this pr also unblocks some compiler auto SIMD ,consider following code

pub fn new() -> Self {
        let mut world = World::new();

        for _ in 0..10000 {
            world.spawn((TableData(0.0), SparseData(0.0))).id();
        }

        let query = world.query_filtered::<&mut TableData, With<SparseData>>();
        Self(world, query)
    }

    #[inline(never)]
    pub fn run(&mut self) {
        self.1
            .iter_mut(&mut self.0)
            .for_each(|mut v1| v1.0 += 1.)
}

Does this fully fix #2144? I suppose not, since it only optimizes for_each.

Does this fully fix #2144? I suppose not, since it only optimizes for_each.

yeah , Optimizing for-style iteration is much more complicated because it could significantly degrade performance due to introducing branch in the hot path.

Sounds good. Let's leave that to follow-up then.

Could you please explain why this code is faster?

        for _ in 0..10000 {
            world.spawn((TableData(0.0), SparseData(0.0))).id();
        }

        let query = world.query_filtered::<&mut TableData, With<SparseData>>();
        Self(world, query)

In this case the entities should be iterated in the same order before/after your change, no?

In this case the entities should be iterated in the same order before/after your change, no?

it would theoretically have the same cache locality. however, dense iteration could imply to the compiler that we are iterating over continuous memory which could enable automatic SIMD optimizations , This could potentially make the operation nearly 4 times faster.

Thank you to everyone involved with the authoring or reviewing of this PR! This work is relatively important and needs release notes! Head over to bevyengine/bevy-website#1667 if you'd like to help out.