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b2f99c6217
* add term->histogram benchmark * add more term aggs --------- Co-authored-by: Pascal Seitz <pascal.seitz@datadoghq.com>
633 lines
20 KiB
Rust
633 lines
20 KiB
Rust
use binggan::plugins::PeakMemAllocPlugin;
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use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
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use rand::distributions::WeightedIndex;
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use rand::prelude::SliceRandom;
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use rand::rngs::StdRng;
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use rand::{Rng, SeedableRng};
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use rand_distr::Distribution;
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use serde_json::json;
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use tantivy::aggregation::agg_req::Aggregations;
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use tantivy::aggregation::AggregationCollector;
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use tantivy::query::{AllQuery, TermQuery};
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use tantivy::schema::{IndexRecordOption, Schema, TextFieldIndexing, FAST, STRING};
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use tantivy::{doc, Index, Term};
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#[global_allocator]
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pub static GLOBAL: &PeakMemAlloc<std::alloc::System> = &INSTRUMENTED_SYSTEM;
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/// Mini macro to register a function via its name
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/// runner.register("average_u64", move |index| average_u64(index));
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macro_rules! register {
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($runner:expr, $func:ident) => {
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$runner.register(stringify!($func), move |index| {
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$func(index);
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})
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};
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}
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fn main() {
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let inputs = vec![
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("full", get_test_index_bench(Cardinality::Full).unwrap()),
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(
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"dense",
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get_test_index_bench(Cardinality::OptionalDense).unwrap(),
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),
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(
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"sparse",
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get_test_index_bench(Cardinality::OptionalSparse).unwrap(),
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),
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(
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"multivalue",
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get_test_index_bench(Cardinality::Multivalued).unwrap(),
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),
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];
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bench_agg(InputGroup::new_with_inputs(inputs));
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}
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fn bench_agg(mut group: InputGroup<Index>) {
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group.add_plugin(PeakMemAllocPlugin::new(GLOBAL));
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register!(group, average_u64);
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register!(group, average_f64);
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register!(group, average_f64_u64);
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register!(group, stats_f64);
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register!(group, extendedstats_f64);
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register!(group, percentiles_f64);
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register!(group, terms_few);
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register!(group, terms_all_unique);
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register!(group, terms_many);
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register!(group, terms_many_top_1000);
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register!(group, terms_many_order_by_term);
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register!(group, terms_many_with_top_hits);
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register!(group, terms_all_unique_with_avg_sub_agg);
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register!(group, terms_many_with_avg_sub_agg);
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register!(group, terms_few_with_avg_sub_agg);
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register!(group, terms_status_with_avg_sub_agg);
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register!(group, terms_status);
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register!(group, terms_few_with_histogram);
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register!(group, terms_status_with_histogram);
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register!(group, terms_many_json_mixed_type_with_avg_sub_agg);
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register!(group, cardinality_agg);
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register!(group, terms_few_with_cardinality_agg);
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register!(group, range_agg);
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register!(group, range_agg_with_avg_sub_agg);
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register!(group, range_agg_with_term_agg_few);
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register!(group, range_agg_with_term_agg_many);
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register!(group, histogram);
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register!(group, histogram_hard_bounds);
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register!(group, histogram_with_avg_sub_agg);
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register!(group, histogram_with_term_agg_few);
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register!(group, avg_and_range_with_avg_sub_agg);
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// Filter aggregation benchmarks
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register!(group, filter_agg_all_query_count_agg);
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register!(group, filter_agg_term_query_count_agg);
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register!(group, filter_agg_all_query_with_sub_aggs);
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register!(group, filter_agg_term_query_with_sub_aggs);
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group.run();
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}
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fn exec_term_with_agg(index: &Index, agg_req: serde_json::Value) {
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let agg_req: Aggregations = serde_json::from_value(agg_req).unwrap();
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let reader = index.reader().unwrap();
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let text_field = reader.searcher().schema().get_field("text").unwrap();
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let term_query = TermQuery::new(
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Term::from_field_text(text_field, "cool"),
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IndexRecordOption::Basic,
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);
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let collector = get_collector(agg_req);
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let searcher = reader.searcher();
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black_box(searcher.search(&term_query, &collector).unwrap());
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}
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fn average_u64(index: &Index) {
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let agg_req = json!({
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"average": { "avg": { "field": "score", } }
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});
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exec_term_with_agg(index, agg_req)
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}
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fn average_f64(index: &Index) {
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let agg_req = json!({
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"average": { "avg": { "field": "score_f64", } }
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});
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exec_term_with_agg(index, agg_req)
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}
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fn average_f64_u64(index: &Index) {
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let agg_req = json!({
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"average_f64": { "avg": { "field": "score_f64" } },
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"average": { "avg": { "field": "score" } },
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});
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exec_term_with_agg(index, agg_req)
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}
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fn stats_f64(index: &Index) {
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let agg_req = json!({
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"average_f64": { "stats": { "field": "score_f64", } }
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});
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exec_term_with_agg(index, agg_req)
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}
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fn extendedstats_f64(index: &Index) {
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let agg_req = json!({
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"extendedstats_f64": { "extended_stats": { "field": "score_f64", } }
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});
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exec_term_with_agg(index, agg_req)
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}
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fn percentiles_f64(index: &Index) {
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let agg_req = json!({
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"mypercentiles": {
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"percentiles": {
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"field": "score_f64",
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"percents": [ 95, 99, 99.9 ]
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}
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}
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});
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execute_agg(index, agg_req);
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}
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fn cardinality_agg(index: &Index) {
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let agg_req = json!({
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"cardinality": {
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"cardinality": {
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"field": "text_many_terms"
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},
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}
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});
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execute_agg(index, agg_req);
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}
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fn terms_few_with_cardinality_agg(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_few_terms" },
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"aggs": {
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"cardinality": {
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"cardinality": {
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"field": "text_many_terms"
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},
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}
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn terms_few(index: &Index) {
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let agg_req = json!({
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"my_texts": { "terms": { "field": "text_few_terms" } },
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});
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execute_agg(index, agg_req);
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}
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fn terms_status(index: &Index) {
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let agg_req = json!({
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"my_texts": { "terms": { "field": "text_few_terms_status" } },
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});
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execute_agg(index, agg_req);
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}
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fn terms_all_unique(index: &Index) {
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let agg_req = json!({
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"my_texts": { "terms": { "field": "text_all_unique_terms" } },
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});
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execute_agg(index, agg_req);
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}
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fn terms_many(index: &Index) {
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let agg_req = json!({
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"my_texts": { "terms": { "field": "text_many_terms" } },
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});
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execute_agg(index, agg_req);
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}
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fn terms_many_top_1000(index: &Index) {
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let agg_req = json!({
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"my_texts": { "terms": { "field": "text_many_terms", "size": 1000 } },
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});
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execute_agg(index, agg_req);
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}
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fn terms_many_order_by_term(index: &Index) {
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let agg_req = json!({
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"my_texts": { "terms": { "field": "text_many_terms", "order": { "_key": "desc" } } },
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});
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execute_agg(index, agg_req);
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}
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fn terms_many_with_top_hits(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_many_terms" },
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"aggs": {
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"top_hits": { "top_hits":
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{
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"sort": [
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{ "score": "desc" }
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],
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"size": 2,
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"doc_value_fields": ["score_f64"]
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}
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}
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn terms_many_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_many_terms" },
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn terms_all_unique_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_all_unique_terms" },
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn terms_few_with_histogram(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_few_terms" },
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"aggs": {
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"histo": {"histogram": { "field": "score_f64", "interval": 10 }}
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}
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}
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});
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execute_agg(index, agg_req);
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}
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fn terms_status_with_histogram(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_few_terms_status" },
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"aggs": {
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"histo": {"histogram": { "field": "score_f64", "interval": 10 }}
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}
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}
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});
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execute_agg(index, agg_req);
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}
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fn terms_few_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_few_terms" },
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn terms_status_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "text_few_terms_status" },
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn terms_many_json_mixed_type_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"my_texts": {
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"terms": { "field": "json.mixed_type" },
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn execute_agg(index: &Index, agg_req: serde_json::Value) {
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let agg_req: Aggregations = serde_json::from_value(agg_req).unwrap();
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let collector = get_collector(agg_req);
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let reader = index.reader().unwrap();
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let searcher = reader.searcher();
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black_box(searcher.search(&AllQuery, &collector).unwrap());
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}
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fn range_agg(index: &Index) {
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let agg_req = json!({
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"range_f64": { "range": { "field": "score_f64", "ranges": [
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{ "from": 3, "to": 7000 },
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{ "from": 7000, "to": 20000 },
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{ "from": 20000, "to": 30000 },
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{ "from": 30000, "to": 40000 },
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{ "from": 40000, "to": 50000 },
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{ "from": 50000, "to": 60000 }
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] } },
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});
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execute_agg(index, agg_req);
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}
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fn range_agg_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"range": {
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"field": "score_f64",
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"ranges": [
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{ "from": 3, "to": 7000 },
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{ "from": 7000, "to": 20000 },
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{ "from": 20000, "to": 30000 },
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{ "from": 30000, "to": 40000 },
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{ "from": 40000, "to": 50000 },
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{ "from": 50000, "to": 60000 }
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]
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},
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn range_agg_with_term_agg_few(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"range": {
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"field": "score_f64",
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"ranges": [
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{ "from": 3, "to": 7000 },
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{ "from": 7000, "to": 20000 },
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{ "from": 20000, "to": 30000 },
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{ "from": 30000, "to": 40000 },
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{ "from": 40000, "to": 50000 },
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{ "from": 50000, "to": 60000 }
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]
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},
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"aggs": {
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"my_texts": { "terms": { "field": "text_few_terms" } },
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn range_agg_with_term_agg_many(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"range": {
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"field": "score_f64",
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"ranges": [
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{ "from": 3, "to": 7000 },
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{ "from": 7000, "to": 20000 },
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{ "from": 20000, "to": 30000 },
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{ "from": 30000, "to": 40000 },
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{ "from": 40000, "to": 50000 },
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{ "from": 50000, "to": 60000 }
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]
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},
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"aggs": {
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"my_texts": { "terms": { "field": "text_many_terms" } },
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}
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},
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});
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execute_agg(index, agg_req);
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}
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fn histogram(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"histogram": {
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"field": "score_f64",
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"interval": 100 // 1000 buckets
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},
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}
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});
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execute_agg(index, agg_req);
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}
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fn histogram_hard_bounds(index: &Index) {
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let agg_req = json!({
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"rangef64": { "histogram": { "field": "score_f64", "interval": 100, "hard_bounds": { "min": 1000, "max": 300000 } } },
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});
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execute_agg(index, agg_req);
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}
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fn histogram_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"histogram": { "field": "score_f64", "interval": 100 },
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"aggs": {
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"average_f64": { "avg": { "field": "score_f64" } }
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}
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}
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});
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execute_agg(index, agg_req);
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}
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fn histogram_with_term_agg_few(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"histogram": { "field": "score_f64", "interval": 10 },
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"aggs": {
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"my_texts": { "terms": { "field": "text_few_terms" } }
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}
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}
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});
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execute_agg(index, agg_req);
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}
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fn avg_and_range_with_avg_sub_agg(index: &Index) {
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let agg_req = json!({
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"rangef64": {
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"range": {
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"field": "score_f64",
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"ranges": [
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{ "from": 3, "to": 7000 },
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{ "from": 7000, "to": 20000 },
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{ "from": 20000, "to": 60000 }
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]
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},
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"aggs": {
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"average_in_range": { "avg": { "field": "score" } }
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}
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},
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"average": { "avg": { "field": "score" } }
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});
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execute_agg(index, agg_req);
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}
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#[derive(Clone, Copy, Hash, Default, Debug, PartialEq, Eq, PartialOrd, Ord)]
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enum Cardinality {
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/// All documents contain exactly one value.
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/// `Full` is the default for auto-detecting the Cardinality, since it is the most strict.
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#[default]
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Full = 0,
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/// All documents contain at most one value.
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OptionalDense = 1,
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/// All documents may contain any number of values.
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Multivalued = 2,
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/// 1 / 20 documents has a value
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OptionalSparse = 3,
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}
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fn get_collector(agg_req: Aggregations) -> AggregationCollector {
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AggregationCollector::from_aggs(agg_req, Default::default())
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}
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fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
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let mut schema_builder = Schema::builder();
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let text_fieldtype = tantivy::schema::TextOptions::default()
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.set_indexing_options(
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TextFieldIndexing::default().set_index_option(IndexRecordOption::WithFreqs),
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)
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.set_stored();
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let text_field = schema_builder.add_text_field("text", text_fieldtype);
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let json_field = schema_builder.add_json_field("json", FAST);
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let text_field_all_unique_terms =
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schema_builder.add_text_field("text_all_unique_terms", STRING | FAST);
|
|
let text_field_many_terms = schema_builder.add_text_field("text_many_terms", STRING | FAST);
|
|
let text_field_many_terms = schema_builder.add_text_field("text_many_terms", STRING | FAST);
|
|
let text_field_few_terms = schema_builder.add_text_field("text_few_terms", STRING | FAST);
|
|
let text_field_few_terms_status =
|
|
schema_builder.add_text_field("text_few_terms_status", STRING | FAST);
|
|
let score_fieldtype = tantivy::schema::NumericOptions::default().set_fast();
|
|
let score_field = schema_builder.add_u64_field("score", score_fieldtype.clone());
|
|
let score_field_f64 = schema_builder.add_f64_field("score_f64", score_fieldtype.clone());
|
|
let score_field_i64 = schema_builder.add_i64_field("score_i64", score_fieldtype);
|
|
let index = Index::create_from_tempdir(schema_builder.build())?;
|
|
let few_terms_data = ["INFO", "ERROR", "WARN", "DEBUG"];
|
|
// Approximate production log proportions: INFO dominant, WARN and DEBUG occasional, ERROR rare.
|
|
let log_level_distribution = WeightedIndex::new([80u32, 3, 12, 5]).unwrap();
|
|
|
|
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
|
|
|
|
let many_terms_data = (0..150_000)
|
|
.map(|num| format!("author{num}"))
|
|
.collect::<Vec<_>>();
|
|
{
|
|
let mut rng = StdRng::from_seed([1u8; 32]);
|
|
let mut index_writer = index.writer_with_num_threads(1, 200_000_000)?;
|
|
// To make the different test cases comparable we just change one doc to force the
|
|
// cardinality
|
|
if cardinality == Cardinality::OptionalDense {
|
|
index_writer.add_document(doc!())?;
|
|
}
|
|
if cardinality == Cardinality::Multivalued {
|
|
let log_level_sample_a = few_terms_data[log_level_distribution.sample(&mut rng)];
|
|
let log_level_sample_b = few_terms_data[log_level_distribution.sample(&mut rng)];
|
|
index_writer.add_document(doc!(
|
|
json_field => json!({"mixed_type": 10.0}),
|
|
json_field => json!({"mixed_type": 10.0}),
|
|
text_field => "cool",
|
|
text_field => "cool",
|
|
text_field_all_unique_terms => "cool",
|
|
text_field_all_unique_terms => "coolo",
|
|
text_field_many_terms => "cool",
|
|
text_field_many_terms => "cool",
|
|
text_field_few_terms => "cool",
|
|
text_field_few_terms => "cool",
|
|
text_field_few_terms_status => log_level_sample_a,
|
|
text_field_few_terms_status => log_level_sample_b,
|
|
score_field => 1u64,
|
|
score_field => 1u64,
|
|
score_field_f64 => lg_norm.sample(&mut rng),
|
|
score_field_f64 => lg_norm.sample(&mut rng),
|
|
score_field_i64 => 1i64,
|
|
score_field_i64 => 1i64,
|
|
))?;
|
|
}
|
|
let mut doc_with_value = 1_000_000;
|
|
if cardinality == Cardinality::OptionalSparse {
|
|
doc_with_value /= 20;
|
|
}
|
|
let _val_max = 1_000_000.0;
|
|
for _ in 0..doc_with_value {
|
|
let val: f64 = rng.gen_range(0.0..1_000_000.0);
|
|
let json = if rng.gen_bool(0.1) {
|
|
// 10% are numeric values
|
|
json!({ "mixed_type": val })
|
|
} else {
|
|
json!({"mixed_type": many_terms_data.choose(&mut rng).unwrap().to_string()})
|
|
};
|
|
index_writer.add_document(doc!(
|
|
text_field => "cool",
|
|
json_field => json,
|
|
text_field_all_unique_terms => format!("unique_term_{}", rng.gen::<u64>()),
|
|
text_field_many_terms => many_terms_data.choose(&mut rng).unwrap().to_string(),
|
|
text_field_few_terms => few_terms_data.choose(&mut rng).unwrap().to_string(),
|
|
text_field_few_terms_status => few_terms_data[log_level_distribution.sample(&mut rng)],
|
|
score_field => val as u64,
|
|
score_field_f64 => lg_norm.sample(&mut rng),
|
|
score_field_i64 => val as i64,
|
|
))?;
|
|
if cardinality == Cardinality::OptionalSparse {
|
|
for _ in 0..20 {
|
|
index_writer.add_document(doc!(text_field => "cool"))?;
|
|
}
|
|
}
|
|
}
|
|
// writing the segment
|
|
index_writer.commit()?;
|
|
}
|
|
|
|
Ok(index)
|
|
}
|
|
|
|
// Filter aggregation benchmarks
|
|
|
|
fn filter_agg_all_query_count_agg(index: &Index) {
|
|
let agg_req = json!({
|
|
"filtered": {
|
|
"filter": "*",
|
|
"aggs": {
|
|
"count": { "value_count": { "field": "score" } }
|
|
}
|
|
}
|
|
});
|
|
execute_agg(index, agg_req);
|
|
}
|
|
|
|
fn filter_agg_term_query_count_agg(index: &Index) {
|
|
let agg_req = json!({
|
|
"filtered": {
|
|
"filter": "text:cool",
|
|
"aggs": {
|
|
"count": { "value_count": { "field": "score" } }
|
|
}
|
|
}
|
|
});
|
|
execute_agg(index, agg_req);
|
|
}
|
|
|
|
fn filter_agg_all_query_with_sub_aggs(index: &Index) {
|
|
let agg_req = json!({
|
|
"filtered": {
|
|
"filter": "*",
|
|
"aggs": {
|
|
"avg_score": { "avg": { "field": "score" } },
|
|
"stats_score": { "stats": { "field": "score_f64" } },
|
|
"terms_text": {
|
|
"terms": { "field": "text_few_terms" }
|
|
}
|
|
}
|
|
}
|
|
});
|
|
execute_agg(index, agg_req);
|
|
}
|
|
|
|
fn filter_agg_term_query_with_sub_aggs(index: &Index) {
|
|
let agg_req = json!({
|
|
"filtered": {
|
|
"filter": "text:cool",
|
|
"aggs": {
|
|
"avg_score": { "avg": { "field": "score" } },
|
|
"stats_score": { "stats": { "field": "score_f64" } },
|
|
"terms_text": {
|
|
"terms": { "field": "text_few_terms" }
|
|
}
|
|
}
|
|
}
|
|
});
|
|
execute_agg(index, agg_req);
|
|
}
|