12 releases

0.2.11 Feb 26, 2025
0.2.10 Feb 24, 2025
0.2.9 Oct 21, 2024
0.2.8 Aug 7, 2024
0.1.0 Oct 29, 2022

#34 in Asynchronous

Download history 39022/week @ 2025-03-07 44750/week @ 2025-03-14 32296/week @ 2025-03-21 30812/week @ 2025-03-28 34070/week @ 2025-04-04 35669/week @ 2025-04-11 34553/week @ 2025-04-18 36723/week @ 2025-04-25 35433/week @ 2025-05-02 35673/week @ 2025-05-09 36053/week @ 2025-05-16 40963/week @ 2025-05-23 48720/week @ 2025-05-30 43992/week @ 2025-06-06 44839/week @ 2025-06-13 63844/week @ 2025-06-20

210,866 downloads per month
Used in 230 crates (17 directly)

MIT license

145KB
2.5K SLoC

futures-buffered

This project provides several future structures, all based around the FuturesUnorderedBounded primtive.

Much like futures::FuturesUnordered, this is a thread-safe, Pin friendly, lifetime friendly, concurrent processing stream.

This primtive is different to FuturesUnordered in that FuturesUnorderedBounded has a fixed capacity for processing count. This means it's less flexible, but produces better memory efficiency.

However, we also provide a FuturesUnordered which allocates larger FuturesUnorderedBounded automatically to mitigate these inflexibilities. This is based on a triangular-array concept to amortise the cost of allocating (much like with a Vec) without violating Pin constraints.

Benchmarks

Speed

Running 65536 100us timers with 256 concurrent jobs in a single threaded tokio runtime:

FuturesUnorderedBounded    [339.9 ms  364.7 ms  380.6 ms]
futures::FuturesUnordered  [377.4 ms  391.4 ms  406.3 ms]
                           [min         mean         max]

Memory usage

Running 512000 Ready<i32> futures with 256 concurrent jobs.

  • count: the number of times alloc/dealloc was called
  • alloc: the number of cumulative bytes allocated
  • dealloc: the number of cumulative bytes deallocated
futures::FuturesUnordered
    count:    1,024,004
    alloc:    40.96 MB
    dealloc:  40.96 MB

FuturesUnorderedBounded
    count:    4
    alloc:    8.28 KB
    dealloc:  8.28 KB

Conclusion

As you can see, FuturesUnorderedBounded massively reduces you memory overhead while providing a small performance gain. Perfect for if you want a fixed batch size

Examples

// create a tcp connection
let stream = TcpStream::connect("example.com:80").await?;

// perform the http handshakes
let (mut rs, conn) = conn::handshake(stream).await?;
runtime.spawn(conn);

/// make http request to example.com and read the response
fn make_req(rs: &mut SendRequest<Body>) -> ResponseFuture {
    let req = Request::builder()
        .header("Host", "example.com")
        .method("GET")
        .body(Body::from(""))
        .unwrap();
    rs.send_request(req)
}

// create a queue that can hold 128 concurrent requests
let mut queue = FuturesUnorderedBounded::new(128);

// start up 128 requests
for _ in 0..128 {
    queue.push(make_req(&mut rs));
}
// wait for a request to finish and start another to fill its place - up to 1024 total requests
for _ in 128..1024 {
    queue.next().await;
    queue.push(make_req(&mut rs));
}
// wait for the tail end to finish
for _ in 0..128 {
    queue.next().await;
}
use futures_buffered::join_all;

async fn foo(i: u32) -> u32 { i }

let futures = vec![foo(1), foo(2), foo(3)];

assert_eq!(join_all(futures).await, [1, 2, 3]);

Dependencies

~0.5–19MB
~299K SLoC