Note: This crate is still in early development and undergoing API changes. Contributions, feature requests, and constructive feedback are warmly welcomed.
Sharded provides safe, fast, and obvious concurrent collections in Rust. This crate splits the
underlying collection into N shards
each with its own lock.
For further reading on the strategy, see a write up on C++'s parallel-hashmap
.
-
Zero unsafe code. This library uses
#![forbid(unsafe_code)]
and was motivated by the complexity and amount of memory errors present in many alternatives. -
Tiny footprint. The core logic is ~100 lines of code. This may build up over time as utilities and ergonomics are added. By default, the library only uses
std
andhashbrown
. If you'd like to pull in some community crates such asparking_lot
,ahash
, etc.. just use add the corresponding feature. -
Really fast. This implementation may be a more performant choice than some of the most popular concurrent hashmaps out there. Try it on your workload and let us know.
- countrie - A concurrent hash-trie map & set.
- dashmap - Blazing fast concurrent HashMap for Rust.
- flurry - A port of Java's
java.util.concurrent.ConcurrentHashMap
to Rust. (Also part of a live stream series)
[dependencies]
# Optionally use `parking_lot`, `ahash`, `fxhash`, `seahash`, and `xxhash`
# by specifing the feature by the same name e.g.
sharded = { version = "0.2", features = ["fxhash", "parking_lot"] }
Insert a key value pair
let users = Map::new();
users.insert(32, "Henry");
Access a storage shard
Map
provides read
and write
which give access to the underlying
storage (which is built using hashbrown::raw
). Both methods return a tuple of (Key, Guard<Shard>)
let (key, shard) = users.read(&32);
assert_eq!(shard.get(key), Some(&"Henry"));
Determine if a storage shard is locked
try_read
and try_write
are available for avoiding blocks or in situations that could
deadlock
match users.try_read(&32) {
Some((key, mut shard)) => Ok(shard.get(key)),
None => Err(WouldBlock)
};
These measurements were generated using jonhoo/bustle
. To reproduce the charts,
see the benchmarks
directory. Benchmarks can be misleading. It is recommended to benchmark using a real application
workload.
This ran each implementation over the presets in bustle::Mix
for 5
iterations / random seeds using a Intel® Core™ i9-9820X. Lower numbers are better. Approaches using a single std::sync
Lock and chashmap
were discarded for clarity (they are
a lot slower). If you know why chashmap
is so slow in this test, please help here.
Many thanks to
-
Reddit community for a few pointers and some motivation to take this project further.
-
Jon Gjengset for the live streams and utility crates involved
-
and countless OSS contributors that made this work possible
Licensed under either of Apache License, Version 2.0 or MIT license at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted
for inclusion in sharded
by you, as defined in the Apache-2.0 license, shall be
dual licensed as above, without any additional terms or conditions.
License: MIT OR Apache-2.0