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Starshard: a high-performance, lazily sharded concurrent HashMap for Rust.

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Starshard

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Starshard: a high-performance, lazily sharded concurrent HashMap for Rust.

Sync + Async + Optional Rayon + Optional Serde


Status

Early stage. API may still evolve (semantic stability prioritized; minor naming changes possible).

Motivation

You often need a fast concurrent map:

  • Standard single RwLock<HashMap<..>> becomes contended under mixed read/write load.
  • Fully lock-free or CHM designs can add memory + complexity cost.
  • Sharding with lazy initialization offers a pragmatic middle ground.

Starshard focuses on:

  1. Minimal uncontended overhead.
  2. Lazy shard allocation (memory proportional to actually touched shards).
  3. Atomic cached length.
  4. Snapshot iteration (parallel if rayon).
  5. Symmetric sync / async APIs.
  6. Extensible design (future: rebalancing, eviction, metrics).

Features

Feature Description Notes
async Adds AsyncShardedHashMap (Tokio RwLock) Independent of rayon
rayon Parallel snapshot flatten for large iteration Used internally; API unchanged
serde Serialize/Deserialize (sync) + async snapshot helper Hasher not persisted
(none) Pure sync core Lowest dependency surface

Enable all in docs.rs via:

[package.metadata.docs.rs]
all-features = true

Installation

[dependencies]
starshard = { version = "0.5", features = ["async", "rayon", "serde"] }
# or minimal:
# starshard = "0.5"

serde_json (tests / examples):

[dev-dependencies]
serde_json = "1"

Quick Start (Sync)

use starshard::ShardedHashMap;
use rustc_hash::FxBuildHasher;

let map: ShardedHashMap<String, i32, FxBuildHasher> = ShardedHashMap::new(64);
map.insert("a".into(), 1);
assert_eq!(map.get(&"a".into()), Some(1));
assert_eq!(map.len(), 1);

Custom Hasher (defense against adversarial keys)

use starshard::ShardedHashMap;
use std::collections::hash_map::RandomState;

let secure = ShardedHashMap::<String, u64, RandomState>
::with_shards_and_hasher(128, RandomState::default ());
secure.insert("k".into(), 7);

Async Usage

#[cfg(feature = "async")]
#[tokio::main]
async fn main() {
    use starshard::AsyncShardedHashMap;
    let m: AsyncShardedHashMap<String, u32> = AsyncShardedHashMap::new(64);
    m.insert("x".into(), 42).await;
    assert_eq!(m.get(&"x".into()).await, Some(42));
}

Parallel Iteration (rayon)

#[cfg(feature = "rayon")]
{
use starshard::ShardedHashMap;
let m: ShardedHashMap<String, u32> = ShardedHashMap::new(32);
for i in 0..50_000 {
m.insert(format ! ("k{i}"), i);
}
let count = m.iter().count(); // internal parallel flatten
assert_eq!(count, 50_000);
}

Serde Semantics

Sync:

  • Serialized shape: { "shard_count": usize, "entries": [[K,V], ...] }.
  • Hasher internal state not preserved; recreated with S::default().
  • Requirements: K: Eq + Hash + Clone + Serialize + Deserialize, V: Clone + Serialize + Deserialize, S: BuildHasher + Default + Clone.

Async:

  • No direct Serialize; call:
#[cfg(all(feature = "async", feature = "serde"))]
{
let snap = async_map.async_snapshot_serializable().await;
let json = serde_json::to_string( & snap).unwrap();
}
  • To reconstruct: create a new async map and bulk insert.

Consistency Model

  • Per-shard ops are linearizable w.r.t that shard.
  • Global iteration builds a per-shard snapshot as each shard lock is taken (not a fully atomic global view).
  • len() is maintained atomically (structural insert/remove only).
  • Iteration after concurrent writes may omit late inserts performed after a shard snapshot was captured.

Performance Notes (Indicative)

Scenario Observation (relative)
Read-heavy mixed workload vs global RwLock<HashMap> Reduced contention
Large snapshot iteration with rayon (100k+) 3-4x speedup flattening
Sparse shard usage Only touched shards allocate

Do benchmark with your own key/value distribution and CPU topology.


Safety / Concurrency

  • No nested multi-shard lock ordering -> avoids deadlocks.
  • Each shard single RwLock; iteration snapshots avoid long-lived global blocking.
  • Cloning values required (trade memory for contention isolation).
  • Not lock-free: intense write focus on one shard can still serialize.

Limitations

  • No dynamic shard rebalancing.
  • No eviction / TTL.
  • Snapshot iteration allocates intermediate vectors.
  • Hasher state not serialized.
  • No lock-free progress guarantees.

Roadmap (Potential)

  • Optional adaptive shard expansion / rebalancing.
  • Per-shard eviction strategies (LRU / segmented).
  • Metrics hooks (pre/post op instrumentation).
  • Batched multi-insert API.
  • Zero-copy or COW snapshot mode.

Design Sketch

Arc -> RwLock<Vec<Option<Arc<RwLock<HashMap<K,V,S>>>>>> + AtomicUsize(len)

Lazy fill of inner Option slot when first key hashes into shard.


Examples Summary

Goal Snippet
Basic sync see Quick Start
Async insert/get see Async Usage
Parallel iterate enable rayon
Serde snapshot (sync) serde_json::to_string(&map)
Async serde snapshot async_snapshot_serializable()
Custom hasher with_shards_and_hasher(..)

License

Dual license: MIT OR Apache-2.0 (choose either).


Contribution

PRs welcome: focus on correctness (tests), simplicity, and documentation clarity.
Run:

cargo clippy --all-features -- -D warnings
cargo test --all-features

Minimal Example (All Features)

use starshard::{ShardedHashMap, AsyncShardedHashMap};
#[cfg(feature = "async")]
#[tokio::main]
async fn main() {
    let sync_map: ShardedHashMap<u64, u64> = ShardedHashMap::new(32);
    sync_map.insert(1, 10);

    #[cfg(feature = "serde")]
    {
        let json = serde_json::to_string(&sync_map).unwrap();
        let _de: ShardedHashMap<u64, u64> = serde_json::from_str(&json).unwrap();
    }

    let async_map: AsyncShardedHashMap<u64, u64> = AsyncShardedHashMap::new(32);
    async_map.insert(2, 20).await;
}

Disclaimer

Benchmarks and behavior notes are indicative only; validate under production load patterns.

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Starshard: a high-performance, lazily sharded concurrent HashMap for Rust.

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