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Merge #4762

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4762: Add search benchmarks r=Kerollmops a=dureuill

# Pull Request

## What does this PR do?
- [x] Modifies `xtask bench` so that workloads support an optional `target` argument. `target` defaults to `indexing::=trace`
- [x] Refactor the spans in the search to offer finer profiling granularity
- [x] Add search workloads  
- [x] Updates documentation in `BENCHMARKS.md`


Co-authored-by: Louis Dureuil <louis@meilisearch.com>
This commit is contained in:
meili-bors[bot] 2024-07-03 08:39:29 +00:00 committed by GitHub
commit b64b4ab6ca
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GPG Key ID: B5690EEEBB952194
23 changed files with 1129 additions and 15 deletions
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6
BENCHMARKS.md
View File

@ -109,6 +109,12 @@ They are JSON files with the following structure (comments are not actually supp
"run_count": 3,
// List of arguments to add to the Meilisearch command line.
"extra_cli_args": ["--max-indexing-threads=1"],
// An expression that can be parsed as a comma-separated list of targets and levels
// as described in [tracing_subscriber's documentation](https://docs.rs/tracing-subscriber/latest/tracing_subscriber/filter/targets/struct.Targets.html#examples).
// The expression is used to filter the spans that are measured for profiling purposes.
// Optional, defaults to "indexing::=trace" (for indexing workloads), common other values is
// "search::=trace"
"target": "indexing::=trace",
// List of named assets that can be used in the commands.
"assets": {
// name of the asset.

13
meilisearch/src/search.rs
View File

@ -752,10 +752,15 @@ fn prepare_search<'t>(
SearchKind::SemanticOnly { embedder_name, embedder } => {
let vector = match query.vector.clone() {
Some(vector) => vector,
None => embedder
.embed_one(query.q.clone().unwrap())
.map_err(milli::vector::Error::from)
.map_err(milli::Error::from)?,
None => {
let span = tracing::trace_span!(target: "search::vector", "embed_one");
let _entered = span.enter();
embedder
.embed_one(query.q.clone().unwrap())
.map_err(milli::vector::Error::from)
.map_err(milli::Error::from)?
}
};
search.semantic(embedder_name.clone(), embedder.clone(), Some(vector));

6
milli/src/search/hybrid.rs
View File

@ -17,6 +17,7 @@ struct ScoreWithRatioResult {
type ScoreWithRatio = (Vec<ScoreDetails>, f32);
#[tracing::instrument(level = "trace", skip_all, target = "search::hybrid")]
fn compare_scores(
&(ref left_scores, left_ratio): &ScoreWithRatio,
&(ref right_scores, right_ratio): &ScoreWithRatio,
@ -84,6 +85,7 @@ impl ScoreWithRatioResult {
}
}
#[tracing::instrument(level = "trace", skip_all, target = "search::hybrid")]
fn merge(
vector_results: Self,
keyword_results: Self,
@ -150,6 +152,7 @@ impl ScoreWithRatioResult {
}
impl<'a> Search<'a> {
#[tracing::instrument(level = "trace", skip_all, target = "search::hybrid")]
pub fn execute_hybrid(&self, semantic_ratio: f32) -> Result<(SearchResult, Option<u32>)> {
// TODO: find classier way to achieve that than to reset vector and query params
// create separate keyword and semantic searches
@ -194,6 +197,9 @@ impl<'a> Search<'a> {
Some(vector_query) => vector_query,
None => {
// attempt to embed the vector
let span = tracing::trace_span!(target: "search::hybrid", "embed_one");
let _entered = span.enter();
match embedder.embed_one(query) {
Ok(embedding) => embedding,
Err(error) => {

4
milli/src/search/new/bucket_sort.rs
View File

@ -213,9 +213,6 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
continue;
}
let span = tracing::trace_span!(target: "search::bucket_sort", "next_bucket", id = ranking_rules[cur_ranking_rule_index].id());
let entered = span.enter();
let Some(next_bucket) = ranking_rules[cur_ranking_rule_index].next_bucket(
ctx,
logger,
@ -225,7 +222,6 @@ pub fn bucket_sort<'ctx, Q: RankingRuleQueryTrait>(
back!();
continue;
};
drop(entered);
ranking_rule_scores.push(next_bucket.score);

3
milli/src/search/new/exact_attribute.rs
View File

@ -27,6 +27,7 @@ impl<'ctx> RankingRule<'ctx, QueryGraph> for ExactAttribute {
"exact_attribute".to_owned()
}
#[tracing::instrument(level = "trace", skip_all, target = "search::exact_attribute")]
fn start_iteration(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -38,6 +39,7 @@ impl<'ctx> RankingRule<'ctx, QueryGraph> for ExactAttribute {
Ok(())
}
#[tracing::instrument(level = "trace", skip_all, target = "search::exact_attribute")]
fn next_bucket(
&mut self,
_ctx: &mut SearchContext<'ctx>,
@ -51,6 +53,7 @@ impl<'ctx> RankingRule<'ctx, QueryGraph> for ExactAttribute {
Ok(output)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::exact_attribute")]
fn end_iteration(
&mut self,
_ctx: &mut SearchContext<'ctx>,

3
milli/src/search/new/geo_sort.rs
View File

@ -209,6 +209,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
"geo_sort".to_owned()
}
#[tracing::instrument(level = "trace", skip_all, target = "search::geo_sort")]
fn start_iteration(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -234,6 +235,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
Ok(())
}
#[tracing::instrument(level = "trace", skip_all, target = "search::geo_sort")]
#[allow(clippy::only_used_in_recursion)]
fn next_bucket(
&mut self,
@ -285,6 +287,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for GeoSort<Q> {
self.next_bucket(ctx, logger, universe)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::geo_sort")]
fn end_iteration(&mut self, _ctx: &mut SearchContext<'ctx>, _logger: &mut dyn SearchLogger<Q>) {
// we do not reset the rtree here, it could be used in a next iteration
self.query = None;

4
milli/src/search/new/graph_based_ranking_rule.rs
View File

@ -127,6 +127,8 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
fn id(&self) -> String {
self.id.clone()
}
#[tracing::instrument(level = "trace", skip_all, target = "search::graph_based")]
fn start_iteration(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -209,6 +211,7 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
Ok(())
}
#[tracing::instrument(level = "trace", skip_all, target = "search::graph_based")]
fn next_bucket(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -358,6 +361,7 @@ impl<'ctx, G: RankingRuleGraphTrait> RankingRule<'ctx, QueryGraph> for GraphBase
Ok(Some(RankingRuleOutput { query: next_query_graph, candidates: bucket, score }))
}
#[tracing::instrument(level = "trace", skip_all, target = "search::graph_based")]
fn end_iteration(
&mut self,
_ctx: &mut SearchContext<'ctx>,

10
milli/src/search/new/mod.rs
View File

@ -212,7 +212,7 @@ fn resolve_maximally_reduced_query_graph(
Ok(docids)
}
#[tracing::instrument(level = "trace", skip_all, target = "search")]
#[tracing::instrument(level = "trace", skip_all, target = "search::universe")]
fn resolve_universe(
ctx: &mut SearchContext,
initial_universe: &RoaringBitmap,
@ -229,7 +229,7 @@ fn resolve_universe(
)
}
#[tracing::instrument(level = "trace", skip_all, target = "search")]
#[tracing::instrument(level = "trace", skip_all, target = "search::query")]
fn resolve_negative_words(
ctx: &mut SearchContext,
negative_words: &[Word],
@ -243,7 +243,7 @@ fn resolve_negative_words(
Ok(negative_bitmap)
}
#[tracing::instrument(level = "trace", skip_all, target = "search")]
#[tracing::instrument(level = "trace", skip_all, target = "search::query")]
fn resolve_negative_phrases(
ctx: &mut SearchContext,
negative_phrases: &[LocatedQueryTerm],
@ -548,7 +548,7 @@ fn resolve_sort_criteria<'ctx, Query: RankingRuleQueryTrait>(
Ok(())
}
#[tracing::instrument(level = "trace", skip_all, target = "search")]
#[tracing::instrument(level = "trace", skip_all, target = "search::universe")]
pub fn filtered_universe(
index: &Index,
txn: &RoTxn<'_>,
@ -620,7 +620,7 @@ pub fn execute_vector_search(
}
#[allow(clippy::too_many_arguments)]
#[tracing::instrument(level = "trace", skip_all, target = "search")]
#[tracing::instrument(level = "trace", skip_all, target = "search::main")]
pub fn execute_search(
ctx: &mut SearchContext,
query: Option<&str>,

3
milli/src/search/new/ranking_rule_graph/exactness/mod.rs
View File

@ -44,6 +44,7 @@ fn compute_docids(
impl RankingRuleGraphTrait for ExactnessGraph {
type Condition = ExactnessCondition;
#[tracing::instrument(level = "trace", skip_all, target = "search::exactness")]
fn resolve_condition(
ctx: &mut SearchContext,
condition: &Self::Condition,
@ -71,6 +72,7 @@ impl RankingRuleGraphTrait for ExactnessGraph {
})
}
#[tracing::instrument(level = "trace", skip_all, target = "search::exactness")]
fn build_edges(
_ctx: &mut SearchContext,
conditions_interner: &mut DedupInterner<Self::Condition>,
@ -86,6 +88,7 @@ impl RankingRuleGraphTrait for ExactnessGraph {
Ok(vec![(0, exact_condition), (dest_node.term_ids.len() as u32, skip_condition)])
}
#[tracing::instrument(level = "trace", skip_all, target = "search::exactness")]
fn rank_to_score(rank: Rank) -> ScoreDetails {
ScoreDetails::ExactWords(score_details::ExactWords::from_rank(rank))
}

3
milli/src/search/new/ranking_rule_graph/fid/mod.rs
View File

@ -20,6 +20,7 @@ pub enum FidGraph {}
impl RankingRuleGraphTrait for FidGraph {
type Condition = FidCondition;
#[tracing::instrument(level = "trace", skip_all, target = "search::fid")]
fn resolve_condition(
ctx: &mut SearchContext,
condition: &Self::Condition,
@ -44,6 +45,7 @@ impl RankingRuleGraphTrait for FidGraph {
})
}
#[tracing::instrument(level = "trace", skip_all, target = "search::fid")]
fn build_edges(
ctx: &mut SearchContext,
conditions_interner: &mut DedupInterner<Self::Condition>,
@ -101,6 +103,7 @@ impl RankingRuleGraphTrait for FidGraph {
Ok(edges)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::fid")]
fn rank_to_score(rank: Rank) -> ScoreDetails {
ScoreDetails::Fid(rank)
}

3
milli/src/search/new/ranking_rule_graph/position/mod.rs
View File

@ -20,6 +20,7 @@ pub enum PositionGraph {}
impl RankingRuleGraphTrait for PositionGraph {
type Condition = PositionCondition;
#[tracing::instrument(level = "trace", skip_all, target = "search::position")]
fn resolve_condition(
ctx: &mut SearchContext,
condition: &Self::Condition,
@ -44,6 +45,7 @@ impl RankingRuleGraphTrait for PositionGraph {
})
}
#[tracing::instrument(level = "trace", skip_all, target = "search::position")]
fn build_edges(
ctx: &mut SearchContext,
conditions_interner: &mut DedupInterner<Self::Condition>,
@ -117,6 +119,7 @@ impl RankingRuleGraphTrait for PositionGraph {
Ok(edges)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::position")]
fn rank_to_score(rank: Rank) -> ScoreDetails {
ScoreDetails::Position(rank)
}

3
milli/src/search/new/ranking_rule_graph/proximity/mod.rs
View File

@ -21,6 +21,7 @@ pub enum ProximityGraph {}
impl RankingRuleGraphTrait for ProximityGraph {
type Condition = ProximityCondition;
#[tracing::instrument(level = "trace", skip_all, target = "search::proximity")]
fn resolve_condition(
ctx: &mut SearchContext,
condition: &Self::Condition,
@ -29,6 +30,7 @@ impl RankingRuleGraphTrait for ProximityGraph {
compute_docids::compute_docids(ctx, condition, universe)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::proximity")]
fn build_edges(
ctx: &mut SearchContext,
conditions_interner: &mut DedupInterner<Self::Condition>,
@ -38,6 +40,7 @@ impl RankingRuleGraphTrait for ProximityGraph {
build::build_edges(ctx, conditions_interner, source_term, dest_term)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::proximity")]
fn rank_to_score(rank: Rank) -> ScoreDetails {
ScoreDetails::Proximity(rank)
}

3
milli/src/search/new/ranking_rule_graph/typo/mod.rs
View File

@ -19,6 +19,7 @@ pub enum TypoGraph {}
impl RankingRuleGraphTrait for TypoGraph {
type Condition = TypoCondition;
#[tracing::instrument(level = "trace", skip_all, target = "search::typo")]
fn resolve_condition(
ctx: &mut SearchContext,
condition: &Self::Condition,
@ -37,6 +38,7 @@ impl RankingRuleGraphTrait for TypoGraph {
})
}
#[tracing::instrument(level = "trace", skip_all, target = "search::typo")]
fn build_edges(
ctx: &mut SearchContext,
conditions_interner: &mut DedupInterner<Self::Condition>,
@ -77,6 +79,7 @@ impl RankingRuleGraphTrait for TypoGraph {
Ok(edges)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::typo")]
fn rank_to_score(rank: Rank) -> ScoreDetails {
ScoreDetails::Typo(score_details::Typo::from_rank(rank))
}

3
milli/src/search/new/ranking_rule_graph/words/mod.rs
View File

@ -18,6 +18,7 @@ pub enum WordsGraph {}
impl RankingRuleGraphTrait for WordsGraph {
type Condition = WordsCondition;
#[tracing::instrument(level = "trace", skip_all, target = "search::words")]
fn resolve_condition(
ctx: &mut SearchContext,
condition: &Self::Condition,
@ -36,6 +37,7 @@ impl RankingRuleGraphTrait for WordsGraph {
})
}
#[tracing::instrument(level = "trace", skip_all, target = "search::words")]
fn build_edges(
_ctx: &mut SearchContext,
conditions_interner: &mut DedupInterner<Self::Condition>,
@ -45,6 +47,7 @@ impl RankingRuleGraphTrait for WordsGraph {
Ok(vec![(0, conditions_interner.insert(WordsCondition { term: to_term.clone() }))])
}
#[tracing::instrument(level = "trace", skip_all, target = "search::words")]
fn rank_to_score(rank: Rank) -> ScoreDetails {
ScoreDetails::Words(score_details::Words::from_rank(rank))
}

4
milli/src/search/new/sort.rs
View File

@ -88,6 +88,8 @@ impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx,
let Self { field_name, is_ascending, .. } = self;
format!("{field_name}:{}", if *is_ascending { "asc" } else { "desc" })
}
#[tracing::instrument(level = "trace", skip_all, target = "search::sort")]
fn start_iteration(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -186,6 +188,7 @@ impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx,
Ok(())
}
#[tracing::instrument(level = "trace", skip_all, target = "search::sort")]
fn next_bucket(
&mut self,
_ctx: &mut SearchContext<'ctx>,
@ -211,6 +214,7 @@ impl<'ctx, Query: RankingRuleQueryTrait> RankingRule<'ctx, Query> for Sort<'ctx,
}
}
#[tracing::instrument(level = "trace", skip_all, target = "search::sort")]
fn end_iteration(
&mut self,
_ctx: &mut SearchContext<'ctx>,

3
milli/src/search/new/vector_sort.rs
View File

@ -73,6 +73,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for VectorSort<Q> {
"vector_sort".to_owned()
}
#[tracing::instrument(level = "trace", skip_all, target = "search::vector_sort")]
fn start_iteration(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -89,6 +90,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for VectorSort<Q> {
}
#[allow(clippy::only_used_in_recursion)]
#[tracing::instrument(level = "trace", skip_all, target = "search::vector_sort")]
fn next_bucket(
&mut self,
ctx: &mut SearchContext<'ctx>,
@ -139,6 +141,7 @@ impl<'ctx, Q: RankingRuleQueryTrait> RankingRule<'ctx, Q> for VectorSort<Q> {
self.next_bucket(ctx, _logger, universe)
}
#[tracing::instrument(level = "trace", skip_all, target = "search::vector_sort")]
fn end_iteration(&mut self, _ctx: &mut SearchContext<'ctx>, _logger: &mut dyn SearchLogger<Q>) {
self.query = None;
}

171
workloads/search/embeddings-movies-subset-hf.json Normal file
View File

@ -0,0 +1,171 @@
{
"name": "search-movies-subset-hf-embeddings",
"run_count": 2,
"target": "search::=trace",
"extra_cli_args": [
"--max-indexing-threads=4"
],
"assets": {
"movies-100.json": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/movies-100.json",
"sha256": "d215e395e4240f12f03b8f1f68901eac82d9e7ded5b462cbf4a6b8efde76c6c6"
}
},
"precommands": [
{
"route": "experimental-features",
"method": "PATCH",
"body": {
"inline": {
"vectorStore": true
}
},
"synchronous": "DontWait"
},
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"searchableAttributes": [
"title",
"overview"
],
"filterableAttributes": [
"genres",
"release_date"
],
"sortableAttributes": [
"release_date"
],
"searchCutoffMs": 15000
}
},
"synchronous": "WaitForTask"
},
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"embedders": {
"default": {
"source": "huggingFace",
"documentTemplate": "A movie titled '{{doc.title}}' whose description starts with {{doc.overview|truncatewords: 20}}"
}
}
}
},
"synchronous": "WaitForTask"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "movies-100.json"
},
"synchronous": "WaitForTask"
}
],
"commands": [
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 0.1
}
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 0.5
}
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 0.9
}
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "puppy cute comforting movie",
"limit": 100,
"hybrid": {
"semanticRatio": 1.0
}
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "shrek",
"limit": 100,
"hybrid": {
"semanticRatio": 1.0
}
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "shrek",
"limit": 100,
"hybrid": {
"semanticRatio": 0.5
}
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "shrek",
"limit": 100,
"hybrid": {
"semanticRatio": 0.1
}
}
},
"synchronous": "WaitForResponse"
}
]
}

94
workloads/search/filterable-movies.json Normal file
View File

@ -0,0 +1,94 @@
{
"name": "search-sortable-movies.json",
"run_count": 10,
"target": "search::=trace",
"extra_cli_args": [],
"assets": {
"movies.json": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/movies.json",
"sha256": "5b6e4cb660bc20327776e8a33ea197b43d9ec84856710ead1cc87ab24df77de1"
}
},
"precommands": [
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"searchableAttributes": [
"title",
"overview"
],
"filterableAttributes": [
"genres",
"release_date"
],
"sortableAttributes": [
"release_date"
],
"searchCutoffMs": 15000
}
},
"synchronous": "DontWait"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "movies.json"
},
"synchronous": "WaitForTask"
}
],
"commands": [
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "",
"limit": 100,
"filter": "genres IN [action, comedy, adventure] AND release_date = 233366400"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "Batman returns",
"limit": 100,
"filter": "genres IN [action, comedy, adventure] AND release_date > 233366400"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "the",
"limit": 100,
"filter": "genres IN [animation, comedy, adventure] AND release_date < 233366400"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "t",
"limit": 100,
"filter": "genres = Family AND release_date <= 233366400 OR release_date >= 1054252800"
}
},
"synchronous": "WaitForResponse"
}
]
}

340
workloads/search/geosort.json Normal file
View File

@ -0,0 +1,340 @@
{
"name": "search-geosort.jsonl_1M",
"run_count": 3,
"target": "search::=trace",
"extra_cli_args": [],
"assets": {
"smol-all-countries-100k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-100k.jsonl",
"sha256": "d00924689abc02d09ec4667cc5a18364ff7bc236bad51367f34b9184b945ece3"
},
"smol-all-countries-200k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-200k.jsonl",
"sha256": "2a215b43b35d596d9da4f1071deab9002a93602e6dbf1308fba53eb89d9c5a9e"
},
"smol-all-countries-300k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-300k.jsonl",
"sha256": "91d94d78eeb10d631557a5ccf775e74a41d14ccaff4d7121dd90c7aa35534f2b"
},
"smol-all-countries-400k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-400k.jsonl",
"sha256": "ee883a353b571f35f4abb79b95cfa628f3f1c582919dd658a388b220f97fe035"
},
"smol-all-countries-500k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-500k.jsonl",
"sha256": "5be254ce4c50db12b7f1795859b8bbdcbc2ec22bccb3a1898899bd4c4765a1bf"
},
"smol-all-countries-600k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-600k.jsonl",
"sha256": "3aa91afe3361f5185c142125dfcdc8ddcb7d39fdeeeb4f5e67439511905e9826"
},
"smol-all-countries-700k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-700k.jsonl",
"sha256": "5a864a1e9d89736147a8da594e2cbce5264979326d38655d0945d8447f3867b3"
},
"smol-all-countries-800k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-800k.jsonl",
"sha256": "d85eb9c85a612fd7b77623e162ecd0f8265ba3be97054e26b9cff7c48735809b"
},
"smol-all-countries-900k.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-900k.jsonl",
"sha256": "4fd6662e8b9bfcd9fad7d5dcd691a47ec985d810d1e340465c056ee84e9c40f3"
},
"smol-all-countries-1M.jsonl": {
"local_location": null,
"format": "NdJson",
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/smol-all-countries/smol-all-countries-1M.jsonl",
"sha256": "585a713b489b154b94e7c07707bd369f888c7fe24eb90bf604578d7adf51a9e6"
}
},
"precommands": [
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"displayedAttributes": [
"geonameid",
"name",
"asciiname",
"alternatenames",
"_geo",
"population"
],
"searchableAttributes": [
"name",
"alternatenames",
"elevation"
],
"filterableAttributes": [
"_geo",
"population",
"elevation"
],
"sortableAttributes": [
"_geo",
"population",
"elevation"
],
"searchCutoffMs": 15000
}
},
"synchronous": "DontWait"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-100k.jsonl"
},
"synchronous": "WaitForTask"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-200k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-300k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-400k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-500k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-600k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-700k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-800k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-900k.jsonl"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "smol-all-countries-1M.jsonl"
},
"synchronous": "WaitForTask"
}
],
"commands": [
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "",
"limit": 100
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"sort": [
"_geoPoint(50.62999333378238, 3.086269263384099):asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"sort": [
"_geoPoint(50.62999333378238, 3.086269263384099):desc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"sort": [
"_geoPoint(35.749512532692144, 139.61664952543356):asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"sort": [
"_geoPoint(35.749512532692144, 139.61664952543356):desc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"sort": [
"_geoPoint(-48.87561645055408, -123.39275749319793):asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"sort": [
"_geoPoint(-48.87561645055408, -123.39275749319793):desc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"filter": "_geoRadius(50.62999333378238, 3.086269263384099, 100000)"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"filter": "_geoRadius(50.62999333378238, 3.086269263384099, 1000)"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"filter": "_geoRadius(35.749512532692144, 139.61664952543356, 100000)"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"filter": "_geoRadius(35.749512532692144, 139.61664952543356, 1000)"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"filter": "_geoRadius(-48.87561645055408, -123.39275749319793, 100000)"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"filter": "_geoRadius(-48.87561645055408, -123.39275749319793, 1000)"
}
},
"synchronous": "WaitForResponse"
}
]
}

255
workloads/search/hackernews.json Normal file
View File

@ -0,0 +1,255 @@
{
"name": "search-hackernews.ndjson_1M",
"run_count": 3,
"target": "search::=trace",
"extra_cli_args": [],
"assets": {
"hackernews-100_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-100_000.ndjson",
"sha256": "60ecd23485d560edbd90d9ca31f0e6dba1455422f2a44e402600fbb5f7f1b213"
},
"hackernews-200_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-200_000.ndjson",
"sha256": "785b0271fdb47cba574fab617d5d332276b835c05dd86e4a95251cf7892a1685"
},
"hackernews-300_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-300_000.ndjson",
"sha256": "de73c7154652eddfaf69cdc3b2f824d5c452f095f40a20a1c97bb1b5c4d80ab2"
},
"hackernews-400_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-400_000.ndjson",
"sha256": "c1b00a24689110f366447e434c201c086d6f456d54ed1c4995894102794d8fe7"
},
"hackernews-500_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-500_000.ndjson",
"sha256": "ae98f9dbef8193d750e3e2dbb6a91648941a1edca5f6e82c143e7996f4840083"
},
"hackernews-600_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-600_000.ndjson",
"sha256": "b495fdc72c4a944801f786400f22076ab99186bee9699f67cbab2f21f5b74dbe"
},
"hackernews-700_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-700_000.ndjson",
"sha256": "4b2c63974f3dabaa4954e3d4598b48324d03c522321ac05b0d583f36cb78a28b"
},
"hackernews-800_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-800_000.ndjson",
"sha256": "cb7b6afe0e6caa1be111be256821bc63b0771b2a0e1fad95af7aaeeffd7ba546"
},
"hackernews-900_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-900_000.ndjson",
"sha256": "e1154ddcd398f1c867758a93db5bcb21a07b9e55530c188a2917fdef332d3ba9"
},
"hackernews-1_000_000.ndjson": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/hackernews/hackernews-1_000_000.ndjson",
"sha256": "27e25efd0b68b159b8b21350d9af76938710cb29ce0393fa71b41c4f3c630ffe"
}
},
"precommands": [
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"displayedAttributes": [
"title",
"by",
"score",
"time"
],
"searchableAttributes": [
"title"
],
"filterableAttributes": [
"by"
],
"sortableAttributes": [
"score",
"time"
],
"rankingRules": [
"sort",
"words",
"typo",
"proximity",
"attribute",
"exactness"
],
"searchCutoffMs": 15000
}
},
"synchronous": "WaitForTask"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-100_000.ndjson"
},
"synchronous": "WaitForTask"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-200_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-300_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-400_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-500_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-600_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-700_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-800_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-900_000.ndjson"
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "hackernews-1_000_000.ndjson"
},
"synchronous": "WaitForTask"
}
],
"commands": [
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "rust meilisearch",
"limit": 100,
"filter": "by = tpayet",
"sort": [
"score:desc",
"time:asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "rust meilisearch",
"limit": 100,
"filter": "NOT by = tpayet",
"sort": [
"score:desc",
"time:asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "meilisearch",
"limit": 100,
"sort": [
"score:desc",
"time:desc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "rust",
"limit": 100,
"filter": "by = dang",
"sort": [
"score:desc",
"time:asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "combinator YC",
"limit": 100,
"filter": "by = dang",
"sort": [
"score:desc",
"time:asc"
]
}
},
"synchronous": "WaitForResponse"
}
]
}

90
workloads/search/movies.json Normal file
View File

@ -0,0 +1,90 @@
{
"name": "search-movies.json",
"run_count": 10,
"target": "search::=trace",
"extra_cli_args": [],
"assets": {
"movies.json": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/movies.json",
"sha256": "5b6e4cb660bc20327776e8a33ea197b43d9ec84856710ead1cc87ab24df77de1"
}
},
"precommands": [
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"searchableAttributes": [
"title",
"overview"
],
"filterableAttributes": [
"genres",
"release_date"
],
"sortableAttributes": [
"release_date"
],
"searchCutoffMs": 15000
}
},
"synchronous": "DontWait"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "movies.json"
},
"synchronous": "WaitForTask"
}
],
"commands": [
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "",
"limit": 100
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "Batman returns",
"limit": 100
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"q": "the"
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"limit": 100,
"q": "t"
}
},
"synchronous": "WaitForResponse"
}
]
}

110
workloads/search/sortable-movies.json Normal file
View File

@ -0,0 +1,110 @@
{
"name": "search-sortable-movies.json",
"run_count": 10,
"target": "search::=trace",
"extra_cli_args": [],
"assets": {
"movies.json": {
"local_location": null,
"remote_location": "https://milli-benchmarks.fra1.digitaloceanspaces.com/bench/datasets/movies.json",
"sha256": "5b6e4cb660bc20327776e8a33ea197b43d9ec84856710ead1cc87ab24df77de1"
}
},
"precommands": [
{
"route": "indexes/movies/settings",
"method": "PATCH",
"body": {
"inline": {
"searchableAttributes": [
"title",
"overview"
],
"filterableAttributes": [
"genres",
"release_date"
],
"sortableAttributes": [
"release_date"
],
"rankingRules": [
"sort",
"words",
"typo",
"proximity",
"attribute",
"exactness"
],
"searchCutoffMs": 15000
}
},
"synchronous": "DontWait"
},
{
"route": "indexes/movies/documents",
"method": "POST",
"body": {
"asset": "movies.json"
},
"synchronous": "WaitForTask"
}
],
"commands": [
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "",
"limit": 100,
"sort": [
"release_date:asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "Batman returns",
"limit": 100,
"sort": [
"release_date:desc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "the",
"limit": 100,
"sort": [
"release_date:asc"
]
}
},
"synchronous": "WaitForResponse"
},
{
"route": "indexes/movies/search",
"method": "POST",
"body": {
"inline": {
"q": "t",
"limit": 100,
"sort": [
"release_date:asc"
]
}
},
"synchronous": "WaitForResponse"
}
]
}

10
xtask/src/bench/workload.rs
View File

@ -23,6 +23,8 @@ pub struct Workload {
pub extra_cli_args: Vec<String>,
pub assets: BTreeMap<String, Asset>,
#[serde(default)]
pub target: String,
#[serde(default)]
pub precommands: Vec<super::command::Command>,
pub commands: Vec<super::command::Command>,
}
@ -54,7 +56,7 @@ async fn run_commands(
let trace_filename = format!("{report_folder}/{workload_name}-{run_number}-trace.json");
let report_filename = format!("{report_folder}/{workload_name}-{run_number}-report.json");
let report_handle = start_report(logs_client, trace_filename).await?;
let report_handle = start_report(logs_client, trace_filename, &workload.target).await?;
for batch in workload
.commands
@ -160,7 +162,11 @@ async fn execute_run(
async fn start_report(
logs_client: &Client,
filename: String,
target: &str,
) -> anyhow::Result<tokio::task::JoinHandle<anyhow::Result<std::fs::File>>> {
const DEFAULT_TARGET: &str = "indexing::=trace";
let target = if target.is_empty() { DEFAULT_TARGET } else { target };
let report_file = std::fs::File::options()
.create(true)
.truncate(true)
@ -174,7 +180,7 @@ async fn start_report(
.post("")
.json(&json!({
"mode": "profile",
"target": "indexing::=trace"
"target": target,
}))
.send()
.await