#container #sparse #cache-friendly #set #elements #lookup #hashing

sparse_set_container

A container based on sparse set. Stable keys, O(1) lookup, cache-friendly iterations, and no hashing.

3 stable releases

1.1.1 Jun 22, 2024
1.0.1 Jun 8, 2024
1.0.0 May 25, 2024

#751 in Data structures

Download history 16/week @ 2024-09-15 1/week @ 2024-09-22 24/week @ 2024-09-29 1/week @ 2024-10-06

178 downloads per month

MIT license

73KB
1K SLoC

Sparse Set Container

A container based on a sparse set.

It is useful if you want a container with performance close to Vec but you also want to safely store the indexes to the elements (so that they are not invalidated on removals).
E.g. you have a list of elements in UI that the user can add and remove, but you want to refer to the elements of that list from somewhere else.

crates.io Documentation

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Usage

Add this to your Cargo.toml:

[dependencies]
sparse_set_container = "1.1"

Description

An array-like container based on sparse set implementation that allows O(1) access to elements without hashing and allows cache-friendly iterations.

Operation SparseSet Vec
push O(1) O(1)
lookup O(1) O(1)
size/len O(1) O(1)
remove O(n) O(n)
swap_remove O(1) O(1)

For iterating over the elements SparseSet exposes an iterator over an internal Vec with values, which is as efficient as iterating over a Vec directly.

Differences to Vec:

  • Instead of using indexes, when adding an element, it returns a lightweight key structure that can be used to access the element later
    • The key is not invalidated when elements are removed from the container
    • If the pointed-at element was removed, the key will not be pointing to any other elements, even if new elements are inserted
  • There is a slight overhead in insertion/lookup/removal operations compared to Vec
  • Consumes more memory:
    • for each value 4*sizeof(usize) bytes on top of the size of the element itself
      • (e.g. 32 bytes per element on 64-bit systems)
    • per each 2^(sizeof(usize)*8) removals the memory consumption will also grow by 2*sizeof(usize)
      • (e.g. 16 bytes per 18446744073709551616 elements removed on 64-bit systems)
  • Many Vec operations are not supported (create an issue on github if you want to request one)

Examples

extern crate sparse_set_container;
use sparse_set_container::SparseSet;

fn main() {
    let mut elements = SparseSet::new();
    elements.push("1");
    let key2 = elements.push("2");
    elements.push("3");

    elements.remove(key2);
    elements.push("4");

    if !elements.contains(key2) {
        println!("Value 2 is not in the container");
    }

    // Prints 1 3 4
    for v in elements.values() {
        print!("{} ", v);
    }

    // Prints 1 3 4
    for k in elements.keys() {
        print!("{} ", elements.get(k).unwrap());
    }
}

Benchmarks

The values captured to illustrate the difference between this SparseSet container implementation, Vec, and standard HashMap:

Benchmark SparseSet<String> Vec<String> HashMap<i32, String>
Create empty 0 ns ±0 0 ns ±0 1 ns ±0
Create with capacity 17 ns ±0 16 ns ±0 32 ns ±1
Push 100 elements 3,254 ns ±14 2,553 ns ±23 5,493 ns ±85
With capacity push 100 3,286 ns ±30 3,156 ns ±106 4,388 ns ±21
Lookup 100 elements 88 ns ±2 39 ns ±14 464 ns ±3
Iterate over 100 elements 30 ns ±0 30 ns ±0 41 ns ±1
Clone with 100 elements 2,184 ns ±23 2,109 ns ±4 1,490 ns ±32
Clone 100 and remove 10 3,055 ns ±107 2,364 ns ±97 1,692 ns ±145
Clone 100 and swap_remove 10 2,475 ns ±119 2,193 ns ±67 N/A

To run the benchmark on your machine, execute cargo run --example bench --release

Or to build this table you can run python tools/collect_benchmark_table.py and then find the results in bench_table.md

License

Licensed under the MIT license: http://opensource.org/licenses/MIT

No runtime deps