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add and/or queries benchmark (#2701)
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224
benches/and_or_queries.rs
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224
benches/and_or_queries.rs
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// Benchmarks boolean conjunction queries using binggan.
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//
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// What’s measured:
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// - Or and And queries with varying selectivity (only `Term` queries for now on leafs)
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// - Nested AND/OR combinations (on multiple fields)
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// - No-scoring path using the Count collector (focus on iterator/skip performance)
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// - Top-K retrieval (k=10) using the TopDocs collector
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//
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// Corpus model:
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// - Synthetic docs; each token a/b/c is independently included per doc
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// - If none of a/b/c are included, emit a neutral filler token to keep doc length similar
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//
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// Notes:
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// - After optimization, when scoring is disabled Tantivy reads doc-only postings
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// (IndexRecordOption::Basic), avoiding frequency decoding overhead.
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// - This bench isolates boolean iteration speed and intersection/union cost.
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// - Use `cargo bench --bench boolean_conjunction` to run.
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use binggan::{black_box, BenchRunner};
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use rand::prelude::*;
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use rand::rngs::StdRng;
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use rand::SeedableRng;
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use tantivy::collector::{Count, TopDocs};
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use tantivy::query::QueryParser;
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use tantivy::schema::{Schema, TEXT};
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use tantivy::{doc, Index, ReloadPolicy, Searcher};
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#[derive(Clone)]
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struct BenchIndex {
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#[allow(dead_code)]
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index: Index,
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searcher: Searcher,
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query_parser: QueryParser,
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}
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impl BenchIndex {
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#[inline(always)]
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fn count_query(&self, query_str: &str) -> usize {
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let query = self.query_parser.parse_query(query_str).unwrap();
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self.searcher.search(&query, &Count).unwrap()
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}
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#[inline(always)]
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fn topk_len(&self, query_str: &str, k: usize) -> usize {
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let query = self.query_parser.parse_query(query_str).unwrap();
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self.searcher
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.search(&query, &TopDocs::with_limit(k))
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.unwrap()
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.len()
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}
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}
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/// Build a single index containing both fields (title, body) and
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/// return two BenchIndex views:
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/// - single_field: QueryParser defaults to only "body"
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/// - multi_field: QueryParser defaults to ["title", "body"]
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fn build_shared_indices(num_docs: usize, p_a: f32, p_b: f32, p_c: f32) -> (BenchIndex, BenchIndex) {
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// Unified schema (two text fields)
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let mut schema_builder = Schema::builder();
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let f_title = schema_builder.add_text_field("title", TEXT);
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let f_body = schema_builder.add_text_field("body", TEXT);
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let schema = schema_builder.build();
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let index = Index::create_in_ram(schema.clone());
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// Populate index with stable RNG for reproducibility.
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let mut rng = StdRng::from_seed([7u8; 32]);
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// Populate: spread each present token 90/10 to body/title
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{
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let mut writer = index.writer(500_000_000).unwrap();
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for _ in 0..num_docs {
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let has_a = rng.gen_bool(p_a as f64);
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let has_b = rng.gen_bool(p_b as f64);
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let has_c = rng.gen_bool(p_c as f64);
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let mut title_tokens: Vec<&str> = Vec::new();
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let mut body_tokens: Vec<&str> = Vec::new();
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if has_a {
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if rng.gen_bool(0.1) {
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title_tokens.push("a");
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} else {
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body_tokens.push("a");
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}
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}
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if has_b {
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if rng.gen_bool(0.1) {
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title_tokens.push("b");
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} else {
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body_tokens.push("b");
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}
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}
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if has_c {
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if rng.gen_bool(0.1) {
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title_tokens.push("c");
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} else {
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body_tokens.push("c");
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}
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}
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if title_tokens.is_empty() && body_tokens.is_empty() {
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body_tokens.push("z");
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}
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writer
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.add_document(doc!(
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f_title=>title_tokens.join(" "),
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f_body=>body_tokens.join(" ")
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))
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.unwrap();
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}
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writer.commit().unwrap();
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}
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// Prepare reader/searcher once.
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let reader = index
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.reader_builder()
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.reload_policy(ReloadPolicy::Manual)
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.try_into()
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.unwrap();
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let searcher = reader.searcher();
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// Build two query parsers with different default fields.
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let qp_single = QueryParser::for_index(&index, vec![f_body]);
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let qp_multi = QueryParser::for_index(&index, vec![f_title, f_body]);
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let single_view = BenchIndex {
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index: index.clone(),
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searcher: searcher.clone(),
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query_parser: qp_single,
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};
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let multi_view = BenchIndex {
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index,
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searcher,
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query_parser: qp_multi,
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};
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(single_view, multi_view)
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}
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fn main() {
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// Prepare corpora with varying selectivity. Build one index per corpus
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// and derive two views (single-field vs multi-field) from it.
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let scenarios = vec![
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(
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"N=1M, p(a)=5%, p(b)=1%, p(c)=15%".to_string(),
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1_000_000,
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0.05,
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0.01,
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0.15,
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),
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(
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"N=1M, p(a)=1%, p(b)=1%, p(c)=15%".to_string(),
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1_000_000,
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0.01,
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0.01,
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0.15,
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),
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];
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let mut runner = BenchRunner::new();
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for (label, n, pa, pb, pc) in scenarios {
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let (single_view, multi_view) = build_shared_indices(n, pa, pb, pc);
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// Single-field group: default field is body only
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{
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let mut group = runner.new_group();
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group.set_name(format!("single_field — {}", label));
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group.register_with_input("+a_+b_count", &single_view, |benv: &BenchIndex| {
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black_box(benv.count_query("+a +b"))
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});
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group.register_with_input("+a_+b_+c_count", &single_view, |benv: &BenchIndex| {
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black_box(benv.count_query("+a +b +c"))
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});
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group.register_with_input("+a_+b_top10", &single_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("+a +b", 10))
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});
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group.register_with_input("+a_+b_+c_top10", &single_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("+a +b +c", 10))
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});
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// OR queries
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group.register_with_input("a_OR_b_count", &single_view, |benv: &BenchIndex| {
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black_box(benv.count_query("a OR b"))
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});
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group.register_with_input("a_OR_b_OR_c_count", &single_view, |benv: &BenchIndex| {
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black_box(benv.count_query("a OR b OR c"))
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});
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group.register_with_input("a_OR_b_top10", &single_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("a OR b", 10))
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});
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group.register_with_input("a_OR_b_OR_c_top10", &single_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("a OR b OR c", 10))
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});
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group.run();
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}
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// Multi-field group: default fields are [title, body]
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{
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let mut group = runner.new_group();
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group.set_name(format!("multi_field — {}", label));
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group.register_with_input("+a_+b_count", &multi_view, |benv: &BenchIndex| {
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black_box(benv.count_query("+a +b"))
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});
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group.register_with_input("+a_+b_+c_count", &multi_view, |benv: &BenchIndex| {
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black_box(benv.count_query("+a +b +c"))
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});
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group.register_with_input("+a_+b_top10", &multi_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("+a +b", 10))
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});
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group.register_with_input("+a_+b_+c_top10", &multi_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("+a +b +c", 10))
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});
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// OR queries
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group.register_with_input("a_OR_b_count", &multi_view, |benv: &BenchIndex| {
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black_box(benv.count_query("a OR b"))
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});
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group.register_with_input("a_OR_b_OR_c_count", &multi_view, |benv: &BenchIndex| {
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black_box(benv.count_query("a OR b OR c"))
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});
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group.register_with_input("a_OR_b_top10", &multi_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("a OR b", 10))
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});
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group.register_with_input("a_OR_b_OR_c_top10", &multi_view, |benv: &BenchIndex| {
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black_box(benv.topk_len("a OR b OR c", 10))
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});
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group.run();
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}
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}
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}
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