2024-05-08 14:26:41 +00:00
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use criterion::measurement::WallTime;
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use criterion::{criterion_group, criterion_main, BenchmarkGroup, Criterion, Throughput};
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use std::collections::HashSet;
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use std::time::{Duration, SystemTime};
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2024-08-20 10:42:58 +00:00
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use surrealdb_core::idx::trees::dynamicset::{AHashSet, ArraySet, DynamicSet};
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2024-05-08 14:26:41 +00:00
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fn bench_hashset(samples_vec: &Vec<Vec<u64>>) {
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for samples in samples_vec {
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let mut h = HashSet::with_capacity(samples.len());
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for &s in samples {
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h.insert(s);
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}
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for s in samples {
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assert!(h.contains(s));
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}
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assert_eq!(h.len(), samples.len());
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}
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}
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fn bench_hashbrown(samples_vec: &Vec<Vec<u64>>) {
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for samples in samples_vec {
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2024-08-20 10:42:58 +00:00
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let mut h = AHashSet::<u64>::with_capacity(samples.len());
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2024-05-08 14:26:41 +00:00
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for &s in samples {
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h.insert(s);
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}
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for s in samples {
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assert!(h.contains(s));
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}
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assert_eq!(h.len(), samples.len());
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}
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}
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fn bench_vector(samples_vec: &Vec<Vec<u64>>) {
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for samples in samples_vec {
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let mut v = Vec::with_capacity(samples.len());
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for &s in samples {
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// Same behaviour than Hash
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if !v.contains(&s) {
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v.push(s);
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}
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}
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for s in samples {
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assert!(v.contains(s));
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}
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assert_eq!(v.len(), samples.len());
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}
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}
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fn bench_array<const N: usize>(samples_vec: &Vec<Vec<u64>>) {
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for samples in samples_vec {
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let mut v = ArraySet::<u64, N>::with_capacity(samples.len());
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for &s in samples {
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v.insert(s);
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}
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for s in samples {
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assert!(v.contains(s));
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}
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assert_eq!(v.len(), samples.len());
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}
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}
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fn create_samples(capacity: usize, num_samples: usize) -> Vec<Vec<u64>> {
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let mut s = SystemTime::now().elapsed().unwrap().as_secs();
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let mut res = Vec::with_capacity(num_samples);
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for _ in 0..num_samples {
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let mut samples = Vec::with_capacity(capacity);
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for _ in 0..capacity {
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s += 1;
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samples.push(s);
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}
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res.push(samples);
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}
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res
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}
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/// This bench compares the performance of insert and search for small size HashSet collections.
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/// It compares HashSet, HashBrown, Vector and SmallVec.
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/// It is used to help choosing the best options for the UndirectedGraph used for the HNSW index.
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/// The ultimate goal is to be sure that the DynamicSet use the best option based on the expected capacity.
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fn bench_hashset_vs_vector(c: &mut Criterion) {
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const ITERATIONS: usize = 1_000_000;
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let mut group = c.benchmark_group("hashset_vs_vector");
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group.throughput(Throughput::Elements(ITERATIONS as u64));
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group.sample_size(10);
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group.measurement_time(Duration::from_secs(10));
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group_test::<4>(&mut group, ITERATIONS);
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group_test::<8>(&mut group, ITERATIONS);
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group_test::<16>(&mut group, ITERATIONS);
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group_test::<24>(&mut group, ITERATIONS);
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group_test::<28>(&mut group, ITERATIONS);
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group_test::<30>(&mut group, ITERATIONS);
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group_test::<32>(&mut group, ITERATIONS);
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group.finish();
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}
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fn group_test<const N: usize>(group: &mut BenchmarkGroup<WallTime>, iterations: usize) {
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let samples = create_samples(N, iterations);
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group.bench_function(format!("hashset_{N}"), |b| {
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b.iter(|| bench_hashset(&samples));
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});
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group.bench_function(format!("hashbrown_{N}"), |b| {
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b.iter(|| bench_hashbrown(&samples));
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});
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group.bench_function(format!("vector_{N}"), |b| {
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b.iter(|| bench_vector(&samples));
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});
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group.bench_function(format!("array_{N}"), |b| {
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b.iter(|| bench_array::<N>(&samples));
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});
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}
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criterion_group!(benches, bench_hashset_vs_vector);
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criterion_main!(benches);
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