Rate-Limiting with leaky buckets in Rust
This crate implements two rate-limiting algorithms in Rust:
- a leaky bucket and
- a variation on the leaky bucket, the generic cell rate algorithm (GCRA) for rate-limiting and scheduling.
Installation
Add the crate ratelimit_meter
to your Cargo.toml
file; the crates.io page
can give you the exact thing to paste.
API Docs
Find them on docs.rs for the latest version!
Design and implementation
Unlike some other token bucket algorithms, the GCRA one assumes that all units of work are of the same "weight", and so allows some optimizations which result in much more concise and fast code (it does not even use multiplication or division in the "hot" path for a single-cell decision).
All rate-limiting algorithm implementations in this crate are thread-safe and lock-free. Here are some benchmarks for repeated decisions (run on my macbook pro, this will differ on your hardware, etc etc):
$ cargo bench
Compiling ratelimit_meter v0.4.1 (file:///Users/asf/Hacks/ratelimit_meter)
Finished release [optimized] target(s) in 1.71 secs
Running target/release/deps/ratelimit_meter-680be7c7547f40f9
running 0 tests
test result: ok. 0 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out
Running target/release/deps/multi_threaded-b206ea78b9fc87cc
running 2 tests
test bench_gcra_20threads ... bench: 185 ns/iter (+/- 71)
test bench_leaky_bucket_20threads ... bench: 667 ns/iter (+/- 16,193)
test result: ok. 0 passed; 0 failed; 0 ignored; 2 measured; 0 filtered out
Running target/release/deps/single_threaded-18617cd4f9e09b0d
running 8 tests
test bench_allower ... bench: 26 ns/iter (+/- 4)
test bench_gcra ... bench: 131 ns/iter (+/- 33)
test bench_gcra_bulk ... bench: 143 ns/iter (+/- 24)
test bench_leaky_bucket ... bench: 156 ns/iter (+/- 27)
test bench_leaky_bucket_bulk ... bench: 152 ns/iter (+/- 24)
test bench_threadsafe_allower ... bench: 50 ns/iter (+/- 8)
test bench_threadsafe_gcra ... bench: 133 ns/iter (+/- 21)
test bench_threadsafe_leaky_bucket ... bench: 154 ns/iter (+/- 47)
test result: ok. 0 passed; 0 failed; 0 ignored; 8 measured; 0 filtered out
Contributions welcome!
I am actively hoping that this project gives people joy in using rate-limiting techniques. You can use these techniques for so many things (from throttling API requests to ensuring you don't spam people with emails about the same thing)!
So if you have any thoughts about the API design, the internals, or you want to implement other rate-limiting algotrithms, I would be thrilled to have your input. See CONTRIBUTING.md for details!