221 lines
6 KiB
Rust
221 lines
6 KiB
Rust
use criterion::measurement::WallTime;
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use criterion::{criterion_group, criterion_main, BenchmarkGroup, Criterion, Throughput};
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use futures::executor::block_on;
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use futures::lock::Mutex;
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use rand::rngs::StdRng;
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use rand::{Rng, SeedableRng};
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use reblessive::TreeStack;
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use std::sync::atomic::{AtomicUsize, Ordering};
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use std::sync::Arc;
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use surrealdb::kvs::Datastore;
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use surrealdb::kvs::LockType::Optimistic;
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use surrealdb::kvs::TransactionType::{Read, Write};
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use surrealdb_core::ctx::Context;
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use surrealdb_core::idx::planner::checker::MTreeConditionChecker;
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use surrealdb_core::idx::trees::mtree::MTreeIndex;
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use surrealdb_core::idx::IndexKeyBase;
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use surrealdb_core::kvs::{Transaction, TransactionType};
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use surrealdb_core::sql::index::{Distance, MTreeParams, VectorType};
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use surrealdb_core::sql::{Id, Number, Thing, Value};
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use tokio::runtime::{Builder, Runtime};
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use tokio::task;
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fn bench_index_mtree_dim_3(c: &mut Criterion) {
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bench_index_mtree(c, 250, 25_000, 3, 100);
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}
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fn bench_index_mtree_dim_3_full_cache(c: &mut Criterion) {
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bench_index_mtree(c, 250, 25_000, 3, 0);
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}
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fn bench_index_mtree_dim_50(c: &mut Criterion) {
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bench_index_mtree(c, 100, 10_000, 50, 100);
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}
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fn bench_index_mtree_dim_50_full_cache(c: &mut Criterion) {
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bench_index_mtree(c, 100, 10_000, 50, 0);
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}
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fn bench_index_mtree_dim_300(c: &mut Criterion) {
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bench_index_mtree(c, 50, 5_000, 300, 100);
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}
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fn bench_index_mtree_dim_300_full_cache(c: &mut Criterion) {
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bench_index_mtree(c, 50, 5_000, 300, 0);
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}
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fn bench_index_mtree_dim_2048(c: &mut Criterion) {
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bench_index_mtree(c, 10, 1_000, 2048, 100);
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}
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fn bench_index_mtree_dim_2048_full_cache(c: &mut Criterion) {
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bench_index_mtree(c, 10, 1_000, 2048, 0);
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}
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async fn mtree_index(
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ds: &Datastore,
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tx: &mut Transaction,
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dimension: usize,
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cache_size: usize,
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tt: TransactionType,
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) -> MTreeIndex {
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let p = MTreeParams::new(
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dimension as u16,
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Distance::Euclidean,
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VectorType::F64,
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40,
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100,
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cache_size as u32,
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cache_size as u32,
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);
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MTreeIndex::new(ds.index_store(), tx, IndexKeyBase::default(), &p, tt).await.unwrap()
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}
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fn runtime() -> Runtime {
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Builder::new_multi_thread().worker_threads(4).enable_all().build().unwrap()
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}
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fn bench_index_mtree(
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c: &mut Criterion,
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debug_samples_len: usize,
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release_samples_len: usize,
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vector_dimension: usize,
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cache_size: usize,
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) {
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let samples_len = if cfg!(debug_assertions) {
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debug_samples_len // Debug is slow
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} else {
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release_samples_len // Release is fast
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};
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// Both benchmark groups are sharing the same datastore
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let ds = block_on(Datastore::new("memory")).unwrap();
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// Indexing benchmark group
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{
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let mut group = get_group(c, "index_mtree_insert", samples_len);
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let id = format!("len_{}_dim_{}_cache_{}", samples_len, vector_dimension, cache_size);
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group.bench_function(id, |b| {
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b.to_async(runtime())
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.iter(|| insert_objects(&ds, samples_len, vector_dimension, cache_size));
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});
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group.finish();
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}
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// Knn lookup benchmark group
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{
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let mut group = get_group(c, "index_mtree_lookup", samples_len);
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for knn in [1, 10] {
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let id = format!(
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"knn_{}_len_{}_dim_{}_cache_{}",
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knn, samples_len, vector_dimension, cache_size
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);
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group.bench_function(id, |b| {
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b.to_async(runtime()).iter(|| {
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knn_lookup_objects(&ds, samples_len, vector_dimension, cache_size, knn)
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});
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});
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}
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group.finish();
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}
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}
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fn get_group<'a>(
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c: &'a mut Criterion,
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group_name: &str,
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samples_len: usize,
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) -> BenchmarkGroup<'a, WallTime> {
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let mut group = c.benchmark_group(group_name);
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group.throughput(Throughput::Elements(samples_len as u64));
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group.sample_size(10);
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group
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}
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fn random_object(rng: &mut StdRng, vector_size: usize) -> Vec<Number> {
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let mut vec = Vec::with_capacity(vector_size);
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for _ in 0..vector_size {
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vec.push(rng.gen_range(-1.0..=1.0).into());
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}
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vec
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}
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async fn insert_objects(
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ds: &Datastore,
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samples_size: usize,
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vector_size: usize,
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cache_size: usize,
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) {
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let mut tx = ds.transaction(Write, Optimistic).await.unwrap();
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let mut mt = mtree_index(ds, &mut tx, vector_size, cache_size, Write).await;
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let mut stack = TreeStack::new();
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let mut rng = StdRng::from_entropy();
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stack
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.enter(|stk| async {
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for i in 0..samples_size {
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let vector: Vec<Number> = random_object(&mut rng, vector_size);
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// Insert the sample
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let rid = Thing::from(("test", Id::from(i as i64)));
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mt.index_document(stk, &mut tx, &rid, &vec![Value::from(vector)]).await.unwrap();
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}
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})
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.finish()
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.await;
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mt.finish(&mut tx).await.unwrap();
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tx.commit().await.unwrap();
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}
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async fn knn_lookup_objects(
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ds: &Datastore,
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samples_size: usize,
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vector_size: usize,
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cache_size: usize,
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knn: usize,
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) {
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let txn = Arc::new(Mutex::new(ds.transaction(Read, Optimistic).await.unwrap()));
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let mut tx = txn.lock().await;
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let mt = Arc::new(mtree_index(ds, &mut tx, vector_size, cache_size, Read).await);
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drop(tx);
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let ctx = Arc::new(Context::default().set_transaction(txn));
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let counter = Arc::new(AtomicUsize::new(0));
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let mut consumers = Vec::with_capacity(4);
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for _ in 0..4 {
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let (ctx, mt, counter) = (ctx.clone(), mt.clone(), counter.clone());
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let c = task::spawn(async move {
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let mut rng = StdRng::from_entropy();
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while counter.fetch_add(1, Ordering::Relaxed) < samples_size {
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let object = random_object(&mut rng, vector_size);
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knn_lookup_object(mt.as_ref(), &ctx, object, knn).await;
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}
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});
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consumers.push(c);
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}
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for c in consumers {
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c.await.unwrap();
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}
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}
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async fn knn_lookup_object(mt: &MTreeIndex, ctx: &Context<'_>, object: Vec<Number>, knn: usize) {
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let mut stack = TreeStack::new();
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stack
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.enter(|stk| async {
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let chk = MTreeConditionChecker::new(ctx);
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let r = mt.knn_search(stk, ctx, &object, knn, chk).await.unwrap();
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assert_eq!(r.len(), knn);
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})
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.finish()
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.await;
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}
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criterion_group!(
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benches,
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bench_index_mtree_dim_3,
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bench_index_mtree_dim_3_full_cache,
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bench_index_mtree_dim_50,
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bench_index_mtree_dim_50_full_cache,
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bench_index_mtree_dim_300,
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bench_index_mtree_dim_300_full_cache,
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bench_index_mtree_dim_2048,
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bench_index_mtree_dim_2048_full_cache
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);
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criterion_main!(benches);
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