this_run )
2022-02-08 03:37:34 +00:00
. is_ok ( )
}
}
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
/// Returns a [`QueryLens`] that can be used to get a query with a more general fetch.
///
/// For example, this can transform a `Query<(&A, &mut B)>` to a `Query<&B>`.
/// This can be useful for passing the query to another function. Note that since
/// filter terms are dropped, non-archetypal filters like [`Added`](crate::query::Added) and
/// [`Changed`](crate::query::Changed) will not be respected. To maintain or change filter
/// terms see [`Self::transmute_lens_filtered`]
///
/// ## Panics
///
/// This will panic if `NewD` is not a subset of the original fetch `Q`
///
/// ## Example
///
/// ```rust
/// # use bevy_ecs::prelude::*;
/// # use bevy_ecs::system::QueryLens;
/// #
/// # #[derive(Component)]
/// # struct A(usize);
/// #
/// # #[derive(Component)]
/// # struct B(usize);
/// #
/// # let mut world = World::new();
/// #
/// # world.spawn((A(10), B(5)));
/// #
/// fn reusable_function(lens: &mut QueryLens<&A>) {
/// assert_eq!(lens.query().single().0, 10);
/// }
///
/// // We can use the function in a system that takes the exact query.
/// fn system_1(mut query: Query<&A>) {
/// reusable_function(&mut query.as_query_lens());
/// }
///
/// // We can also use it with a query that does not match exactly
/// // by transmuting it.
/// fn system_2(mut query: Query<(&mut A, &B)>) {
/// let mut lens = query.transmute_lens::<&A>();
/// reusable_function(&mut lens);
/// }
///
/// # let mut schedule = Schedule::default();
/// # schedule.add_systems((system_1, system_2));
/// # schedule.run(&mut world);
/// ```
///
/// ## Allowed Transmutes
///
/// Besides removing parameters from the query, you can also
2024-02-22 18:55:22 +00:00
/// make limited changes to the types of parameters.
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
///
2024-03-29 06:41:01 +00:00
/// * Can always add/remove [`Entity`]
/// * Can always add/remove [`EntityLocation`]
/// * Can always add/remove [`&Archetype`]
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
/// * `Ref<T>` <-> `&T`
/// * `&mut T` -> `&T`
/// * `&mut T` -> `Ref<T>`
/// * [`EntityMut`](crate::world::EntityMut) -> [`EntityRef`](crate::world::EntityRef)
2024-10-13 20:32:06 +00:00
///
2024-03-29 06:41:01 +00:00
/// [`EntityLocation`]: crate::entity::EntityLocation
/// [`&Archetype`]: crate::archetype::Archetype
2024-04-24 04:51:18 +00:00
#[ track_caller ]
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
pub fn transmute_lens < NewD : QueryData > ( & mut self ) -> QueryLens < '_ , NewD > {
self . transmute_lens_filtered ::< NewD , ( ) > ( )
}
/// Equivalent to [`Self::transmute_lens`] but also includes a [`QueryFilter`] type.
///
/// Note that the lens will iterate the same tables and archetypes as the original query. This means that
/// additional archetypal query terms like [`With`](crate::query::With) and [`Without`](crate::query::Without)
/// will not necessarily be respected and non-archetypal terms like [`Added`](crate::query::Added) and
/// [`Changed`](crate::query::Changed) will only be respected if they are in the type signature.
2024-04-24 04:51:18 +00:00
#[ track_caller ]
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
pub fn transmute_lens_filtered < NewD : QueryData , NewF : QueryFilter > (
& mut self ,
) -> QueryLens < '_ , NewD , NewF > {
2024-08-05 22:39:31 +00:00
let state = self . state . transmute_filtered ::< NewD , NewF > ( self . world ) ;
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
QueryLens {
world : self . world ,
state ,
last_run : self . last_run ,
this_run : self . this_run ,
}
}
/// Gets a [`QueryLens`] with the same accesses as the existing query
pub fn as_query_lens ( & mut self ) -> QueryLens < '_ , D > {
self . transmute_lens ( )
}
2024-03-11 19:07:36 +00:00
/// Returns a [`QueryLens`] that can be used to get a query with the combined fetch.
///
2024-06-11 23:24:53 +00:00
/// For example, this can take a `Query<&A>` and a `Query<&B>` and return a `Query<(&A, &B)>`.
/// The returned query will only return items with both `A` and `B`. Note that since filters
/// are dropped, non-archetypal filters like `Added` and `Changed` will not be respected.
2024-03-11 19:07:36 +00:00
/// To maintain or change filter terms see `Self::join_filtered`.
///
/// ## Example
///
/// ```rust
/// # use bevy_ecs::prelude::*;
/// # use bevy_ecs::system::QueryLens;
/// #
/// # #[derive(Component)]
/// # struct Transform;
/// #
/// # #[derive(Component)]
/// # struct Player;
/// #
/// # #[derive(Component)]
/// # struct Enemy;
/// #
/// # let mut world = World::default();
/// # world.spawn((Transform, Player));
/// # world.spawn((Transform, Enemy));
///
/// fn system(
/// mut transforms: Query<&Transform>,
/// mut players: Query<&Player>,
/// mut enemies: Query<&Enemy>
/// ) {
/// let mut players_transforms: QueryLens<(&Transform, &Player)> = transforms.join(&mut players);
/// for (transform, player) in &players_transforms.query() {
/// // do something with a and b
/// }
///
/// let mut enemies_transforms: QueryLens<(&Transform, &Enemy)> = transforms.join(&mut enemies);
/// for (transform, enemy) in &enemies_transforms.query() {
/// // do something with a and b
/// }
/// }
///
/// # let mut schedule = Schedule::default();
/// # schedule.add_systems(system);
/// # schedule.run(&mut world);
/// ```
/// ## Panics
///
/// This will panic if `NewD` is not a subset of the union of the original fetch `Q` and `OtherD`.
///
/// ## Allowed Transmutes
///
/// Like `transmute_lens` the query terms can be changed with some restrictions.
/// See [`Self::transmute_lens`] for more details.
pub fn join < OtherD : QueryData , NewD : QueryData > (
& mut self ,
other : & mut Query < OtherD > ,
) -> QueryLens < '_ , NewD > {
self . join_filtered ( other )
}
/// Equivalent to [`Self::join`] but also includes a [`QueryFilter`] type.
///
2024-06-11 23:24:53 +00:00
/// Note that the lens with iterate a subset of the original queries' tables
2024-03-11 19:07:36 +00:00
/// and archetypes. This means that additional archetypal query terms like
/// `With` and `Without` will not necessarily be respected and non-archetypal
/// terms like `Added` and `Changed` will only be respected if they are in
/// the type signature.
pub fn join_filtered <
OtherD : QueryData ,
OtherF : QueryFilter ,
NewD : QueryData ,
NewF : QueryFilter ,
> (
& mut self ,
other : & mut Query < OtherD , OtherF > ,
) -> QueryLens < '_ , NewD , NewF > {
let state = self
. state
2024-08-05 22:39:31 +00:00
. join_filtered ::< OtherD , OtherF , NewD , NewF > ( self . world , other . state ) ;
2024-03-11 19:07:36 +00:00
QueryLens {
world : self . world ,
state ,
last_run : self . last_run ,
this_run : self . this_run ,
}
}
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
}
2023-12-13 18:50:46 +00:00
impl < ' w , ' s , D : QueryData , F : QueryFilter > IntoIterator for & ' w Query < '_ , ' s , D , F > {
type Item = ROQueryItem < ' w , D > ;
type IntoIter = QueryIter < ' w , ' s , D ::ReadOnly , F > ;
2022-05-09 13:37:39 +00:00
fn into_iter ( self ) -> Self ::IntoIter {
self . iter ( )
}
}
2023-12-13 18:50:46 +00:00
impl < ' w , ' s , D : QueryData , F : QueryFilter > IntoIterator for & ' w mut Query < '_ , ' s , D , F > {
type Item = D ::Item < ' w > ;
type IntoIter = QueryIter < ' w , ' s , D , F > ;
2022-05-09 13:37:39 +00:00
fn into_iter ( self ) -> Self ::IntoIter {
self . iter_mut ( )
}
}
2023-12-13 18:50:46 +00:00
impl < ' w , ' s , D : ReadOnlyQueryData , F : QueryFilter > Query < ' w , ' s , D , F > {
2022-09-02 16:33:19 +00:00
/// Returns the query item for the given [`Entity`], with the actual "inner" world lifetime.
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
///
/// In case of a nonexisting entity or mismatched component, a [`QueryEntityError`] is
/// returned instead.
///
/// This can only return immutable data (mutable data will be cast to an immutable form).
/// See [`get_mut`](Self::get_mut) for queries that contain at least one mutable component.
///
/// # Example
///
2022-09-02 16:33:19 +00:00
/// Here, `get` is used to retrieve the exact query item of the entity specified by the
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
/// `SelectedCharacter` resource.
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
Make `Resource` trait opt-in, requiring `#[derive(Resource)]` V2 (#5577)
*This PR description is an edited copy of #5007, written by @alice-i-cecile.*
# Objective
Follow-up to https://github.com/bevyengine/bevy/pull/2254. The `Resource` trait currently has a blanket implementation for all types that meet its bounds.
While ergonomic, this results in several drawbacks:
* it is possible to make confusing, silent mistakes such as inserting a function pointer (Foo) rather than a value (Foo::Bar) as a resource
* it is challenging to discover if a type is intended to be used as a resource
* we cannot later add customization options (see the [RFC](https://github.com/bevyengine/rfcs/blob/main/rfcs/27-derive-component.md) for the equivalent choice for Component).
* dependencies can use the same Rust type as a resource in invisibly conflicting ways
* raw Rust types used as resources cannot preserve privacy appropriately, as anyone able to access that type can read and write to internal values
* we cannot capture a definitive list of possible resources to display to users in an editor
## Notes to reviewers
* Review this commit-by-commit; there's effectively no back-tracking and there's a lot of churn in some of these commits.
*ira: My commits are not as well organized :')*
* I've relaxed the bound on Local to Send + Sync + 'static: I don't think these concerns apply there, so this can keep things simple. Storing e.g. a u32 in a Local is fine, because there's a variable name attached explaining what it does.
* I think this is a bad place for the Resource trait to live, but I've left it in place to make reviewing easier. IMO that's best tackled with https://github.com/bevyengine/bevy/issues/4981.
## Changelog
`Resource` is no longer automatically implemented for all matching types. Instead, use the new `#[derive(Resource)]` macro.
## Migration Guide
Add `#[derive(Resource)]` to all types you are using as a resource.
If you are using a third party type as a resource, wrap it in a tuple struct to bypass orphan rules. Consider deriving `Deref` and `DerefMut` to improve ergonomics.
`ClearColor` no longer implements `Component`. Using `ClearColor` as a component in 0.8 did nothing.
Use the `ClearColorConfig` in the `Camera3d` and `Camera2d` components instead.
Co-authored-by: Alice <alice.i.cecile@gmail.com>
Co-authored-by: Alice Cecile <alice.i.cecile@gmail.com>
Co-authored-by: devil-ira <justthecooldude@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-08-08 21:36:35 +00:00
/// # #[derive(Resource)]
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
/// # struct SelectedCharacter { entity: Entity }
/// # #[derive(Component)]
/// # struct Character { name: String }
/// #
/// fn print_selected_character_name_system(
/// query: Query<&Character>,
/// selection: Res<SelectedCharacter>
/// )
/// {
/// if let Ok(selected_character) = query.get(selection.entity) {
/// println!("{}", selected_character.name);
/// }
/// }
/// # bevy_ecs::system::assert_is_system(print_selected_character_name_system);
/// ```
#[ inline ]
2023-12-13 18:50:46 +00:00
pub fn get_inner ( & self , entity : Entity ) -> Result < ROQueryItem < ' w , D > , QueryEntityError > {
2022-07-04 14:44:24 +00:00
// SAFETY: system runs without conflicts with other systems.
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
// same-system queries have runtime borrow checks when they conflict
unsafe {
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
self . state . as_readonly ( ) . get_unchecked_manual (
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
self . world ,
entity ,
2023-03-09 17:17:02 +00:00
self . last_run ,
self . this_run ,
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
)
}
}
2022-09-02 16:33:19 +00:00
/// Returns an [`Iterator`] over the query items, with the actual "inner" world lifetime.
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
///
/// This can only return immutable data (mutable data will be cast to an immutable form).
/// See [`Self::iter_mut`] for queries that contain at least one mutable component.
///
/// # Example
///
/// Here, the `report_names_system` iterates over the `Player` component of every entity
/// that contains it:
///
/// ```
/// # use bevy_ecs::prelude::*;
/// #
/// # #[derive(Component)]
/// # struct Player { name: String }
/// #
/// fn report_names_system(query: Query<&Player>) {
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/// for player in &query {
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
/// println!("Say hello to {}!", player.name);
/// }
/// }
/// # bevy_ecs::system::assert_is_system(report_names_system);
/// ```
#[ inline ]
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pub fn iter_inner ( & self ) -> QueryIter < ' w , ' s , D ::ReadOnly , F > {
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// SAFETY: system runs without conflicts with other systems.
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
// same-system queries have runtime borrow checks when they conflict
unsafe {
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self . state
. as_readonly ( )
. iter_unchecked_manual ( self . world , self . last_run , self . this_run )
yeet unsound lifetime annotations on `Query` methods (#4243)
# Objective
Continuation of #2964 (I really should have checked other methods when I made that PR)
yeet unsound lifetime annotations on `Query` methods.
Example unsoundness:
```rust
use bevy::prelude::*;
fn main() {
App::new().add_startup_system(bar).add_system(foo).run();
}
pub fn bar(mut cmds: Commands) {
let e = cmds.spawn().insert(Foo { a: 10 }).id();
cmds.insert_resource(e);
}
#[derive(Component, Debug, PartialEq, Eq)]
pub struct Foo {
a: u32,
}
pub fn foo(mut query: Query<&mut Foo>, e: Res<Entity>) {
dbg!("hi");
{
let data: &Foo = query.get(*e).unwrap();
let data2: Mut<Foo> = query.get_mut(*e).unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.single();
let data2: Mut<Foo> = query.single_mut();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.get_single().unwrap();
let data2: Mut<Foo> = query.get_single_mut().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let data: &Foo = query.iter().next().unwrap();
let data2: Mut<Foo> = query.iter_mut().next().unwrap();
assert_eq!(data, &*data2); // oops UB
}
{
let mut opt_data: Option<&Foo> = None;
let mut opt_data_2: Option<Mut<Foo>> = None;
query.for_each(|data| opt_data = Some(data));
query.for_each_mut(|data| opt_data_2 = Some(data));
assert_eq!(opt_data.unwrap(), &*opt_data_2.unwrap()); // oops UB
}
dbg!("bye");
}
```
## Solution
yeet unsound lifetime annotations on `Query` methods
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2022-03-22 02:49:41 +00:00
}
}
}
Dynamic queries and builder API (#9774)
# Objective
Expand the existing `Query` API to support more dynamic use cases i.e.
scripting.
## Prior Art
- #6390
- #8308
- #10037
## Solution
- Create a `QueryBuilder` with runtime methods to define the set of
component accesses for a built query.
- Create new `WorldQueryData` implementations `FilteredEntityMut` and
`FilteredEntityRef` as variants of `EntityMut` and `EntityRef` that
provide run time checked access to the components included in a given
query.
- Add new methods to `Query` to create "query lens" with a subset of the
access of the initial query.
### Query Builder
The `QueryBuilder` API allows you to define a query at runtime. At it's
most basic use it will simply create a query with the corresponding type
signature:
```rust
let query = QueryBuilder::<Entity, With<A>>::new(&mut world).build();
// is equivalent to
let query = QueryState::<Entity, With<A>>::new(&mut world);
```
Before calling `.build()` you also have the opportunity to add
additional accesses and filters. Here is a simple example where we add
additional filter terms:
```rust
let entity_a = world.spawn((A(0), B(0))).id();
let entity_b = world.spawn((A(0), C(0))).id();
let mut query_a = QueryBuilder::<Entity>::new(&mut world)
.with::<A>()
.without::<C>()
.build();
assert_eq!(entity_a, query_a.single(&world));
```
This alone is useful in that allows you to decide which archetypes your
query will match at runtime. However it is also very limited, consider a
case like the following:
```rust
let query_a = QueryBuilder::<&A>::new(&mut world)
// Add an additional access
.data::<&B>()
.build();
```
This will grant the query an additional read access to component B
however we have no way of accessing the data while iterating as the type
signature still only includes &A. For an even more concrete example of
this consider dynamic components:
```rust
let query_a = QueryBuilder::<Entity>::new(&mut world)
// Adding a filter is easy since it doesn't need be read later
.with_id(component_id_a)
// How do I access the data of this component?
.ref_id(component_id_b)
.build();
```
With this in mind the `QueryBuilder` API seems somewhat incomplete by
itself, we need some way method of accessing the components dynamically.
So here's one:
### Query Transmutation
If the problem is not having the component in the type signature why not
just add it? This PR also adds transmute methods to `QueryBuilder` and
`QueryState`. Here's a simple example:
```rust
world.spawn(A(0));
world.spawn((A(1), B(0)));
let mut query = QueryBuilder::<()>::new(&mut world)
.with::<B>()
.transmute::<&A>()
.build();
query.iter(&world).for_each(|a| assert_eq!(a.0, 1));
```
The `QueryState` and `QueryBuilder` transmute methods look quite similar
but are different in one respect. Transmuting a builder will always
succeed as it will just add the additional accesses needed for the new
terms if they weren't already included. Transmuting a `QueryState` will
panic in the case that the new type signature would give it access it
didn't already have, for example:
```rust
let query = QueryState::<&A, Option<&B>>::new(&mut world);
/// This is fine, the access for Option<&A> is less restrictive than &A
query.transmute::<Option<&A>>(&world);
/// Oh no, this would allow access to &B on entities that might not have it, so it panics
query.transmute::<&B>(&world);
/// This is right out
query.transmute::<&C>(&world);
```
This is quite an appealing API to also have available on `Query` however
it does pose one additional wrinkle: In order to to change the iterator
we need to create a new `QueryState` to back it. `Query` doesn't own
it's own state though, it just borrows it, so we need a place to borrow
it from. This is why `QueryLens` exists, it is a place to store the new
state so it can be borrowed when you call `.query()` leaving you with an
API like this:
```rust
fn function_that_takes_a_query(query: &Query<&A>) {
// ...
}
fn system(query: Query<(&A, &B)>) {
let lens = query.transmute_lens::<&A>();
let q = lens.query();
function_that_takes_a_query(&q);
}
```
Now you may be thinking: Hey, wait a second, you introduced the problem
with dynamic components and then described a solution that only works
for static components! Ok, you got me, I guess we need a bit more:
### Filtered Entity References
Currently the only way you can access dynamic components on entities
through a query is with either `EntityMut` or `EntityRef`, however these
can access all components and so conflict with all other accesses. This
PR introduces `FilteredEntityMut` and `FilteredEntityRef` as
alternatives that have additional runtime checking to prevent accessing
components that you shouldn't. This way you can build a query with a
`QueryBuilder` and actually access the components you asked for:
```rust
let mut query = QueryBuilder::<FilteredEntityRef>::new(&mut world)
.ref_id(component_id_a)
.with(component_id_b)
.build();
let entity_ref = query.single(&world);
// Returns Some(Ptr) as we have that component and are allowed to read it
let a = entity_ref.get_by_id(component_id_a);
// Will return None even though the entity does have the component, as we are not allowed to read it
let b = entity_ref.get_by_id(component_id_b);
```
For the most part these new structs have the exact same methods as their
non-filtered equivalents.
Putting all of this together we can do some truly dynamic ECS queries,
check out the `dynamic` example to see it in action:
```
Commands:
comp, c Create new components
spawn, s Spawn entities
query, q Query for entities
Enter a command with no parameters for usage.
> c A, B, C, Data 4
Component A created with id: 0
Component B created with id: 1
Component C created with id: 2
Component Data created with id: 3
> s A, B, Data 1
Entity spawned with id: 0v0
> s A, C, Data 0
Entity spawned with id: 1v0
> q &Data
0v0: Data: [1, 0, 0, 0]
1v0: Data: [0, 0, 0, 0]
> q B, &mut Data
0v0: Data: [2, 1, 1, 1]
> q B || C, &Data
0v0: Data: [2, 1, 1, 1]
1v0: Data: [0, 0, 0, 0]
```
## Changelog
- Add new `transmute_lens` methods to `Query`.
- Add new types `QueryBuilder`, `FilteredEntityMut`, `FilteredEntityRef`
and `QueryLens`
- `update_archetype_component_access` has been removed, archetype
component accesses are now determined by the accesses set in
`update_component_access`
- Added method `set_access` to `WorldQuery`, this is called before
`update_component_access` for queries that have a restricted set of
accesses, such as those built by `QueryBuilder` or `QueryLens`. This is
primarily used by the `FilteredEntity*` variants and has an empty trait
implementation.
- Added method `get_state` to `WorldQuery` as a fallible version of
`init_state` when you don't have `&mut World` access.
## Future Work
Improve performance of `FilteredEntityMut` and `FilteredEntityRef`,
currently they have to determine the accesses a query has in a given
archetype during iteration which is far from ideal, especially since we
already did the work when matching the archetype in the first place. To
avoid making more internal API changes I have left it out of this PR.
---------
Co-authored-by: Mike Hsu <mike.hsu@gmail.com>
2024-01-16 19:16:49 +00:00
/// Type returned from [`Query::transmute_lens`] containing the new [`QueryState`].
///
/// Call [`query`](QueryLens::query) or [`into`](Into::into) to construct the resulting [`Query`]
pub struct QueryLens < ' w , Q : QueryData , F : QueryFilter = ( ) > {
world : UnsafeWorldCell < ' w > ,
state : QueryState < Q , F > ,
last_run : Tick ,
this_run : Tick ,
}
impl < ' w , Q : QueryData , F : QueryFilter > QueryLens < ' w , Q , F > {
/// Create a [`Query`] from the underlying [`QueryState`].
pub fn query ( & mut self ) -> Query < ' w , '_ , Q , F > {
Query {
world : self . world ,
state : & self . state ,
last_run : self . last_run ,
this_run : self . this_run ,
}
}
}
impl < ' w , ' s , Q : QueryData , F : QueryFilter > From < & ' s mut QueryLens < ' w , Q , F > >
for Query < ' w , ' s , Q , F >
{
fn from ( value : & ' s mut QueryLens < ' w , Q , F > ) -> Query < ' w , ' s , Q , F > {
value . query ( )
}
}
impl < ' w , ' q , Q : QueryData , F : QueryFilter > From < & ' q mut Query < ' w , '_ , Q , F > >
for QueryLens < ' q , Q , F >
{
fn from ( value : & ' q mut Query < ' w , '_ , Q , F > ) -> QueryLens < ' q , Q , F > {
value . transmute_lens_filtered ( )
}
}
2024-09-28 19:35:27 +00:00
/// [System parameter] that provides access to single entity's components, much like [`Query::single`]/[`Query::single_mut`].
///
/// This [`SystemParam`](crate::system::SystemParam) fails validation if zero or more than one matching entity exists.
/// This will cause systems that use this parameter to be skipped.
///
2024-09-29 03:26:28 +00:00
/// Use [`Option<Single<D, F>>`] instead if zero or one matching entities can exist.
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///
/// See [`Query`] for more details.
2024-11-03 16:14:26 +00:00
///
/// [System parameter]: crate::system::SystemParam
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pub struct Single < ' w , D : QueryData , F : QueryFilter = ( ) > {
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pub ( crate ) item : D ::Item < ' w > ,
pub ( crate ) _filter : PhantomData < F > ,
}
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impl < ' w , D : QueryData , F : QueryFilter > Deref for Single < ' w , D , F > {
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type Target = D ::Item < ' w > ;
fn deref ( & self ) -> & Self ::Target {
& self . item
}
}
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impl < ' w , D : QueryData , F : QueryFilter > DerefMut for Single < ' w , D , F > {
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fn deref_mut ( & mut self ) -> & mut Self ::Target {
& mut self . item
}
}
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impl < ' w , D : QueryData , F : QueryFilter > Single < ' w , D , F > {
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/// Returns the inner item with ownership.
pub fn into_inner ( self ) -> D ::Item < ' w > {
self . item
}
}
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/// [System parameter] that works very much like [`Query`] except it always contains at least one matching entity.
///
/// This [`SystemParam`](crate::system::SystemParam) fails validation if no matching entities exist.
/// This will cause systems that use this parameter to be skipped.
///
/// Much like [`Query::is_empty`] the worst case runtime will be `O(n)` where `n` is the number of *potential* matches.
/// This can be notably expensive for queries that rely on non-archetypal filters such as [`Added`](crate::query::Added) or [`Changed`](crate::query::Changed)
/// which must individually check each query result for a match.
///
/// See [`Query`] for more details.
2024-11-03 16:14:26 +00:00
///
/// [System parameter]: crate::system::SystemParam
2024-09-30 18:05:00 +00:00
pub struct Populated < ' w , ' s , D : QueryData , F : QueryFilter = ( ) > ( pub ( crate ) Query < ' w , ' s , D , F > ) ;
impl < ' w , ' s , D : QueryData , F : QueryFilter > Deref for Populated < ' w , ' s , D , F > {
type Target = Query < ' w , ' s , D , F > ;
fn deref ( & self ) -> & Self ::Target {
& self . 0
}
}
impl < D : QueryData , F : QueryFilter > DerefMut for Populated < '_ , '_ , D , F > {
fn deref_mut ( & mut self ) -> & mut Self ::Target {
& mut self . 0
}
}
impl < ' w , ' s , D : QueryData , F : QueryFilter > Populated < ' w , ' s , D , F > {
/// Returns the inner item with ownership.
pub fn into_inner ( self ) -> Query < ' w , ' s , D , F > {
self . 0
}
}