add benchmark for boolean query with range sub query (#2787)

Cargo.toml

@@ -184,3 +184,7 @@ harness = false
 [[bench]]
 name = "range_queries"
 harness = false
+
+[[bench]]
+name = "bool_queries_with_range"
+harness = false

benches/bool_queries_with_range.rs

@@ -0,0 +1,288 @@
+use binggan::{black_box, BenchGroup, BenchRunner};
+use rand::prelude::*;
+use rand::rngs::StdRng;
+use rand::SeedableRng;
+use tantivy::collector::{Collector, Count, DocSetCollector, TopDocs};
+use tantivy::query::{Query, QueryParser};
+use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
+use tantivy::{doc, Index, Order, ReloadPolicy, Searcher};
+
+#[derive(Clone)]
+struct BenchIndex {
+    #[allow(dead_code)]
+    index: Index,
+    searcher: Searcher,
+    query_parser: QueryParser,
+}
+
+fn build_shared_indices(num_docs: usize, p_title_a: f32, distribution: &str) -> BenchIndex {
+    // Unified schema
+    let mut schema_builder = Schema::builder();
+    let f_title = schema_builder.add_text_field("title", TEXT);
+    let f_num_rand = schema_builder.add_u64_field("num_rand", INDEXED);
+    let f_num_asc = schema_builder.add_u64_field("num_asc", INDEXED);
+    let f_num_rand_fast = schema_builder.add_u64_field("num_rand_fast", INDEXED | FAST);
+    let f_num_asc_fast = schema_builder.add_u64_field("num_asc_fast", INDEXED | FAST);
+    let schema = schema_builder.build();
+    let index = Index::create_in_ram(schema.clone());
+
+    // Populate index with stable RNG for reproducibility.
+    let mut rng = StdRng::from_seed([7u8; 32]);
+
+    {
+        let mut writer = index.writer_with_num_threads(1, 4_000_000_000).unwrap();
+
+        match distribution {
+            "dense" => {
+                for doc_id in 0..num_docs {
+                    // Always add title to avoid empty documents
+                    let title_token = if rng.gen_bool(p_title_a as f64) {
+                        "a"
+                    } else {
+                        "b"
+                    };
+
+                    let num_rand = rng.gen_range(0u64..1000u64);
+
+                    let num_asc = (doc_id / 10000) as u64;
+
+                    writer
+                        .add_document(doc!(
+                            f_title=>title_token,
+                            f_num_rand=>num_rand,
+                            f_num_asc=>num_asc,
+                            f_num_rand_fast=>num_rand,
+                            f_num_asc_fast=>num_asc,
+                        ))
+                        .unwrap();
+                }
+            }
+            "sparse" => {
+                for doc_id in 0..num_docs {
+                    // Always add title to avoid empty documents
+                    let title_token = if rng.gen_bool(p_title_a as f64) {
+                        "a"
+                    } else {
+                        "b"
+                    };
+
+                    let num_rand = rng.gen_range(0u64..10000000u64);
+
+                    let num_asc = doc_id as u64;
+
+                    writer
+                        .add_document(doc!(
+                            f_title=>title_token,
+                            f_num_rand=>num_rand,
+                            f_num_asc=>num_asc,
+                            f_num_rand_fast=>num_rand,
+                            f_num_asc_fast=>num_asc,
+                        ))
+                        .unwrap();
+                }
+            }
+            _ => {
+                panic!("Unsupported distribution type");
+            }
+        }
+        writer.commit().unwrap();
+    }
+
+    // Prepare reader/searcher once.
+    let reader = index
+        .reader_builder()
+        .reload_policy(ReloadPolicy::Manual)
+        .try_into()
+        .unwrap();
+    let searcher = reader.searcher();
+
+    // Build query parser for title field
+    let qp_title = QueryParser::for_index(&index, vec![f_title]);
+
+    BenchIndex {
+        index,
+        searcher,
+        query_parser: qp_title,
+    }
+}
+
+fn main() {
+    // Prepare corpora with varying scenarios
+    let scenarios = vec![
+        (
+            "dense and 99% a".to_string(),
+            10_000_000,
+            0.99,
+            "dense",
+            0,
+            9,
+        ),
+        (
+            "dense and 99% a".to_string(),
+            10_000_000,
+            0.99,
+            "dense",
+            990,
+            999,
+        ),
+        (
+            "sparse and 99% a".to_string(),
+            10_000_000,
+            0.99,
+            "sparse",
+            0,
+            9,
+        ),
+        (
+            "sparse and 99% a".to_string(),
+            10_000_000,
+            0.99,
+            "sparse",
+            9_999_990,
+            9_999_999,
+        ),
+    ];
+
+    let mut runner = BenchRunner::new();
+    for (scenario_id, n, p_title_a, num_rand_distribution, range_low, range_high) in scenarios {
+        // Build index for this scenario
+        let bench_index = build_shared_indices(n, p_title_a, num_rand_distribution);
+
+        // Create benchmark group
+        let mut group = runner.new_group();
+
+        // Now set the name (this moves scenario_id)
+        group.set_name(scenario_id);
+
+        // Define all four field types
+        let field_names = ["num_rand", "num_asc", "num_rand_fast", "num_asc_fast"];
+
+        // Define the three terms we want to test with
+        let terms = ["a", "b", "z"];
+
+        // Generate all combinations of terms and field names
+        let mut queries = Vec::new();
+        for &term in &terms {
+            for &field_name in &field_names {
+                let query_str = format!(
+                    "{} AND {}:[{} TO {}]",
+                    term, field_name, range_low, range_high
+                );
+                queries.push((query_str, field_name.to_string()));
+            }
+        }
+
+        let query_str = format!(
+            "{}:[{} TO {}] AND {}:[{} TO {}]",
+            "num_rand_fast", range_low, range_high, "num_asc_fast", range_low, range_high
+        );
+        queries.push((query_str, "num_asc_fast".to_string()));
+
+        // Run all benchmark tasks for each query and its corresponding field name
+        for (query_str, field_name) in queries {
+            run_benchmark_tasks(&mut group, &bench_index, &query_str, &field_name);
+        }
+
+        group.run();
+    }
+}
+
+/// Run all benchmark tasks for a given query string and field name
+fn run_benchmark_tasks(
+    bench_group: &mut BenchGroup,
+    bench_index: &BenchIndex,
+    query_str: &str,
+    field_name: &str,
+) {
+    // Test count
+    add_bench_task(bench_group, bench_index, query_str, Count, "count");
+
+    // Test all results
+    add_bench_task(
+        bench_group,
+        bench_index,
+        query_str,
+        DocSetCollector,
+        "all results",
+    );
+
+    // Test top 100 by the field (if it's a FAST field)
+    if field_name.ends_with("_fast") {
+        // Ascending order
+        {
+            let collector_name = format!("top100_by_{}_asc", field_name);
+            let field_name_owned = field_name.to_string();
+            add_bench_task(
+                bench_group,
+                bench_index,
+                query_str,
+                TopDocs::with_limit(100).order_by_fast_field::<u64>(field_name_owned, Order::Asc),
+                &collector_name,
+            );
+        }
+
+        // Descending order
+        {
+            let collector_name = format!("top100_by_{}_desc", field_name);
+            let field_name_owned = field_name.to_string();
+            add_bench_task(
+                bench_group,
+                bench_index,
+                query_str,
+                TopDocs::with_limit(100).order_by_fast_field::<u64>(field_name_owned, Order::Desc),
+                &collector_name,
+            );
+        }
+    }
+}
+
+fn add_bench_task<C: Collector + 'static>(
+    bench_group: &mut BenchGroup,
+    bench_index: &BenchIndex,
+    query_str: &str,
+    collector: C,
+    collector_name: &str,
+) {
+    let task_name = format!("{}_{}", query_str.replace(" ", "_"), collector_name);
+    let query = bench_index.query_parser.parse_query(query_str).unwrap();
+    let search_task = SearchTask {
+        searcher: bench_index.searcher.clone(),
+        collector,
+        query,
+    };
+    bench_group.register(task_name, move |_| black_box(search_task.run()));
+}
+
+struct SearchTask<C: Collector> {
+    searcher: Searcher,
+    collector: C,
+    query: Box<dyn Query>,
+}
+
+impl<C: Collector> SearchTask<C> {
+    #[inline(never)]
+    pub fn run(&self) -> usize {
+        let result = self.searcher.search(&self.query, &self.collector).unwrap();
+        if let Some(count) = (&result as &dyn std::any::Any).downcast_ref::<usize>() {
+            *count
+        } else if let Some(top_docs) = (&result as &dyn std::any::Any)
+            .downcast_ref::<Vec<(Option<u64>, tantivy::DocAddress)>>()
+        {
+            top_docs.len()
+        } else if let Some(top_docs) =
+            (&result as &dyn std::any::Any).downcast_ref::<Vec<(u64, tantivy::DocAddress)>>()
+        {
+            top_docs.len()
+        } else if let Some(doc_set) = (&result as &dyn std::any::Any)
+            .downcast_ref::<std::collections::HashSet<tantivy::DocAddress>>()
+        {
+            doc_set.len()
+        } else {
+            eprintln!(
+                "Unknown collector result type: {:?}",
+                std::any::type_name::<C::Fruit>()
+            );
+            0
+        }
+    }
+}