opthash

Rust implementations of Elastic Hashing and Funnel Hashing from Optimal Bounds for Open Addressing Without Reordering (Farach-Colton, Krapivin, Kuszmaul, 2025).

Both are open-addressing hash maps that achieve optimal expected probe complexity without reordering elements after insertion.

Data Structures

Both maps share a common core: RawTable-backed multi-level layouts, 7-bit fingerprint control bytes, SIMD control-byte scans for occupancy + lookup, tombstone accounting, and per-level Lemire fastmod magics for the hash → slot mapping. The default BuildHasher is foldhash.

• ElasticHashMap<K, V> — Flat RawTable per level wsith geometrically halving capacities; insertion uses per-level probe budgets + coprime group steps.
• FunnelHashMap<K, V> — Bucketed levels plus a split special array: primary (group-probed) and fallback (two-choice buckets).

Both support insert, get, get_mut, contains_key, remove, and clear. Maps start with zero allocation (new()) and grow dynamically on demand. Advanced tuning is available through ElasticOptions, FunnelOptions, and with_options(...).

Usage

Rust

cargo add opthash

use opthash::{ElasticHashMap, ElasticOptions, FunnelHashMap, FunnelOptions};

let mut map = ElasticHashMap::new();
map.insert("key", 42);
assert_eq!(map.get("key"), Some(&42));

let mut map = ElasticHashMap::with_options(ElasticOptions {
    capacity: 1024,
    reserve_fraction: 0.10,
    probe_scale: 12.0,
});
map.insert("key", 42);
assert_eq!(map.get("key"), Some(&42));

let mut map = FunnelHashMap::with_options(FunnelOptions {
    capacity: 1024,
    reserve_fraction: 0.10,
    primary_probe_limit: Some(8),
});
map.insert("key", 42);
assert_eq!(map.get("key"), Some(&42));

Python

pip install opthash

from opthash import ElasticHashMap, ElasticOptions, FunnelHashMap, FunnelOptions

m = ElasticHashMap()
m["key"] = 42
assert m["key"] == 42
assert "key" in m and len(m) == 1

m = ElasticHashMap.with_options(ElasticOptions(
    capacity=1024, reserve_fraction=0.10, probe_scale=12.0,
))

m = FunnelHashMap.with_options(FunnelOptions(
    capacity=1024, reserve_fraction=0.10, primary_probe_limit=8,
))

Layout Sketch

RawTable (shared by both maps)
==============================

  fp = fingerprint (7-bit control byte)
  kv = key-value entry, __ = empty, xx = tombstone

  Single allocation, slots first, controls at the end:

  data_ptr ► [kv][kv][  ][kv][  ][kv]... [pad] [fp][fp][__][xx][__][fp]...
             └──── slots (T-aligned) ────┘     └─ controls (16-aligned) ──┘
                                               ▲ ctrl_offset

  No per-group metadata. Occupancy is derived from SIMD scans of the control bytes
  (eq_mask_16 for fingerprints, free_mask_16 for free slots).


ElasticHashMap
==============

  levels: Vec<Level>

    Level 0    RawTable  (largest, ~half of total capacity)
    Level 1    RawTable  (geometrically halved)
    Level 2    ...

    per-level  len, tombstones, half_reserve_slot_threshold,
               limited_probe_budgets, group_steps, salt,
               group_count_magic, step_count_magic

  table-wide   len, capacity, max_insertions, reserve_fraction,
               probe_scale, batch_plan, current_batch_index,
               batch_remaining, max_populated_level, hash_builder


FunnelHashMap
=============

  levels: Vec<BucketLevel>

    Level 0
      slots:     kv kv __ __ ... kv kv __ __ ... kv ...
      controls:  fp fp __ __ ... fp fp __ __ ... fp ...
                 └── bucket 0 ──┘└── bucket 1 ──┘

    Level 1    (same layout, smaller buckets)
    ...

    per-level  len, tombstones, bucket_size, bucket_count,
               salt, bucket_count_magic

  special: SpecialArray

    primary    RawTable, group-probed (like elastic)
    (paper B)  len, group_summaries, group_tombstones, group_steps

    fallback   RawTable, two-choice bucketed
    (paper C)  len, tombstones, bucket_size, bucket_count

  table-wide   len, capacity, max_insertions, reserve_fraction,
               primary_probe_limit, max_populated_level, hash_builder

Benchmarks

See benches/README.md for bench target layout, charts, CLI flags, chart regeneration, and flamegraph profiling.