2020-11-16 04:32:23 +00:00
use crate ::{
2022-04-07 20:50:43 +00:00
archetype ::{ ArchetypeComponentId , ArchetypeGeneration , ArchetypeId } ,
Make change lifespan deterministic and update docs (#3956)
## Objective
- ~~Make absurdly long-lived changes stay detectable for even longer (without leveling up to `u64`).~~
- Give all changes a consistent maximum lifespan.
- Improve code clarity.
## Solution
- ~~Increase the frequency of `check_tick` scans to increase the oldest reliably-detectable change.~~
(Deferred until we can benchmark the cost of a scan.)
- Ignore changes older than the maximum reliably-detectable age.
- General refactoring—name the constants, use them everywhere, and update the docs.
- Update test cases to check for the specified behavior.
## Related
This PR addresses (at least partially) the concerns raised in:
- #3071
- #3082 (and associated PR #3084)
## Background
- #1471
Given the minimum interval between `check_ticks` scans, `N`, the oldest reliably-detectable change is `u32::MAX - (2 * N - 1)` (or `MAX_CHANGE_AGE`). Reducing `N` from ~530 million (current value) to something like ~2 million would extend the lifetime of changes by a billion.
| minimum `check_ticks` interval | oldest reliably-detectable change | usable % of `u32::MAX` |
| --- | --- | --- |
| `u32::MAX / 8` (536,870,911) | `(u32::MAX / 4) * 3` | 75.0% |
| `2_000_000` | `u32::MAX - 3_999_999` | 99.9% |
Similarly, changes are still allowed to be between `MAX_CHANGE_AGE`-old and `u32::MAX`-old in the interim between `check_tick` scans. While we prevent their age from overflowing, the test to detect changes still compares raw values. This makes failure ultimately unreliable, since when ancient changes stop being detected varies depending on when the next scan occurs.
## Open Question
Currently, systems and system states are incorrectly initialized with their `last_change_tick` set to `0`, which doesn't handle wraparound correctly.
For consistent behavior, they should either be initialized to the world's `last_change_tick` (and detect no changes) or to `MAX_CHANGE_AGE` behind the world's current `change_tick` (and detect everything as a change). I've currently gone with the latter since that was closer to the existing behavior.
## Follow-up Work
(Edited: entire section)
We haven't actually profiled how long a `check_ticks` scan takes on a "large" `World` , so we don't know if it's safe to increase their frequency. However, we are currently relying on play sessions not lasting long enough to trigger a scan and apps not having enough entities/archetypes for it to be "expensive" (our assumption). That isn't a real solution. (Either scanning never costs enough to impact frame times or we provide an option to use `u64` change ticks. Nobody will accept random hiccups.)
To further extend the lifetime of changes, we actually only need to increment the world tick if a system has `Fetch: !ReadOnlySystemParamFetch`. The behavior will be identical because all writes are sequenced, but I'm not sure how to implement that in a way that the compiler can optimize the branch out.
Also, since having no false positives depends on a `check_ticks` scan running at least every `2 * N - 1` ticks, a `last_check_tick` should also be stored in the `World` so that any lull in system execution (like a command flush) could trigger a scan if needed. To be completely robust, all the systems initialized on the world should be scanned, not just those in the current stage.
2022-05-09 14:00:16 +00:00
change_detection ::MAX_CHANGE_AGE ,
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
component ::ComponentId ,
2022-04-05 20:04:34 +00:00
prelude ::FromWorld ,
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
query ::{ Access , FilteredAccessSet } ,
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
schedule ::{ SystemLabel , SystemLabelId } ,
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
system ::{
2021-09-30 20:54:47 +00:00
check_system_change_tick , ReadOnlySystemParamFetch , System , SystemParam , SystemParamFetch ,
2022-05-30 17:59:20 +00:00
SystemParamItem , SystemParamState ,
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
} ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
world ::{ World , WorldId } ,
2020-11-16 04:32:23 +00:00
} ;
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
use bevy_ecs_macros ::all_tuples ;
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
use std ::{ borrow ::Cow , fmt ::Debug , marker ::PhantomData } ;
2020-11-08 20:34:05 +00:00
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
/// The metadata of a [`System`].
2022-03-29 23:39:38 +00:00
#[ derive(Clone) ]
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
pub struct SystemMeta {
2020-11-08 20:34:05 +00:00
pub ( crate ) name : Cow < 'static , str > ,
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
pub ( crate ) component_access_set : FilteredAccessSet < ComponentId > ,
pub ( crate ) archetype_component_access : Access < ArchetypeComponentId > ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
// NOTE: this must be kept private. making a SystemMeta non-send is irreversible to prevent
2021-03-11 00:27:30 +00:00
// SystemParams from overriding each other
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
is_send : bool ,
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 ) last_change_tick : u32 ,
2020-11-08 20:34:05 +00:00
}
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
impl SystemMeta {
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
fn new < T > ( ) -> Self {
Self {
name : std ::any ::type_name ::< T > ( ) . into ( ) ,
archetype_component_access : Access ::default ( ) ,
component_access_set : FilteredAccessSet ::default ( ) ,
is_send : true ,
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
last_change_tick : 0 ,
2020-11-08 20:34:05 +00:00
}
}
2020-12-16 05:57:16 +00:00
2021-04-15 20:36:16 +00:00
/// Returns true if the system is [`Send`].
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 ]
pub fn is_send ( & self ) -> bool {
self . is_send
2020-12-16 05:57:16 +00:00
}
2021-04-15 20:36:16 +00:00
/// Sets the system to be not [`Send`].
///
/// This is irreversible.
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 ]
pub fn set_non_send ( & mut self ) {
self . is_send = false ;
2020-12-16 05:57:16 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
}
2020-12-16 05:57:16 +00:00
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
// TODO: Actually use this in FunctionSystem. We should probably only do this once Systems are constructed using a World reference
// (to avoid the need for unwrapping to retrieve SystemMeta)
2022-01-07 09:25:12 +00:00
/// Holds on to persistent state required to drive [`SystemParam`] for a [`System`].
2022-02-15 21:53:52 +00:00
///
/// This is a very powerful and convenient tool for working with exclusive world access,
/// allowing you to fetch data from the [`World`] as if you were running a [`System`].
///
/// Borrow-checking is handled for you, allowing you to mutably access multiple compatible system parameters at once,
/// and arbitrary system parameters (like [`EventWriter`](crate::event::EventWriter)) can be conveniently fetched.
///
/// For an alternative approach to split mutable access to the world, see [`World::resource_scope`].
///
/// # Warning
///
/// [`SystemState`] values created can be cached to improve performance,
/// and *must* be cached and reused in order for system parameters that rely on local state to work correctly.
/// These include:
/// - [`Added`](crate::query::Added) and [`Changed`](crate::query::Changed) query filters
/// - [`Local`](crate::system::Local) variables that hold state
/// - [`EventReader`](crate::event::EventReader) system parameters, which rely on a [`Local`](crate::system::Local) to track which events have been seen
///
/// # Example
///
/// Basic usage:
/// ```rust
/// use bevy_ecs::prelude::*;
/// use bevy_ecs::{system::SystemState};
/// use bevy_ecs::event::Events;
///
/// struct MyEvent;
/// struct MyResource(u32);
///
/// #[derive(Component)]
/// struct MyComponent;
///
/// // Work directly on the `World`
/// let mut world = World::new();
/// world.init_resource::<Events<MyEvent>>();
///
/// // Construct a `SystemState` struct, passing in a tuple of `SystemParam`
/// // as if you were writing an ordinary system.
/// let mut system_state: SystemState<(
/// EventWriter<MyEvent>,
/// Option<ResMut<MyResource>>,
/// Query<&MyComponent>,
/// )> = SystemState::new(&mut world);
///
/// // Use system_state.get_mut(&mut world) and unpack your system parameters into variables!
/// // system_state.get(&world) provides read-only versions of your system parameters instead.
/// let (event_writer, maybe_resource, query) = system_state.get_mut(&mut world);
/// ```
/// Caching:
/// ```rust
/// use bevy_ecs::prelude::*;
/// use bevy_ecs::{system::SystemState};
/// use bevy_ecs::event::Events;
///
/// struct MyEvent;
/// struct CachedSystemState<'w, 's>{
/// event_state: SystemState<EventReader<'w, 's, MyEvent>>
/// }
///
/// // Create and store a system state once
/// let mut world = World::new();
/// world.init_resource::<Events<MyEvent>>();
/// let initial_state: SystemState<EventReader<MyEvent>> = SystemState::new(&mut world);
///
/// // The system state is cached in a resource
/// world.insert_resource(CachedSystemState{event_state: initial_state});
///
/// // Later, fetch the cached system state, saving on overhead
/// world.resource_scope(|world, mut cached_state: Mut<CachedSystemState>| {
/// let mut event_reader = cached_state.event_state.get_mut(world);
///
2022-07-11 15:28:50 +00:00
/// for events in event_reader.iter() {
2022-02-15 21:53:52 +00:00
/// println!("Hello World!");
/// };
/// });
/// ```
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
pub struct SystemState < Param : SystemParam > {
meta : SystemMeta ,
param_state : < Param as SystemParam > ::Fetch ,
world_id : WorldId ,
archetype_generation : ArchetypeGeneration ,
}
impl < Param : SystemParam > SystemState < Param > {
pub fn new ( world : & mut World ) -> Self {
let mut meta = SystemMeta ::new ::< Param > ( ) ;
Make change lifespan deterministic and update docs (#3956)
## Objective
- ~~Make absurdly long-lived changes stay detectable for even longer (without leveling up to `u64`).~~
- Give all changes a consistent maximum lifespan.
- Improve code clarity.
## Solution
- ~~Increase the frequency of `check_tick` scans to increase the oldest reliably-detectable change.~~
(Deferred until we can benchmark the cost of a scan.)
- Ignore changes older than the maximum reliably-detectable age.
- General refactoring—name the constants, use them everywhere, and update the docs.
- Update test cases to check for the specified behavior.
## Related
This PR addresses (at least partially) the concerns raised in:
- #3071
- #3082 (and associated PR #3084)
## Background
- #1471
Given the minimum interval between `check_ticks` scans, `N`, the oldest reliably-detectable change is `u32::MAX - (2 * N - 1)` (or `MAX_CHANGE_AGE`). Reducing `N` from ~530 million (current value) to something like ~2 million would extend the lifetime of changes by a billion.
| minimum `check_ticks` interval | oldest reliably-detectable change | usable % of `u32::MAX` |
| --- | --- | --- |
| `u32::MAX / 8` (536,870,911) | `(u32::MAX / 4) * 3` | 75.0% |
| `2_000_000` | `u32::MAX - 3_999_999` | 99.9% |
Similarly, changes are still allowed to be between `MAX_CHANGE_AGE`-old and `u32::MAX`-old in the interim between `check_tick` scans. While we prevent their age from overflowing, the test to detect changes still compares raw values. This makes failure ultimately unreliable, since when ancient changes stop being detected varies depending on when the next scan occurs.
## Open Question
Currently, systems and system states are incorrectly initialized with their `last_change_tick` set to `0`, which doesn't handle wraparound correctly.
For consistent behavior, they should either be initialized to the world's `last_change_tick` (and detect no changes) or to `MAX_CHANGE_AGE` behind the world's current `change_tick` (and detect everything as a change). I've currently gone with the latter since that was closer to the existing behavior.
## Follow-up Work
(Edited: entire section)
We haven't actually profiled how long a `check_ticks` scan takes on a "large" `World` , so we don't know if it's safe to increase their frequency. However, we are currently relying on play sessions not lasting long enough to trigger a scan and apps not having enough entities/archetypes for it to be "expensive" (our assumption). That isn't a real solution. (Either scanning never costs enough to impact frame times or we provide an option to use `u64` change ticks. Nobody will accept random hiccups.)
To further extend the lifetime of changes, we actually only need to increment the world tick if a system has `Fetch: !ReadOnlySystemParamFetch`. The behavior will be identical because all writes are sequenced, but I'm not sure how to implement that in a way that the compiler can optimize the branch out.
Also, since having no false positives depends on a `check_ticks` scan running at least every `2 * N - 1` ticks, a `last_check_tick` should also be stored in the `World` so that any lull in system execution (like a command flush) could trigger a scan if needed. To be completely robust, all the systems initialized on the world should be scanned, not just those in the current stage.
2022-05-09 14:00:16 +00:00
meta . last_change_tick = world . change_tick ( ) . wrapping_sub ( MAX_CHANGE_AGE ) ;
2022-02-25 03:10:59 +00:00
let param_state = < Param ::Fetch as SystemParamState > ::init ( world , & mut meta ) ;
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
Self {
meta ,
param_state ,
world_id : world . id ( ) ,
archetype_generation : ArchetypeGeneration ::initial ( ) ,
}
}
#[ inline ]
pub fn meta ( & self ) -> & SystemMeta {
& self . meta
}
/// Retrieve the [`SystemParam`] values. This can only be called when all parameters are read-only.
#[ inline ]
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.
2021-08-15 20:51:53 +00:00
pub fn get < ' w , ' s > (
& ' s mut self ,
world : & ' w World ,
) -> < Param ::Fetch as SystemParamFetch < ' w , ' s > > ::Item
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
where
Param ::Fetch : ReadOnlySystemParamFetch ,
{
self . validate_world_and_update_archetypes ( world ) ;
2022-07-04 14:44:24 +00:00
// SAFETY: Param is read-only and doesn't allow mutable access to World. It also matches the World this SystemState was created with.
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
unsafe { self . get_unchecked_manual ( world ) }
}
/// Retrieve the mutable [`SystemParam`] values.
#[ inline ]
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.
2021-08-15 20:51:53 +00:00
pub fn get_mut < ' w , ' s > (
& ' s mut self ,
world : & ' w mut World ,
) -> < Param ::Fetch as SystemParamFetch < ' w , ' s > > ::Item {
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
self . validate_world_and_update_archetypes ( world ) ;
2022-07-04 14:44:24 +00:00
// SAFETY: World is uniquely borrowed and matches the World this SystemState was created with.
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
unsafe { self . get_unchecked_manual ( world ) }
}
/// Applies all state queued up for [`SystemParam`] values. For example, this will apply commands queued up
/// by a [`Commands`](`super::Commands`) parameter to the given [`World`].
2022-01-07 09:25:12 +00:00
/// This function should be called manually after the values returned by [`SystemState::get`] and [`SystemState::get_mut`]
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
/// are finished being used.
pub fn apply ( & mut self , world : & mut World ) {
self . param_state . apply ( world ) ;
}
#[ inline ]
pub fn matches_world ( & self , world : & World ) -> bool {
self . world_id = = world . id ( )
}
fn validate_world_and_update_archetypes ( & mut self , world : & World ) {
assert! ( self . matches_world ( world ) , " Encountered a mismatched World. A SystemState cannot be used with Worlds other than the one it was created with. " ) ;
let archetypes = world . archetypes ( ) ;
let new_generation = archetypes . generation ( ) ;
let old_generation = std ::mem ::replace ( & mut self . archetype_generation , new_generation ) ;
let archetype_index_range = old_generation . value ( ) .. new_generation . value ( ) ;
for archetype_index in archetype_index_range {
self . param_state . new_archetype (
& archetypes [ ArchetypeId ::new ( archetype_index ) ] ,
& mut self . meta ,
) ;
}
}
/// Retrieve the [`SystemParam`] values. This will not update archetypes automatically.
///
/// # Safety
/// This call might access any of the input parameters in a way that violates Rust's mutability rules. Make sure the data
/// access is safe in the context of global [`World`] access. The passed-in [`World`] _must_ be the [`World`] the [`SystemState`] was
2022-01-07 09:25:12 +00:00
/// created with.
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
#[ inline ]
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.
2021-08-15 20:51:53 +00:00
pub unsafe fn get_unchecked_manual < ' w , ' s > (
& ' s mut self ,
world : & ' w World ,
) -> < Param ::Fetch as SystemParamFetch < ' w , ' s > > ::Item {
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
let change_tick = world . increment_change_tick ( ) ;
let param = < Param ::Fetch as SystemParamFetch > ::get_param (
& mut self . param_state ,
& self . meta ,
world ,
change_tick ,
) ;
self . meta . last_change_tick = change_tick ;
param
}
Modular Rendering (#2831)
This changes how render logic is composed to make it much more modular. Previously, all extraction logic was centralized for a given "type" of rendered thing. For example, we extracted meshes into a vector of ExtractedMesh, which contained the mesh and material asset handles, the transform, etc. We looked up bindings for "drawn things" using their index in the `Vec<ExtractedMesh>`. This worked fine for built in rendering, but made it hard to reuse logic for "custom" rendering. It also prevented us from reusing things like "extracted transforms" across contexts.
To make rendering more modular, I made a number of changes:
* Entities now drive rendering:
* We extract "render components" from "app components" and store them _on_ entities. No more centralized uber lists! We now have true "ECS-driven rendering"
* To make this perform well, I implemented #2673 in upstream Bevy for fast batch insertions into specific entities. This was merged into the `pipelined-rendering` branch here: #2815
* Reworked the `Draw` abstraction:
* Generic `PhaseItems`: each draw phase can define its own type of "rendered thing", which can define its own "sort key"
* Ported the 2d, 3d, and shadow phases to the new PhaseItem impl (currently Transparent2d, Transparent3d, and Shadow PhaseItems)
* `Draw` trait and and `DrawFunctions` are now generic on PhaseItem
* Modular / Ergonomic `DrawFunctions` via `RenderCommands`
* RenderCommand is a trait that runs an ECS query and produces one or more RenderPass calls. Types implementing this trait can be composed to create a final DrawFunction. For example the DrawPbr DrawFunction is created from the following DrawCommand tuple. Const generics are used to set specific bind group locations:
```rust
pub type DrawPbr = (
SetPbrPipeline,
SetMeshViewBindGroup<0>,
SetStandardMaterialBindGroup<1>,
SetTransformBindGroup<2>,
DrawMesh,
);
```
* The new `custom_shader_pipelined` example illustrates how the commands above can be reused to create a custom draw function:
```rust
type DrawCustom = (
SetCustomMaterialPipeline,
SetMeshViewBindGroup<0>,
SetTransformBindGroup<2>,
DrawMesh,
);
```
* ExtractComponentPlugin and UniformComponentPlugin:
* Simple, standardized ways to easily extract individual components and write them to GPU buffers
* Ported PBR and Sprite rendering to the new primitives above.
* Removed staging buffer from UniformVec in favor of direct Queue usage
* Makes UniformVec much easier to use and more ergonomic. Completely removes the need for custom render graph nodes in these contexts (see the PbrNode and view Node removals and the much simpler call patterns in the relevant Prepare systems).
* Added a many_cubes_pipelined example to benchmark baseline 3d rendering performance and ensure there were no major regressions during this port. Avoiding regressions was challenging given that the old approach of extracting into centralized vectors is basically the "optimal" approach. However thanks to a various ECS optimizations and render logic rephrasing, we pretty much break even on this benchmark!
* Lifetimeless SystemParams: this will be a bit divisive, but as we continue to embrace "trait driven systems" (ex: ExtractComponentPlugin, UniformComponentPlugin, DrawCommand), the ergonomics of `(Query<'static, 'static, (&'static A, &'static B, &'static)>, Res<'static, C>)` were getting very hard to bear. As a compromise, I added "static type aliases" for the relevant SystemParams. The previous example can now be expressed like this: `(SQuery<(Read<A>, Read<B>)>, SRes<C>)`. If anyone has better ideas / conflicting opinions, please let me know!
* RunSystem trait: a way to define Systems via a trait with a SystemParam associated type. This is used to implement the various plugins mentioned above. I also added SystemParamItem and QueryItem type aliases to make "trait stye" ecs interactions nicer on the eyes (and fingers).
* RenderAsset retrying: ensures that render assets are only created when they are "ready" and allows us to create bind groups directly inside render assets (which significantly simplified the StandardMaterial code). I think ultimately we should swap this out on "asset dependency" events to wait for dependencies to load, but this will require significant asset system changes.
* Updated some built in shaders to account for missing MeshUniform fields
2021-09-23 06:16:11 +00:00
}
2022-04-05 20:04:34 +00:00
impl < Param : SystemParam > FromWorld for SystemState < Param > {
fn from_world ( world : & mut World ) -> Self {
Self ::new ( world )
}
}
2021-04-15 20:36:16 +00:00
/// Conversion trait to turn something into a [`System`].
///
2021-04-21 23:19:34 +00:00
/// Use this to get a system from a function. Also note that every system implements this trait as
/// well.
2021-04-15 20:36:16 +00:00
///
/// # Examples
///
/// ```
/// use bevy_ecs::system::IntoSystem;
/// use bevy_ecs::system::Res;
///
/// fn my_system_function(an_usize_resource: Res<usize>) {}
///
2022-04-16 21:33:51 +00:00
/// let system = IntoSystem::into_system(my_system_function);
2021-04-15 20:36:16 +00:00
/// ```
2021-06-27 00:40:09 +00:00
// This trait has to be generic because we have potentially overlapping impls, in particular
// because Rust thinks a type could impl multiple different `FnMut` combinations
// even though none can currently
2022-02-08 04:00:58 +00:00
pub trait IntoSystem < In , Out , Params > : Sized {
2021-06-27 00:40:09 +00:00
type System : System < In = In , Out = Out > ;
2021-04-15 20:36:16 +00:00
/// Turns this value into its corresponding [`System`].
2022-02-08 04:00:58 +00:00
fn into_system ( this : Self ) -> Self ::System ;
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
}
2021-02-09 20:14:10 +00:00
2021-06-27 00:40:09 +00:00
pub struct AlreadyWasSystem ;
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
// Systems implicitly implement IntoSystem
2021-06-27 00:40:09 +00:00
impl < In , Out , Sys : System < In = In , Out = Out > > IntoSystem < In , Out , AlreadyWasSystem > for Sys {
type System = Sys ;
2022-02-08 04:00:58 +00:00
fn into_system ( this : Self ) -> Sys {
this
2020-12-16 05:57:16 +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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}
2020-12-16 05:57:16 +00:00
2021-04-15 20:36:16 +00:00
/// Wrapper type to mark a [`SystemParam`] as an input.
///
/// [`System`]s may take an optional input which they require to be passed to them when they
/// are being [`run`](System::run). For [`FunctionSystems`](FunctionSystem) the input may be marked
/// with this `In` type, but only the first param of a function may be tagged as an input. This also
2022-07-21 20:46:54 +00:00
/// means a system can only have one or zero input parameters.
2021-04-15 20:36:16 +00:00
///
/// # Examples
///
/// Here is a simple example of a system that takes a [`usize`] returning the square of it.
///
/// ```
/// use bevy_ecs::prelude::*;
///
/// fn main() {
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/// let mut square_system = IntoSystem::into_system(square);
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///
/// let mut world = World::default();
/// square_system.initialize(&mut world);
/// assert_eq!(square_system.run(12, &mut world), 144);
/// }
///
/// fn square(In(input): In<usize>) -> usize {
/// input * input
/// }
/// ```
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
pub struct In < In > ( pub In ) ;
2022-03-21 05:23:36 +00:00
#[ doc(hidden) ]
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
pub struct InputMarker ;
2021-04-15 20:36:16 +00:00
/// The [`System`] counter part of an ordinary function.
///
2022-04-16 21:33:51 +00:00
/// You get this by calling [`IntoSystem::into_system`] on a function that only accepts
2021-04-21 23:19:34 +00:00
/// [`SystemParam`]s. The output of the system becomes the functions return type, while the input
2021-08-06 20:55:24 +00:00
/// becomes the functions [`In`] tagged parameter or `()` if no such parameter exists.
2022-05-02 16:04:49 +00:00
///
/// [`FunctionSystem`] must be `.initialized` before they can be 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
pub struct FunctionSystem < In , Out , Param , Marker , F >
where
Param : SystemParam ,
{
func : F ,
param_state : Option < Param ::Fetch > ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
system_meta : SystemMeta ,
2022-04-07 20:50:43 +00:00
world_id : Option < WorldId > ,
archetype_generation : ArchetypeGeneration ,
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
// NOTE: PhantomData<fn()-> T> gives this safe Send/Sync impls
marker : PhantomData < fn ( ) -> ( In , Out , Marker ) > ,
}
2020-12-16 05:57:16 +00:00
2021-06-27 00:40:09 +00:00
pub struct IsFunctionSystem ;
2020-12-16 05:57:16 +00:00
2021-06-27 00:40:09 +00:00
impl < In , Out , Param , Marker , F > IntoSystem < In , Out , ( IsFunctionSystem , Param , Marker ) > for F
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
where
In : 'static ,
Out : 'static ,
Param : SystemParam + 'static ,
Marker : 'static ,
F : SystemParamFunction < In , Out , Param , Marker > + Send + Sync + 'static ,
{
2021-06-27 00:40:09 +00:00
type System = FunctionSystem < In , Out , Param , Marker , F > ;
2022-02-08 04:00:58 +00:00
fn into_system ( func : Self ) -> Self ::System {
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
FunctionSystem {
2022-02-08 04:00:58 +00:00
func ,
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
param_state : None ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
system_meta : SystemMeta ::new ::< F > ( ) ,
2022-04-07 20:50:43 +00:00
world_id : None ,
archetype_generation : ArchetypeGeneration ::initial ( ) ,
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
marker : PhantomData ,
2021-02-09 20:14:10 +00:00
}
2020-12-16 05:57:16 +00:00
}
}
2022-05-30 17:59:20 +00:00
impl < In , Out , Param , Marker , F > FunctionSystem < In , Out , Param , Marker , F >
where
Param : SystemParam ,
{
/// Message shown when a system isn't initialised
// When lines get too long, rustfmt can sometimes refuse to format them.
// Work around this by storing the message separately.
const PARAM_MESSAGE : & 'static str = " System's param_state was not found. Did you forget to initialize this system before running it? " ;
}
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
impl < In , Out , Param , Marker , F > System for FunctionSystem < In , Out , Param , Marker , F >
where
In : 'static ,
Out : 'static ,
Param : SystemParam + 'static ,
Marker : 'static ,
F : SystemParamFunction < In , Out , Param , Marker > + Send + Sync + 'static ,
{
2020-12-13 02:04:42 +00:00
type In = In ;
type Out = Out ;
2020-11-17 02:18:00 +00:00
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
fn name ( & self ) -> Cow < 'static , str > {
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
self . system_meta . name . clone ( )
2020-11-08 20:34:05 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
fn component_access ( & self ) -> & Access < ComponentId > {
2021-07-29 20:52:15 +00:00
self . system_meta . component_access_set . combined_access ( )
2021-02-09 20:14:10 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
fn archetype_component_access ( & self ) -> & Access < ArchetypeComponentId > {
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
& self . system_meta . archetype_component_access
2020-07-16 00:20:36 +00:00
}
2020-07-14 02:29:34 +00:00
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
fn is_send ( & self ) -> bool {
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
self . system_meta . is_send
2020-07-10 04:18:35 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
unsafe fn run_unsafe ( & mut self , input : Self ::In , world : & World ) -> Self ::Out {
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
let change_tick = world . increment_change_tick ( ) ;
2022-05-30 17:59:20 +00:00
// Safety:
// We update the archetype component access correctly based on `Param`'s requirements
// in `update_archetype_component_access`.
// Our caller upholds the requirements.
let params = < Param as SystemParam > ::Fetch ::get_param (
self . param_state . as_mut ( ) . expect ( Self ::PARAM_MESSAGE ) ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
& self . system_meta ,
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
world ,
Reliable change detection (#1471)
# Problem Definition
The current change tracking (via flags for both components and resources) fails to detect changes made by systems that are scheduled to run earlier in the frame than they are.
This issue is discussed at length in [#68](https://github.com/bevyengine/bevy/issues/68) and [#54](https://github.com/bevyengine/bevy/issues/54).
This is very much a draft PR, and contributions are welcome and needed.
# Criteria
1. Each change is detected at least once, no matter the ordering.
2. Each change is detected at most once, no matter the ordering.
3. Changes should be detected the same frame that they are made.
4. Competitive ergonomics. Ideally does not require opting-in.
5. Low CPU overhead of computation.
6. Memory efficient. This must not increase over time, except where the number of entities / resources does.
7. Changes should not be lost for systems that don't run.
8. A frame needs to act as a pure function. Given the same set of entities / components it needs to produce the same end state without side-effects.
**Exact** change-tracking proposals satisfy criteria 1 and 2.
**Conservative** change-tracking proposals satisfy criteria 1 but not 2.
**Flaky** change tracking proposals satisfy criteria 2 but not 1.
# Code Base Navigation
There are three types of flags:
- `Added`: A piece of data was added to an entity / `Resources`.
- `Mutated`: A piece of data was able to be modified, because its `DerefMut` was accessed
- `Changed`: The bitwise OR of `Added` and `Changed`
The special behavior of `ChangedRes`, with respect to the scheduler is being removed in [#1313](https://github.com/bevyengine/bevy/pull/1313) and does not need to be reproduced.
`ChangedRes` and friends can be found in "bevy_ecs/core/resources/resource_query.rs".
The `Flags` trait for Components can be found in "bevy_ecs/core/query.rs".
`ComponentFlags` are stored in "bevy_ecs/core/archetypes.rs", defined on line 446.
# Proposals
**Proposal 5 was selected for implementation.**
## Proposal 0: No Change Detection
The baseline, where computations are performed on everything regardless of whether it changed.
**Type:** Conservative
**Pros:**
- already implemented
- will never miss events
- no overhead
**Cons:**
- tons of repeated work
- doesn't allow users to avoid repeating work (or monitoring for other changes)
## Proposal 1: Earlier-This-Tick Change Detection
The current approach as of Bevy 0.4. Flags are set, and then flushed at the end of each frame.
**Type:** Flaky
**Pros:**
- already implemented
- simple to understand
- low memory overhead (2 bits per component)
- low time overhead (clear every flag once per frame)
**Cons:**
- misses systems based on ordering
- systems that don't run every frame miss changes
- duplicates detection when looping
- can lead to unresolvable circular dependencies
## Proposal 2: Two-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in either the current frame's list of changes or the previous frame's.
**Type:** Conservative
**Pros:**
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- can result in a great deal of duplicated work
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 3: Last-Tick Change Detection
Flags persist for two frames, using a double-buffer system identical to that used in events.
A change is observed if it is found in the previous frame's list of changes.
**Type:** Exact
**Pros:**
- exact
- easy to understand
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- change detection is always delayed, possibly causing painful chained delays
- systems that don't run every frame miss changes
- duplicates detection when looping
## Proposal 4: Flag-Doubling Change Detection
Combine Proposal 2 and Proposal 3. Differentiate between `JustChanged` (current behavior) and `Changed` (Proposal 3).
Pack this data into the flags according to [this implementation proposal](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804).
**Type:** Flaky + Exact
**Pros:**
- allows users to acc
- easy to implement
- low memory overhead (4 bits per component)
- low time overhead (bit mask and shift every flag once per frame)
**Cons:**
- users must specify the type of change detection required
- still quite fragile to system ordering effects when using the flaky `JustChanged` form
- cannot get immediate + exact results
- systems that don't run every frame miss changes
- duplicates detection when looping
## [SELECTED] Proposal 5: Generation-Counter Change Detection
A global counter is increased after each system is run. Each component saves the time of last mutation, and each system saves the time of last execution. Mutation is detected when the component's counter is greater than the system's counter. Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-769174804). How to handle addition detection is unsolved; the current proposal is to use the highest bit of the counter as in proposal 1.
**Type:** Exact (for mutations), flaky (for additions)
**Pros:**
- low time overhead (set component counter on access, set system counter after execution)
- robust to systems that don't run every frame
- robust to systems that loop
**Cons:**
- moderately complex implementation
- must be modified as systems are inserted dynamically
- medium memory overhead (4 bytes per component + system)
- unsolved addition detection
## Proposal 6: System-Data Change Detection
For each system, track which system's changes it has seen. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- conceptually simple
**Cons:**
- requires storing data on each system
- implementation is complex
- must be modified as systems are inserted dynamically
## Proposal 7: Total-Order Change Detection
Discussed [here](https://github.com/bevyengine/bevy/issues/68#issuecomment-754326523). This proposal is somewhat complicated by the new scheduler, but I believe it should still be conceptually feasible. This approach is only worth fully designing and implementing if Proposal 5 fails in some way.
**Type:** Exact
**Pros:**
- exact
- efficient data storage relative to other exact proposals
**Cons:**
- requires access to the scheduler
- complex implementation and difficulty grokking
- must be modified as systems are inserted dynamically
# Tests
- We will need to verify properties 1, 2, 3, 7 and 8. Priority: 1 > 2 = 3 > 8 > 7
- Ideally we can use identical user-facing syntax for all proposals, allowing us to re-use the same syntax for each.
- When writing tests, we need to carefully specify order using explicit dependencies.
- These tests will need to be duplicated for both components and resources.
- We need to be sure to handle cases where ambiguous system orders exist.
`changing_system` is always the system that makes the changes, and `detecting_system` always detects the changes.
The component / resource changed will be simple boolean wrapper structs.
## Basic Added / Mutated / Changed
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 2
## At Least Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs after `detecting_system`
- verify at the end of tick 2
## At Most Once
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs once before `detecting_system`
- increment a counter based on the number of changes detected
- verify at the end of tick 2
## Fast Detection
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs before `detecting_system`
- verify at the end of tick 1
## Ambiguous System Ordering Robustness
2 x 3 x 2 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs [before/after] `detecting_system` in tick 1
- `changing_system` runs [after/before] `detecting_system` in tick 2
## System Pausing
2 x 3 design:
- Resources vs. Components
- Added vs. Changed vs. Mutated
- `changing_system` runs in tick 1, then is disabled by run criteria
- `detecting_system` is disabled by run criteria until it is run once during tick 3
- verify at the end of tick 3
## Addition Causes Mutation
2 design:
- Resources vs. Components
- `adding_system_1` adds a component / resource
- `adding system_2` adds the same component / resource
- verify the `Mutated` flag at the end of the tick
- verify the `Added` flag at the end of the tick
First check tests for: https://github.com/bevyengine/bevy/issues/333
Second check tests for: https://github.com/bevyengine/bevy/issues/1443
## Changes Made By Commands
- `adding_system` runs in Update in tick 1, and sends a command to add a component
- `detecting_system` runs in Update in tick 1 and 2, after `adding_system`
- We can't detect the changes in tick 1, since they haven't been processed yet
- If we were to track these changes as being emitted by `adding_system`, we can't detect the changes in tick 2 either, since `detecting_system` has already run once after `adding_system` :(
# Benchmarks
See: [general advice](https://github.com/bevyengine/bevy/blob/master/docs/profiling.md), [Criterion crate](https://github.com/bheisler/criterion.rs)
There are several critical parameters to vary:
1. entity count (1 to 10^9)
2. fraction of entities that are changed (0% to 100%)
3. cost to perform work on changed entities, i.e. workload (1 ns to 1s)
1 and 2 should be varied between benchmark runs. 3 can be added on computationally.
We want to measure:
- memory cost
- run time
We should collect these measurements across several frames (100?) to reduce bootup effects and accurately measure the mean, variance and drift.
Entity-component change detection is much more important to benchmark than resource change detection, due to the orders of magnitude higher number of pieces of data.
No change detection at all should be included in benchmarks as a second control for cases where missing changes is unacceptable.
## Graphs
1. y: performance, x: log_10(entity count), color: proposal, facet: performance metric. Set cost to perform work to 0.
2. y: run time, x: cost to perform work, color: proposal, facet: fraction changed. Set number of entities to 10^6
3. y: memory, x: frames, color: proposal
# Conclusions
1. Is the theoretical categorization of the proposals correct according to our tests?
2. How does the performance of the proposals compare without any load?
3. How does the performance of the proposals compare with realistic loads?
4. At what workload does more exact change tracking become worth the (presumably) higher overhead?
5. When does adding change-detection to save on work become worthwhile?
6. Is there enough divergence in performance between the best solutions in each class to ship more than one change-tracking solution?
# Implementation Plan
1. Write a test suite.
2. Verify that tests fail for existing approach.
3. Write a benchmark suite.
4. Get performance numbers for existing approach.
5. Implement, test and benchmark various solutions using a Git branch per proposal.
6. Create a draft PR with all solutions and present results to team.
7. Select a solution and replace existing change detection.
Co-authored-by: Brice DAVIER <bricedavier@gmail.com>
Co-authored-by: Carter Anderson <mcanders1@gmail.com>
2021-03-19 17:53:26 +00:00
change_tick ,
) ;
2022-05-30 17:59:20 +00:00
let out = self . func . run ( input , params ) ;
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
self . system_meta . last_change_tick = change_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
out
2020-07-10 04:18:35 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
fn apply_buffers ( & mut self , world : & mut World ) {
2022-05-30 17:59:20 +00:00
let param_state = self . param_state . as_mut ( ) . expect ( Self ::PARAM_MESSAGE ) ;
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
param_state . apply ( world ) ;
2020-07-10 04:18:35 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
fn initialize ( & mut self , world : & mut World ) {
2022-04-07 20:50:43 +00:00
self . world_id = Some ( world . id ( ) ) ;
Make change lifespan deterministic and update docs (#3956)
## Objective
- ~~Make absurdly long-lived changes stay detectable for even longer (without leveling up to `u64`).~~
- Give all changes a consistent maximum lifespan.
- Improve code clarity.
## Solution
- ~~Increase the frequency of `check_tick` scans to increase the oldest reliably-detectable change.~~
(Deferred until we can benchmark the cost of a scan.)
- Ignore changes older than the maximum reliably-detectable age.
- General refactoring—name the constants, use them everywhere, and update the docs.
- Update test cases to check for the specified behavior.
## Related
This PR addresses (at least partially) the concerns raised in:
- #3071
- #3082 (and associated PR #3084)
## Background
- #1471
Given the minimum interval between `check_ticks` scans, `N`, the oldest reliably-detectable change is `u32::MAX - (2 * N - 1)` (or `MAX_CHANGE_AGE`). Reducing `N` from ~530 million (current value) to something like ~2 million would extend the lifetime of changes by a billion.
| minimum `check_ticks` interval | oldest reliably-detectable change | usable % of `u32::MAX` |
| --- | --- | --- |
| `u32::MAX / 8` (536,870,911) | `(u32::MAX / 4) * 3` | 75.0% |
| `2_000_000` | `u32::MAX - 3_999_999` | 99.9% |
Similarly, changes are still allowed to be between `MAX_CHANGE_AGE`-old and `u32::MAX`-old in the interim between `check_tick` scans. While we prevent their age from overflowing, the test to detect changes still compares raw values. This makes failure ultimately unreliable, since when ancient changes stop being detected varies depending on when the next scan occurs.
## Open Question
Currently, systems and system states are incorrectly initialized with their `last_change_tick` set to `0`, which doesn't handle wraparound correctly.
For consistent behavior, they should either be initialized to the world's `last_change_tick` (and detect no changes) or to `MAX_CHANGE_AGE` behind the world's current `change_tick` (and detect everything as a change). I've currently gone with the latter since that was closer to the existing behavior.
## Follow-up Work
(Edited: entire section)
We haven't actually profiled how long a `check_ticks` scan takes on a "large" `World` , so we don't know if it's safe to increase their frequency. However, we are currently relying on play sessions not lasting long enough to trigger a scan and apps not having enough entities/archetypes for it to be "expensive" (our assumption). That isn't a real solution. (Either scanning never costs enough to impact frame times or we provide an option to use `u64` change ticks. Nobody will accept random hiccups.)
To further extend the lifetime of changes, we actually only need to increment the world tick if a system has `Fetch: !ReadOnlySystemParamFetch`. The behavior will be identical because all writes are sequenced, but I'm not sure how to implement that in a way that the compiler can optimize the branch out.
Also, since having no false positives depends on a `check_ticks` scan running at least every `2 * N - 1` ticks, a `last_check_tick` should also be stored in the `World` so that any lull in system execution (like a command flush) could trigger a scan if needed. To be completely robust, all the systems initialized on the world should be scanned, not just those in the current stage.
2022-05-09 14:00:16 +00:00
self . system_meta . last_change_tick = world . change_tick ( ) . wrapping_sub ( MAX_CHANGE_AGE ) ;
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
self . param_state = Some ( < Param ::Fetch as SystemParamState > ::init (
world ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
& mut self . system_meta ,
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
) ) ;
2020-07-10 04:18:35 +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
2022-04-07 20:50:43 +00:00
fn update_archetype_component_access ( & mut self , world : & World ) {
assert! ( self . world_id = = Some ( world . id ( ) ) , " Encountered a mismatched World. A System cannot be used with Worlds other than the one it was initialized with. " ) ;
let archetypes = world . archetypes ( ) ;
let new_generation = archetypes . generation ( ) ;
let old_generation = std ::mem ::replace ( & mut self . archetype_generation , new_generation ) ;
let archetype_index_range = old_generation . value ( ) .. new_generation . value ( ) ;
for archetype_index in archetype_index_range {
self . param_state . as_mut ( ) . unwrap ( ) . new_archetype (
& archetypes [ ArchetypeId ::new ( archetype_index ) ] ,
& mut self . system_meta ,
) ;
}
}
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
#[ inline ]
fn check_change_tick ( & mut self , change_tick : u32 ) {
check_system_change_tick (
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
& mut self . system_meta . last_change_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
change_tick ,
Add new SystemState and rename old SystemState to SystemMeta (#2283)
This enables `SystemParams` to be used outside of function systems. Anything can create and store `SystemState`, which enables efficient "param state cached" access to `SystemParams`.
It adds a `ReadOnlySystemParamFetch` trait, which enables safe `SystemState::get` calls without unique world access.
I renamed the old `SystemState` to `SystemMeta` to enable us to mirror the `QueryState` naming convention (but I'm happy to discuss alternative names if people have other ideas). I initially pitched this as `ParamState`, but given that it needs to include full system metadata, that doesn't feel like a particularly accurate name.
```rust
#[derive(Eq, PartialEq, Debug)]
struct A(usize);
#[derive(Eq, PartialEq, Debug)]
struct B(usize);
let mut world = World::default();
world.insert_resource(A(42));
world.spawn().insert(B(7));
// we get nice lifetime elision when declaring the type on the left hand side
let mut system_state: SystemState<(Res<A>, Query<&B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get(&world);
assert_eq!(*a, A(42), "returned resource matches initial value");
assert_eq!(
*query.single().unwrap(),
B(7),
"returned component matches initial value"
);
// mutable system params require unique world access
let mut system_state: SystemState<(ResMut<A>, Query<&mut B>)> = SystemState::new(&mut world);
let (a, query) = system_state.get_mut(&mut world);
// static lifetimes are required when declaring inside of structs
struct SomeContainer {
state: SystemState<(Res<'static, A>, Res<'static, B>)>
}
// this can be shortened using type aliases, which will be useful for complex param tuples
type MyParams<'a> = (Res<'a, A>, Res<'a, B>);
struct SomeContainer {
state: SystemState<MyParams<'static>>
}
// It is the user's responsibility to call SystemState::apply(world) for parameters that queue up work
let mut system_state: SystemState<(Commands, Query<&B>)> = SystemState::new(&mut world);
{
let (mut commands, query) = system_state.get(&world);
commands.insert_resource(3.14);
}
system_state.apply(&mut world);
```
## Future Work
* Actually use SystemState inside FunctionSystem. This would be trivial, but it requires FunctionSystem to wrap SystemState in Option in its current form (which complicates system metadata lookup). I'd prefer to hold off until we adopt something like the later designs linked in #1364, which enable us to contruct Systems using a World reference (and also remove the need for `.system`).
* Consider a "scoped" approach to automatically call SystemState::apply when systems params are no longer being used (either a container type with a Drop impl, or a function that takes a closure for user logic operating on params).
2021-06-02 19:57:38 +00:00
self . system_meta . name . as_ref ( ) ,
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
) ;
}
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
fn default_labels ( & self ) -> Vec < SystemLabelId > {
vec! [ self . func . as_system_label ( ) . as_label ( ) ]
2022-03-23 22:53:56 +00:00
}
}
/// A [`SystemLabel`] that was automatically generated for a system on the basis of its `TypeId`.
pub struct SystemTypeIdLabel < T : 'static > ( PhantomData < fn ( ) -> T > ) ;
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
impl < T : 'static > SystemLabel for SystemTypeIdLabel < T > {
#[ inline ]
fn as_str ( & self ) -> & 'static str {
std ::any ::type_name ::< T > ( )
}
}
2022-03-23 22:53:56 +00:00
impl < T > Debug for SystemTypeIdLabel < T > {
fn fmt ( & self , f : & mut std ::fmt ::Formatter < '_ > ) -> std ::fmt ::Result {
f . debug_tuple ( " SystemTypeIdLabel " )
. field ( & std ::any ::type_name ::< T > ( ) )
. finish ( )
}
}
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
2022-03-23 22:53:56 +00:00
impl < T > Clone for SystemTypeIdLabel < T > {
fn clone ( & self ) -> Self {
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
* self
2022-03-23 22:53:56 +00:00
}
}
impl < T > Copy for SystemTypeIdLabel < T > { }
2021-04-15 20:36:16 +00:00
/// A trait implemented for all functions that can be used as [`System`]s.
2022-05-30 17:59:20 +00:00
///
/// This trait can be useful for making your own systems which accept other systems,
/// sometimes called higher order systems.
///
/// This should be used in combination with [`ParamSet`] when calling other systems
/// within your system.
/// Using [`ParamSet`] in this case avoids [`SystemParam`] collisions.
///
/// # Example
///
/// To create something like [`ChainSystem`], but in entirely safe code.
///
/// ```rust
/// use std::num::ParseIntError;
///
/// use bevy_ecs::prelude::*;
/// use bevy_ecs::system::{SystemParam, SystemParamItem};
///
/// // Unfortunately, we need all of these generics. `A` is the first system, with its
/// // parameters and marker type required for coherence. `B` is the second system, and
2022-07-12 13:06:16 +00:00
/// // the other generics are for the input/output types of `A` and `B`.
2022-05-30 17:59:20 +00:00
/// /// Chain creates a new system which calls `a`, then calls `b` with the output of `a`
/// pub fn chain<AIn, Shared, BOut, A, AParam, AMarker, B, BParam, BMarker>(
/// mut a: A,
/// mut b: B,
/// ) -> impl FnMut(In<AIn>, ParamSet<(SystemParamItem<AParam>, SystemParamItem<BParam>)>) -> BOut
/// where
/// // We need A and B to be systems, add those bounds
/// A: SystemParamFunction<AIn, Shared, AParam, AMarker>,
/// B: SystemParamFunction<Shared, BOut, BParam, BMarker>,
/// AParam: SystemParam,
/// BParam: SystemParam,
/// {
/// // The type of `params` is inferred based on the return of this function above
/// move |In(a_in), mut params| {
/// let shared = a.run(a_in, params.p0());
/// b.run(shared, params.p1())
/// }
/// }
///
/// // Usage example for `chain`:
/// fn main() {
/// let mut world = World::default();
/// world.insert_resource(Message("42".to_string()));
///
/// // chain the `parse_message_system`'s output into the `filter_system`s input
/// let mut chained_system = IntoSystem::into_system(chain(parse_message, filter));
/// chained_system.initialize(&mut world);
/// assert_eq!(chained_system.run((), &mut world), Some(42));
/// }
///
/// struct Message(String);
///
/// fn parse_message(message: Res<Message>) -> Result<usize, ParseIntError> {
/// message.0.parse::<usize>()
/// }
///
/// fn filter(In(result): In<Result<usize, ParseIntError>>) -> Option<usize> {
/// result.ok().filter(|&n| n < 100)
/// }
/// ```
/// [`ChainSystem`]: crate::system::ChainSystem
/// [`ParamSet`]: crate::system::ParamSet
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
pub trait SystemParamFunction < In , Out , Param : SystemParam , Marker > : Send + Sync + 'static {
2022-05-30 17:59:20 +00:00
fn run ( & mut self , input : In , param_value : SystemParamItem < Param > ) -> Out ;
2020-07-10 04:18:35 +00:00
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
macro_rules ! impl_system_function {
2020-11-08 20:34:05 +00:00
( $( $param : ident ) , * ) = > {
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
#[ allow(non_snake_case) ]
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impl < Out , Func : Send + Sync + 'static , $( $param : SystemParam ) , * > SystemParamFunction < ( ) , Out , ( $( $param , ) * ) , ( ) > for Func
2020-12-16 05:57:16 +00:00
where
2021-06-27 00:40:09 +00:00
for < ' a > & ' a mut Func :
2020-12-16 05:57:16 +00:00
FnMut ( $( $param ) , * ) -> Out +
2022-05-30 17:59:20 +00:00
FnMut ( $( SystemParamItem < $param > ) , * ) -> Out , Out : 'static
2020-07-10 04:18:35 +00:00
{
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
2022-05-30 17:59:20 +00:00
fn run ( & mut self , _input : ( ) , param_value : SystemParamItem < ( $( $param , ) * ) > ) -> Out {
// Yes, this is strange, but `rustc` fails to compile this impl
// without using this function. It fails to recognise that `func`
// is a function, potentially because of the multiple impls of `FnMut`
2021-06-27 00:40:09 +00:00
#[ allow(clippy::too_many_arguments) ]
fn call_inner < Out , $( $param , ) * > (
mut f : impl FnMut ( $( $param , ) * ) ->Out ,
$( $param : $param , ) *
) ->Out {
f ( $( $param , ) * )
}
2022-05-30 17:59:20 +00:00
let ( $( $param , ) * ) = param_value ;
2021-06-27 00:40:09 +00:00
call_inner ( self , $( $param ) , * )
2020-12-16 05:57:16 +00:00
}
}
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ allow(non_snake_case) ]
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impl < Input , Out , Func : Send + Sync + 'static , $( $param : SystemParam ) , * > SystemParamFunction < Input , Out , ( $( $param , ) * ) , InputMarker > for Func
2020-12-16 05:57:16 +00:00
where
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for < ' a > & ' a mut Func :
2020-12-16 05:57:16 +00:00
FnMut ( In < Input > , $( $param ) , * ) -> Out +
2021-06-27 00:40:09 +00:00
FnMut ( In < Input > , $( < < $param as SystemParam > ::Fetch as SystemParamFetch > ::Item ) , * ) -> Out , Out : 'static
2020-12-16 05:57:16 +00:00
{
Bevy ECS V2 (#1525)
# Bevy ECS V2
This is a rewrite of Bevy ECS (basically everything but the new executor/schedule, which are already awesome). The overall goal was to improve the performance and versatility of Bevy ECS. Here is a quick bulleted list of changes before we dive into the details:
* Complete World rewrite
* Multiple component storage types:
* Tables: fast cache friendly iteration, slower add/removes (previously called Archetypes)
* Sparse Sets: fast add/remove, slower iteration
* Stateful Queries (caches query results for faster iteration. fragmented iteration is _fast_ now)
* Stateful System Params (caches expensive operations. inspired by @DJMcNab's work in #1364)
* Configurable System Params (users can set configuration when they construct their systems. once again inspired by @DJMcNab's work)
* Archetypes are now "just metadata", component storage is separate
* Archetype Graph (for faster archetype changes)
* Component Metadata
* Configure component storage type
* Retrieve information about component size/type/name/layout/send-ness/etc
* Components are uniquely identified by a densely packed ComponentId
* TypeIds are now totally optional (which should make implementing scripting easier)
* Super fast "for_each" query iterators
* Merged Resources into World. Resources are now just a special type of component
* EntityRef/EntityMut builder apis (more efficient and more ergonomic)
* Fast bitset-backed `Access<T>` replaces old hashmap-based approach everywhere
* Query conflicts are determined by component access instead of archetype component access (to avoid random failures at runtime)
* With/Without are still taken into account for conflicts, so this should still be comfy to use
* Much simpler `IntoSystem` impl
* Significantly reduced the amount of hashing throughout the ecs in favor of Sparse Sets (indexed by densely packed ArchetypeId, ComponentId, BundleId, and TableId)
* Safety Improvements
* Entity reservation uses a normal world reference instead of unsafe transmute
* QuerySets no longer transmute lifetimes
* Made traits "unsafe" where relevant
* More thorough safety docs
* WorldCell
* Exposes safe mutable access to multiple resources at a time in a World
* Replaced "catch all" `System::update_archetypes(world: &World)` with `System::new_archetype(archetype: &Archetype)`
* Simpler Bundle implementation
* Replaced slow "remove_bundle_one_by_one" used as fallback for Commands::remove_bundle with fast "remove_bundle_intersection"
* Removed `Mut<T>` query impl. it is better to only support one way: `&mut T`
* Removed with() from `Flags<T>` in favor of `Option<Flags<T>>`, which allows querying for flags to be "filtered" by default
* Components now have is_send property (currently only resources support non-send)
* More granular module organization
* New `RemovedComponents<T>` SystemParam that replaces `query.removed::<T>()`
* `world.resource_scope()` for mutable access to resources and world at the same time
* WorldQuery and QueryFilter traits unified. FilterFetch trait added to enable "short circuit" filtering. Auto impled for cases that don't need it
* Significantly slimmed down SystemState in favor of individual SystemParam state
* System Commands changed from `commands: &mut Commands` back to `mut commands: Commands` (to allow Commands to have a World reference)
Fixes #1320
## `World` Rewrite
This is a from-scratch rewrite of `World` that fills the niche that `hecs` used to. Yes, this means Bevy ECS is no longer a "fork" of hecs. We're going out our own!
(the only shared code between the projects is the entity id allocator, which is already basically ideal)
A huge shout out to @SanderMertens (author of [flecs](https://github.com/SanderMertens/flecs)) for sharing some great ideas with me (specifically hybrid ecs storage and archetype graphs). He also helped advise on a number of implementation details.
## Component Storage (The Problem)
Two ECS storage paradigms have gained a lot of traction over the years:
* **Archetypal ECS**:
* Stores components in "tables" with static schemas. Each "column" stores components of a given type. Each "row" is an entity.
* Each "archetype" has its own table. Adding/removing an entity's component changes the archetype.
* Enables super-fast Query iteration due to its cache-friendly data layout
* Comes at the cost of more expensive add/remove operations for an Entity's components, because all components need to be copied to the new archetype's "table"
* **Sparse Set ECS**:
* Stores components of the same type in densely packed arrays, which are sparsely indexed by densely packed unsigned integers (Entity ids)
* Query iteration is slower than Archetypal ECS because each entity's component could be at any position in the sparse set. This "random access" pattern isn't cache friendly. Additionally, there is an extra layer of indirection because you must first map the entity id to an index in the component array.
* Adding/removing components is a cheap, constant time operation
Bevy ECS V1, hecs, legion, flec, and Unity DOTS are all "archetypal ecs-es". I personally think "archetypal" storage is a good default for game engines. An entity's archetype doesn't need to change frequently in general, and it creates "fast by default" query iteration (which is a much more common operation). It is also "self optimizing". Users don't need to think about optimizing component layouts for iteration performance. It "just works" without any extra boilerplate.
Shipyard and EnTT are "sparse set ecs-es". They employ "packing" as a way to work around the "suboptimal by default" iteration performance for specific sets of components. This helps, but I didn't think this was a good choice for a general purpose engine like Bevy because:
1. "packs" conflict with each other. If bevy decides to internally pack the Transform and GlobalTransform components, users are then blocked if they want to pack some custom component with Transform.
2. users need to take manual action to optimize
Developers selecting an ECS framework are stuck with a hard choice. Select an "archetypal" framework with "fast iteration everywhere" but without the ability to cheaply add/remove components, or select a "sparse set" framework to cheaply add/remove components but with slower iteration performance.
## Hybrid Component Storage (The Solution)
In Bevy ECS V2, we get to have our cake and eat it too. It now has _both_ of the component storage types above (and more can be added later if needed):
* **Tables** (aka "archetypal" storage)
* The default storage. If you don't configure anything, this is what you get
* Fast iteration by default
* Slower add/remove operations
* **Sparse Sets**
* Opt-in
* Slower iteration
* Faster add/remove operations
These storage types complement each other perfectly. By default Query iteration is fast. If developers know that they want to add/remove a component at high frequencies, they can set the storage to "sparse set":
```rust
world.register_component(
ComponentDescriptor::new::<MyComponent>(StorageType::SparseSet)
).unwrap();
```
## Archetypes
Archetypes are now "just metadata" ... they no longer store components directly. They do store:
* The `ComponentId`s of each of the Archetype's components (and that component's storage type)
* Archetypes are uniquely defined by their component layouts
* For example: entities with "table" components `[A, B, C]` _and_ "sparse set" components `[D, E]` will always be in the same archetype.
* The `TableId` associated with the archetype
* For now each archetype has exactly one table (which can have no components),
* There is a 1->Many relationship from Tables->Archetypes. A given table could have any number of archetype components stored in it:
* Ex: an entity with "table storage" components `[A, B, C]` and "sparse set" components `[D, E]` will share the same `[A, B, C]` table as an entity with `[A, B, C]` table component and `[F]` sparse set components.
* This 1->Many relationship is how we preserve fast "cache friendly" iteration performance when possible (more on this later)
* A list of entities that are in the archetype and the row id of the table they are in
* ArchetypeComponentIds
* unique densely packed identifiers for (ArchetypeId, ComponentId) pairs
* used by the schedule executor for cheap system access control
* "Archetype Graph Edges" (see the next section)
## The "Archetype Graph"
Archetype changes in Bevy (and a number of other archetypal ecs-es) have historically been expensive to compute. First, you need to allocate a new vector of the entity's current component ids, add or remove components based on the operation performed, sort it (to ensure it is order-independent), then hash it to find the archetype (if it exists). And thats all before we get to the _already_ expensive full copy of all components to the new table storage.
The solution is to build a "graph" of archetypes to cache these results. @SanderMertens first exposed me to the idea (and he got it from @gjroelofs, who came up with it). They propose adding directed edges between archetypes for add/remove component operations. If `ComponentId`s are densely packed, you can use sparse sets to cheaply jump between archetypes.
Bevy takes this one step further by using add/remove `Bundle` edges instead of `Component` edges. Bevy encourages the use of `Bundles` to group add/remove operations. This is largely for "clearer game logic" reasons, but it also helps cut down on the number of archetype changes required. `Bundles` now also have densely-packed `BundleId`s. This allows us to use a _single_ edge for each bundle operation (rather than needing to traverse N edges ... one for each component). Single component operations are also bundles, so this is strictly an improvement over a "component only" graph.
As a result, an operation that used to be _heavy_ (both for allocations and compute) is now two dirt-cheap array lookups and zero allocations.
## Stateful Queries
World queries are now stateful. This allows us to:
1. Cache archetype (and table) matches
* This resolves another issue with (naive) archetypal ECS: query performance getting worse as the number of archetypes goes up (and fragmentation occurs).
2. Cache Fetch and Filter state
* The expensive parts of fetch/filter operations (such as hashing the TypeId to find the ComponentId) now only happen once when the Query is first constructed
3. Incrementally build up state
* When new archetypes are added, we only process the new archetypes (no need to rebuild state for old archetypes)
As a result, the direct `World` query api now looks like this:
```rust
let mut query = world.query::<(&A, &mut B)>();
for (a, mut b) in query.iter_mut(&mut world) {
}
```
Requiring `World` to generate stateful queries (rather than letting the `QueryState` type be constructed separately) allows us to ensure that _all_ queries are properly initialized (and the relevant world state, such as ComponentIds). This enables QueryState to remove branches from its operations that check for initialization status (and also enables query.iter() to take an immutable world reference because it doesn't need to initialize anything in world).
However in systems, this is a non-breaking change. State management is done internally by the relevant SystemParam.
## Stateful SystemParams
Like Queries, `SystemParams` now also cache state. For example, `Query` system params store the "stateful query" state mentioned above. Commands store their internal `CommandQueue`. This means you can now safely use as many separate `Commands` parameters in your system as you want. `Local<T>` system params store their `T` value in their state (instead of in Resources).
SystemParam state also enabled a significant slim-down of SystemState. It is much nicer to look at now.
Per-SystemParam state naturally insulates us from an "aliased mut" class of errors we have hit in the past (ex: using multiple `Commands` system params).
(credit goes to @DJMcNab for the initial idea and draft pr here #1364)
## Configurable SystemParams
@DJMcNab also had the great idea to make SystemParams configurable. This allows users to provide some initial configuration / values for system parameters (when possible). Most SystemParams have no config (the config type is `()`), but the `Local<T>` param now supports user-provided parameters:
```rust
fn foo(value: Local<usize>) {
}
app.add_system(foo.system().config(|c| c.0 = Some(10)));
```
## Uber Fast "for_each" Query Iterators
Developers now have the choice to use a fast "for_each" iterator, which yields ~1.5-3x iteration speed improvements for "fragmented iteration", and minor ~1.2x iteration speed improvements for unfragmented iteration.
```rust
fn system(query: Query<(&A, &mut B)>) {
// you now have the option to do this for a speed boost
query.for_each_mut(|(a, mut b)| {
});
// however normal iterators are still available
for (a, mut b) in query.iter_mut() {
}
}
```
I think in most cases we should continue to encourage "normal" iterators as they are more flexible and more "rust idiomatic". But when that extra "oomf" is needed, it makes sense to use `for_each`.
We should also consider using `for_each` for internal bevy systems to give our users a nice speed boost (but that should be a separate pr).
## Component Metadata
`World` now has a `Components` collection, which is accessible via `world.components()`. This stores mappings from `ComponentId` to `ComponentInfo`, as well as `TypeId` to `ComponentId` mappings (where relevant). `ComponentInfo` stores information about the component, such as ComponentId, TypeId, memory layout, send-ness (currently limited to resources), and storage type.
## Significantly Cheaper `Access<T>`
We used to use `TypeAccess<TypeId>` to manage read/write component/archetype-component access. This was expensive because TypeIds must be hashed and compared individually. The parallel executor got around this by "condensing" type ids into bitset-backed access types. This worked, but it had to be re-generated from the `TypeAccess<TypeId>`sources every time archetypes changed.
This pr removes TypeAccess in favor of faster bitset access everywhere. We can do this thanks to the move to densely packed `ComponentId`s and `ArchetypeComponentId`s.
## Merged Resources into World
Resources had a lot of redundant functionality with Components. They stored typed data, they had access control, they had unique ids, they were queryable via SystemParams, etc. In fact the _only_ major difference between them was that they were unique (and didn't correlate to an entity).
Separate resources also had the downside of requiring a separate set of access controls, which meant the parallel executor needed to compare more bitsets per system and manage more state.
I initially got the "separate resources" idea from `legion`. I think that design was motivated by the fact that it made the direct world query/resource lifetime interactions more manageable. It certainly made our lives easier when using Resources alongside hecs/bevy_ecs. However we already have a construct for safely and ergonomically managing in-world lifetimes: systems (which use `Access<T>` internally).
This pr merges Resources into World:
```rust
world.insert_resource(1);
world.insert_resource(2.0);
let a = world.get_resource::<i32>().unwrap();
let mut b = world.get_resource_mut::<f64>().unwrap();
*b = 3.0;
```
Resources are now just a special kind of component. They have their own ComponentIds (and their own resource TypeId->ComponentId scope, so they don't conflict wit components of the same type). They are stored in a special "resource archetype", which stores components inside the archetype using a new `unique_components` sparse set (note that this sparse set could later be used to implement Tags). This allows us to keep the code size small by reusing existing datastructures (namely Column, Archetype, ComponentFlags, and ComponentInfo). This allows us the executor to use a single `Access<ArchetypeComponentId>` per system. It should also make scripting language integration easier.
_But_ this merge did create problems for people directly interacting with `World`. What if you need mutable access to multiple resources at the same time? `world.get_resource_mut()` borrows World mutably!
## WorldCell
WorldCell applies the `Access<ArchetypeComponentId>` concept to direct world access:
```rust
let world_cell = world.cell();
let a = world_cell.get_resource_mut::<i32>().unwrap();
let b = world_cell.get_resource_mut::<f64>().unwrap();
```
This adds cheap runtime checks (a sparse set lookup of `ArchetypeComponentId` and a counter) to ensure that world accesses do not conflict with each other. Each operation returns a `WorldBorrow<'w, T>` or `WorldBorrowMut<'w, T>` wrapper type, which will release the relevant ArchetypeComponentId resources when dropped.
World caches the access sparse set (and only one cell can exist at a time), so `world.cell()` is a cheap operation.
WorldCell does _not_ use atomic operations. It is non-send, does a mutable borrow of world to prevent other accesses, and uses a simple `Rc<RefCell<ArchetypeComponentAccess>>` wrapper in each WorldBorrow pointer.
The api is currently limited to resource access, but it can and should be extended to queries / entity component access.
## Resource Scopes
WorldCell does not yet support component queries, and even when it does there are sometimes legitimate reasons to want a mutable world ref _and_ a mutable resource ref (ex: bevy_render and bevy_scene both need this). In these cases we could always drop down to the unsafe `world.get_resource_unchecked_mut()`, but that is not ideal!
Instead developers can use a "resource scope"
```rust
world.resource_scope(|world: &mut World, a: &mut A| {
})
```
This temporarily removes the `A` resource from `World`, provides mutable pointers to both, and re-adds A to World when finished. Thanks to the move to ComponentIds/sparse sets, this is a cheap operation.
If multiple resources are required, scopes can be nested. We could also consider adding a "resource tuple" to the api if this pattern becomes common and the boilerplate gets nasty.
## Query Conflicts Use ComponentId Instead of ArchetypeComponentId
For safety reasons, systems cannot contain queries that conflict with each other without wrapping them in a QuerySet. On bevy `main`, we use ArchetypeComponentIds to determine conflicts. This is nice because it can take into account filters:
```rust
// these queries will never conflict due to their filters
fn filter_system(a: Query<&mut A, With<B>>, b: Query<&mut B, Without<B>>) {
}
```
But it also has a significant downside:
```rust
// these queries will not conflict _until_ an entity with A, B, and C is spawned
fn maybe_conflicts_system(a: Query<(&mut A, &C)>, b: Query<(&mut A, &B)>) {
}
```
The system above will panic at runtime if an entity with A, B, and C is spawned. This makes it hard to trust that your game logic will run without crashing.
In this pr, I switched to using `ComponentId` instead. This _is_ more constraining. `maybe_conflicts_system` will now always fail, but it will do it consistently at startup. Naively, it would also _disallow_ `filter_system`, which would be a significant downgrade in usability. Bevy has a number of internal systems that rely on disjoint queries and I expect it to be a common pattern in userspace.
To resolve this, I added a new `FilteredAccess<T>` type, which wraps `Access<T>` and adds with/without filters. If two `FilteredAccess` have with/without values that prove they are disjoint, they will no longer conflict.
## EntityRef / EntityMut
World entity operations on `main` require that the user passes in an `entity` id to each operation:
```rust
let entity = world.spawn((A, )); // create a new entity with A
world.get::<A>(entity);
world.insert(entity, (B, C));
world.insert_one(entity, D);
```
This means that each operation needs to look up the entity location / verify its validity. The initial spawn operation also requires a Bundle as input. This can be awkward when no components are required (or one component is required).
These operations have been replaced by `EntityRef` and `EntityMut`, which are "builder-style" wrappers around world that provide read and read/write operations on a single, pre-validated entity:
```rust
// spawn now takes no inputs and returns an EntityMut
let entity = world.spawn()
.insert(A) // insert a single component into the entity
.insert_bundle((B, C)) // insert a bundle of components into the entity
.id() // id returns the Entity id
// Returns EntityMut (or panics if the entity does not exist)
world.entity_mut(entity)
.insert(D)
.insert_bundle(SomeBundle::default());
{
// returns EntityRef (or panics if the entity does not exist)
let d = world.entity(entity)
.get::<D>() // gets the D component
.unwrap();
// world.get still exists for ergonomics
let d = world.get::<D>(entity).unwrap();
}
// These variants return Options if you want to check existence instead of panicing
world.get_entity_mut(entity)
.unwrap()
.insert(E);
if let Some(entity_ref) = world.get_entity(entity) {
let d = entity_ref.get::<D>().unwrap();
}
```
This _does not_ affect the current Commands api or terminology. I think that should be a separate conversation as that is a much larger breaking change.
## Safety Improvements
* Entity reservation in Commands uses a normal world borrow instead of an unsafe transmute
* QuerySets no longer transmutes lifetimes
* Made traits "unsafe" when implementing a trait incorrectly could cause unsafety
* More thorough safety docs
## RemovedComponents SystemParam
The old approach to querying removed components: `query.removed:<T>()` was confusing because it had no connection to the query itself. I replaced it with the following, which is both clearer and allows us to cache the ComponentId mapping in the SystemParamState:
```rust
fn system(removed: RemovedComponents<T>) {
for entity in removed.iter() {
}
}
```
## Simpler Bundle implementation
Bundles are no longer responsible for sorting (or deduping) TypeInfo. They are just a simple ordered list of component types / data. This makes the implementation smaller and opens the door to an easy "nested bundle" implementation in the future (which i might even add in this pr). Duplicate detection is now done once per bundle type by World the first time a bundle is used.
## Unified WorldQuery and QueryFilter types
(don't worry they are still separate type _parameters_ in Queries .. this is a non-breaking change)
WorldQuery and QueryFilter were already basically identical apis. With the addition of `FetchState` and more storage-specific fetch methods, the overlap was even clearer (and the redundancy more painful).
QueryFilters are now just `F: WorldQuery where F::Fetch: FilterFetch`. FilterFetch requires `Fetch<Item = bool>` and adds new "short circuit" variants of fetch methods. This enables a filter tuple like `(With<A>, Without<B>, Changed<C>)` to stop evaluating the filter after the first mismatch is encountered. FilterFetch is automatically implemented for `Fetch` implementations that return bool.
This forces fetch implementations that return things like `(bool, bool, bool)` (such as the filter above) to manually implement FilterFetch and decide whether or not to short-circuit.
## More Granular Modules
World no longer globs all of the internal modules together. It now exports `core`, `system`, and `schedule` separately. I'm also considering exporting `core` submodules directly as that is still pretty "glob-ey" and unorganized (feedback welcome here).
## Remaining Draft Work (to be done in this pr)
* ~~panic on conflicting WorldQuery fetches (&A, &mut A)~~
* ~~bevy `main` and hecs both currently allow this, but we should protect against it if possible~~
* ~~batch_iter / par_iter (currently stubbed out)~~
* ~~ChangedRes~~
* ~~I skipped this while we sort out #1313. This pr should be adapted to account for whatever we land on there~~.
* ~~The `Archetypes` and `Tables` collections use hashes of sorted lists of component ids to uniquely identify each archetype/table. This hash is then used as the key in a HashMap to look up the relevant ArchetypeId or TableId. (which doesn't handle hash collisions properly)~~
* ~~It is currently unsafe to generate a Query from "World A", then use it on "World B" (despite the api claiming it is safe). We should probably close this gap. This could be done by adding a randomly generated WorldId to each world, then storing that id in each Query. They could then be compared to each other on each `query.do_thing(&world)` operation. This _does_ add an extra branch to each query operation, so I'm open to other suggestions if people have them.~~
* ~~Nested Bundles (if i find time)~~
## Potential Future Work
* Expand WorldCell to support queries.
* Consider not allocating in the empty archetype on `world.spawn()`
* ex: return something like EntityMutUninit, which turns into EntityMut after an `insert` or `insert_bundle` op
* this actually regressed performance last time i tried it, but in theory it should be faster
* Optimize SparseSet::insert (see `PERF` comment on insert)
* Replace SparseArray `Option<T>` with T::MAX to cut down on branching
* would enable cheaper get_unchecked() operations
* upstream fixedbitset optimizations
* fixedbitset could be allocation free for small block counts (store blocks in a SmallVec)
* fixedbitset could have a const constructor
* Consider implementing Tags (archetype-specific by-value data that affects archetype identity)
* ex: ArchetypeA could have `[A, B, C]` table components and `[D(1)]` "tag" component. ArchetypeB could have `[A, B, C]` table components and a `[D(2)]` tag component. The archetypes are different, despite both having D tags because the value inside D is different.
* this could potentially build on top of the `archetype.unique_components` added in this pr for resource storage.
* Consider reverting `all_tuples` proc macro in favor of the old `macro_rules` implementation
* all_tuples is more flexible and produces cleaner documentation (the macro_rules version produces weird type parameter orders due to parser constraints)
* but unfortunately all_tuples also appears to make Rust Analyzer sad/slow when working inside of `bevy_ecs` (does not affect user code)
* Consider "resource queries" and/or "mixed resource and entity component queries" as an alternative to WorldCell
* this is basically just "systems" so maybe it's not worth it
* Add more world ops
* `world.clear()`
* `world.reserve<T: Bundle>(count: usize)`
* Try using the old archetype allocation strategy (allocate new memory on resize and copy everything over). I expect this to improve batch insertion performance at the cost of unbatched performance. But thats just a guess. I'm not an allocation perf pro :)
* Adapt Commands apis for consistency with new World apis
## Benchmarks
key:
* `bevy_old`: bevy `main` branch
* `bevy`: this branch
* `_foreach`: uses an optimized for_each iterator
* ` _sparse`: uses sparse set storage (if unspecified assume table storage)
* `_system`: runs inside a system (if unspecified assume test happens via direct world ops)
### Simple Insert (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245573-9c3ce100-7795-11eb-9003-bfd41cd5c51f.png)
### Simpler Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245795-ffc70e80-7795-11eb-92fb-3ffad09aabf7.png)
### Fragment Iter (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109245849-0fdeee00-7796-11eb-8d25-eb6b7a682c48.png)
### Sparse Fragmented Iter
Iterate a query that matches 5 entities from a single matching archetype, but there are 100 unmatching archetypes
![image](https://user-images.githubusercontent.com/2694663/109245916-2b49f900-7796-11eb-9a8f-ed89c203f940.png)
### Schedule (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246428-1fab0200-7797-11eb-8841-1b2161e90fa4.png)
### Add Remove Component (from ecs_bench_suite)
![image](https://user-images.githubusercontent.com/2694663/109246492-39e4e000-7797-11eb-8985-2706bd0495ab.png)
### Add Remove Component Big
Same as the test above, but each entity has 5 "large" matrix components and 1 "large" matrix component is added and removed
![image](https://user-images.githubusercontent.com/2694663/109246517-449f7500-7797-11eb-835e-28b6790daeaa.png)
### Get Component
Looks up a single component value a large number of times
![image](https://user-images.githubusercontent.com/2694663/109246129-87ad1880-7796-11eb-9fcb-c38012aa7c70.png)
2021-03-05 07:54:35 +00:00
#[ inline ]
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fn run ( & mut self , input : Input , param_value : SystemParamItem < ( $( $param , ) * ) > ) -> Out {
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#[ allow(clippy::too_many_arguments) ]
fn call_inner < Input , Out , $( $param , ) * > (
mut f : impl FnMut ( In < Input > , $( $param , ) * ) ->Out ,
input : In < Input > ,
$( $param : $param , ) *
) ->Out {
f ( input , $( $param , ) * )
}
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let ( $( $param , ) * ) = param_value ;
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call_inner ( self , In ( input ) , $( $param ) , * )
2020-07-10 04:18:35 +00:00
}
}
} ;
}
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// Note that we rely on the highest impl to be <= the highest order of the tuple impls
// of `SystemParam` created.
2021-04-03 23:13:54 +00:00
all_tuples! ( impl_system_function , 0 , 16 , F ) ;
2022-03-23 22:53:56 +00:00
/// Used to implicitly convert systems to their default labels. For example, it will convert
/// "system functions" to their [`SystemTypeIdLabel`].
pub trait AsSystemLabel < Marker > {
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
fn as_system_label ( & self ) -> SystemLabelId ;
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}
impl < In , Out , Param : SystemParam , Marker , T : SystemParamFunction < In , Out , Param , Marker > >
AsSystemLabel < ( In , Out , Param , Marker ) > for T
{
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
#[ inline ]
fn as_system_label ( & self ) -> SystemLabelId {
SystemTypeIdLabel ::< T > ( PhantomData ) . as_label ( )
2022-03-23 22:53:56 +00:00
}
}
Simplify design for `*Label`s (#4957)
# Objective
- Closes #4954
- Reduce the complexity of the `{System, App, *}Label` APIs.
## Solution
For the sake of brevity I will only refer to `SystemLabel`, but everything applies to all of the other label types as well.
- Add `SystemLabelId`, a lightweight, `copy` struct.
- Convert custom types into `SystemLabelId` using the trait `SystemLabel`.
## Changelog
- String literals implement `SystemLabel` for now, but this should be changed with #4409 .
## Migration Guide
- Any previous use of `Box<dyn SystemLabel>` should be replaced with `SystemLabelId`.
- `AsSystemLabel` trait has been modified.
- No more output generics.
- Method `as_system_label` now returns `SystemLabelId`, removing an unnecessary level of indirection.
- If you *need* a label that is determined at runtime, you can use `Box::leak`. Not recommended.
## Questions for later
* Should we generate a `Debug` impl along with `#[derive(*Label)]`?
* Should we rename `as_str()`?
* Should we remove the extra derives (such as `Hash`) from builtin `*Label` types?
* Should we automatically derive types like `Clone, Copy, PartialEq, Eq`?
* More-ergonomic comparisons between `Label` and `LabelId`.
* Move `Dyn{Eq, Hash,Clone}` somewhere else.
* Some API to make interning dynamic labels easier.
* Optimize string representation
* Empty string for unit structs -- no debug info but faster comparisons
* Don't show enum types -- same tradeoffs as asbove.
2022-07-14 18:23:01 +00:00
impl < T : SystemLabel > AsSystemLabel < ( ) > for T {
#[ inline ]
fn as_system_label ( & self ) -> SystemLabelId {
self . as_label ( )
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}
}