simplify fetch block in column_block_accessor

remove clone
move data in term req, single doc opt for stats

CHANGELOG.md

@@ -14,6 +14,18 @@ Tantivy 0.25
 - Support mixed field types in query parser [#2676](https://github.com/quickwit-oss/tantivy/pull/2676)(@trinity-1686a)
 - Add per-field size details [#2679](https://github.com/quickwit-oss/tantivy/pull/2679)(@fulmicoton)
 
+Tantivy 0.24.2
+================================
+- Fix TopNComputer for reverse order. [#2672](https://github.com/quickwit-oss/tantivy/pull/2672)(@stuhood @PSeitz) 
+
+Affected queries are [order_by_fast_field](https://docs.rs/tantivy/latest/tantivy/collector/struct.TopDocs.html#method.order_by_fast_field) and
+[order_by_u64_field](https://docs.rs/tantivy/latest/tantivy/collector/struct.TopDocs.html#method.order_by_u64_field)
+for `Order::Asc`
+
+Tantivy 0.24.1
+================================
+- Fix: bump required rust version to 1.81
+  
 Tantivy 0.24
 ================================
 Tantivy 0.24 will be backwards compatible with indices created with v0.22 and v0.21. The new minimum rust version will be 1.75. Tantivy 0.23 will be skipped.
@@ -66,7 +78,7 @@ This will slightly increase space and access time. [#2439](https://github.com/qu
 
 - **Store DateTime as nanoseconds in doc store** DateTime in the doc store was truncated to microseconds previously. This removes this truncation, while still keeping backwards compatibility. [#2486](https://github.com/quickwit-oss/tantivy/pull/2486)(@PSeitz)
 
-- **Performace/Memory**
+- **Performance/Memory**
     - lift clauses in LogicalAst for optimized ast during execution [#2449](https://github.com/quickwit-oss/tantivy/pull/2449)(@PSeitz)
     - Use Vec instead of BTreeMap to back OwnedValue object [#2364](https://github.com/quickwit-oss/tantivy/pull/2364)(@fulmicoton)
     - Replace TantivyDocument with CompactDoc. CompactDoc is much smaller and provides similar performance. [#2402](https://github.com/quickwit-oss/tantivy/pull/2402)(@PSeitz)
@@ -96,6 +108,14 @@ This will slightly increase space and access time. [#2439](https://github.com/qu
 - Fix trait bound of StoreReader::iter [#2360](https://github.com/quickwit-oss/tantivy/pull/2360)(@adamreichold)
 - remove read_postings_no_deletes [#2526](https://github.com/quickwit-oss/tantivy/pull/2526)(@PSeitz)
 
+Tantivy 0.22.1
+================================
+- Fix TopNComputer for reverse order. [#2672](https://github.com/quickwit-oss/tantivy/pull/2672)(@stuhood @PSeitz) 
+
+Affected queries are [order_by_fast_field](https://docs.rs/tantivy/latest/tantivy/collector/struct.TopDocs.html#method.order_by_fast_field) and
+[order_by_u64_field](https://docs.rs/tantivy/latest/tantivy/collector/struct.TopDocs.html#method.order_by_u64_field)
+for `Order::Asc`
+
 Tantivy 0.22
 ================================
 

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "tantivy"
-version = "0.25.0"
+version = "0.26.0"
 authors = ["Paul Masurel <paul.masurel@gmail.com>"]
 license = "MIT"
 categories = ["database-implementations", "data-structures"]
@@ -69,6 +69,7 @@ hyperloglogplus = { version = "0.4.1", features = ["const-loop"] }
 futures-util = { version = "0.3.28", optional = true }
 futures-channel = { version = "0.3.28", optional = true }
 fnv = "1.0.7"
+typetag = "0.2.21"
 
 [target.'cfg(windows)'.dependencies]
 winapi = "0.3.9"
@@ -87,7 +88,7 @@ more-asserts = "0.3.1"
 rand_distr = "0.4.3"
 time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
 postcard = { version = "1.0.4", features = [
-  "use-std",
+    "use-std",
 ], default-features = false }
 
 [target.'cfg(not(windows))'.dev-dependencies]
@@ -167,3 +168,11 @@ harness = false
 [[bench]]
 name = "agg_bench"
 harness = false
+
+[[bench]]
+name = "exists_json"
+harness = false
+
+[[bench]]
+name = "and_or_queries"
+harness = false

README.md

@@ -23,8 +23,6 @@ performance for different types of queries/collections.
 
 Your mileage WILL vary depending on the nature of queries and their load.
 
-<img src="doc/assets/images/searchbenchmark.png">
-
 Details about the benchmark can be found at this [repository](https://github.com/quickwit-oss/search-benchmark-game).
 
 ## Features
@@ -125,6 +123,7 @@ You can also find other bindings on [GitHub](https://github.com/search?q=tantivy
 - [seshat](https://github.com/matrix-org/seshat/): A matrix message database/indexer
 - [tantiny](https://github.com/baygeldin/tantiny): Tiny full-text search for Ruby
 - [lnx](https://github.com/lnx-search/lnx): adaptable, typo tolerant search engine with a REST API
+- [Bichon](https://github.com/rustmailer/bichon): A lightweight, high-performance Rust email archiver with WebUI
 - and [more](https://github.com/search?q=tantivy)!
 
 ### On average, how much faster is Tantivy compared to Lucene?

TODO.txt

@@ -10,7 +10,7 @@ rename FastFieldReaders::open to load
 remove fast field reader
 
 find a way to unify the two DateTime.
-readd type check in the filter wrapper
+re-add type check in the filter wrapper
 
 add unit test on columnar list columns.
 

benches/agg_bench.rs

@@ -1,5 +1,6 @@
 use binggan::plugins::PeakMemAllocPlugin;
 use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
+use rand::distributions::WeightedIndex;
 use rand::prelude::SliceRandom;
 use rand::rngs::StdRng;
 use rand::{Rng, SeedableRng};
@@ -53,26 +54,41 @@ fn bench_agg(mut group: InputGroup<Index>) {
     register!(group, stats_f64);
     register!(group, extendedstats_f64);
     register!(group, percentiles_f64);
-    register!(group, terms_few);
-    register!(group, terms_many);
+    register!(group, terms_7);
+    register!(group, terms_all_unique);
+    register!(group, terms_150_000);
     register!(group, terms_many_top_1000);
     register!(group, terms_many_order_by_term);
     register!(group, terms_many_with_top_hits);
+    register!(group, terms_all_unique_with_avg_sub_agg);
     register!(group, terms_many_with_avg_sub_agg);
+    register!(group, terms_status_with_avg_sub_agg);
+    register!(group, terms_status_with_histogram);
+    register!(group, terms_zipf_1000);
+    register!(group, terms_zipf_1000_with_histogram);
+    register!(group, terms_zipf_1000_with_avg_sub_agg);
+
     register!(group, terms_many_json_mixed_type_with_avg_sub_agg);
 
     register!(group, cardinality_agg);
-    register!(group, terms_few_with_cardinality_agg);
+    register!(group, terms_status_with_cardinality_agg);
 
     register!(group, range_agg);
     register!(group, range_agg_with_avg_sub_agg);
-    register!(group, range_agg_with_term_agg_few);
+    register!(group, range_agg_with_term_agg_status);
     register!(group, range_agg_with_term_agg_many);
     register!(group, histogram);
     register!(group, histogram_hard_bounds);
     register!(group, histogram_with_avg_sub_agg);
+    register!(group, histogram_with_term_agg_status);
     register!(group, avg_and_range_with_avg_sub_agg);
 
+    // Filter aggregation benchmarks
+    register!(group, filter_agg_all_query_count_agg);
+    register!(group, filter_agg_term_query_count_agg);
+    register!(group, filter_agg_all_query_with_sub_aggs);
+    register!(group, filter_agg_term_query_with_sub_aggs);
+
     group.run();
 }
 
@@ -123,12 +139,12 @@ fn extendedstats_f64(index: &Index) {
 }
 fn percentiles_f64(index: &Index) {
     let agg_req = json!({
-      "mypercentiles": {
-        "percentiles": {
-          "field": "score_f64",
-          "percents": [ 95, 99, 99.9 ]
+        "mypercentiles": {
+            "percentiles": {
+                "field": "score_f64",
+                "percents": [ 95, 99, 99.9 ]
+            }
         }
-      }
     });
     execute_agg(index, agg_req);
 }
@@ -143,10 +159,10 @@ fn cardinality_agg(index: &Index) {
     });
     execute_agg(index, agg_req);
 }
-fn terms_few_with_cardinality_agg(index: &Index) {
+fn terms_status_with_cardinality_agg(index: &Index) {
     let agg_req = json!({
         "my_texts": {
-            "terms": { "field": "text_few_terms" },
+            "terms": { "field": "text_few_terms_status" },
             "aggs": {
                 "cardinality": {
                     "cardinality": {
@@ -159,13 +175,20 @@ fn terms_few_with_cardinality_agg(index: &Index) {
     execute_agg(index, agg_req);
 }
 
-fn terms_few(index: &Index) {
+fn terms_7(index: &Index) {
     let agg_req = json!({
-        "my_texts": { "terms": { "field": "text_few_terms" } },
+        "my_texts": { "terms": { "field": "text_few_terms_status" } },
     });
     execute_agg(index, agg_req);
 }
-fn terms_many(index: &Index) {
+fn terms_all_unique(index: &Index) {
+    let agg_req = json!({
+        "my_texts": { "terms": { "field": "text_all_unique_terms" } },
+    });
+    execute_agg(index, agg_req);
+}
+
+fn terms_150_000(index: &Index) {
     let agg_req = json!({
         "my_texts": { "terms": { "field": "text_many_terms" } },
     });
@@ -213,6 +236,72 @@ fn terms_many_with_avg_sub_agg(index: &Index) {
     });
     execute_agg(index, agg_req);
 }
+fn terms_all_unique_with_avg_sub_agg(index: &Index) {
+    let agg_req = json!({
+        "my_texts": {
+            "terms": { "field": "text_all_unique_terms" },
+            "aggs": {
+                "average_f64": { "avg": { "field": "score_f64" } }
+            }
+        },
+    });
+    execute_agg(index, agg_req);
+}
+fn terms_status_with_histogram(index: &Index) {
+    let agg_req = json!({
+        "my_texts": {
+            "terms": { "field": "text_few_terms_status" },
+            "aggs": {
+                "histo": {"histogram": { "field": "score_f64", "interval": 10 }}
+            }
+        }
+    });
+    execute_agg(index, agg_req);
+}
+
+fn terms_zipf_1000_with_histogram(index: &Index) {
+    let agg_req = json!({
+        "my_texts": {
+            "terms": { "field": "text_1000_terms_zipf" },
+            "aggs": {
+                "histo": {"histogram": { "field": "score_f64", "interval": 10 }}
+            }
+        }
+    });
+    execute_agg(index, agg_req);
+}
+
+fn terms_status_with_avg_sub_agg(index: &Index) {
+    let agg_req = json!({
+        "my_texts": {
+            "terms": { "field": "text_few_terms_status" },
+            "aggs": {
+                "average_f64": { "avg": { "field": "score_f64" } }
+            }
+        },
+    });
+    execute_agg(index, agg_req);
+}
+
+fn terms_zipf_1000_with_avg_sub_agg(index: &Index) {
+    let agg_req = json!({
+        "my_texts": {
+            "terms": { "field": "text_1000_terms_zipf" },
+            "aggs": {
+                "average_f64": { "avg": { "field": "score_f64" } }
+            }
+        },
+    });
+    execute_agg(index, agg_req);
+}
+
+fn terms_zipf_1000(index: &Index) {
+    let agg_req = json!({
+        "my_texts": { "terms": { "field": "text_1000_terms_zipf" } },
+    });
+    execute_agg(index, agg_req);
+}
+
 fn terms_many_json_mixed_type_with_avg_sub_agg(index: &Index) {
     let agg_req = json!({
         "my_texts": {
@@ -268,7 +357,7 @@ fn range_agg_with_avg_sub_agg(index: &Index) {
     execute_agg(index, agg_req);
 }
 
-fn range_agg_with_term_agg_few(index: &Index) {
+fn range_agg_with_term_agg_status(index: &Index) {
     let agg_req = json!({
         "rangef64": {
             "range": {
@@ -283,7 +372,7 @@ fn range_agg_with_term_agg_few(index: &Index) {
                 ]
             },
             "aggs": {
-                "my_texts": { "terms": { "field": "text_few_terms" } },
+                "my_texts": { "terms": { "field": "text_few_terms_status" } },
             }
         },
     });
@@ -339,6 +428,17 @@ fn histogram_with_avg_sub_agg(index: &Index) {
     });
     execute_agg(index, agg_req);
 }
+fn histogram_with_term_agg_status(index: &Index) {
+    let agg_req = json!({
+        "rangef64": {
+            "histogram": { "field": "score_f64", "interval": 10 },
+            "aggs": {
+                "my_texts": { "terms": { "field": "text_few_terms_status" } }
+            }
+        }
+    });
+    execute_agg(index, agg_req);
+}
 fn avg_and_range_with_avg_sub_agg(index: &Index) {
     let agg_req = json!({
         "rangef64": {
@@ -378,6 +478,13 @@ fn get_collector(agg_req: Aggregations) -> AggregationCollector {
 }
 
 fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
+    // Flag to use existing index
+    let reuse_index = std::env::var("REUSE_AGG_BENCH_INDEX").is_ok();
+    if reuse_index && std::path::Path::new("agg_bench").exists() {
+        return Index::open_in_dir("agg_bench");
+    }
+    // crreate dir
+    std::fs::create_dir_all("agg_bench")?;
     let mut schema_builder = Schema::builder();
     let text_fieldtype = tantivy::schema::TextOptions::default()
         .set_indexing_options(
@@ -386,20 +493,47 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
         .set_stored();
     let text_field = schema_builder.add_text_field("text", text_fieldtype);
     let json_field = schema_builder.add_json_field("json", FAST);
+    let text_field_all_unique_terms =
+        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_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 text_field_1000_terms_zipf =
+        schema_builder.add_text_field("text_1000_terms_zipf", 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"];
+    // use tmp dir
+    let index = if reuse_index {
+        Index::create_in_dir("agg_bench", schema_builder.build())?
+    } else {
+        Index::create_from_tempdir(schema_builder.build())?
+    };
+    // Approximate log proportions
+    let status_field_data = [
+        ("INFO", 8000),
+        ("ERROR", 300),
+        ("WARN", 1200),
+        ("DEBUG", 500),
+        ("OK", 500),
+        ("CRITICAL", 20),
+        ("EMERGENCY", 1),
+    ];
+    let log_level_distribution =
+        WeightedIndex::new(status_field_data.iter().map(|item| item.1)).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<_>>();
+
+    // Prepare 1000 unique terms sampled using a Zipf distribution.
+    // Exponent ~1.1 approximates top-20 terms covering around ~20%.
+    let terms_1000: Vec<String> = (1..=1000).map(|i| format!("term_{i}")).collect();
+    let zipf_1000 = rand_distr::Zipf::new(1000, 1.1f64).unwrap();
+
     {
         let mut rng = StdRng::from_seed([1u8; 32]);
         let mut index_writer = index.writer_with_num_threads(1, 200_000_000)?;
@@ -409,15 +543,25 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
             index_writer.add_document(doc!())?;
         }
         if cardinality == Cardinality::Multivalued {
+            let log_level_sample_a = status_field_data[log_level_distribution.sample(&mut rng)].0;
+            let log_level_sample_b = status_field_data[log_level_distribution.sample(&mut rng)].0;
+            let idx_a = zipf_1000.sample(&mut rng) as usize - 1;
+            let idx_b = zipf_1000.sample(&mut rng) as usize - 1;
+            let term_1000_a = &terms_1000[idx_a];
+            let term_1000_b = &terms_1000[idx_b];
             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,
+                text_field_1000_terms_zipf => term_1000_a.as_str(),
+                text_field_1000_terms_zipf => term_1000_b.as_str(),
                 score_field => 1u64,
                 score_field => 1u64,
                 score_field_f64 => lg_norm.sample(&mut rng),
@@ -442,8 +586,10 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
             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 => status_field_data[log_level_distribution.sample(&mut rng)].0,
+                text_field_1000_terms_zipf => terms_1000[zipf_1000.sample(&mut rng) as usize - 1].as_str(),
                 score_field => val as u64,
                 score_field_f64 => lg_norm.sample(&mut rng),
                 score_field_i64 => val as i64,
@@ -460,3 +606,61 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
 
     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_status" }
+                }
+            }
+        }
+    });
+    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_status" }
+                }
+            }
+        }
+    });
+    execute_agg(index, agg_req);
+}

benches/and_or_queries.rs

@@ -0,0 +1,218 @@
+// Benchmarks boolean conjunction queries using binggan.
+//
+// What’s measured:
+// - Or and And queries with varying selectivity (only `Term` queries for now on leafs)
+// - Nested AND/OR combinations (on multiple fields)
+// - No-scoring path using the Count collector (focus on iterator/skip performance)
+// - Top-K retrieval (k=10) using the TopDocs collector
+//
+// Corpus model:
+// - Synthetic docs; each token a/b/c is independently included per doc
+// - If none of a/b/c are included, emit a neutral filler token to keep doc length similar
+//
+// Notes:
+// - After optimization, when scoring is disabled Tantivy reads doc-only postings
+//   (IndexRecordOption::Basic), avoiding frequency decoding overhead.
+// - This bench isolates boolean iteration speed and intersection/union cost.
+// - Use `cargo bench --bench boolean_conjunction` to run.
+
+use binggan::{black_box, BenchGroup, BenchRunner};
+use rand::prelude::*;
+use rand::rngs::StdRng;
+use rand::SeedableRng;
+use tantivy::collector::sort_key::SortByStaticFastValue;
+use tantivy::collector::{Collector, Count, TopDocs};
+use tantivy::query::{Query, QueryParser};
+use tantivy::schema::{Schema, FAST, TEXT};
+use tantivy::{doc, Index, Order, ReloadPolicy, Searcher};
+
+#[derive(Clone)]
+struct BenchIndex {
+    #[allow(dead_code)]
+    index: Index,
+    searcher: Searcher,
+    query_parser: QueryParser,
+}
+
+/// Build a single index containing both fields (title, body) and
+/// return two BenchIndex views:
+/// - single_field: QueryParser defaults to only "body"
+/// - multi_field:  QueryParser defaults to ["title", "body"]
+fn build_shared_indices(num_docs: usize, p_a: f32, p_b: f32, p_c: f32) -> (BenchIndex, BenchIndex) {
+    // Unified schema (two text fields)
+    let mut schema_builder = Schema::builder();
+    let f_title = schema_builder.add_text_field("title", TEXT);
+    let f_body = schema_builder.add_text_field("body", TEXT);
+    let f_score = schema_builder.add_u64_field("score", FAST);
+    let f_score2 = schema_builder.add_u64_field("score2", 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]);
+
+    // Populate: spread each present token 90/10 to body/title
+    {
+        let mut writer = index.writer_with_num_threads(1, 500_000_000).unwrap();
+        for _ in 0..num_docs {
+            let has_a = rng.gen_bool(p_a as f64);
+            let has_b = rng.gen_bool(p_b as f64);
+            let has_c = rng.gen_bool(p_c as f64);
+            let score = rng.gen_range(0u64..100u64);
+            let score2 = rng.gen_range(0u64..100_000u64);
+            let mut title_tokens: Vec<&str> = Vec::new();
+            let mut body_tokens: Vec<&str> = Vec::new();
+            if has_a {
+                if rng.gen_bool(0.1) {
+                    title_tokens.push("a");
+                } else {
+                    body_tokens.push("a");
+                }
+            }
+            if has_b {
+                if rng.gen_bool(0.1) {
+                    title_tokens.push("b");
+                } else {
+                    body_tokens.push("b");
+                }
+            }
+            if has_c {
+                if rng.gen_bool(0.1) {
+                    title_tokens.push("c");
+                } else {
+                    body_tokens.push("c");
+                }
+            }
+            if title_tokens.is_empty() && body_tokens.is_empty() {
+                body_tokens.push("z");
+            }
+            writer
+                .add_document(doc!(
+                    f_title=>title_tokens.join(" "),
+                    f_body=>body_tokens.join(" "),
+                    f_score=>score,
+                    f_score2=>score2,
+                ))
+                .unwrap();
+        }
+        writer.commit().unwrap();
+    }
+
+    // Prepare reader/searcher once.
+    let reader = index
+        .reader_builder()
+        .reload_policy(ReloadPolicy::Manual)
+        .try_into()
+        .unwrap();
+    let searcher = reader.searcher();
+
+    // Build two query parsers with different default fields.
+    let qp_single = QueryParser::for_index(&index, vec![f_body]);
+    let qp_multi = QueryParser::for_index(&index, vec![f_title, f_body]);
+
+    let single_view = BenchIndex {
+        index: index.clone(),
+        searcher: searcher.clone(),
+        query_parser: qp_single,
+    };
+    let multi_view = BenchIndex {
+        index,
+        searcher,
+        query_parser: qp_multi,
+    };
+    (single_view, multi_view)
+}
+
+fn main() {
+    // Prepare corpora with varying selectivity. Build one index per corpus
+    // and derive two views (single-field vs multi-field) from it.
+    let scenarios = vec![
+        (
+            "N=1M, p(a)=5%, p(b)=1%, p(c)=15%".to_string(),
+            1_000_000,
+            0.05,
+            0.01,
+            0.15,
+        ),
+        (
+            "N=1M, p(a)=1%, p(b)=1%, p(c)=15%".to_string(),
+            1_000_000,
+            0.01,
+            0.01,
+            0.15,
+        ),
+    ];
+
+    let queries = &["a", "+a +b", "+a +b +c", "a OR b", "a OR b OR c"];
+
+    let mut runner = BenchRunner::new();
+    for (label, n, pa, pb, pc) in scenarios {
+        let (single_view, multi_view) = build_shared_indices(n, pa, pb, pc);
+
+        for (view_name, bench_index) in [("single_field", single_view), ("multi_field", multi_view)]
+        {
+            // Single-field group: default field is body only
+            let mut group = runner.new_group();
+            group.set_name(format!("{} — {}", view_name, label));
+            for query_str in queries {
+                add_bench_task(&mut group, &bench_index, query_str, Count, "count");
+                add_bench_task(
+                    &mut group,
+                    &bench_index,
+                    query_str,
+                    TopDocs::with_limit(10).order_by_score(),
+                    "top10",
+                );
+                add_bench_task(
+                    &mut group,
+                    &bench_index,
+                    query_str,
+                    TopDocs::with_limit(10).order_by_fast_field::<u64>("score", Order::Asc),
+                    "top10_by_ff",
+                );
+                add_bench_task(
+                    &mut group,
+                    &bench_index,
+                    query_str,
+                    TopDocs::with_limit(10).order_by((
+                        SortByStaticFastValue::<u64>::for_field("score"),
+                        SortByStaticFastValue::<u64>::for_field("score2"),
+                    )),
+                    "top10_by_2ff",
+                );
+            }
+            group.run();
+        }
+    }
+}
+
+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 {
+        self.searcher.search(&self.query, &self.collector).unwrap();
+        1
+    }
+}

benches/exists_json.rs

@@ -0,0 +1,69 @@
+use binggan::plugins::PeakMemAllocPlugin;
+use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
+use serde_json::json;
+use tantivy::collector::Count;
+use tantivy::query::ExistsQuery;
+use tantivy::schema::{Schema, FAST, TEXT};
+use tantivy::{doc, Index};
+
+#[global_allocator]
+pub static GLOBAL: &PeakMemAlloc<std::alloc::System> = &INSTRUMENTED_SYSTEM;
+
+fn main() {
+    let doc_count: usize = 500_000;
+    let subfield_counts: &[usize] = &[1, 2, 3, 4, 5, 6, 7, 8, 16, 256, 4096, 65536, 262144];
+
+    let indices: Vec<(String, Index)> = subfield_counts
+        .iter()
+        .map(|&sub_fields| {
+            (
+                format!("subfields={sub_fields}"),
+                build_index_with_json_subfields(doc_count, sub_fields),
+            )
+        })
+        .collect();
+
+    let mut group = InputGroup::new_with_inputs(indices);
+    group.add_plugin(PeakMemAllocPlugin::new(GLOBAL));
+
+    group.config().num_iter_group = Some(1);
+    group.config().num_iter_bench = Some(1);
+    group.register("exists_json", exists_json_union);
+
+    group.run();
+}
+
+fn exists_json_union(index: &Index) {
+    let reader = index.reader().expect("reader");
+    let searcher = reader.searcher();
+    let query = ExistsQuery::new("json".to_string(), true);
+    let count = searcher.search(&query, &Count).expect("exists search");
+    // Prevents optimizer from eliding the search
+    black_box(count);
+}
+
+fn build_index_with_json_subfields(num_docs: usize, num_subfields: usize) -> Index {
+    // Schema: single JSON field stored as FAST to support ExistsQuery.
+    let mut schema_builder = Schema::builder();
+    let json_field = schema_builder.add_json_field("json", TEXT | FAST);
+    let schema = schema_builder.build();
+
+    let index = Index::create_from_tempdir(schema).expect("create index");
+    {
+        let mut index_writer = index
+            .writer_with_num_threads(1, 200_000_000)
+            .expect("writer");
+        for i in 0..num_docs {
+            let sub = i % num_subfields;
+            // Only one subpath set per document; rotate subpaths so that
+            // no single subpath is full, but the union covers all docs.
+            let v = json!({ format!("field_{sub}"): i as u64 });
+            index_writer
+                .add_document(doc!(json_field => v))
+                .expect("add_document");
+        }
+        index_writer.commit().expect("commit");
+    }
+
+    index
+}

bitpacker/src/bitpacker.rs

@@ -48,7 +48,7 @@ impl BitPacker {
 
     pub fn flush<TWrite: io::Write + ?Sized>(&mut self, output: &mut TWrite) -> io::Result<()> {
         if self.mini_buffer_written > 0 {
-            let num_bytes = (self.mini_buffer_written + 7) / 8;
+            let num_bytes = self.mini_buffer_written.div_ceil(8);
             let bytes = self.mini_buffer.to_le_bytes();
             output.write_all(&bytes[..num_bytes])?;
             self.mini_buffer_written = 0;
@@ -138,7 +138,7 @@ impl BitUnpacker {
 
         // We use `usize` here to avoid overflow issues.
         let end_bit_read = (end_idx as usize) * self.num_bits;
-        let end_byte_read = (end_bit_read + 7) / 8;
+        let end_byte_read = end_bit_read.div_ceil(8);
         assert!(
             end_byte_read <= data.len(),
             "Requested index is out of bounds."
@@ -258,7 +258,7 @@ mod test {
             bitpacker.write(val, num_bits, &mut data).unwrap();
         }
         bitpacker.close(&mut data).unwrap();
-        assert_eq!(data.len(), ((num_bits as usize) * len + 7) / 8);
+        assert_eq!(data.len(), ((num_bits as usize) * len).div_ceil(8));
         let bitunpacker = BitUnpacker::new(num_bits);
         (bitunpacker, vals, data)
     }
@@ -304,7 +304,7 @@ mod test {
             bitpacker.write(val, num_bits, &mut buffer).unwrap();
         }
         bitpacker.flush(&mut buffer).unwrap();
-        assert_eq!(buffer.len(), (vals.len() * num_bits as usize + 7) / 8);
+        assert_eq!(buffer.len(), (vals.len() * num_bits as usize).div_ceil(8));
         let bitunpacker = BitUnpacker::new(num_bits);
         let max_val = if num_bits == 64 {
             u64::MAX

bitpacker/src/blocked_bitpacker.rs

@@ -140,10 +140,10 @@ impl BlockedBitpacker {
     pub fn iter(&self) -> impl Iterator<Item = u64> + '_ {
         // todo performance: we could decompress a whole block and cache it instead
         let bitpacked_elems = self.offset_and_bits.len() * BLOCK_SIZE;
-        let iter = (0..bitpacked_elems)
+
+        (0..bitpacked_elems)
             .map(move |idx| self.get(idx))
-            .chain(self.buffer.iter().cloned());
-        iter
+            .chain(self.buffer.iter().cloned())
     }
 }
 

bitpacker/src/filter_vec/avx2.rs

@@ -19,7 +19,7 @@ fn u32_to_i32(val: u32) -> i32 {
 #[inline]
 unsafe fn u32_to_i32_avx2(vals_u32x8s: DataType) -> DataType {
     const HIGHEST_BIT_MASK: DataType = from_u32x8([HIGHEST_BIT; NUM_LANES]);
-    op_xor(vals_u32x8s, HIGHEST_BIT_MASK)
+    unsafe { op_xor(vals_u32x8s, HIGHEST_BIT_MASK) }
 }
 
 pub fn filter_vec_in_place(range: RangeInclusive<u32>, offset: u32, output: &mut Vec<u32>) {
@@ -66,17 +66,19 @@ unsafe fn filter_vec_avx2_aux(
     ]);
     const SHIFT: __m256i = from_u32x8([NUM_LANES as u32; NUM_LANES]);
     for _ in 0..num_words {
-        let word = load_unaligned(input);
-        let word = u32_to_i32_avx2(word);
-        let keeper_bitset = compute_filter_bitset(word, range_simd.clone());
-        let added_len = keeper_bitset.count_ones();
-        let filtered_doc_ids = compact(ids, keeper_bitset);
-        store_unaligned(output_tail as *mut __m256i, filtered_doc_ids);
-        output_tail = output_tail.offset(added_len as isize);
-        ids = op_add(ids, SHIFT);
-        input = input.offset(1);
+        unsafe {
+            let word = load_unaligned(input);
+            let word = u32_to_i32_avx2(word);
+            let keeper_bitset = compute_filter_bitset(word, range_simd.clone());
+            let added_len = keeper_bitset.count_ones();
+            let filtered_doc_ids = compact(ids, keeper_bitset);
+            store_unaligned(output_tail as *mut __m256i, filtered_doc_ids);
+            output_tail = output_tail.offset(added_len as isize);
+            ids = op_add(ids, SHIFT);
+            input = input.offset(1);
+        }
     }
-    output_tail.offset_from(output) as usize
+    unsafe { output_tail.offset_from(output) as usize }
 }
 
 #[inline]
@@ -92,8 +94,7 @@ unsafe fn compute_filter_bitset(val: __m256i, range: std::ops::RangeInclusive<__
     let too_low = op_greater(*range.start(), val);
     let too_high = op_greater(val, *range.end());
     let inside = op_or(too_low, too_high);
-    255 - std::arch::x86_64::_mm256_movemask_ps(std::mem::transmute::<DataType, __m256>(inside))
-        as u8
+    255 - std::arch::x86_64::_mm256_movemask_ps(_mm256_castsi256_ps(inside)) as u8
 }
 
 union U8x32 {

columnar/README.md

@@ -73,7 +73,7 @@ The crate introduces the following concepts.
 `Columnar` is an equivalent of a dataframe.
 It maps `column_key` to `Column`.
 
-A `Column<T>` asssociates a `RowId` (u32) to any
+A `Column<T>` associates a `RowId` (u32) to any
 number of values.
 
 This is made possible by wrapping a `ColumnIndex` and a `ColumnValue` object.

columnar/benches/bench_first_vals.rs

@@ -89,13 +89,6 @@ fn main() {
         black_box(sum);
     });
 
-    group.register("first_block_fetch", |column| {
-        let mut block: Vec<Option<u64>> = vec![None; 64];
-        let fetch_docids = (0..64).collect::<Vec<_>>();
-        column.first_vals(&fetch_docids, &mut block);
-        black_box(block[0]);
-    });
-
     group.register("first_block_single_calls", |column| {
         let mut block: Vec<Option<u64>> = vec![None; 64];
         let fetch_docids = (0..64).collect::<Vec<_>>();

columnar/src/block_accessor.rs

@@ -29,12 +29,20 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
         }
     }
     #[inline]
-    pub fn fetch_block_with_missing(&mut self, docs: &[u32], accessor: &Column<T>, missing: T) {
+    pub fn fetch_block_with_missing(
+        &mut self,
+        docs: &[u32],
+        accessor: &Column<T>,
+        missing: Option<T>,
+    ) {
         self.fetch_block(docs, accessor);
         // no missing values
         if accessor.index.get_cardinality().is_full() {
             return;
         }
+        let Some(missing) = missing else {
+            return;
+        };
 
         // We can compare docid_cache length with docs to find missing docs
         // For multi value columns we can't rely on the length and always need to scan

columnar/src/column/mod.rs

@@ -131,6 +131,8 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
         self.index.docids_to_rowids(doc_ids, doc_ids_out, row_ids)
     }
 
+    /// Get an iterator over the values for the provided docid.
+    #[inline]
     pub fn values_for_doc(&self, doc_id: DocId) -> impl Iterator<Item = T> + '_ {
         self.index
             .value_row_ids(doc_id)
@@ -158,15 +160,6 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
             .select_batch_in_place(selected_docid_range.start, doc_ids);
     }
 
-    /// Fills the output vector with the (possibly multiple values that are associated_with
-    /// `row_id`.
-    ///
-    /// This method clears the `output` vector.
-    pub fn fill_vals(&self, row_id: RowId, output: &mut Vec<T>) {
-        output.clear();
-        output.extend(self.values_for_doc(row_id));
-    }
-
     pub fn first_or_default_col(self, default_value: T) -> Arc<dyn ColumnValues<T>> {
         Arc::new(FirstValueWithDefault {
             column: self,

columnar/src/column_index/merge/stacked.rs

@@ -56,7 +56,7 @@ fn get_doc_ids_with_values<'a>(
         ColumnIndex::Full => Box::new(doc_range),
         ColumnIndex::Optional(optional_index) => Box::new(
             optional_index
-                .iter_docs()
+                .iter_non_null_docs()
                 .map(move |row| row + doc_range.start),
         ),
         ColumnIndex::Multivalued(multivalued_index) => match multivalued_index {
@@ -73,7 +73,7 @@ fn get_doc_ids_with_values<'a>(
             MultiValueIndex::MultiValueIndexV2(multivalued_index) => Box::new(
                 multivalued_index
                     .optional_index
-                    .iter_docs()
+                    .iter_non_null_docs()
                     .map(move |row| row + doc_range.start),
             ),
         },
@@ -105,10 +105,11 @@ fn get_num_values_iterator<'a>(
 ) -> Box<dyn Iterator<Item = u32> + 'a> {
     match column_index {
         ColumnIndex::Empty { .. } => Box::new(std::iter::empty()),
-        ColumnIndex::Full => Box::new(std::iter::repeat(1u32).take(num_docs as usize)),
-        ColumnIndex::Optional(optional_index) => {
-            Box::new(std::iter::repeat(1u32).take(optional_index.num_non_nulls() as usize))
-        }
+        ColumnIndex::Full => Box::new(std::iter::repeat_n(1u32, num_docs as usize)),
+        ColumnIndex::Optional(optional_index) => Box::new(std::iter::repeat_n(
+            1u32,
+            optional_index.num_non_nulls() as usize,
+        )),
         ColumnIndex::Multivalued(multivalued_index) => Box::new(
             multivalued_index
                 .get_start_index_column()
@@ -177,7 +178,7 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
                         ColumnIndex::Full => Box::new(columnar_row_range),
                         ColumnIndex::Optional(optional_index) => Box::new(
                             optional_index
-                                .iter_docs()
+                                .iter_non_null_docs()
                                 .map(move |row_id: RowId| columnar_row_range.start + row_id),
                         ),
                         ColumnIndex::Multivalued(_) => {

columnar/src/column_index/multivalued_index.rs

@@ -215,6 +215,32 @@ impl MultiValueIndex {
         }
     }
 
+    /// Returns an iterator over document ids that have at least one value.
+    pub fn iter_non_null_docs(&self) -> Box<dyn Iterator<Item = DocId> + '_> {
+        match self {
+            MultiValueIndex::MultiValueIndexV1(idx) => {
+                let mut doc: DocId = 0u32;
+                let num_docs = idx.num_docs();
+                Box::new(std::iter::from_fn(move || {
+                    // This is not the most efficient way to do this, but it's legacy code.
+                    while doc < num_docs {
+                        let cur = doc;
+                        doc += 1;
+                        let start = idx.start_index_column.get_val(cur);
+                        let end = idx.start_index_column.get_val(cur + 1);
+                        if end > start {
+                            return Some(cur);
+                        }
+                    }
+                    None
+                }))
+            }
+            MultiValueIndex::MultiValueIndexV2(idx) => {
+                Box::new(idx.optional_index.iter_non_null_docs())
+            }
+        }
+    }
+
     /// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
     /// docids. Positions are converted inplace to docids.
     ///

columnar/src/column_index/optional_index/mod.rs

@@ -1,4 +1,4 @@
-use std::io::{self, Write};
+use std::io;
 use std::sync::Arc;
 
 mod set;
@@ -11,7 +11,7 @@ use set_block::{
 };
 
 use crate::iterable::Iterable;
-use crate::{DocId, InvalidData, RowId};
+use crate::{DocId, RowId};
 
 /// The threshold for for number of elements after which we switch to dense block encoding.
 ///
@@ -88,7 +88,7 @@ pub struct OptionalIndex {
 
 impl Iterable<u32> for &OptionalIndex {
     fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
-        Box::new(self.iter_docs())
+        Box::new(self.iter_non_null_docs())
     }
 }
 
@@ -280,8 +280,9 @@ impl OptionalIndex {
         self.num_non_null_docs
     }
 
-    pub fn iter_docs(&self) -> impl Iterator<Item = RowId> + '_ {
-        // TODO optimize
+    pub fn iter_non_null_docs(&self) -> impl Iterator<Item = RowId> + '_ {
+        // TODO optimize. We could iterate over the blocks directly.
+        // We use the dense value ids and retrieve the doc ids via select.
         let mut select_batch = self.select_cursor();
         (0..self.num_non_null_docs).map(move |rank| select_batch.select(rank))
     }
@@ -334,38 +335,6 @@ enum Block<'a> {
     Sparse(SparseBlock<'a>),
 }
 
-#[derive(Debug, Copy, Clone)]
-enum OptionalIndexCodec {
-    Dense = 0,
-    Sparse = 1,
-}
-
-impl OptionalIndexCodec {
-    fn to_code(self) -> u8 {
-        self as u8
-    }
-
-    fn try_from_code(code: u8) -> Result<Self, InvalidData> {
-        match code {
-            0 => Ok(Self::Dense),
-            1 => Ok(Self::Sparse),
-            _ => Err(InvalidData),
-        }
-    }
-}
-
-impl BinarySerializable for OptionalIndexCodec {
-    fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_all(&[self.to_code()])
-    }
-
-    fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
-        let optional_codec_code = u8::deserialize(reader)?;
-        let optional_codec = Self::try_from_code(optional_codec_code)?;
-        Ok(optional_codec)
-    }
-}
-
 fn serialize_optional_index_block(block_els: &[u16], out: &mut impl io::Write) -> io::Result<()> {
     let is_sparse = is_sparse(block_els.len() as u32);
     if is_sparse {

columnar/src/column_index/optional_index/tests.rs

@@ -164,7 +164,11 @@ fn test_optional_index_large() {
 fn test_optional_index_iter_aux(row_ids: &[RowId], num_rows: RowId) {
     let optional_index = OptionalIndex::for_test(num_rows, row_ids);
     assert_eq!(optional_index.num_docs(), num_rows);
-    assert!(optional_index.iter_docs().eq(row_ids.iter().copied()));
+    assert!(
+        optional_index
+            .iter_non_null_docs()
+            .eq(row_ids.iter().copied())
+    );
 }
 
 #[test]

columnar/src/column_values/monotonic_mapping_u128.rs

@@ -1,7 +1,7 @@
 use std::fmt::Debug;
 use std::net::Ipv6Addr;
 
-/// Montonic maps a value to u128 value space
+/// Monotonic maps a value to u128 value space
 /// Monotonic mapping enables `PartialOrd` on u128 space without conversion to original space.
 pub trait MonotonicallyMappableToU128: 'static + PartialOrd + Copy + Debug + Send + Sync {
     /// Converts a value to u128.

columnar/src/column_values/u128_based/compact_space/build_compact_space.rs

@@ -185,10 +185,10 @@ impl CompactSpaceBuilder {
         let mut covered_space = Vec::with_capacity(self.blanks.len());
 
         // beginning of the blanks
-        if let Some(first_blank_start) = self.blanks.first().map(RangeInclusive::start) {
-            if *first_blank_start != 0 {
-                covered_space.push(0..=first_blank_start - 1);
-            }
+        if let Some(first_blank_start) = self.blanks.first().map(RangeInclusive::start)
+            && *first_blank_start != 0
+        {
+            covered_space.push(0..=first_blank_start - 1);
         }
 
         // Between the blanks
@@ -202,10 +202,10 @@ impl CompactSpaceBuilder {
         covered_space.extend(between_blanks);
 
         // end of the blanks
-        if let Some(last_blank_end) = self.blanks.last().map(RangeInclusive::end) {
-            if *last_blank_end != u128::MAX {
-                covered_space.push(last_blank_end + 1..=u128::MAX);
-            }
+        if let Some(last_blank_end) = self.blanks.last().map(RangeInclusive::end)
+            && *last_blank_end != u128::MAX
+        {
+            covered_space.push(last_blank_end + 1..=u128::MAX);
         }
 
         if covered_space.is_empty() {

columnar/src/column_values/u64_based/bitpacked.rs

@@ -105,7 +105,7 @@ impl ColumnCodecEstimator for BitpackedCodecEstimator {
 
     fn estimate(&self, stats: &ColumnStats) -> Option<u64> {
         let num_bits_per_value = num_bits(stats);
-        Some(stats.num_bytes() + (stats.num_rows as u64 * (num_bits_per_value as u64) + 7) / 8)
+        Some(stats.num_bytes() + (stats.num_rows as u64 * (num_bits_per_value as u64)).div_ceil(8))
     }
 
     fn serialize(

columnar/src/column_values/u64_based/line.rs

@@ -8,7 +8,7 @@ use crate::column_values::ColumnValues;
 const MID_POINT: u64 = (1u64 << 32) - 1u64;
 
 /// `Line` describes a line function `y: ax + b` using integer
-/// arithmetics.
+/// arithmetic.
 ///
 /// The slope is in fact a decimal split into a 32 bit integer value,
 /// and a 32-bit decimal value.
@@ -94,7 +94,7 @@ impl Line {
         // `(i, ys[])`.
         //
         // The best intercept therefore has the form
-        // `y[i] - line.eval(i)` (using wrapping arithmetics).
+        // `y[i] - line.eval(i)` (using wrapping arithmetic).
         // In other words, the best intercept is one of the `y - Line::eval(ys[i])`
         // and our task is just to pick the one that minimizes our error.
         //

columnar/src/column_values/u64_based/linear.rs

@@ -117,7 +117,7 @@ impl ColumnCodecEstimator for LinearCodecEstimator {
         Some(
             stats.num_bytes()
                 + linear_params.num_bytes()
-                + (num_bits as u64 * stats.num_rows as u64 + 7) / 8,
+                + (num_bits as u64 * stats.num_rows as u64).div_ceil(8),
         )
     }
 

columnar/src/column_values/u64_based/mod.rs

@@ -52,7 +52,7 @@ pub trait ColumnCodecEstimator<T = u64>: 'static {
     ) -> io::Result<()>;
 }
 
-/// A column codec describes a colunm serialization format.
+/// A column codec describes a column serialization format.
 pub trait ColumnCodec<T: PartialOrd = u64> {
     /// Specialized `ColumnValues` type.
     type ColumnValues: ColumnValues<T> + 'static;

columnar/src/columnar/merge/mod.rs

@@ -367,7 +367,7 @@ fn is_empty_after_merge(
                     ColumnIndex::Empty { .. } => true,
                     ColumnIndex::Full => alive_bitset.len() == 0,
                     ColumnIndex::Optional(optional_index) => {
-                        for doc in optional_index.iter_docs() {
+                        for doc in optional_index.iter_non_null_docs() {
                             if alive_bitset.contains(doc) {
                                 return false;
                             }

columnar/src/columnar/writer/column_operation.rs

@@ -244,7 +244,7 @@ impl SymbolValue for UnorderedId {
 
 fn compute_num_bytes_for_u64(val: u64) -> usize {
     let msb = (64u32 - val.leading_zeros()) as usize;
-    (msb + 7) / 8
+    msb.div_ceil(8)
 }
 
 fn encode_zig_zag(n: i64) -> u64 {

columnar/src/value.rs

@@ -1,3 +1,5 @@
+use std::str::FromStr;
+
 use common::DateTime;
 
 use crate::InvalidData;
@@ -9,6 +11,23 @@ pub enum NumericalValue {
     F64(f64),
 }
 
+impl FromStr for NumericalValue {
+    type Err = ();
+
+    fn from_str(s: &str) -> Result<Self, ()> {
+        if let Ok(val_i64) = s.parse::<i64>() {
+            return Ok(val_i64.into());
+        }
+        if let Ok(val_u64) = s.parse::<u64>() {
+            return Ok(val_u64.into());
+        }
+        if let Ok(val_f64) = s.parse::<f64>() {
+            return Ok(NumericalValue::from(val_f64).normalize());
+        }
+        Err(())
+    }
+}
+
 impl NumericalValue {
     pub fn numerical_type(&self) -> NumericalType {
         match self {
@@ -26,7 +45,7 @@ impl NumericalValue {
                 if val <= i64::MAX as u64 {
                     NumericalValue::I64(val as i64)
                 } else {
-                    NumericalValue::F64(val as f64)
+                    NumericalValue::U64(val)
                 }
             }
             NumericalValue::I64(val) => NumericalValue::I64(val),
@@ -141,6 +160,7 @@ impl Coerce for DateTime {
 #[cfg(test)]
 mod tests {
     use super::NumericalType;
+    use crate::NumericalValue;
 
     #[test]
     fn test_numerical_type_code() {
@@ -153,4 +173,58 @@ mod tests {
         }
         assert_eq!(num_numerical_type, 3);
     }
+
+    #[test]
+    fn test_parse_numerical() {
+        assert_eq!(
+            "123".parse::<NumericalValue>().unwrap(),
+            NumericalValue::I64(123)
+        );
+        assert_eq!(
+            "18446744073709551615".parse::<NumericalValue>().unwrap(),
+            NumericalValue::U64(18446744073709551615u64)
+        );
+        assert_eq!(
+            "1.0".parse::<NumericalValue>().unwrap(),
+            NumericalValue::I64(1i64)
+        );
+        assert_eq!(
+            "1.1".parse::<NumericalValue>().unwrap(),
+            NumericalValue::F64(1.1f64)
+        );
+        assert_eq!(
+            "-1.0".parse::<NumericalValue>().unwrap(),
+            NumericalValue::I64(-1i64)
+        );
+    }
+
+    #[test]
+    fn test_normalize_numerical() {
+        assert_eq!(
+            NumericalValue::from(1u64).normalize(),
+            NumericalValue::I64(1i64),
+        );
+        let limit_val = i64::MAX as u64 + 1u64;
+        assert_eq!(
+            NumericalValue::from(limit_val).normalize(),
+            NumericalValue::U64(limit_val),
+        );
+        assert_eq!(
+            NumericalValue::from(-1i64).normalize(),
+            NumericalValue::I64(-1i64),
+        );
+        assert_eq!(
+            NumericalValue::from(-2.0f64).normalize(),
+            NumericalValue::I64(-2i64),
+        );
+        assert_eq!(
+            NumericalValue::from(-2.1f64).normalize(),
+            NumericalValue::F64(-2.1f64),
+        );
+        let large_float = 2.0f64.powf(70.0f64);
+        assert_eq!(
+            NumericalValue::from(large_float).normalize(),
+            NumericalValue::F64(large_float),
+        );
+    }
 }

common/src/bitset.rs

@@ -181,9 +181,17 @@ pub struct BitSet {
     len: u64,
     max_value: u32,
 }
+impl std::fmt::Debug for BitSet {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        f.debug_struct("BitSet")
+            .field("len", &self.len)
+            .field("max_value", &self.max_value)
+            .finish()
+    }
+}
 
 fn num_buckets(max_val: u32) -> u32 {
-    (max_val + 63u32) / 64u32
+    max_val.div_ceil(64u32)
 }
 
 impl BitSet {

common/src/vint.rs

@@ -28,7 +28,9 @@ impl BinarySerializable for VIntU128 {
         writer.write_all(&buffer)
     }
 
+    #[allow(clippy::unbuffered_bytes)]
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
+        #[allow(clippy::unbuffered_bytes)]
         let mut bytes = reader.bytes();
         let mut result = 0u128;
         let mut shift = 0u64;
@@ -195,7 +197,9 @@ impl BinarySerializable for VInt {
         writer.write_all(&buffer[0..num_bytes])
     }
 
+    #[allow(clippy::unbuffered_bytes)]
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
+        #[allow(clippy::unbuffered_bytes)]
         let mut bytes = reader.bytes();
         let mut result = 0u64;
         let mut shift = 0u64;

examples/basic_search.rs

@@ -208,7 +208,7 @@ fn main() -> tantivy::Result<()> {
     // is the role of the `TopDocs` collector.
 
     // We can now perform our query.
-    let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
+    let top_docs = searcher.search(&query, &TopDocs::with_limit(10).order_by_score())?;
 
     // The actual documents still need to be
     // retrieved from Tantivy's store.
@@ -226,7 +226,7 @@ fn main() -> tantivy::Result<()> {
     let query = query_parser.parse_query("title:sea^20 body:whale^70")?;
 
     let (_score, doc_address) = searcher
-        .search(&query, &TopDocs::with_limit(1))?
+        .search(&query, &TopDocs::with_limit(1).order_by_score())?
         .into_iter()
         .next()
         .unwrap();

examples/custom_tokenizer.rs

@@ -100,7 +100,7 @@ fn main() -> tantivy::Result<()> {
     // here we want to get a hit on the 'ken' in Frankenstein
     let query = query_parser.parse_query("ken")?;
 
-    let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
+    let top_docs = searcher.search(&query, &TopDocs::with_limit(10).order_by_score())?;
 
     for (_, doc_address) in top_docs {
         let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;

examples/date_time_field.rs

@@ -50,14 +50,14 @@ fn main() -> tantivy::Result<()> {
     {
         // Simple exact search on the date
         let query = query_parser.parse_query("occurred_at:\"2022-06-22T12:53:50.53Z\"")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(5))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(5).order_by_score())?;
         assert_eq!(count_docs.len(), 1);
     }
     {
         // Range query on the date field
         let query = query_parser
             .parse_query(r#"occurred_at:[2022-06-22T12:58:00Z TO 2022-06-23T00:00:00Z}"#)?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(4))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(4).order_by_score())?;
         assert_eq!(count_docs.len(), 1);
         for (_score, doc_address) in count_docs {
             let retrieved_doc = searcher.doc::<TantivyDocument>(doc_address)?;

examples/deleting_updating_documents.rs

@@ -28,7 +28,7 @@ fn extract_doc_given_isbn(
     // The second argument is here to tell we don't care about decoding positions,
     // or term frequencies.
     let term_query = TermQuery::new(isbn_term.clone(), IndexRecordOption::Basic);
-    let top_docs = searcher.search(&term_query, &TopDocs::with_limit(1))?;
+    let top_docs = searcher.search(&term_query, &TopDocs::with_limit(1).order_by_score())?;
 
     if let Some((_score, doc_address)) = top_docs.first() {
         let doc = searcher.doc(*doc_address)?;

examples/filter_aggregation.rs

@@ -0,0 +1,212 @@
+// # Filter Aggregation Example
+//
+// This example demonstrates filter aggregations - creating buckets of documents
+// matching specific queries, with nested aggregations computed on each bucket.
+//
+// Filter aggregations are useful for computing metrics on different subsets of
+// your data in a single query, like "average price overall + average price for
+// electronics + count of in-stock items".
+
+use serde_json::json;
+use tantivy::aggregation::agg_req::Aggregations;
+use tantivy::aggregation::AggregationCollector;
+use tantivy::query::AllQuery;
+use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
+use tantivy::{doc, Index};
+
+fn main() -> tantivy::Result<()> {
+    // Create a simple product schema
+    let mut schema_builder = Schema::builder();
+    schema_builder.add_text_field("category", TEXT | FAST);
+    schema_builder.add_text_field("brand", TEXT | FAST);
+    schema_builder.add_u64_field("price", FAST);
+    schema_builder.add_f64_field("rating", FAST);
+    schema_builder.add_bool_field("in_stock", FAST | INDEXED);
+    let schema = schema_builder.build();
+
+    // Create index and add sample products
+    let index = Index::create_in_ram(schema.clone());
+    let mut writer = index.writer(50_000_000)?;
+
+    writer.add_document(doc!(
+        schema.get_field("category")? => "electronics",
+        schema.get_field("brand")? => "apple",
+        schema.get_field("price")? => 999u64,
+        schema.get_field("rating")? => 4.5f64,
+        schema.get_field("in_stock")? => true
+    ))?;
+    writer.add_document(doc!(
+        schema.get_field("category")? => "electronics",
+        schema.get_field("brand")? => "samsung",
+        schema.get_field("price")? => 799u64,
+        schema.get_field("rating")? => 4.2f64,
+        schema.get_field("in_stock")? => true
+    ))?;
+    writer.add_document(doc!(
+        schema.get_field("category")? => "clothing",
+        schema.get_field("brand")? => "nike",
+        schema.get_field("price")? => 120u64,
+        schema.get_field("rating")? => 4.1f64,
+        schema.get_field("in_stock")? => false
+    ))?;
+    writer.add_document(doc!(
+        schema.get_field("category")? => "books",
+        schema.get_field("brand")? => "penguin",
+        schema.get_field("price")? => 25u64,
+        schema.get_field("rating")? => 4.8f64,
+        schema.get_field("in_stock")? => true
+    ))?;
+
+    writer.commit()?;
+
+    let reader = index.reader()?;
+    let searcher = reader.searcher();
+
+    // Example 1: Basic filter with metric aggregation
+    println!("=== Example 1: Electronics average price ===");
+    let agg_req = json!({
+        "electronics": {
+            "filter": "category:electronics",
+            "aggs": {
+                "avg_price": { "avg": { "field": "price" } }
+            }
+        }
+    });
+
+    let agg: Aggregations = serde_json::from_value(agg_req)?;
+    let collector = AggregationCollector::from_aggs(agg, Default::default());
+    let result = searcher.search(&AllQuery, &collector)?;
+
+    let expected = json!({
+        "electronics": {
+            "doc_count": 2,
+            "avg_price": { "value": 899.0 }
+        }
+    });
+    assert_eq!(serde_json::to_value(&result)?, expected);
+    println!("{}\n", serde_json::to_string_pretty(&result)?);
+
+    // Example 2: Multiple independent filters
+    println!("=== Example 2: Multiple filters in one query ===");
+    let agg_req = json!({
+        "electronics": {
+            "filter": "category:electronics",
+            "aggs": { "avg_price": { "avg": { "field": "price" } } }
+        },
+        "in_stock": {
+            "filter": "in_stock:true",
+            "aggs": { "count": { "value_count": { "field": "brand" } } }
+        },
+        "high_rated": {
+            "filter": "rating:[4.5 TO *]",
+            "aggs": { "count": { "value_count": { "field": "brand" } } }
+        }
+    });
+
+    let agg: Aggregations = serde_json::from_value(agg_req)?;
+    let collector = AggregationCollector::from_aggs(agg, Default::default());
+    let result = searcher.search(&AllQuery, &collector)?;
+
+    let expected = json!({
+        "electronics": {
+            "doc_count": 2,
+            "avg_price": { "value": 899.0 }
+        },
+        "in_stock": {
+            "doc_count": 3,
+            "count": { "value": 3.0 }
+        },
+        "high_rated": {
+            "doc_count": 2,
+            "count": { "value": 2.0 }
+        }
+    });
+    assert_eq!(serde_json::to_value(&result)?, expected);
+    println!("{}\n", serde_json::to_string_pretty(&result)?);
+
+    // Example 3: Nested filters - progressive refinement
+    println!("=== Example 3: Nested filters ===");
+    let agg_req = json!({
+        "in_stock": {
+            "filter": "in_stock:true",
+            "aggs": {
+                "electronics": {
+                    "filter": "category:electronics",
+                    "aggs": {
+                        "expensive": {
+                            "filter": "price:[800 TO *]",
+                            "aggs": {
+                                "avg_rating": { "avg": { "field": "rating" } }
+                            }
+                        }
+                    }
+                }
+            }
+        }
+    });
+
+    let agg: Aggregations = serde_json::from_value(agg_req)?;
+    let collector = AggregationCollector::from_aggs(agg, Default::default());
+    let result = searcher.search(&AllQuery, &collector)?;
+
+    let expected = json!({
+        "in_stock": {
+            "doc_count": 3,  // apple, samsung, penguin
+            "electronics": {
+                "doc_count": 2,  // apple, samsung
+                "expensive": {
+                    "doc_count": 1,  // only apple (999)
+                    "avg_rating": { "value": 4.5 }
+                }
+            }
+        }
+    });
+    assert_eq!(serde_json::to_value(&result)?, expected);
+    println!("{}\n", serde_json::to_string_pretty(&result)?);
+
+    // Example 4: Filter with sub-aggregation (terms)
+    println!("=== Example 4: Filter with terms sub-aggregation ===");
+    let agg_req = json!({
+        "electronics": {
+            "filter": "category:electronics",
+            "aggs": {
+                "by_brand": {
+                    "terms": { "field": "brand" },
+                    "aggs": {
+                        "avg_price": { "avg": { "field": "price" } }
+                    }
+                }
+            }
+        }
+    });
+
+    let agg: Aggregations = serde_json::from_value(agg_req)?;
+    let collector = AggregationCollector::from_aggs(agg, Default::default());
+    let result = searcher.search(&AllQuery, &collector)?;
+
+    let expected = json!({
+        "electronics": {
+            "doc_count": 2,
+            "by_brand": {
+                "buckets": [
+                    {
+                        "key": "samsung",
+                        "doc_count": 1,
+                        "avg_price": { "value": 799.0 }
+                    },
+                    {
+                        "key": "apple",
+                        "doc_count": 1,
+                        "avg_price": { "value": 999.0 }
+                    }
+                ],
+                "sum_other_doc_count": 0,
+                "doc_count_error_upper_bound": 0
+            }
+        }
+    });
+    assert_eq!(serde_json::to_value(&result)?, expected);
+    println!("{}", serde_json::to_string_pretty(&result)?);
+
+    Ok(())
+}

examples/fuzzy_search.rs

@@ -85,7 +85,6 @@ fn main() -> tantivy::Result<()> {
     index_writer.add_document(doc!(
         title => "The Diary of a Young Girl",
     ))?;
-    index_writer.commit()?;
 
     // ### Committing
     //
@@ -146,7 +145,7 @@ fn main() -> tantivy::Result<()> {
         let query = FuzzyTermQuery::new(term, 2, true);
 
         let (top_docs, count) = searcher
-            .search(&query, &(TopDocs::with_limit(5), Count))
+            .search(&query, &(TopDocs::with_limit(5).order_by_score(), Count))
             .unwrap();
         assert_eq!(count, 3);
         assert_eq!(top_docs.len(), 3);

examples/ip_field.rs

@@ -69,25 +69,25 @@ fn main() -> tantivy::Result<()> {
     {
         // Inclusive range queries
         let query = query_parser.parse_query("ip:[192.168.0.80 TO 192.168.0.100]")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(5))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(5).order_by_score())?;
         assert_eq!(count_docs.len(), 1);
     }
     {
         // Exclusive range queries
         let query = query_parser.parse_query("ip:{192.168.0.80 TO 192.168.1.100]")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(count_docs.len(), 0);
     }
     {
         // Find docs with IP addresses smaller equal 192.168.1.100
         let query = query_parser.parse_query("ip:[* TO 192.168.1.100]")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(count_docs.len(), 2);
     }
     {
         // Find docs with IP addresses smaller than 192.168.1.100
         let query = query_parser.parse_query("ip:[* TO 192.168.1.100}")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(count_docs.len(), 2);
     }
 

examples/json_field.rs

@@ -59,12 +59,12 @@ fn main() -> tantivy::Result<()> {
     let query_parser = QueryParser::for_index(&index, vec![event_type, attributes]);
     {
         let query = query_parser.parse_query("target:submit-button")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(count_docs.len(), 2);
     }
     {
         let query = query_parser.parse_query("target:submit")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(count_docs.len(), 2);
     }
     {
@@ -74,33 +74,33 @@ fn main() -> tantivy::Result<()> {
     }
     {
         let query = query_parser.parse_query("click AND cart.product_id:133")?;
-        let hits = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let hits = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(hits.len(), 1);
     }
     {
         // The sub-fields in the json field marked as default field still need to be explicitly
         // addressed
         let query = query_parser.parse_query("click AND 133")?;
-        let hits = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let hits = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(hits.len(), 0);
     }
     {
         // Default json fields are ignored if they collide with the schema
         let query = query_parser.parse_query("event_type:holiday-sale")?;
-        let hits = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let hits = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(hits.len(), 0);
     }
     // # Query via full attribute path
     {
         // This only searches in our schema's `event_type` field
         let query = query_parser.parse_query("event_type:click")?;
-        let hits = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let hits = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(hits.len(), 2);
     }
     {
         // Default json fields can still be accessed by full path
         let query = query_parser.parse_query("attributes.event_type:holiday-sale")?;
-        let hits = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        let hits = searcher.search(&*query, &TopDocs::with_limit(2).order_by_score())?;
         assert_eq!(hits.len(), 1);
     }
     Ok(())

examples/phrase_prefix_search.rs

@@ -63,7 +63,7 @@ fn main() -> Result<()> {
     // but not "in the Gulf Stream".
     let query = query_parser.parse_query("\"in the su\"*")?;
 
-    let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
+    let top_docs = searcher.search(&query, &TopDocs::with_limit(10).order_by_score())?;
     let mut titles = top_docs
         .into_iter()
         .map(|(_score, doc_address)| {

examples/pre_tokenized_text.rs

@@ -107,7 +107,8 @@ fn main() -> tantivy::Result<()> {
         IndexRecordOption::Basic,
     );
 
-    let (top_docs, count) = searcher.search(&query, &(TopDocs::with_limit(2), Count))?;
+    let (top_docs, count) =
+        searcher.search(&query, &(TopDocs::with_limit(2).order_by_score(), Count))?;
 
     assert_eq!(count, 2);
 
@@ -128,7 +129,8 @@ fn main() -> tantivy::Result<()> {
         IndexRecordOption::Basic,
     );
 
-    let (_top_docs, count) = searcher.search(&query, &(TopDocs::with_limit(2), Count))?;
+    let (_top_docs, count) =
+        searcher.search(&query, &(TopDocs::with_limit(2).order_by_score(), Count))?;
 
     assert_eq!(count, 0);
 

examples/snippet.rs

@@ -50,7 +50,7 @@ fn main() -> tantivy::Result<()> {
     let query_parser = QueryParser::for_index(&index, vec![title, body]);
     let query = query_parser.parse_query("sycamore spring")?;
 
-    let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
+    let top_docs = searcher.search(&query, &TopDocs::with_limit(10).order_by_score())?;
 
     let snippet_generator = SnippetGenerator::create(&searcher, &*query, body)?;
 

examples/stop_words.rs

@@ -102,7 +102,7 @@ fn main() -> tantivy::Result<()> {
     // stop words are applied on the query as well.
     // The following will be equivalent to `title:frankenstein`
     let query = query_parser.parse_query("title:\"the Frankenstein\"")?;
-    let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
+    let top_docs = searcher.search(&query, &TopDocs::with_limit(10).order_by_score())?;
 
     for (score, doc_address) in top_docs {
         let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;

examples/warmer.rs

@@ -164,7 +164,7 @@ fn main() -> tantivy::Result<()> {
         move |doc_id: DocId| Reverse(price[doc_id as usize])
     };
 
-    let most_expensive_first = TopDocs::with_limit(10).custom_score(score_by_price);
+    let most_expensive_first = TopDocs::with_limit(10).order_by(score_by_price);
 
     let hits = searcher.search(&query, &most_expensive_first)?;
     assert_eq!(

query-grammar/Cargo.toml

@@ -15,3 +15,5 @@ edition = "2024"
 nom = "7"
 serde = { version = "1.0.219", features = ["derive"] }
 serde_json = "1.0.140"
+ordered-float = "5.0.0"
+fnv = "1.0.7"

query-grammar/src/infallible.rs

@@ -117,6 +117,22 @@ where F: nom::Parser<I, (O, ErrorList), Infallible> {
     }
 }
 
+pub(crate) fn terminated_infallible<I, O1, O2, F, G>(
+    mut first: F,
+    mut second: G,
+) -> impl FnMut(I) -> JResult<I, O1>
+where
+    F: nom::Parser<I, (O1, ErrorList), Infallible>,
+    G: nom::Parser<I, (O2, ErrorList), Infallible>,
+{
+    move |input: I| {
+        let (input, (o1, mut err)) = first.parse(input)?;
+        let (input, (_, mut err2)) = second.parse(input)?;
+        err.append(&mut err2);
+        Ok((input, (o1, err)))
+    }
+}
+
 pub(crate) fn delimited_infallible<I, O1, O2, O3, F, G, H>(
     mut first: F,
     mut second: G,

query-grammar/src/lib.rs

@@ -31,7 +31,17 @@ pub fn parse_query_lenient(query: &str) -> (UserInputAst, Vec<LenientError>) {
 
 #[cfg(test)]
 mod tests {
-    use crate::{parse_query, parse_query_lenient};
+    use crate::{UserInputAst, parse_query, parse_query_lenient};
+
+    #[test]
+    fn test_deduplication() {
+        let ast: UserInputAst = parse_query("a a").unwrap();
+        let json = serde_json::to_string(&ast).unwrap();
+        assert_eq!(
+            json,
+            r#"{"type":"bool","clauses":[[null,{"type":"literal","field_name":null,"phrase":"a","delimiter":"none","slop":0,"prefix":false}]]}"#
+        );
+    }
 
     #[test]
     fn test_parse_query_serialization() {

query-grammar/src/query_grammar.rs

@@ -1,6 +1,7 @@
 use std::borrow::Cow;
 use std::iter::once;
 
+use fnv::FnvHashSet;
 use nom::IResult;
 use nom::branch::alt;
 use nom::bytes::complete::tag;
@@ -68,7 +69,7 @@ fn interpret_escape(source: &str) -> String {
 
 /// Consume a word outside of any context.
 // TODO should support escape sequences
-fn word(inp: &str) -> IResult<&str, Cow<str>> {
+fn word(inp: &str) -> IResult<&str, Cow<'_, str>> {
     map_res(
         recognize(tuple((
             alt((
@@ -305,15 +306,14 @@ fn term_group_infallible(inp: &str) -> JResult<&str, UserInputAst> {
     let (inp, (field_name, _, _, _)) =
         tuple((field_name, multispace0, char('('), multispace0))(inp).expect("precondition failed");
 
-    let res = delimited_infallible(
+    delimited_infallible(
         nothing,
         map(ast_infallible, |(mut ast, errors)| {
             ast.set_default_field(field_name.to_string());
             (ast, errors)
         }),
         opt_i_err(char(')'), "expected ')'"),
-    )(inp);
-    res
+    )(inp)
 }
 
 fn exists(inp: &str) -> IResult<&str, UserInputLeaf> {
@@ -367,7 +367,10 @@ fn literal(inp: &str) -> IResult<&str, UserInputAst> {
     // something (a field name) got parsed before
     alt((
         map(
-            tuple((opt(field_name), alt((range, set, exists, term_or_phrase)))),
+            tuple((
+                opt(field_name),
+                alt((range, set, exists, regex, term_or_phrase)),
+            )),
             |(field_name, leaf): (Option<String>, UserInputLeaf)| leaf.set_field(field_name).into(),
         ),
         term_group,
@@ -389,6 +392,10 @@ fn literal_no_group_infallible(inp: &str) -> JResult<&str, Option<UserInputAst>>
                         value((), peek(one_of("{[><"))),
                         map(range_infallible, |(range, errs)| (Some(range), errs)),
                     ),
+                    (
+                        value((), peek(one_of("/"))),
+                        map(regex_infallible, |(regex, errs)| (Some(regex), errs)),
+                    ),
                 ),
                 delimited_infallible(space0_infallible, term_or_phrase_infallible, nothing),
             ),
@@ -689,6 +696,61 @@ fn set_infallible(mut inp: &str) -> JResult<&str, UserInputLeaf> {
     }
 }
 
+fn regex(inp: &str) -> IResult<&str, UserInputLeaf> {
+    map(
+        terminated(
+            delimited(
+                char('/'),
+                many1(alt((preceded(char('\\'), char('/')), none_of("/")))),
+                char('/'),
+            ),
+            peek(alt((multispace1, eof))),
+        ),
+        |elements| UserInputLeaf::Regex {
+            field: None,
+            pattern: elements.into_iter().collect::<String>(),
+        },
+    )(inp)
+}
+
+fn regex_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
+    match terminated_infallible(
+        delimited_infallible(
+            opt_i_err(char('/'), "missing delimiter /"),
+            opt_i(many1(alt((preceded(char('\\'), char('/')), none_of("/"))))),
+            opt_i_err(char('/'), "missing delimiter /"),
+        ),
+        opt_i_err(
+            peek(alt((multispace1, eof))),
+            "expected whitespace or end of input",
+        ),
+    )(inp)
+    {
+        Ok((rest, (elements_part, errors))) => {
+            let pattern = match elements_part {
+                Some(elements_part) => elements_part.into_iter().collect(),
+                None => String::new(),
+            };
+            let res = UserInputLeaf::Regex {
+                field: None,
+                pattern,
+            };
+            Ok((rest, (res, errors)))
+        }
+        Err(e) => {
+            let errs = vec![LenientErrorInternal {
+                pos: inp.len(),
+                message: e.to_string(),
+            }];
+            let res = UserInputLeaf::Regex {
+                field: None,
+                pattern: String::new(),
+            };
+            Ok((inp, (res, errs)))
+        }
+    }
+}
+
 fn negate(expr: UserInputAst) -> UserInputAst {
     expr.unary(Occur::MustNot)
 }
@@ -696,7 +758,17 @@ fn negate(expr: UserInputAst) -> UserInputAst {
 fn leaf(inp: &str) -> IResult<&str, UserInputAst> {
     alt((
         delimited(char('('), ast, char(')')),
-        map(char('*'), |_| UserInputAst::from(UserInputLeaf::All)),
+        map(
+            terminated(
+                char('*'),
+                peek(alt((
+                    value((), multispace1),
+                    value((), char(')')),
+                    value((), eof),
+                ))),
+            ),
+            |_| UserInputAst::from(UserInputLeaf::All),
+        ),
         map(preceded(tuple((tag("NOT"), multispace1)), leaf), negate),
         literal,
     ))(inp)
@@ -717,7 +789,17 @@ fn leaf_infallible(inp: &str) -> JResult<&str, Option<UserInputAst>> {
                 ),
             ),
             (
-                value((), char('*')),
+                value(
+                    (),
+                    terminated(
+                        char('*'),
+                        peek(alt((
+                            value((), multispace1),
+                            value((), char(')')),
+                            value((), eof),
+                        ))),
+                    ),
+                ),
                 map(nothing, |_| {
                     (Some(UserInputAst::from(UserInputLeaf::All)), Vec::new())
                 }),
@@ -753,7 +835,7 @@ fn boosted_leaf(inp: &str) -> IResult<&str, UserInputAst> {
         tuple((leaf, fallible(boost))),
         |(leaf, boost_opt)| match boost_opt {
             Some(boost) if (boost - 1.0).abs() > f64::EPSILON => {
-                UserInputAst::Boost(Box::new(leaf), boost)
+                UserInputAst::Boost(Box::new(leaf), boost.into())
             }
             _ => leaf,
         },
@@ -765,7 +847,7 @@ fn boosted_leaf_infallible(inp: &str) -> JResult<&str, Option<UserInputAst>> {
         tuple_infallible((leaf_infallible, boost)),
         |((leaf, boost_opt), error)| match boost_opt {
             Some(boost) if (boost - 1.0).abs() > f64::EPSILON => (
-                leaf.map(|leaf| UserInputAst::Boost(Box::new(leaf), boost)),
+                leaf.map(|leaf| UserInputAst::Boost(Box::new(leaf), boost.into())),
                 error,
             ),
             _ => (leaf, error),
@@ -1016,12 +1098,25 @@ pub fn parse_to_ast_lenient(query_str: &str) -> (UserInputAst, Vec<LenientError>
     (rewrite_ast(res), errors)
 }
 
-/// Removes unnecessary children clauses in AST
-///
-/// Motivated by [issue #1433](https://github.com/quickwit-oss/tantivy/issues/1433)
 fn rewrite_ast(mut input: UserInputAst) -> UserInputAst {
-    if let UserInputAst::Clause(terms) = &mut input {
-        for term in terms {
+    if let UserInputAst::Clause(sub_clauses) = &mut input {
+        // call rewrite_ast recursively on children clauses if applicable
+        let mut new_clauses = Vec::with_capacity(sub_clauses.len());
+        for (occur, clause) in sub_clauses.drain(..) {
+            let rewritten_clause = rewrite_ast(clause);
+            new_clauses.push((occur, rewritten_clause));
+        }
+        *sub_clauses = new_clauses;
+
+        // remove duplicate child clauses
+        // e.g. (+a +b) OR (+c +d) OR (+a +b)  => (+a +b) OR (+c +d)
+        let mut seen = FnvHashSet::default();
+        sub_clauses.retain(|term| seen.insert(term.clone()));
+
+        // Removes unnecessary children clauses in AST
+        //
+        // Motivated by [issue #1433](https://github.com/quickwit-oss/tantivy/issues/1433)
+        for term in sub_clauses {
             rewrite_ast_clause(term);
         }
     }
@@ -1596,6 +1691,21 @@ mod test {
         test_parse_query_to_ast_helper("abc:a b", "(*\"abc\":a *b)");
         test_parse_query_to_ast_helper("abc:\"a b\"", "\"abc\":\"a b\"");
         test_parse_query_to_ast_helper("foo:[1 TO 5]", "\"foo\":[\"1\" TO \"5\"]");
+
+        // Phrase prefixed with *
+        test_parse_query_to_ast_helper("foo:(*A)", "\"foo\":*A");
+        test_parse_query_to_ast_helper("*A", "*A");
+        test_parse_query_to_ast_helper("(*A)", "*A");
+        test_parse_query_to_ast_helper("foo:(A OR B)", "(?\"foo\":A ?\"foo\":B)");
+        test_parse_query_to_ast_helper("foo:(A* OR B*)", "(?\"foo\":A* ?\"foo\":B*)");
+        test_parse_query_to_ast_helper("foo:(*A OR *B)", "(?\"foo\":*A ?\"foo\":*B)");
+    }
+
+    #[test]
+    fn test_parse_query_all() {
+        test_parse_query_to_ast_helper("*", "*");
+        test_parse_query_to_ast_helper("(*)", "*");
+        test_parse_query_to_ast_helper("(* )", "*");
     }
 
     #[test]
@@ -1694,6 +1804,63 @@ mod test {
         test_is_parse_err(r#"!bc:def"#, "!bc:def");
     }
 
+    #[test]
+    fn test_regex_parser() {
+        let r = parse_to_ast(r#"a:/joh?n(ath[oa]n)/"#);
+        assert!(r.is_ok(), "Failed to parse custom query: {r:?}");
+        let (_, input) = r.unwrap();
+        match input {
+            UserInputAst::Leaf(leaf) => match leaf.as_ref() {
+                UserInputLeaf::Regex { field, pattern } => {
+                    assert_eq!(field, &Some("a".to_string()));
+                    assert_eq!(pattern, "joh?n(ath[oa]n)");
+                }
+                _ => panic!("Expected a regex leaf, got {leaf:?}"),
+            },
+            _ => panic!("Expected a leaf"),
+        }
+        let r = parse_to_ast(r#"a:/\\/cgi-bin\\/luci.*/"#);
+        assert!(r.is_ok(), "Failed to parse custom query: {r:?}");
+        let (_, input) = r.unwrap();
+        match input {
+            UserInputAst::Leaf(leaf) => match leaf.as_ref() {
+                UserInputLeaf::Regex { field, pattern } => {
+                    assert_eq!(field, &Some("a".to_string()));
+                    assert_eq!(pattern, "\\/cgi-bin\\/luci.*");
+                }
+                _ => panic!("Expected a regex leaf, got {leaf:?}"),
+            },
+            _ => panic!("Expected a leaf"),
+        }
+    }
+
+    #[test]
+    fn test_regex_parser_lenient() {
+        let literal = |query| literal_infallible(query).unwrap().1;
+
+        let (res, errs) = literal(r#"a:/joh?n(ath[oa]n)/"#);
+        let expected = UserInputLeaf::Regex {
+            field: Some("a".to_string()),
+            pattern: "joh?n(ath[oa]n)".to_string(),
+        }
+        .into();
+        assert_eq!(res.unwrap(), expected);
+        assert!(errs.is_empty(), "Expected no errors, got: {errs:?}");
+
+        let (res, errs) = literal("title:/joh?n(ath[oa]n)");
+        let expected = UserInputLeaf::Regex {
+            field: Some("title".to_string()),
+            pattern: "joh?n(ath[oa]n)".to_string(),
+        }
+        .into();
+        assert_eq!(res.unwrap(), expected);
+        assert_eq!(errs.len(), 1, "Expected 1 error, got: {errs:?}");
+        assert_eq!(
+            errs[0].message, "missing delimiter /",
+            "Unexpected error message",
+        );
+    }
+
     #[test]
     fn test_space_before_value() {
         test_parse_query_to_ast_helper("field : a", r#""field":a"#);

query-grammar/src/user_input_ast.rs

@@ -5,7 +5,7 @@ use serde::Serialize;
 
 use crate::Occur;
 
-#[derive(PartialEq, Clone, Serialize)]
+#[derive(PartialEq, Eq, Hash, Clone, Serialize)]
 #[serde(tag = "type")]
 #[serde(rename_all = "snake_case")]
 pub enum UserInputLeaf {
@@ -23,6 +23,10 @@ pub enum UserInputLeaf {
     Exists {
         field: String,
     },
+    Regex {
+        field: Option<String>,
+        pattern: String,
+    },
 }
 
 impl UserInputLeaf {
@@ -46,6 +50,7 @@ impl UserInputLeaf {
             UserInputLeaf::Exists { field: _ } => UserInputLeaf::Exists {
                 field: field.expect("Exist query without a field isn't allowed"),
             },
+            UserInputLeaf::Regex { field: _, pattern } => UserInputLeaf::Regex { field, pattern },
         }
     }
 
@@ -103,11 +108,19 @@ impl Debug for UserInputLeaf {
             UserInputLeaf::Exists { field } => {
                 write!(formatter, "$exists(\"{field}\")")
             }
+            UserInputLeaf::Regex { field, pattern } => {
+                if let Some(field) = field {
+                    // TODO properly escape field (in case of \")
+                    write!(formatter, "\"{field}\":")?;
+                }
+                // TODO properly escape pattern (in case of \")
+                write!(formatter, "/{pattern}/")
+            }
         }
     }
 }
 
-#[derive(Copy, Clone, Eq, PartialEq, Debug, Serialize)]
+#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug, Serialize)]
 #[serde(rename_all = "snake_case")]
 pub enum Delimiter {
     SingleQuotes,
@@ -115,7 +128,7 @@ pub enum Delimiter {
     None,
 }
 
-#[derive(PartialEq, Clone, Serialize)]
+#[derive(PartialEq, Eq, Hash, Clone, Serialize)]
 #[serde(rename_all = "snake_case")]
 pub struct UserInputLiteral {
     pub field_name: Option<String>,
@@ -154,7 +167,7 @@ impl fmt::Debug for UserInputLiteral {
     }
 }
 
-#[derive(PartialEq, Debug, Clone, Serialize)]
+#[derive(PartialEq, Eq, Hash, Debug, Clone, Serialize)]
 #[serde(tag = "type", content = "value")]
 #[serde(rename_all = "snake_case")]
 pub enum UserInputBound {
@@ -191,11 +204,11 @@ impl UserInputBound {
     }
 }
 
-#[derive(PartialEq, Clone, Serialize)]
+#[derive(PartialEq, Eq, Hash, Clone, Serialize)]
 #[serde(into = "UserInputAstSerde")]
 pub enum UserInputAst {
     Clause(Vec<(Option<Occur>, UserInputAst)>),
-    Boost(Box<UserInputAst>, f64),
+    Boost(Box<UserInputAst>, ordered_float::OrderedFloat<f64>),
     Leaf(Box<UserInputLeaf>),
 }
 
@@ -217,9 +230,10 @@ impl From<UserInputAst> for UserInputAstSerde {
     fn from(ast: UserInputAst) -> Self {
         match ast {
             UserInputAst::Clause(clause) => UserInputAstSerde::Bool { clauses: clause },
-            UserInputAst::Boost(underlying, boost) => {
-                UserInputAstSerde::Boost { underlying, boost }
-            }
+            UserInputAst::Boost(underlying, boost) => UserInputAstSerde::Boost {
+                underlying,
+                boost: boost.into_inner(),
+            },
             UserInputAst::Leaf(leaf) => UserInputAstSerde::Leaf(leaf),
         }
     }
@@ -378,7 +392,7 @@ mod tests {
     #[test]
     fn test_boost_serialization() {
         let inner_ast = UserInputAst::Leaf(Box::new(UserInputLeaf::All));
-        let boost_ast = UserInputAst::Boost(Box::new(inner_ast), 2.5);
+        let boost_ast = UserInputAst::Boost(Box::new(inner_ast), 2.5.into());
         let json = serde_json::to_string(&boost_ast).unwrap();
         assert_eq!(
             json,
@@ -405,7 +419,7 @@ mod tests {
                     }))),
                 ),
             ])),
-            2.5,
+            2.5.into(),
         );
         let json = serde_json::to_string(&boost_ast).unwrap();
         assert_eq!(

src/aggregation/README.md

@@ -20,17 +20,16 @@ Contains all metric aggregations, like average aggregation. Metric aggregations
 #### agg_req
 agg_req contains the users aggregation request. Deserialization from json is compatible with elasticsearch aggregation requests.
 
-#### agg_req_with_accessor
-agg_req_with_accessor contains the users aggregation request enriched with fast field accessors etc, which are
+#### agg_data
+agg_data contains the users aggregation request enriched with fast field accessors etc, which are
 used during collection.
 
 #### segment_agg_result
 segment_agg_result contains the aggregation result tree, which is used for collection of a segment.
-The tree from agg_req_with_accessor is passed during collection.
+agg_data is passed during collection.
 
 #### intermediate_agg_result
 intermediate_agg_result contains the aggregation tree for merging with other trees.
 
 #### agg_result
 agg_result contains the final aggregation tree.
-

src/aggregation/accessor_helpers.rs

@@ -0,0 +1,105 @@
+//! This will enhance the request tree with access to the fastfield and metadata.
+
+use std::io;
+
+use columnar::{Column, ColumnType};
+
+use crate::aggregation::{f64_to_fastfield_u64, Key};
+use crate::index::SegmentReader;
+
+/// Get the missing value as internal u64 representation
+///
+/// For terms we use u64::MAX as sentinel value
+/// For numerical data we convert the value into the representation
+/// we would get from the fast field, when we open it as u64_lenient_for_type.
+///
+/// That way we can use it the same way as if it would come from the fastfield.
+pub(crate) fn get_missing_val_as_u64_lenient(
+    column_type: ColumnType,
+    column_max_value: u64,
+    missing: &Key,
+    field_name: &str,
+) -> crate::Result<Option<u64>> {
+    let missing_val = match missing {
+        Key::Str(_) if column_type == ColumnType::Str => Some(column_max_value + 1),
+        // Allow fallback to number on text fields
+        Key::F64(_) if column_type == ColumnType::Str => Some(column_max_value + 1),
+        Key::U64(_) if column_type == ColumnType::Str => Some(column_max_value + 1),
+        Key::I64(_) if column_type == ColumnType::Str => Some(column_max_value + 1),
+        Key::F64(val) if column_type.numerical_type().is_some() => {
+            f64_to_fastfield_u64(*val, &column_type)
+        }
+        // NOTE: We may loose precision of the passed missing value by casting i64 and u64 to f64.
+        Key::I64(val) if column_type.numerical_type().is_some() => {
+            f64_to_fastfield_u64(*val as f64, &column_type)
+        }
+        Key::U64(val) if column_type.numerical_type().is_some() => {
+            f64_to_fastfield_u64(*val as f64, &column_type)
+        }
+        _ => {
+            return Err(crate::TantivyError::InvalidArgument(format!(
+                "Missing value {missing:?} for field {field_name} is not supported for column \
+                 type {column_type:?}"
+            )));
+        }
+    };
+    Ok(missing_val)
+}
+
+pub(crate) fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
+    &[
+        ColumnType::F64,
+        ColumnType::U64,
+        ColumnType::I64,
+        ColumnType::DateTime,
+    ]
+}
+
+/// Get fast field reader or empty as default.
+pub(crate) fn get_ff_reader(
+    reader: &SegmentReader,
+    field_name: &str,
+    allowed_column_types: Option<&[ColumnType]>,
+) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
+    let ff_fields = reader.fast_fields();
+    let ff_field_with_type = ff_fields
+        .u64_lenient_for_type(allowed_column_types, field_name)?
+        .unwrap_or_else(|| {
+            (
+                Column::build_empty_column(reader.num_docs()),
+                ColumnType::U64,
+            )
+        });
+    Ok(ff_field_with_type)
+}
+
+pub(crate) fn get_dynamic_columns(
+    reader: &SegmentReader,
+    field_name: &str,
+) -> crate::Result<Vec<columnar::DynamicColumn>> {
+    let ff_fields = reader.fast_fields().dynamic_column_handles(field_name)?;
+    let cols = ff_fields
+        .iter()
+        .map(|h| h.open())
+        .collect::<io::Result<_>>()?;
+    assert!(!ff_fields.is_empty(), "field {field_name} not found");
+    Ok(cols)
+}
+
+/// Get all fast field reader or empty as default.
+///
+/// Is guaranteed to return at least one column.
+pub(crate) fn get_all_ff_reader_or_empty(
+    reader: &SegmentReader,
+    field_name: &str,
+    allowed_column_types: Option<&[ColumnType]>,
+    fallback_type: ColumnType,
+) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
+    let ff_fields = reader.fast_fields();
+    let mut ff_field_with_type =
+        ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
+    if ff_field_with_type.is_empty() {
+        ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
+    }
+    Ok(ff_field_with_type)
+}

src/aggregation/agg_limits.rs

@@ -35,6 +35,7 @@ pub struct AggregationLimitsGuard {
     /// Allocated memory with this guard.
     allocated_with_the_guard: u64,
 }
+
 impl Clone for AggregationLimitsGuard {
     fn clone(&self) -> Self {
         Self {
@@ -70,7 +71,7 @@ impl AggregationLimitsGuard {
     /// *memory_limit*
     /// memory_limit is defined in bytes.
     /// Aggregation fails when the estimated memory consumption of the aggregation is higher than
-    /// memory_limit.     
+    /// memory_limit.
     /// memory_limit will default to `DEFAULT_MEMORY_LIMIT` (500MB)
     ///
     /// *bucket_limit*

src/aggregation/agg_req.rs

@@ -26,12 +26,14 @@
 //! let _agg_req: Aggregations = serde_json::from_str(elasticsearch_compatible_json_req).unwrap();
 //! ```
 
-use std::collections::{HashMap, HashSet};
+use std::collections::HashSet;
 
+use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 
 use super::bucket::{
-    DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
+    DateHistogramAggregationReq, FilterAggregation, HistogramAggregation, RangeAggregation,
+    TermsAggregation,
 };
 use super::metric::{
     AverageAggregation, CardinalityAggregationReq, CountAggregation, ExtendedStatsAggregation,
@@ -43,7 +45,7 @@ use super::metric::{
 /// defined names. It is also used in buckets aggregations to define sub-aggregations.
 ///
 /// The key is the user defined name of the aggregation.
-pub type Aggregations = HashMap<String, Aggregation>;
+pub type Aggregations = FxHashMap<String, Aggregation>;
 
 /// Aggregation request.
 ///
@@ -129,6 +131,9 @@ pub enum AggregationVariants {
     /// Put data into buckets of terms.
     #[serde(rename = "terms")]
     Terms(TermsAggregation),
+    /// Filter documents into a single bucket.
+    #[serde(rename = "filter")]
+    Filter(FilterAggregation),
 
     // Metric aggregation types
     /// Computes the average of the extracted values.
@@ -174,6 +179,7 @@ impl AggregationVariants {
             AggregationVariants::Range(range) => vec![range.field.as_str()],
             AggregationVariants::Histogram(histogram) => vec![histogram.field.as_str()],
             AggregationVariants::DateHistogram(histogram) => vec![histogram.field.as_str()],
+            AggregationVariants::Filter(filter) => filter.get_fast_field_names(),
             AggregationVariants::Average(avg) => vec![avg.field_name()],
             AggregationVariants::Count(count) => vec![count.field_name()],
             AggregationVariants::Max(max) => vec![max.field_name()],
@@ -208,13 +214,6 @@ impl AggregationVariants {
             _ => None,
         }
     }
-    pub(crate) fn as_top_hits(&self) -> Option<&TopHitsAggregationReq> {
-        match &self {
-            AggregationVariants::TopHits(top_hits) => Some(top_hits),
-            _ => None,
-        }
-    }
-
     pub(crate) fn as_percentile(&self) -> Option<&PercentilesAggregationReq> {
         match &self {
             AggregationVariants::Percentiles(percentile_req) => Some(percentile_req),

src/aggregation/agg_req_with_accessor.rs

@@ -1,471 +0,0 @@
-//! This will enhance the request tree with access to the fastfield and metadata.
-
-use std::collections::HashMap;
-use std::io;
-
-use columnar::{Column, ColumnBlockAccessor, ColumnType, DynamicColumn, StrColumn};
-
-use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
-use super::bucket::{
-    DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
-};
-use super::metric::{
-    AverageAggregation, CardinalityAggregationReq, CountAggregation, ExtendedStatsAggregation,
-    MaxAggregation, MinAggregation, StatsAggregation, SumAggregation,
-};
-use super::segment_agg_result::AggregationLimitsGuard;
-use super::VecWithNames;
-use crate::aggregation::{f64_to_fastfield_u64, Key};
-use crate::index::SegmentReader;
-use crate::SegmentOrdinal;
-
-#[derive(Default)]
-pub(crate) struct AggregationsWithAccessor {
-    pub aggs: VecWithNames<AggregationWithAccessor>,
-}
-
-impl AggregationsWithAccessor {
-    fn from_data(aggs: VecWithNames<AggregationWithAccessor>) -> Self {
-        Self { aggs }
-    }
-
-    pub fn is_empty(&self) -> bool {
-        self.aggs.is_empty()
-    }
-}
-
-pub struct AggregationWithAccessor {
-    pub(crate) segment_ordinal: SegmentOrdinal,
-    /// In general there can be buckets without fast field access, e.g. buckets that are created
-    /// based on search terms. That is not that case currently, but eventually this needs to be
-    /// Option or moved.
-    pub(crate) accessor: Column<u64>,
-    /// Load insert u64 for missing use case
-    pub(crate) missing_value_for_accessor: Option<u64>,
-    pub(crate) str_dict_column: Option<StrColumn>,
-    pub(crate) field_type: ColumnType,
-    pub(crate) sub_aggregation: AggregationsWithAccessor,
-    pub(crate) limits: AggregationLimitsGuard,
-    pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
-    /// Used for missing term aggregation, which checks all columns for existence.
-    /// And also for `top_hits` aggregation, which may sort on multiple fields.
-    /// By convention the missing aggregation is chosen, when this property is set
-    /// (instead bein set in `agg`).
-    /// If this needs to used by other aggregations, we need to refactor this.
-    // NOTE: we can make all other aggregations use this instead of the `accessor` and `field_type`
-    // (making them obsolete) But will it have a performance impact?
-    pub(crate) accessors: Vec<(Column<u64>, ColumnType)>,
-    /// Map field names to all associated column accessors.
-    /// This field is used for `docvalue_fields`, which is currently only supported for `top_hits`.
-    pub(crate) value_accessors: HashMap<String, Vec<DynamicColumn>>,
-    pub(crate) agg: Aggregation,
-}
-
-impl AggregationWithAccessor {
-    /// May return multiple accessors if the aggregation is e.g. on mixed field types.
-    fn try_from_agg(
-        agg: &Aggregation,
-        sub_aggregation: &Aggregations,
-        reader: &SegmentReader,
-        segment_ordinal: SegmentOrdinal,
-        limits: AggregationLimitsGuard,
-    ) -> crate::Result<Vec<AggregationWithAccessor>> {
-        let mut agg = agg.clone();
-
-        let add_agg_with_accessor = |agg: &Aggregation,
-                                     accessor: Column<u64>,
-                                     column_type: ColumnType,
-                                     aggs: &mut Vec<AggregationWithAccessor>|
-         -> crate::Result<()> {
-            let res = AggregationWithAccessor {
-                segment_ordinal,
-                accessor,
-                accessors: Default::default(),
-                value_accessors: Default::default(),
-                field_type: column_type,
-                sub_aggregation: get_aggs_with_segment_accessor_and_validate(
-                    sub_aggregation,
-                    reader,
-                    segment_ordinal,
-                    &limits,
-                )?,
-                agg: agg.clone(),
-                limits: limits.clone(),
-                missing_value_for_accessor: None,
-                str_dict_column: None,
-                column_block_accessor: Default::default(),
-            };
-            aggs.push(res);
-            Ok(())
-        };
-
-        let add_agg_with_accessors = |agg: &Aggregation,
-                                      accessors: Vec<(Column<u64>, ColumnType)>,
-                                      aggs: &mut Vec<AggregationWithAccessor>,
-                                      value_accessors: HashMap<String, Vec<DynamicColumn>>|
-         -> crate::Result<()> {
-            let (accessor, field_type) = accessors.first().expect("at least one accessor");
-            let limits = limits.clone();
-            let res = AggregationWithAccessor {
-                segment_ordinal,
-                // TODO: We should do away with the `accessor` field altogether
-                accessor: accessor.clone(),
-                value_accessors,
-                field_type: *field_type,
-                accessors,
-                sub_aggregation: get_aggs_with_segment_accessor_and_validate(
-                    sub_aggregation,
-                    reader,
-                    segment_ordinal,
-                    &limits,
-                )?,
-                agg: agg.clone(),
-                limits,
-                missing_value_for_accessor: None,
-                str_dict_column: None,
-                column_block_accessor: Default::default(),
-            };
-            aggs.push(res);
-            Ok(())
-        };
-
-        let mut res: Vec<AggregationWithAccessor> = Vec::new();
-        use AggregationVariants::*;
-
-        match agg.agg {
-            Range(RangeAggregation {
-                field: ref field_name,
-                ..
-            }) => {
-                let (accessor, column_type) =
-                    get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
-                add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
-            }
-            Histogram(HistogramAggregation {
-                field: ref field_name,
-                ..
-            }) => {
-                let (accessor, column_type) =
-                    get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
-                add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
-            }
-            DateHistogram(DateHistogramAggregationReq {
-                field: ref field_name,
-                ..
-            }) => {
-                let (accessor, column_type) =
-                    // Only DateTime is supported for DateHistogram
-                    get_ff_reader(reader, field_name, Some(&[ColumnType::DateTime]))?;
-                add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
-            }
-            Terms(TermsAggregation {
-                field: ref field_name,
-                ref missing,
-                ..
-            })
-            | Cardinality(CardinalityAggregationReq {
-                field: ref field_name,
-                ref missing,
-                ..
-            }) => {
-                let str_dict_column = reader.fast_fields().str(field_name)?;
-                let allowed_column_types = [
-                    ColumnType::I64,
-                    ColumnType::U64,
-                    ColumnType::F64,
-                    ColumnType::Str,
-                    ColumnType::DateTime,
-                    ColumnType::Bool,
-                    ColumnType::IpAddr,
-                    // ColumnType::Bytes Unsupported
-                ];
-
-                // In case the column is empty we want the shim column to match the missing type
-                let fallback_type = missing
-                    .as_ref()
-                    .map(|missing| match missing {
-                        Key::Str(_) => ColumnType::Str,
-                        Key::F64(_) => ColumnType::F64,
-                        Key::I64(_) => ColumnType::I64,
-                        Key::U64(_) => ColumnType::U64,
-                    })
-                    .unwrap_or(ColumnType::U64);
-                let column_and_types = get_all_ff_reader_or_empty(
-                    reader,
-                    field_name,
-                    Some(&allowed_column_types),
-                    fallback_type,
-                )?;
-                let missing_and_more_than_one_col = column_and_types.len() > 1 && missing.is_some();
-                let text_on_non_text_col = column_and_types.len() == 1
-                    && column_and_types[0].1.numerical_type().is_some()
-                    && missing
-                        .as_ref()
-                        .map(|m| matches!(m, Key::Str(_)))
-                        .unwrap_or(false);
-
-                // Actually we could convert the text to a number and have the fast path, if it is
-                // provided in Rfc3339 format. But this use case is probably common
-                // enough to justify the effort.
-                let text_on_date_col = column_and_types.len() == 1
-                    && column_and_types[0].1 == ColumnType::DateTime
-                    && missing
-                        .as_ref()
-                        .map(|m| matches!(m, Key::Str(_)))
-                        .unwrap_or(false);
-
-                let use_special_missing_agg =
-                    missing_and_more_than_one_col || text_on_non_text_col || text_on_date_col;
-                if use_special_missing_agg {
-                    let column_and_types =
-                        get_all_ff_reader_or_empty(reader, field_name, None, fallback_type)?;
-
-                    let accessors = column_and_types
-                        .iter()
-                        .map(|c_t| (c_t.0.clone(), c_t.1))
-                        .collect();
-                    add_agg_with_accessors(&agg, accessors, &mut res, Default::default())?;
-                }
-
-                for (accessor, column_type) in column_and_types {
-                    let missing_value_term_agg = if use_special_missing_agg {
-                        None
-                    } else {
-                        missing.clone()
-                    };
-
-                    let missing_value_for_accessor =
-                        if let Some(missing) = missing_value_term_agg.as_ref() {
-                            get_missing_val_as_u64_lenient(
-                                column_type,
-                                missing,
-                                agg.agg.get_fast_field_names()[0],
-                            )?
-                        } else {
-                            None
-                        };
-
-                    let limits = limits.clone();
-                    let agg = AggregationWithAccessor {
-                        segment_ordinal,
-                        missing_value_for_accessor,
-                        accessor,
-                        accessors: Default::default(),
-                        value_accessors: Default::default(),
-                        field_type: column_type,
-                        sub_aggregation: get_aggs_with_segment_accessor_and_validate(
-                            sub_aggregation,
-                            reader,
-                            segment_ordinal,
-                            &limits,
-                        )?,
-                        agg: agg.clone(),
-                        str_dict_column: str_dict_column.clone(),
-                        limits,
-                        column_block_accessor: Default::default(),
-                    };
-                    res.push(agg);
-                }
-            }
-            Average(AverageAggregation {
-                field: ref field_name,
-                ..
-            })
-            | Max(MaxAggregation {
-                field: ref field_name,
-                ..
-            })
-            | Min(MinAggregation {
-                field: ref field_name,
-                ..
-            })
-            | Stats(StatsAggregation {
-                field: ref field_name,
-                ..
-            })
-            | ExtendedStats(ExtendedStatsAggregation {
-                field: ref field_name,
-                ..
-            })
-            | Sum(SumAggregation {
-                field: ref field_name,
-                ..
-            }) => {
-                let (accessor, column_type) =
-                    get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
-                add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
-            }
-            Count(CountAggregation {
-                field: ref field_name,
-                ..
-            }) => {
-                let allowed_column_types = [
-                    ColumnType::I64,
-                    ColumnType::U64,
-                    ColumnType::F64,
-                    ColumnType::Str,
-                    ColumnType::DateTime,
-                    ColumnType::Bool,
-                    ColumnType::IpAddr,
-                    // ColumnType::Bytes Unsupported
-                ];
-                let (accessor, column_type) =
-                    get_ff_reader(reader, field_name, Some(&allowed_column_types))?;
-                add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
-            }
-            Percentiles(ref percentiles) => {
-                let (accessor, column_type) = get_ff_reader(
-                    reader,
-                    percentiles.field_name(),
-                    Some(get_numeric_or_date_column_types()),
-                )?;
-                add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
-            }
-            TopHits(ref mut top_hits) => {
-                top_hits.validate_and_resolve_field_names(reader.fast_fields().columnar())?;
-                let accessors: Vec<(Column<u64>, ColumnType)> = top_hits
-                    .field_names()
-                    .iter()
-                    .map(|field| {
-                        get_ff_reader(reader, field, Some(get_numeric_or_date_column_types()))
-                    })
-                    .collect::<crate::Result<_>>()?;
-
-                let value_accessors = top_hits
-                    .value_field_names()
-                    .iter()
-                    .map(|field_name| {
-                        Ok((
-                            field_name.to_string(),
-                            get_dynamic_columns(reader, field_name)?,
-                        ))
-                    })
-                    .collect::<crate::Result<_>>()?;
-
-                add_agg_with_accessors(&agg, accessors, &mut res, value_accessors)?;
-            }
-        };
-
-        Ok(res)
-    }
-}
-
-/// Get the missing value as internal u64 representation
-///
-/// For terms we use u64::MAX as sentinel value
-/// For numerical data we convert the value into the representation
-/// we would get from the fast field, when we open it as u64_lenient_for_type.
-///
-/// That way we can use it the same way as if it would come from the fastfield.
-fn get_missing_val_as_u64_lenient(
-    column_type: ColumnType,
-    missing: &Key,
-    field_name: &str,
-) -> crate::Result<Option<u64>> {
-    let missing_val = match missing {
-        Key::Str(_) if column_type == ColumnType::Str => Some(u64::MAX),
-        // Allow fallback to number on text fields
-        Key::F64(_) if column_type == ColumnType::Str => Some(u64::MAX),
-        Key::U64(_) if column_type == ColumnType::Str => Some(u64::MAX),
-        Key::I64(_) if column_type == ColumnType::Str => Some(u64::MAX),
-        Key::F64(val) if column_type.numerical_type().is_some() => {
-            f64_to_fastfield_u64(*val, &column_type)
-        }
-        // NOTE: We may loose precision of the passed missing value by casting i64 and u64 to f64.
-        Key::I64(val) if column_type.numerical_type().is_some() => {
-            f64_to_fastfield_u64(*val as f64, &column_type)
-        }
-        Key::U64(val) if column_type.numerical_type().is_some() => {
-            f64_to_fastfield_u64(*val as f64, &column_type)
-        }
-        _ => {
-            return Err(crate::TantivyError::InvalidArgument(format!(
-                "Missing value {missing:?} for field {field_name} is not supported for column \
-                 type {column_type:?}"
-            )));
-        }
-    };
-    Ok(missing_val)
-}
-
-fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
-    &[
-        ColumnType::F64,
-        ColumnType::U64,
-        ColumnType::I64,
-        ColumnType::DateTime,
-    ]
-}
-
-pub(crate) fn get_aggs_with_segment_accessor_and_validate(
-    aggs: &Aggregations,
-    reader: &SegmentReader,
-    segment_ordinal: SegmentOrdinal,
-    limits: &AggregationLimitsGuard,
-) -> crate::Result<AggregationsWithAccessor> {
-    let mut aggss = Vec::new();
-    for (key, agg) in aggs.iter() {
-        let aggs = AggregationWithAccessor::try_from_agg(
-            agg,
-            agg.sub_aggregation(),
-            reader,
-            segment_ordinal,
-            limits.clone(),
-        )?;
-        for agg in aggs {
-            aggss.push((key.to_string(), agg));
-        }
-    }
-    Ok(AggregationsWithAccessor::from_data(
-        VecWithNames::from_entries(aggss),
-    ))
-}
-
-/// Get fast field reader or empty as default.
-fn get_ff_reader(
-    reader: &SegmentReader,
-    field_name: &str,
-    allowed_column_types: Option<&[ColumnType]>,
-) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
-    let ff_fields = reader.fast_fields();
-    let ff_field_with_type = ff_fields
-        .u64_lenient_for_type(allowed_column_types, field_name)?
-        .unwrap_or_else(|| {
-            (
-                Column::build_empty_column(reader.num_docs()),
-                ColumnType::U64,
-            )
-        });
-    Ok(ff_field_with_type)
-}
-
-fn get_dynamic_columns(
-    reader: &SegmentReader,
-    field_name: &str,
-) -> crate::Result<Vec<columnar::DynamicColumn>> {
-    let ff_fields = reader.fast_fields().dynamic_column_handles(field_name)?;
-    let cols = ff_fields
-        .iter()
-        .map(|h| h.open())
-        .collect::<io::Result<_>>()?;
-    assert!(!ff_fields.is_empty(), "field {field_name} not found");
-    Ok(cols)
-}
-
-/// Get all fast field reader or empty as default.
-///
-/// Is guaranteed to return at least one column.
-fn get_all_ff_reader_or_empty(
-    reader: &SegmentReader,
-    field_name: &str,
-    allowed_column_types: Option<&[ColumnType]>,
-    fallback_type: ColumnType,
-) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
-    let ff_fields = reader.fast_fields();
-    let mut ff_field_with_type =
-        ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
-    if ff_field_with_type.is_empty() {
-        ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
-    }
-    Ok(ff_field_with_type)
-}

src/aggregation/agg_result.rs

@@ -16,7 +16,7 @@ use super::{AggregationError, Key};
 use crate::TantivyError;
 
 #[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
-/// The final aggegation result.
+/// The final aggregation result.
 pub struct AggregationResults(pub FxHashMap<String, AggregationResult>);
 
 impl AggregationResults {
@@ -156,6 +156,8 @@ pub enum BucketResult {
         /// The upper bound error for the doc count of each term.
         doc_count_error_upper_bound: Option<u64>,
     },
+    /// This is the filter result - a single bucket with sub-aggregations
+    Filter(FilterBucketResult),
 }
 
 impl BucketResult {
@@ -172,6 +174,11 @@ impl BucketResult {
                 sum_other_doc_count: _,
                 doc_count_error_upper_bound: _,
             } => buckets.iter().map(|bucket| bucket.get_bucket_count()).sum(),
+            BucketResult::Filter(filter_result) => {
+                // Filter doesn't add to bucket count - it's not a user-facing bucket
+                // Only count sub-aggregation buckets
+                filter_result.sub_aggregations.get_bucket_count()
+            }
         }
     }
 }
@@ -308,3 +315,25 @@ impl RangeBucketEntry {
         1 + self.sub_aggregation.get_bucket_count()
     }
 }
+
+/// This is the filter bucket result, which contains the document count and sub-aggregations.
+///
+/// # JSON Format
+/// ```json
+/// {
+///   "electronics_only": {
+///     "doc_count": 2,
+///     "avg_price": {
+///       "value": 150.0
+///     }
+///   }
+/// }
+/// ```
+#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
+pub struct FilterBucketResult {
+    /// Number of documents in the filter bucket
+    pub doc_count: u64,
+    /// Sub-aggregation results
+    #[serde(flatten)]
+    pub sub_aggregations: AggregationResults,
+}

src/aggregation/agg_tests.rs

@@ -2,16 +2,441 @@ use serde_json::Value;
 
 use crate::aggregation::agg_req::{Aggregation, Aggregations};
 use crate::aggregation::agg_result::AggregationResults;
-use crate::aggregation::buf_collector::DOC_BLOCK_SIZE;
 use crate::aggregation::collector::AggregationCollector;
 use crate::aggregation::intermediate_agg_result::IntermediateAggregationResults;
-use crate::aggregation::segment_agg_result::AggregationLimitsGuard;
 use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_values_and_terms};
 use crate::aggregation::DistributedAggregationCollector;
+use crate::docset::COLLECT_BLOCK_BUFFER_LEN;
 use crate::query::{AllQuery, TermQuery};
 use crate::schema::{IndexRecordOption, Schema, FAST};
 use crate::{Index, IndexWriter, Term};
 
+// The following tests ensure that each bucket aggregation type correctly functions as a
+// sub-aggregation of another bucket aggregation in two scenarios:
+// 1) The parent has more buckets than the child sub-aggregation
+// 2) The child sub-aggregation has more buckets than the parent
+//
+// These scenarios exercise the bucket id mapping and sub-aggregation routing logic.
+
+#[test]
+fn test_terms_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
+    let index = get_test_index_2_segments(false)?;
+
+    // Case A: parent has more buckets than child
+    // Parent: range with 4 buckets
+    // Child: terms on text -> 2 buckets
+    let agg_parent_more: Aggregations = serde_json::from_value(json!({
+        "parent_range": {
+            "range": {
+                "field": "score",
+                "ranges": [
+                    {"to": 3.0},
+                    {"from": 3.0, "to": 7.0},
+                    {"from": 7.0, "to": 20.0},
+                    {"from": 20.0}
+                ]
+            },
+            "aggs": {
+                "child_terms": {"terms": {"field": "text", "order": {"_key": "asc"}}}
+            }
+        }
+    }))
+    .unwrap();
+
+    let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
+    // Exact expected structure and counts
+    assert_eq!(
+        res["parent_range"]["buckets"],
+        json!([
+            {
+                "key": "*-3",
+                "doc_count": 1,
+                "to": 3.0,
+                "child_terms": {
+                    "buckets": [
+                        {"doc_count": 1, "key": "cool"}
+                    ],
+                    "sum_other_doc_count": 0
+                }
+            },
+            {
+                "key": "3-7",
+                "doc_count": 3,
+                "from": 3.0,
+                "to": 7.0,
+                "child_terms": {
+                    "buckets": [
+                        {"doc_count": 2, "key": "cool"},
+                        {"doc_count": 1, "key": "nohit"}
+                    ],
+                    "sum_other_doc_count": 0
+                }
+            },
+            {
+                "key": "7-20",
+                "doc_count": 3,
+                "from": 7.0,
+                "to": 20.0,
+                "child_terms": {
+                    "buckets": [
+                        {"doc_count": 3, "key": "cool"}
+                    ],
+                    "sum_other_doc_count": 0
+                }
+            },
+            {
+                "key": "20-*",
+                "doc_count": 2,
+                "from": 20.0,
+                "child_terms": {
+                    "buckets": [
+                        {"doc_count": 1, "key": "cool"},
+                        {"doc_count": 1, "key": "nohit"}
+                    ],
+                    "sum_other_doc_count": 0
+                }
+            }
+        ])
+    );
+
+    // Case B: child has more buckets than parent
+    // Parent: histogram on score with large interval -> 1 bucket
+    // Child: terms on text -> 2 buckets (cool/nohit)
+    let agg_child_more: Aggregations = serde_json::from_value(json!({
+        "parent_hist": {
+            "histogram": {"field": "score", "interval": 100.0},
+            "aggs": {
+                "child_terms": {"terms": {"field": "text", "order": {"_key": "asc"}}}
+            }
+        }
+    }))
+    .unwrap();
+
+    let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
+    assert_eq!(
+        res["parent_hist"],
+        json!({
+            "buckets": [
+                {
+                    "key": 0.0,
+                    "doc_count": 9,
+                    "child_terms": {
+                        "buckets": [
+                            {"doc_count": 7, "key": "cool"},
+                            {"doc_count": 2, "key": "nohit"}
+                        ],
+                        "sum_other_doc_count": 0
+                    }
+                }
+            ]
+        })
+    );
+
+    Ok(())
+}
+
+#[test]
+fn test_range_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
+    let index = get_test_index_2_segments(false)?;
+
+    // Case A: parent has more buckets than child
+    // Parent: range with 5 buckets
+    // Child: coarse range with 3 buckets
+    let agg_parent_more: Aggregations = serde_json::from_value(json!({
+        "parent_range": {
+            "range": {
+                "field": "score",
+                "ranges": [
+                    {"to": 3.0},
+                    {"from": 3.0, "to": 7.0},
+                    {"from": 7.0, "to": 11.0},
+                    {"from": 11.0, "to": 20.0},
+                    {"from": 20.0}
+                ]
+            },
+            "aggs": {
+                "child_range": {
+                    "range": {
+                        "field": "score",
+                        "ranges": [
+                            {"to": 3.0},
+                            {"from": 3.0, "to": 20.0}
+                        ]
+                    }
+                }
+            }
+        }
+    }))
+    .unwrap();
+    let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
+    assert_eq!(
+        res["parent_range"]["buckets"],
+        json!([
+            {"key": "*-3", "doc_count": 1, "to": 3.0,
+                "child_range": {"buckets": [
+                    {"key": "*-3", "doc_count": 1, "to": 3.0},
+                    {"key": "3-20", "doc_count": 0, "from": 3.0, "to": 20.0},
+                    {"key": "20-*", "doc_count": 0, "from": 20.0}
+                ]}
+            },
+            {"key": "3-7", "doc_count": 3, "from": 3.0, "to": 7.0,
+                "child_range": {"buckets": [
+                    {"key": "*-3", "doc_count": 0, "to": 3.0},
+                    {"key": "3-20", "doc_count": 3, "from": 3.0, "to": 20.0},
+                    {"key": "20-*", "doc_count": 0, "from": 20.0}
+                ]}
+            },
+            {"key": "7-11", "doc_count": 1, "from": 7.0, "to": 11.0,
+                "child_range": {"buckets": [
+                    {"key": "*-3", "doc_count": 0, "to": 3.0},
+                    {"key": "3-20", "doc_count": 1, "from": 3.0, "to": 20.0},
+                    {"key": "20-*", "doc_count": 0, "from": 20.0}
+                ]}
+            },
+            {"key": "11-20", "doc_count": 2, "from": 11.0, "to": 20.0,
+                "child_range": {"buckets": [
+                    {"key": "*-3", "doc_count": 0, "to": 3.0},
+                    {"key": "3-20", "doc_count": 2, "from": 3.0, "to": 20.0},
+                    {"key": "20-*", "doc_count": 0, "from": 20.0}
+                ]}
+            },
+            {"key": "20-*", "doc_count": 2, "from": 20.0,
+                "child_range": {"buckets": [
+                    {"key": "*-3", "doc_count": 0, "to": 3.0},
+                    {"key": "3-20", "doc_count": 0, "from": 3.0, "to": 20.0},
+                    {"key": "20-*", "doc_count": 2, "from": 20.0}
+                ]}
+            }
+        ])
+    );
+
+    // Case B: child has more buckets than parent
+    // Parent: terms on text (2 buckets)
+    // Child: range with 4 buckets
+    let agg_child_more: Aggregations = serde_json::from_value(json!({
+        "parent_terms": {
+            "terms": {"field": "text"},
+            "aggs": {
+                "child_range": {
+                    "range": {
+                        "field": "score",
+                        "ranges": [
+                            {"to": 3.0},
+                            {"from": 3.0, "to": 7.0},
+                            {"from": 7.0, "to": 20.0}
+                        ]
+                    }
+                }
+            }
+        }
+    }))
+    .unwrap();
+    let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
+
+    assert_eq!(
+        res["parent_terms"],
+        json!({
+            "buckets": [
+                {
+                    "key": "cool",
+                    "doc_count": 7,
+                    "child_range": {
+                        "buckets": [
+                            {"key": "*-3", "doc_count": 1, "to": 3.0},
+                            {"key": "3-7", "doc_count": 2, "from": 3.0, "to": 7.0},
+                            {"key": "7-20", "doc_count": 3, "from": 7.0, "to": 20.0},
+                            {"key": "20-*", "doc_count": 1, "from": 20.0}
+                        ]
+                    }
+                },
+                {
+                    "key": "nohit",
+                    "doc_count": 2,
+                    "child_range": {
+                        "buckets": [
+                            {"key": "*-3", "doc_count": 0, "to": 3.0},
+                            {"key": "3-7", "doc_count": 1, "from": 3.0, "to": 7.0},
+                            {"key": "7-20", "doc_count": 0, "from": 7.0, "to": 20.0},
+                            {"key": "20-*", "doc_count": 1, "from": 20.0}
+                        ]
+                    }
+                }
+            ],
+            "doc_count_error_upper_bound": 0,
+            "sum_other_doc_count": 0
+        })
+    );
+
+    Ok(())
+}
+
+#[test]
+fn test_histogram_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
+    let index = get_test_index_2_segments(false)?;
+
+    // Case A: parent has more buckets than child
+    // Parent: range with several ranges
+    // Child: histogram with large interval (single bucket per parent)
+    let agg_parent_more: Aggregations = serde_json::from_value(json!({
+        "parent_range": {
+            "range": {
+                "field": "score",
+                "ranges": [
+                    {"to": 3.0},
+                    {"from": 3.0, "to": 7.0},
+                    {"from": 7.0, "to": 11.0},
+                    {"from": 11.0, "to": 20.0},
+                    {"from": 20.0}
+                ]
+            },
+            "aggs": {
+                "child_hist": {"histogram": {"field": "score", "interval": 100.0}}
+            }
+        }
+    }))
+    .unwrap();
+    let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
+    assert_eq!(
+        res["parent_range"]["buckets"],
+        json!([
+            {"key": "*-3", "doc_count": 1, "to": 3.0,
+                "child_hist": {"buckets": [ {"key": 0.0, "doc_count": 1} ]}
+            },
+            {"key": "3-7", "doc_count": 3, "from": 3.0, "to": 7.0,
+                "child_hist": {"buckets": [ {"key": 0.0, "doc_count": 3} ]}
+            },
+            {"key": "7-11", "doc_count": 1, "from": 7.0, "to": 11.0,
+                "child_hist": {"buckets": [ {"key": 0.0, "doc_count": 1} ]}
+            },
+            {"key": "11-20", "doc_count": 2, "from": 11.0, "to": 20.0,
+                "child_hist": {"buckets": [ {"key": 0.0, "doc_count": 2} ]}
+            },
+            {"key": "20-*", "doc_count": 2, "from": 20.0,
+                "child_hist": {"buckets": [ {"key": 0.0, "doc_count": 2} ]}
+            }
+        ])
+    );
+
+    // Case B: child has more buckets than parent
+    // Parent: terms on text -> 2 buckets
+    // Child: histogram with small interval -> multiple buckets including empties
+    let agg_child_more: Aggregations = serde_json::from_value(json!({
+        "parent_terms": {
+            "terms": {"field": "text"},
+            "aggs": {
+                "child_hist": {"histogram": {"field": "score", "interval": 10.0}}
+            }
+        }
+    }))
+    .unwrap();
+    let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
+    assert_eq!(
+        res["parent_terms"],
+        json!({
+            "buckets": [
+                {
+                    "key": "cool",
+                    "doc_count": 7,
+                    "child_hist": {
+                        "buckets": [
+                            {"key": 0.0, "doc_count": 4},
+                            {"key": 10.0, "doc_count": 2},
+                            {"key": 20.0, "doc_count": 0},
+                            {"key": 30.0, "doc_count": 0},
+                            {"key": 40.0, "doc_count": 1}
+                        ]
+                    }
+                },
+                {
+                    "key": "nohit",
+                    "doc_count": 2,
+                    "child_hist": {
+                        "buckets": [
+                            {"key": 0.0, "doc_count": 1},
+                            {"key": 10.0, "doc_count": 0},
+                            {"key": 20.0, "doc_count": 0},
+                            {"key": 30.0, "doc_count": 0},
+                            {"key": 40.0, "doc_count": 1}
+                        ]
+                    }
+                }
+            ],
+            "doc_count_error_upper_bound": 0,
+            "sum_other_doc_count": 0
+        })
+    );
+
+    Ok(())
+}
+
+#[test]
+fn test_date_histogram_as_subagg_parent_more_vs_child_more() -> crate::Result<()> {
+    let index = get_test_index_2_segments(false)?;
+
+    // Case A: parent has more buckets than child
+    // Parent: range with several buckets
+    // Child: date_histogram with 30d -> single bucket per parent
+    let agg_parent_more: Aggregations = serde_json::from_value(json!({
+        "parent_range": {
+            "range": {
+                "field": "score",
+                "ranges": [
+                    {"to": 3.0},
+                    {"from": 3.0, "to": 7.0},
+                    {"from": 7.0, "to": 11.0},
+                    {"from": 11.0, "to": 20.0},
+                    {"from": 20.0}
+                ]
+            },
+            "aggs": {
+                "child_date_hist": {"date_histogram": {"field": "date", "fixed_interval": "30d"}}
+            }
+        }
+    }))
+    .unwrap();
+    let res = crate::aggregation::tests::exec_request(agg_parent_more, &index)?;
+    let buckets = res["parent_range"]["buckets"].as_array().unwrap();
+    // Verify each parent bucket has exactly one child date bucket with matching doc_count
+    for bucket in buckets {
+        let parent_count = bucket["doc_count"].as_u64().unwrap();
+        let child_buckets = bucket["child_date_hist"]["buckets"].as_array().unwrap();
+        assert_eq!(child_buckets.len(), 1);
+        assert_eq!(child_buckets[0]["doc_count"], parent_count);
+    }
+
+    // Case B: child has more buckets than parent
+    // Parent: terms on text (2 buckets)
+    // Child: date_histogram with 1d -> multiple buckets
+    let agg_child_more: Aggregations = serde_json::from_value(json!({
+        "parent_terms": {
+            "terms": {"field": "text"},
+            "aggs": {
+                "child_date_hist": {"date_histogram": {"field": "date", "fixed_interval": "1d"}}
+            }
+        }
+    }))
+    .unwrap();
+    let res = crate::aggregation::tests::exec_request(agg_child_more, &index)?;
+    let buckets = res["parent_terms"]["buckets"].as_array().unwrap();
+
+    // cool bucket
+    assert_eq!(buckets[0]["key"], "cool");
+    let cool_buckets = buckets[0]["child_date_hist"]["buckets"].as_array().unwrap();
+    assert_eq!(cool_buckets.len(), 3);
+    assert_eq!(cool_buckets[0]["doc_count"], 1); // day 0
+    assert_eq!(cool_buckets[1]["doc_count"], 4); // day 1
+    assert_eq!(cool_buckets[2]["doc_count"], 2); // day 2
+
+    // nohit bucket
+    assert_eq!(buckets[1]["key"], "nohit");
+    let nohit_buckets = buckets[1]["child_date_hist"]["buckets"].as_array().unwrap();
+    assert_eq!(nohit_buckets.len(), 2);
+    assert_eq!(nohit_buckets[0]["doc_count"], 1); // day 1
+    assert_eq!(nohit_buckets[1]["doc_count"], 1); // day 2
+
+    Ok(())
+}
+
 fn get_avg_req(field_name: &str) -> Aggregation {
     serde_json::from_value(json!({
         "avg": {
@@ -26,6 +451,10 @@ fn get_collector(agg_req: Aggregations) -> AggregationCollector {
 }
 
 // *** EVERY BUCKET-TYPE SHOULD BE TESTED HERE ***
+// Note: The flushng part of these  tests are outdated, since the buffering change after converting
+// the collection into one collector per request instead of per bucket.
+//
+// However they are useful as they test a complex aggregation requests.
 fn test_aggregation_flushing(
     merge_segments: bool,
     use_distributed_collector: bool,
@@ -38,8 +467,9 @@ fn test_aggregation_flushing(
 
     let reader = index.reader()?;
 
-    assert_eq!(DOC_BLOCK_SIZE, 64);
-    // In the tree we cache Documents of DOC_BLOCK_SIZE, before passing them down as one block.
+    assert_eq!(COLLECT_BLOCK_BUFFER_LEN, 64);
+    // In the tree we cache documents of COLLECT_BLOCK_BUFFER_LEN before passing them down as one
+    // block.
     //
     // Build a request so that on the first level we have one full cache, which is then flushed.
     // The same cache should have some residue docs at the end, which are flushed (Range 0-70)
@@ -128,10 +558,8 @@ fn test_aggregation_flushing(
             .unwrap();
 
     let agg_res: AggregationResults = if use_distributed_collector {
-        let collector = DistributedAggregationCollector::from_aggs(
-            agg_req.clone(),
-            AggregationLimitsGuard::default(),
-        );
+        let collector =
+            DistributedAggregationCollector::from_aggs(agg_req.clone(), Default::default());
 
         let searcher = reader.searcher();
         let intermediate_agg_result = searcher.search(&AllQuery, &collector).unwrap();
@@ -155,7 +583,7 @@ fn test_aggregation_flushing(
         searcher.search(&AllQuery, &collector).unwrap()
     };
 
-    let res: Value = serde_json::to_value(&agg_res)?;
+    let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
 
     assert_eq!(res["bucketsL1"]["buckets"][0]["doc_count"], 3);
     assert_eq!(
@@ -270,7 +698,7 @@ fn test_aggregation_level1_simple() -> crate::Result<()> {
     let searcher = reader.searcher();
     let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();
 
-    let res: Value = serde_json::to_value(&agg_res)?;
+    let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
     assert_eq!(res["average"]["value"], 12.142857142857142);
     assert_eq!(
         res["range"]["buckets"],
@@ -304,29 +732,6 @@ fn test_aggregation_level1_simple() -> crate::Result<()> {
     Ok(())
 }
 
-#[test]
-fn test_aggregation_term_truncate_sum_other_doc_count() {
-    let index = get_test_index_2_segments(true).unwrap();
-    let reader = index.reader().unwrap();
-    let count_per_text: Aggregation = serde_json::from_value(json!({ "terms": { "field": "text", "size": 1 } })).unwrap();
-    let aggs: Aggregations = vec![("group_by_term_truncate".to_string(),  count_per_text)]
-        .into_iter()
-        .collect();
-
-    let collector = get_collector(aggs);
-    let searcher = reader.searcher();
-    let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
-
-    let res: Value = serde_json::to_value(&agg_res).unwrap();
-    assert_eq!(res, serde_json::json!({
-        "group_by_term_truncate": {
-             "buckets": [{ "doc_count": 7, "key": "cool" }],
-             "doc_count_error_upper_bound": 0,
-             "sum_other_doc_count": 2,
-         },
-    }));
-}
-
 #[test]
 fn test_aggregation_level1() -> crate::Result<()> {
     let index = get_test_index_2_segments(true)?;
@@ -365,7 +770,7 @@ fn test_aggregation_level1() -> crate::Result<()> {
     let searcher = reader.searcher();
     let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();
 
-    let res: Value = serde_json::to_value(&agg_res)?;
+    let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
     assert_eq!(res["average"]["value"], 12.142857142857142);
     assert_eq!(res["average_f64"]["value"], 12.214285714285714);
     assert_eq!(res["average_i64"]["value"], 12.142857142857142);
@@ -420,7 +825,7 @@ fn test_aggregation_level2(
         IndexRecordOption::Basic,
     );
 
-    let elasticsearch_compatible_json_req = serde_json::json!(
+    let elasticsearch_compatible_json_req = r#"
 {
   "rangef64": {
     "range": {
@@ -473,8 +878,9 @@ fn test_aggregation_level2(
       "term_agg": { "terms": { "field": "text" } }
     }
   }
-});
-    let agg_req: Aggregations = serde_json::from_value(elasticsearch_compatible_json_req).unwrap();
+}
+"#;
+    let agg_req: Aggregations = serde_json::from_str(elasticsearch_compatible_json_req).unwrap();
 
     let agg_res: AggregationResults = if use_distributed_collector {
         let collector =
@@ -491,7 +897,7 @@ fn test_aggregation_level2(
         searcher.search(&term_query, &collector).unwrap()
     };
 
-    let res: Value = serde_json::to_value(agg_res)?;
+    let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
 
     assert_eq!(res["range"]["buckets"][1]["key"], "3-7");
     assert_eq!(res["range"]["buckets"][1]["doc_count"], 2u64);

src/aggregation/bucket/histogram/histogram.rs

@@ -1,25 +1,49 @@
 use std::cmp::Ordering;
 
+use columnar::{Column, ColumnType};
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 use tantivy_bitpacker::minmax;
 
-use crate::aggregation::agg_limits::MemoryConsumption;
-use crate::aggregation::agg_req::Aggregations;
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationWithAccessor, AggregationsWithAccessor,
+use crate::aggregation::agg_data::{
+    build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
 };
+use crate::aggregation::agg_req::Aggregations;
 use crate::aggregation::agg_result::BucketEntry;
+use crate::aggregation::cached_sub_aggs::CachedSubAggs;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
     IntermediateHistogramBucketEntry,
 };
-use crate::aggregation::segment_agg_result::{
-    build_segment_agg_collector, SegmentAggregationCollector,
-};
+use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
 use crate::aggregation::*;
 use crate::TantivyError;
 
+/// Contains all information required by the SegmentHistogramCollector to perform the
+/// histogram or date_histogram aggregation on a segment.
+pub struct HistogramAggReqData {
+    /// The column accessor to access the fast field values.
+    pub accessor: Column<u64>,
+    /// The field type of the fast field.
+    pub field_type: ColumnType,
+    /// The name of the aggregation.
+    pub name: String,
+    /// The histogram aggregation request.
+    pub req: HistogramAggregation,
+    /// True if this is a date_histogram aggregation.
+    pub is_date_histogram: bool,
+    /// The bounds to limit the buckets to.
+    pub bounds: HistogramBounds,
+    /// The offset used to calculate the bucket position.
+    pub offset: f64,
+}
+impl HistogramAggReqData {
+    /// Estimate the memory consumption of this struct in bytes.
+    pub fn get_memory_consumption(&self) -> usize {
+        std::mem::size_of::<Self>()
+    }
+}
+
 /// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
 /// Each document value is rounded down to its bucket.
 ///
@@ -228,18 +252,24 @@ impl HistogramBounds {
 pub(crate) struct SegmentHistogramBucketEntry {
     pub key: f64,
     pub doc_count: u64,
+    pub bucket_id: BucketId,
 }
 
 impl SegmentHistogramBucketEntry {
     pub(crate) fn into_intermediate_bucket_entry(
         self,
-        sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        sub_aggregation: &mut Option<CachedSubAggs>,
+        agg_data: &AggregationsSegmentCtx,
     ) -> crate::Result<IntermediateHistogramBucketEntry> {
         let mut sub_aggregation_res = IntermediateAggregationResults::default();
         if let Some(sub_aggregation) = sub_aggregation {
             sub_aggregation
-                .add_intermediate_aggregation_result(agg_with_accessor, &mut sub_aggregation_res)?;
+                .get_sub_agg_collector()
+                .add_intermediate_aggregation_result(
+                    agg_data,
+                    &mut sub_aggregation_res,
+                    self.bucket_id,
+                )?;
         }
         Ok(IntermediateHistogramBucketEntry {
             key: self.key,
@@ -249,31 +279,38 @@ impl SegmentHistogramBucketEntry {
     }
 }
 
+#[derive(Clone, Debug, Default)]
+struct HistogramBuckets {
+    pub buckets: FxHashMap<i64, SegmentHistogramBucketEntry>,
+}
+
 /// The collector puts values from the fast field into the correct buckets and does a conversion to
 /// the correct datatype.
-#[derive(Clone, Debug)]
+#[derive(Debug)]
 pub struct SegmentHistogramCollector {
     /// The buckets containing the aggregation data.
-    buckets: FxHashMap<i64, SegmentHistogramBucketEntry>,
-    sub_aggregations: FxHashMap<i64, Box<dyn SegmentAggregationCollector>>,
-    sub_aggregation_blueprint: Option<Box<dyn SegmentAggregationCollector>>,
-    column_type: ColumnType,
-    interval: f64,
-    offset: f64,
-    bounds: HistogramBounds,
+    /// One Histogram bucket per parent bucket id.
+    parent_buckets: Vec<HistogramBuckets>,
+    sub_agg: Option<CachedSubAggs>,
     accessor_idx: usize,
+    bucket_id_provider: BucketIdProvider,
 }
 
 impl SegmentAggregationCollector for SegmentHistogramCollector {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
-        let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
-
-        let bucket = self.into_intermediate_bucket_result(agg_with_accessor)?;
+        let name = agg_data
+            .get_histogram_req_data(self.accessor_idx)
+            .name
+            .clone();
+        // TODO: avoid prepare_max_bucket here and handle empty buckets.
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
+        let histogram = std::mem::take(&mut self.parent_buckets[parent_bucket_id as usize]);
+        let bucket = self.add_intermediate_bucket_result(agg_data, histogram)?;
         results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
 
         Ok(())
@@ -282,72 +319,77 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
     #[inline]
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collect_block(&[doc], agg_with_accessor)
-    }
-
-    #[inline]
-    fn collect_block(
-        &mut self,
+        parent_bucket_id: BucketId,
         docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
-
+        let req = agg_data.take_histogram_req_data(self.accessor_idx);
         let mem_pre = self.get_memory_consumption();
+        let buckets = &mut self.parent_buckets[parent_bucket_id as usize].buckets;
 
-        let bounds = self.bounds;
-        let interval = self.interval;
-        let offset = self.offset;
-        let get_bucket_pos = |val| (get_bucket_pos_f64(val, interval, offset) as i64);
+        let bounds = req.bounds;
+        let interval = req.req.interval;
+        let offset = req.offset;
+        let get_bucket_pos = |val| get_bucket_pos_f64(val, interval, offset) as i64;
 
-        bucket_agg_accessor
+        agg_data
             .column_block_accessor
-            .fetch_block(docs, &bucket_agg_accessor.accessor);
-
-        for (doc, val) in bucket_agg_accessor
+            .fetch_block(docs, &req.accessor);
+        for (doc, val) in agg_data
             .column_block_accessor
-            .iter_docid_vals(docs, &bucket_agg_accessor.accessor)
+            .iter_docid_vals(docs, &req.accessor)
         {
-            let val = self.f64_from_fastfield_u64(val);
-
+            let val = f64_from_fastfield_u64(val, req.field_type);
             let bucket_pos = get_bucket_pos(val);
-
             if bounds.contains(val) {
-                let bucket = self.buckets.entry(bucket_pos).or_insert_with(|| {
+                let bucket = buckets.entry(bucket_pos).or_insert_with(|| {
                     let key = get_bucket_key_from_pos(bucket_pos as f64, interval, offset);
-                    SegmentHistogramBucketEntry { key, doc_count: 0 }
+                    SegmentHistogramBucketEntry {
+                        key,
+                        doc_count: 0,
+                        bucket_id: self.bucket_id_provider.next_bucket_id(),
+                    }
                 });
                 bucket.doc_count += 1;
-                if let Some(sub_aggregation_blueprint) = self.sub_aggregation_blueprint.as_mut() {
-                    self.sub_aggregations
-                        .entry(bucket_pos)
-                        .or_insert_with(|| sub_aggregation_blueprint.clone())
-                        .collect(doc, &mut bucket_agg_accessor.sub_aggregation)?;
+                if let Some(sub_agg) = &mut self.sub_agg {
+                    sub_agg.push(bucket.bucket_id, doc);
                 }
             }
         }
+        agg_data.put_back_histogram_req_data(self.accessor_idx, req);
 
         let mem_delta = self.get_memory_consumption() - mem_pre;
         if mem_delta > 0 {
-            bucket_agg_accessor
+            agg_data
+                .context
                 .limits
                 .add_memory_consumed(mem_delta as u64)?;
         }
 
+        if let Some(sub_agg) = &mut self.sub_agg {
+            sub_agg.check_flush_local(agg_data)?;
+        }
+
         Ok(())
     }
 
-    fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
-        let sub_aggregation_accessor =
-            &mut agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
-
-        for sub_aggregation in self.sub_aggregations.values_mut() {
-            sub_aggregation.flush(sub_aggregation_accessor)?;
+    fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
+        if let Some(sub_aggregation) = &mut self.sub_agg {
+            sub_aggregation.flush(agg_data)?;
         }
+        Ok(())
+    }
 
+    fn prepare_max_bucket(
+        &mut self,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        while self.parent_buckets.len() <= max_bucket as usize {
+            self.parent_buckets.push(HistogramBuckets {
+                buckets: FxHashMap::default(),
+            });
+        }
         Ok(())
     }
 }
@@ -355,72 +397,62 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
 impl SegmentHistogramCollector {
     fn get_memory_consumption(&self) -> usize {
         let self_mem = std::mem::size_of::<Self>();
-        let sub_aggs_mem = self.sub_aggregations.memory_consumption();
-        let buckets_mem = self.buckets.memory_consumption();
-        self_mem + sub_aggs_mem + buckets_mem
+        let buckets_mem = self.parent_buckets.len() * std::mem::size_of::<HistogramBuckets>();
+        self_mem + buckets_mem
     }
     /// Converts the collector result into a intermediate bucket result.
-    pub fn into_intermediate_bucket_result(
-        self,
-        agg_with_accessor: &AggregationWithAccessor,
+    fn add_intermediate_bucket_result(
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
+        histogram: HistogramBuckets,
     ) -> crate::Result<IntermediateBucketResult> {
-        let mut buckets = Vec::with_capacity(self.buckets.len());
+        let mut buckets = Vec::with_capacity(histogram.buckets.len());
 
-        for (bucket_pos, bucket) in self.buckets {
-            let bucket_res = bucket.into_intermediate_bucket_entry(
-                self.sub_aggregations.get(&bucket_pos).cloned(),
-                &agg_with_accessor.sub_aggregation,
-            );
+        for bucket in histogram.buckets.into_values() {
+            let bucket_res = bucket.into_intermediate_bucket_entry(&mut self.sub_agg, agg_data);
 
             buckets.push(bucket_res?);
         }
         buckets.sort_unstable_by(|b1, b2| b1.key.total_cmp(&b2.key));
 
+        let is_date_agg = agg_data
+            .get_histogram_req_data(self.accessor_idx)
+            .field_type
+            == ColumnType::DateTime;
         Ok(IntermediateBucketResult::Histogram {
             buckets,
-            is_date_agg: self.column_type == ColumnType::DateTime,
+            is_date_agg,
         })
     }
 
     pub(crate) fn from_req_and_validate(
-        mut req: HistogramAggregation,
-        sub_aggregation: &mut AggregationsWithAccessor,
-        field_type: ColumnType,
-        accessor_idx: usize,
+        agg_data: &mut AggregationsSegmentCtx,
+        node: &AggRefNode,
     ) -> crate::Result<Self> {
-        req.validate()?;
-        if field_type == ColumnType::DateTime {
-            req.normalize_date_time();
-        }
-
-        let sub_aggregation_blueprint = if sub_aggregation.is_empty() {
-            None
+        let sub_agg = if !node.children.is_empty() {
+            Some(build_segment_agg_collectors(agg_data, &node.children)?)
         } else {
-            let sub_aggregation = build_segment_agg_collector(sub_aggregation)?;
-            Some(sub_aggregation)
+            None
         };
-
-        let bounds = req.hard_bounds.unwrap_or(HistogramBounds {
+        let req_data = agg_data.get_histogram_req_data_mut(node.idx_in_req_data);
+        req_data.req.validate()?;
+        if req_data.field_type == ColumnType::DateTime && !req_data.is_date_histogram {
+            req_data.req.normalize_date_time();
+        }
+        req_data.bounds = req_data.req.hard_bounds.unwrap_or(HistogramBounds {
             min: f64::MIN,
             max: f64::MAX,
         });
+        req_data.offset = req_data.req.offset.unwrap_or(0.0);
+        let sub_agg = sub_agg.map(CachedSubAggs::new);
 
         Ok(Self {
-            buckets: Default::default(),
-            column_type: field_type,
-            interval: req.interval,
-            offset: req.offset.unwrap_or(0.0),
-            bounds,
-            sub_aggregations: Default::default(),
-            sub_aggregation_blueprint,
-            accessor_idx,
+            parent_buckets: Default::default(),
+            sub_agg,
+            accessor_idx: node.idx_in_req_data,
+            bucket_id_provider: BucketIdProvider::default(),
         })
     }
-
-    #[inline]
-    fn f64_from_fastfield_u64(&self, val: u64) -> f64 {
-        f64_from_fastfield_u64(val, &self.column_type)
-    }
 }
 
 #[inline]

src/aggregation/bucket/mod.rs

@@ -22,6 +22,7 @@
 //! - [Range](RangeAggregation)
 //! - [Terms](TermsAggregation)
 
+mod filter;
 mod histogram;
 mod range;
 mod term_agg;
@@ -30,6 +31,7 @@ mod term_missing_agg;
 use std::collections::HashMap;
 use std::fmt;
 
+pub use filter::*;
 pub use histogram::*;
 pub use range::*;
 use serde::{de, Deserialize, Deserializer, Serialize, Serializer};

src/aggregation/bucket/range.rs

@@ -1,20 +1,45 @@
 use std::fmt::Debug;
 use std::ops::Range;
 
+use columnar::{Column, ColumnType};
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 
-use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
+use crate::aggregation::agg_data::{
+    build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
+};
+use crate::aggregation::agg_limits::AggregationLimitsGuard;
+use crate::aggregation::cached_sub_aggs::CachedSubAggs;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
     IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
 };
-use crate::aggregation::segment_agg_result::{
-    build_segment_agg_collector, SegmentAggregationCollector,
-};
+use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
 use crate::aggregation::*;
 use crate::TantivyError;
 
+/// Contains all information required by the SegmentRangeCollector to perform the
+/// range aggregation on a segment.
+pub struct RangeAggReqData {
+    /// The column accessor to access the fast field values.
+    pub accessor: Column<u64>,
+    /// The type of the fast field.
+    pub field_type: ColumnType,
+    /// The range aggregation request.
+    pub req: RangeAggregation,
+    /// The name of the aggregation.
+    pub name: String,
+    /// Whether this is a top-level aggregation.
+    pub is_top_level: bool,
+}
+
+impl RangeAggReqData {
+    /// Estimate the memory consumption of this struct in bytes.
+    pub fn get_memory_consumption(&self) -> usize {
+        std::mem::size_of::<Self>()
+    }
+}
+
 /// Provide user-defined buckets to aggregate on.
 ///
 /// Two special buckets will automatically be created to cover the whole range of values.
@@ -128,19 +153,47 @@ pub(crate) struct SegmentRangeAndBucketEntry {
 
 /// The collector puts values from the fast field into the correct buckets and does a conversion to
 /// the correct datatype.
-#[derive(Clone, Debug)]
-pub struct SegmentRangeCollector {
+pub struct SegmentRangeCollector<const LOWCARD: bool = false> {
     /// The buckets containing the aggregation data.
-    buckets: Vec<SegmentRangeAndBucketEntry>,
+    /// One for each ParentBucketId
+    parent_buckets: Vec<Vec<SegmentRangeAndBucketEntry>>,
     column_type: ColumnType,
     pub(crate) accessor_idx: usize,
+    sub_agg: Option<CachedSubAggs<LOWCARD>>,
+    /// Here things get a bit weird. We need to assign unique bucket ids across all
+    /// parent buckets. So we keep track of the next available bucket id here.
+    /// This allows a kind of flattening of the bucket ids across all parent buckets.
+    /// E.g. in nested aggregations:
+    /// Term Agg -> Range aggregation -> Stats aggregation
+    /// E.g. the Term Agg creates 3 buckets ["INFO", "ERROR", "WARN"], each of these has a Range
+    /// aggregation with 4 buckets. The Range aggregation will create buckets with ids:
+    /// - INFO: 0,1,2,3
+    /// - ERROR: 4,5,6,7
+    /// - WARN: 8,9,10,11
+    ///
+    /// This allows the Stats aggregation to have unique bucket ids to refer to.
+    bucket_id_provider: BucketIdProvider,
+    limits: AggregationLimitsGuard,
 }
 
+impl<const LOWCARD: bool> Debug for SegmentRangeCollector<LOWCARD> {
+    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+        f.debug_struct("SegmentRangeCollector")
+            .field("parent_buckets_len", &self.parent_buckets.len())
+            .field("column_type", &self.column_type)
+            .field("accessor_idx", &self.accessor_idx)
+            .field("has_sub_agg", &self.sub_agg.is_some())
+            .finish()
+    }
+}
+
+/// TODO: Bad naming, there's also SegmentRangeAndBucketEntry
 #[derive(Clone)]
 pub(crate) struct SegmentRangeBucketEntry {
     pub key: Key,
     pub doc_count: u64,
-    pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
+    // pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
+    pub bucket_id: BucketId,
     /// The from range of the bucket. Equals `f64::MIN` when `None`.
     pub from: Option<f64>,
     /// The to range of the bucket. Equals `f64::MAX` when `None`. Open interval, `to` is not
@@ -161,46 +214,50 @@ impl Debug for SegmentRangeBucketEntry {
 impl SegmentRangeBucketEntry {
     pub(crate) fn into_intermediate_bucket_entry(
         self,
-        agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<IntermediateRangeBucketEntry> {
-        let mut sub_aggregation_res = IntermediateAggregationResults::default();
-        if let Some(sub_aggregation) = self.sub_aggregation {
-            sub_aggregation
-                .add_intermediate_aggregation_result(agg_with_accessor, &mut sub_aggregation_res)?
-        } else {
-            Default::default()
-        };
+        let sub_aggregation = IntermediateAggregationResults::default();
 
         Ok(IntermediateRangeBucketEntry {
             key: self.key.into(),
             doc_count: self.doc_count,
-            sub_aggregation: sub_aggregation_res,
+            sub_aggregation_res: sub_aggregation,
             from: self.from,
             to: self.to,
         })
     }
 }
 
-impl SegmentAggregationCollector for SegmentRangeCollector {
+impl<const LOWCARD: bool> SegmentAggregationCollector for SegmentRangeCollector<LOWCARD> {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
         let field_type = self.column_type;
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
-        let sub_agg = &agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
+        let name = agg_data
+            .get_range_req_data(self.accessor_idx)
+            .name
+            .to_string();
 
-        let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
-            .buckets
+        let buckets = std::mem::take(&mut self.parent_buckets[parent_bucket_id as usize]);
+
+        let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = buckets
             .into_iter()
-            .map(move |range_bucket| {
-                Ok((
-                    range_to_string(&range_bucket.range, &field_type)?,
-                    range_bucket
-                        .bucket
-                        .into_intermediate_bucket_entry(sub_agg)?,
-                ))
+            .map(|range_bucket| {
+                let bucket_id = range_bucket.bucket.bucket_id;
+                let mut agg = range_bucket.bucket.into_intermediate_bucket_entry()?;
+                if let Some(sub_aggregation) = &mut self.sub_agg {
+                    sub_aggregation
+                        .get_sub_agg_collector()
+                        .add_intermediate_aggregation_result(
+                            agg_data,
+                            &mut agg.sub_aggregation_res,
+                            bucket_id,
+                        )?;
+                }
+                Ok((range_to_string(&range_bucket.range, &field_type)?, agg))
             })
             .collect::<crate::Result<_>>()?;
 
@@ -217,69 +274,114 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
     #[inline]
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collect_block(&[doc], agg_with_accessor)
-    }
-
-    #[inline]
-    fn collect_block(
-        &mut self,
+        parent_bucket_id: BucketId,
         docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
+        let req = agg_data.take_range_req_data(self.accessor_idx);
 
-        bucket_agg_accessor
+        agg_data
             .column_block_accessor
-            .fetch_block(docs, &bucket_agg_accessor.accessor);
+            .fetch_block(docs, &req.accessor);
 
-        for (doc, val) in bucket_agg_accessor
+        let buckets = &mut self.parent_buckets[parent_bucket_id as usize];
+
+        for (doc, val) in agg_data
             .column_block_accessor
-            .iter_docid_vals(docs, &bucket_agg_accessor.accessor)
+            .iter_docid_vals(docs, &req.accessor)
         {
-            let bucket_pos = self.get_bucket_pos(val);
-
-            let bucket = &mut self.buckets[bucket_pos];
-
+            let bucket_pos = get_bucket_pos(val, buckets);
+            let bucket = &mut buckets[bucket_pos];
             bucket.bucket.doc_count += 1;
-            if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
-                sub_aggregation.collect(doc, &mut bucket_agg_accessor.sub_aggregation)?;
+            if let Some(sub_agg) = self.sub_agg.as_mut() {
+                sub_agg.push(bucket.bucket.bucket_id, doc);
             }
         }
 
+        agg_data.put_back_range_req_data(self.accessor_idx, req);
+        if let Some(sub_agg) = self.sub_agg.as_mut() {
+            sub_agg.check_flush_local(agg_data)?;
+        }
+
         Ok(())
     }
 
-    fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
-        let sub_aggregation_accessor =
-            &mut agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
+    fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
+        if let Some(sub_agg) = self.sub_agg.as_mut() {
+            sub_agg.flush(agg_data)?;
+        }
+        Ok(())
+    }
 
-        for bucket in self.buckets.iter_mut() {
-            if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
-                sub_agg.flush(sub_aggregation_accessor)?;
-            }
+    fn prepare_max_bucket(
+        &mut self,
+        max_bucket: BucketId,
+        agg_data: &AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        while self.parent_buckets.len() <= max_bucket as usize {
+            let new_buckets = self.create_new_buckets(agg_data)?;
+            self.parent_buckets.push(new_buckets);
         }
 
         Ok(())
     }
 }
+/// Build a concrete `SegmentRangeCollector` with either a Vec- or HashMap-backed
+/// bucket storage, depending on the column type and aggregation level.
+pub(crate) fn build_segment_range_collector(
+    agg_data: &mut AggregationsSegmentCtx,
+    node: &AggRefNode,
+) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
+    let accessor_idx = node.idx_in_req_data;
+    let req_data = agg_data.get_range_req_data(node.idx_in_req_data);
+    let field_type = req_data.field_type;
 
-impl SegmentRangeCollector {
-    pub(crate) fn from_req_and_validate(
-        req: &RangeAggregation,
-        sub_aggregation: &mut AggregationsWithAccessor,
-        limits: &mut AggregationLimitsGuard,
-        field_type: ColumnType,
-        accessor_idx: usize,
-    ) -> crate::Result<Self> {
+    // TODO: A better metric instead of is_top_level would be the number of buckets expected.
+    // E.g. If range agg is not top level, but the parent is a bucket agg with less than 10 buckets,
+    // we can are still in low cardinality territory.
+    let is_low_card = req_data.is_top_level && req_data.req.ranges.len() <= 64;
+
+    let sub_agg = if !node.children.is_empty() {
+        Some(build_segment_agg_collectors(agg_data, &node.children)?)
+    } else {
+        None
+    };
+
+    if is_low_card {
+        Ok(Box::new(SegmentRangeCollector {
+            sub_agg: sub_agg.map(CachedSubAggs::<true>::new),
+            column_type: field_type,
+            accessor_idx,
+            parent_buckets: Vec::new(),
+            bucket_id_provider: BucketIdProvider::default(),
+            limits: agg_data.context.limits.clone(),
+        }))
+    } else {
+        Ok(Box::new(SegmentRangeCollector {
+            sub_agg: sub_agg.map(CachedSubAggs::<false>::new),
+            column_type: field_type,
+            accessor_idx,
+            parent_buckets: Vec::new(),
+            bucket_id_provider: BucketIdProvider::default(),
+            limits: agg_data.context.limits.clone(),
+        }))
+    }
+}
+
+impl<const LOWCARD: bool> SegmentRangeCollector<LOWCARD> {
+    pub(crate) fn create_new_buckets(
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
+    ) -> crate::Result<Vec<SegmentRangeAndBucketEntry>> {
+        let field_type = self.column_type;
+        let req_data = agg_data.get_range_req_data(self.accessor_idx);
         // The range input on the request is f64.
         // We need to convert to u64 ranges, because we read the values as u64.
         // The mapping from the conversion is monotonic so ordering is preserved.
-        let buckets: Vec<_> = extend_validate_ranges(&req.ranges, &field_type)?
+        let buckets: Vec<_> = extend_validate_ranges(&req_data.req.ranges, &field_type)?
             .iter()
             .map(|range| {
+                let bucket_id = self.bucket_id_provider.next_bucket_id();
                 let key = range
                     .key
                     .clone()
@@ -288,24 +390,20 @@ impl SegmentRangeCollector {
                 let to = if range.range.end == u64::MAX {
                     None
                 } else {
-                    Some(f64_from_fastfield_u64(range.range.end, &field_type))
+                    Some(f64_from_fastfield_u64(range.range.end, field_type))
                 };
                 let from = if range.range.start == u64::MIN {
                     None
                 } else {
-                    Some(f64_from_fastfield_u64(range.range.start, &field_type))
-                };
-                let sub_aggregation = if sub_aggregation.is_empty() {
-                    None
-                } else {
-                    Some(build_segment_agg_collector(sub_aggregation)?)
+                    Some(f64_from_fastfield_u64(range.range.start, field_type))
                 };
+                // let sub_aggregation = sub_agg_prototype.clone();
 
                 Ok(SegmentRangeAndBucketEntry {
                     range: range.range.clone(),
                     bucket: SegmentRangeBucketEntry {
                         doc_count: 0,
-                        sub_aggregation,
+                        bucket_id,
                         key,
                         from,
                         to,
@@ -314,27 +412,20 @@ impl SegmentRangeCollector {
             })
             .collect::<crate::Result<_>>()?;
 
-        limits.add_memory_consumed(
+        self.limits.add_memory_consumed(
             buckets.len() as u64 * std::mem::size_of::<SegmentRangeAndBucketEntry>() as u64,
         )?;
-
-        Ok(SegmentRangeCollector {
-            buckets,
-            column_type: field_type,
-            accessor_idx,
-        })
-    }
-
-    #[inline]
-    fn get_bucket_pos(&self, val: u64) -> usize {
-        let pos = self
-            .buckets
-            .binary_search_by_key(&val, |probe| probe.range.start)
-            .unwrap_or_else(|pos| pos - 1);
-        debug_assert!(self.buckets[pos].range.contains(&val));
-        pos
+        Ok(buckets)
     }
 }
+#[inline]
+fn get_bucket_pos(val: u64, buckets: &[SegmentRangeAndBucketEntry]) -> usize {
+    let pos = buckets
+        .binary_search_by_key(&val, |probe| probe.range.start)
+        .unwrap_or_else(|pos| pos - 1);
+    debug_assert!(buckets[pos].range.contains(&val));
+    pos
+}
 
 /// Converts the user provided f64 range value to fast field value space.
 ///
@@ -431,7 +522,7 @@ pub(crate) fn range_to_string(
             let val = i64::from_u64(val);
             format_date(val)
         } else {
-            Ok(f64_from_fastfield_u64(val, field_type).to_string())
+            Ok(f64_from_fastfield_u64(val, *field_type).to_string())
         }
     };
 
@@ -467,15 +558,48 @@ mod tests {
             ranges,
             ..Default::default()
         };
+        // Build buckets directly as in from_req_and_validate without AggregationsData
+        let buckets: Vec<_> = extend_validate_ranges(&req.ranges, &field_type)
+            .expect("unexpected error in extend_validate_ranges")
+            .iter()
+            .map(|range| {
+                let key = range
+                    .key
+                    .clone()
+                    .map(|key| Ok(Key::Str(key)))
+                    .unwrap_or_else(|| range_to_key(&range.range, &field_type))
+                    .expect("unexpected error in range_to_key");
+                let to = if range.range.end == u64::MAX {
+                    None
+                } else {
+                    Some(f64_from_fastfield_u64(range.range.end, field_type))
+                };
+                let from = if range.range.start == u64::MIN {
+                    None
+                } else {
+                    Some(f64_from_fastfield_u64(range.range.start, field_type))
+                };
+                SegmentRangeAndBucketEntry {
+                    range: range.range.clone(),
+                    bucket: SegmentRangeBucketEntry {
+                        doc_count: 0,
+                        key,
+                        from,
+                        to,
+                        bucket_id: 0,
+                    },
+                }
+            })
+            .collect();
 
-        SegmentRangeCollector::from_req_and_validate(
-            &req,
-            &mut Default::default(),
-            &mut AggregationLimitsGuard::default(),
-            field_type,
-            0,
-        )
-        .expect("unexpected error")
+        SegmentRangeCollector {
+            parent_buckets: vec![buckets],
+            column_type: field_type,
+            accessor_idx: 0,
+            sub_agg: None,
+            bucket_id_provider: Default::default(),
+            limits: AggregationLimitsGuard::default(),
+        }
     }
 
     #[test]
@@ -721,7 +845,7 @@ mod tests {
         let buckets = vec![(10f64..20f64).into(), (30f64..40f64).into()];
         let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
-        let buckets = collector.buckets;
+        let buckets = collector.parent_buckets[0].clone();
         assert_eq!(buckets[0].range.start, u64::MIN);
         assert_eq!(buckets[0].range.end, 10f64.to_u64());
         assert_eq!(buckets[1].range.start, 10f64.to_u64());
@@ -744,7 +868,7 @@ mod tests {
         ];
         let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
-        let buckets = collector.buckets;
+        let buckets = collector.parent_buckets[0].clone();
         assert_eq!(buckets[0].range.start, u64::MIN);
         assert_eq!(buckets[0].range.end, 10f64.to_u64());
         assert_eq!(buckets[1].range.start, 10f64.to_u64());
@@ -759,7 +883,7 @@ mod tests {
         let buckets = vec![(-10f64..-1f64).into()];
         let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
-        let buckets = collector.buckets;
+        let buckets = collector.parent_buckets[0].clone();
         assert_eq!(&buckets[0].bucket.key.to_string(), "*--10");
         assert_eq!(&buckets[buckets.len() - 1].bucket.key.to_string(), "-1-*");
     }
@@ -768,7 +892,7 @@ mod tests {
         let buckets = vec![(0f64..10f64).into()];
         let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
-        let buckets = collector.buckets;
+        let buckets = collector.parent_buckets[0].clone();
         assert_eq!(&buckets[0].bucket.key.to_string(), "*-0");
         assert_eq!(&buckets[buckets.len() - 1].bucket.key.to_string(), "10-*");
     }
@@ -777,7 +901,7 @@ mod tests {
     fn range_binary_search_test_u64() {
         let check_ranges = |ranges: Vec<RangeAggregationRange>| {
             let collector = get_collector_from_ranges(ranges, ColumnType::U64);
-            let search = |val: u64| collector.get_bucket_pos(val);
+            let search = |val: u64| get_bucket_pos(val, &collector.parent_buckets[0]);
 
             assert_eq!(search(u64::MIN), 0);
             assert_eq!(search(9), 0);
@@ -823,7 +947,7 @@ mod tests {
         let ranges = vec![(10.0..100.0).into()];
 
         let collector = get_collector_from_ranges(ranges, ColumnType::F64);
-        let search = |val: u64| collector.get_bucket_pos(val);
+        let search = |val: u64| get_bucket_pos(val, &collector.parent_buckets[0]);
 
         assert_eq!(search(u64::MIN), 0);
         assert_eq!(search(9f64.to_u64()), 0);
@@ -835,63 +959,3 @@ mod tests {
                                              // the max value
     }
 }
-
-#[cfg(all(test, feature = "unstable"))]
-mod bench {
-
-    use itertools::Itertools;
-    use rand::seq::SliceRandom;
-    use rand::thread_rng;
-
-    use super::*;
-    use crate::aggregation::bucket::range::tests::get_collector_from_ranges;
-
-    const TOTAL_DOCS: u64 = 1_000_000u64;
-    const NUM_DOCS: u64 = 50_000u64;
-
-    fn get_collector_with_buckets(num_buckets: u64, num_docs: u64) -> SegmentRangeCollector {
-        let bucket_size = num_docs / num_buckets;
-        let mut buckets: Vec<RangeAggregationRange> = vec![];
-        for i in 0..num_buckets {
-            let bucket_start = (i * bucket_size) as f64;
-            buckets.push((bucket_start..bucket_start + bucket_size as f64).into())
-        }
-
-        get_collector_from_ranges(buckets, ColumnType::U64)
-    }
-
-    fn get_rand_docs(total_docs: u64, num_docs_returned: u64) -> Vec<u64> {
-        let mut rng = thread_rng();
-
-        let all_docs = (0..total_docs - 1).collect_vec();
-        let mut vals = all_docs
-            .as_slice()
-            .choose_multiple(&mut rng, num_docs_returned as usize)
-            .cloned()
-            .collect_vec();
-        vals.sort();
-        vals
-    }
-
-    fn bench_range_binary_search(b: &mut test::Bencher, num_buckets: u64) {
-        let collector = get_collector_with_buckets(num_buckets, TOTAL_DOCS);
-        let vals = get_rand_docs(TOTAL_DOCS, NUM_DOCS);
-        b.iter(|| {
-            let mut bucket_pos = 0;
-            for val in &vals {
-                bucket_pos = collector.get_bucket_pos(*val);
-            }
-            bucket_pos
-        })
-    }
-
-    #[bench]
-    fn bench_range_100_buckets(b: &mut test::Bencher) {
-        bench_range_binary_search(b, 100)
-    }
-
-    #[bench]
-    fn bench_range_10_buckets(b: &mut test::Bencher) {
-        bench_range_binary_search(b, 10)
-    }
-}

src/aggregation/bucket/term_missing_agg.rs

@@ -1,55 +1,93 @@
+use columnar::{Column, ColumnType};
 use rustc_hash::FxHashMap;
 
-use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
+use crate::aggregation::agg_data::{
+    build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
+};
+use crate::aggregation::bucket::term_agg::TermsAggregation;
+use crate::aggregation::cached_sub_aggs::CachedSubAggs;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
     IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
 };
-use crate::aggregation::segment_agg_result::{
-    build_segment_agg_collector, SegmentAggregationCollector,
-};
+use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
+use crate::aggregation::BucketId;
+
+/// Special aggregation to handle missing values for term aggregations.
+/// This missing aggregation will check multiple columns for existence.
+///
+/// This is needed when:
+/// - The field is multi-valued and we therefore have multiple columns
+/// - The field is not text and missing is provided as string (we cannot use the numeric missing
+///   value optimization)
+#[derive(Default)]
+pub struct MissingTermAggReqData {
+    /// The accessors to check for existence of a value.
+    pub accessors: Vec<(Column<u64>, ColumnType)>,
+    /// The name of the aggregation.
+    pub name: String,
+    /// The original terms aggregation request.
+    pub req: TermsAggregation,
+}
+
+impl MissingTermAggReqData {
+    /// Estimate the memory consumption of this struct in bytes.
+    pub fn get_memory_consumption(&self) -> usize {
+        std::mem::size_of::<Self>()
+    }
+}
+
+#[derive(Default, Debug, Clone)]
+struct MissingCount {
+    missing_count: u32,
+    bucket_id: BucketId,
+}
 
 /// The specialized missing term aggregation.
-#[derive(Default, Debug, Clone)]
+#[derive(Default, Debug)]
 pub struct TermMissingAgg {
-    missing_count: u32,
     accessor_idx: usize,
-    sub_agg: Option<Box<dyn SegmentAggregationCollector>>,
+    sub_agg: Option<CachedSubAggs>,
+    /// Idx = parent bucket id, Value = missing count for that bucket
+    missing_count_per_bucket: Vec<MissingCount>,
+    bucket_id_provider: BucketIdProvider,
 }
 impl TermMissingAgg {
     pub(crate) fn new(
-        accessor_idx: usize,
-        sub_aggregations: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
+        node: &AggRefNode,
     ) -> crate::Result<Self> {
-        let has_sub_aggregations = !sub_aggregations.is_empty();
+        let has_sub_aggregations = !node.children.is_empty();
+        let accessor_idx = node.idx_in_req_data;
         let sub_agg = if has_sub_aggregations {
-            let sub_aggregation = build_segment_agg_collector(sub_aggregations)?;
+            let sub_aggregation = build_segment_agg_collectors(agg_data, &node.children)?;
             Some(sub_aggregation)
         } else {
             None
         };
 
+        let sub_agg = sub_agg.map(CachedSubAggs::new);
+        let bucket_id_provider = BucketIdProvider::default();
+
         Ok(Self {
             accessor_idx,
             sub_agg,
-            ..Default::default()
+            missing_count_per_bucket: Vec::new(),
+            bucket_id_provider,
         })
     }
 }
 
 impl SegmentAggregationCollector for TermMissingAgg {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
-        let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
-        let term_agg = agg_with_accessor
-            .agg
-            .agg
-            .as_term()
-            .expect("TermMissingAgg collector must be term agg req");
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
+        let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
+        let term_agg = &req_data.req;
         let missing = term_agg
             .missing
             .as_ref()
@@ -58,16 +96,16 @@ impl SegmentAggregationCollector for TermMissingAgg {
         let mut entries: FxHashMap<IntermediateKey, IntermediateTermBucketEntry> =
             Default::default();
 
+        let missing_count = &self.missing_count_per_bucket[parent_bucket_id as usize];
         let mut missing_entry = IntermediateTermBucketEntry {
-            doc_count: self.missing_count,
+            doc_count: missing_count.missing_count,
             sub_aggregation: Default::default(),
         };
-        if let Some(sub_agg) = self.sub_agg {
+        if let Some(sub_agg) = &mut self.sub_agg {
             let mut res = IntermediateAggregationResults::default();
-            sub_agg.add_intermediate_aggregation_result(
-                &agg_with_accessor.sub_aggregation,
-                &mut res,
-            )?;
+            sub_agg
+                .get_sub_agg_collector()
+                .add_intermediate_aggregation_result(agg_data, &mut res, missing_count.bucket_id)?;
             missing_entry.sub_aggregation = res;
         }
         entries.insert(missing.into(), missing_entry);
@@ -80,37 +118,62 @@ impl SegmentAggregationCollector for TermMissingAgg {
             },
         };
 
-        results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
+        results.push(
+            req_data.name.to_string(),
+            IntermediateAggregationResult::Bucket(bucket),
+        )?;
 
         Ok(())
     }
 
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        parent_bucket_id: BucketId,
+        docs: &[crate::DocId],
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let agg = &mut agg_with_accessor.aggs.values[self.accessor_idx];
-        let has_value = agg
-            .accessors
-            .iter()
-            .any(|(acc, _)| acc.index.has_value(doc));
-        if !has_value {
-            self.missing_count += 1;
-            if let Some(sub_agg) = self.sub_agg.as_mut() {
-                sub_agg.collect(doc, &mut agg.sub_aggregation)?;
+        let bucket = &mut self.missing_count_per_bucket[parent_bucket_id as usize];
+        let req_data = agg_data.get_missing_term_req_data(self.accessor_idx);
+
+        for doc in docs {
+            let doc = *doc;
+            let has_value = req_data
+                .accessors
+                .iter()
+                .any(|(acc, _)| acc.index.has_value(doc));
+            if !has_value {
+                bucket.missing_count += 1;
+
+                if let Some(sub_agg) = self.sub_agg.as_mut() {
+                    sub_agg.push(bucket.bucket_id, doc);
+                }
             }
         }
+
+        if let Some(sub_agg) = self.sub_agg.as_mut() {
+            sub_agg.check_flush_local(agg_data)?;
+        }
         Ok(())
     }
 
-    fn collect_block(
+    fn prepare_max_bucket(
         &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        for doc in docs {
-            self.collect(*doc, agg_with_accessor)?;
+        while self.missing_count_per_bucket.len() <= max_bucket as usize {
+            let bucket_id = self.bucket_id_provider.next_bucket_id();
+            self.missing_count_per_bucket.push(MissingCount {
+                missing_count: 0,
+                bucket_id,
+            });
+        }
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
+        if let Some(sub_agg) = self.sub_agg.as_mut() {
+            sub_agg.flush(agg_data)?;
         }
         Ok(())
     }

src/aggregation/buf_collector.rs

@@ -1,83 +0,0 @@
-use super::agg_req_with_accessor::AggregationsWithAccessor;
-use super::intermediate_agg_result::IntermediateAggregationResults;
-use super::segment_agg_result::SegmentAggregationCollector;
-use crate::DocId;
-
-pub(crate) const DOC_BLOCK_SIZE: usize = 64;
-pub(crate) type DocBlock = [DocId; DOC_BLOCK_SIZE];
-
-/// BufAggregationCollector buffers documents before calling collect_block().
-#[derive(Clone)]
-pub(crate) struct BufAggregationCollector {
-    pub(crate) collector: Box<dyn SegmentAggregationCollector>,
-    staged_docs: DocBlock,
-    num_staged_docs: usize,
-}
-
-impl std::fmt::Debug for BufAggregationCollector {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        f.debug_struct("SegmentAggregationResultsCollector")
-            .field("staged_docs", &&self.staged_docs[..self.num_staged_docs])
-            .field("num_staged_docs", &self.num_staged_docs)
-            .finish()
-    }
-}
-
-impl BufAggregationCollector {
-    pub fn new(collector: Box<dyn SegmentAggregationCollector>) -> Self {
-        Self {
-            collector,
-            num_staged_docs: 0,
-            staged_docs: [0; DOC_BLOCK_SIZE],
-        }
-    }
-}
-
-impl SegmentAggregationCollector for BufAggregationCollector {
-    #[inline]
-    fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
-        results: &mut IntermediateAggregationResults,
-    ) -> crate::Result<()> {
-        Box::new(self.collector).add_intermediate_aggregation_result(agg_with_accessor, results)
-    }
-
-    #[inline]
-    fn collect(
-        &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.staged_docs[self.num_staged_docs] = doc;
-        self.num_staged_docs += 1;
-        if self.num_staged_docs == self.staged_docs.len() {
-            self.collector
-                .collect_block(&self.staged_docs[..self.num_staged_docs], agg_with_accessor)?;
-            self.num_staged_docs = 0;
-        }
-        Ok(())
-    }
-
-    #[inline]
-    fn collect_block(
-        &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collector.collect_block(docs, agg_with_accessor)?;
-
-        Ok(())
-    }
-
-    #[inline]
-    fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
-        self.collector
-            .collect_block(&self.staged_docs[..self.num_staged_docs], agg_with_accessor)?;
-        self.num_staged_docs = 0;
-
-        self.collector.flush(agg_with_accessor)?;
-
-        Ok(())
-    }
-}

src/aggregation/cached_sub_aggs.rs

@@ -0,0 +1,185 @@
+use super::segment_agg_result::SegmentAggregationCollector;
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
+use crate::aggregation::bucket::MAX_NUM_TERMS_FOR_VEC;
+use crate::aggregation::BucketId;
+use crate::DocId;
+
+#[derive(Debug)]
+/// A cache for sub-aggregations, storing doc ids per bucket id.
+/// Depending on the cardinality of the parent aggregation, we use different
+/// storage strategies.
+///
+/// ## Low Cardinality
+/// Cardinality here refers to the number of unique flattened buckets that can be created
+/// by the parent aggregation.
+/// Flattened buckets are the result of combining all buckets per collector
+/// into a single list of buckets, where each bucket is identified by its BucketId.
+///
+/// ## Usage
+/// Since this is caching for sub-aggregations, it is only used by bucket
+/// aggregations.
+///
+/// TODO: consider using a more advanced data structure for high cardinality
+/// aggregations.
+/// What this datastructure does in general is to group docs by bucket id.
+pub(crate) struct CachedSubAggs<const LOWCARD: bool = false> {
+    /// Only used when LOWCARD is true.
+    /// Cache doc ids per bucket for sub-aggregations.
+    ///
+    /// The outer Vec is indexed by BucketId.
+    per_bucket_docs: Vec<Vec<DocId>>,
+    /// Only used when LOWCARD is false.
+    ///
+    /// This weird partitioning is used to do some cheap grouping on the bucket ids.
+    /// bucket ids are dense, e.g. when we don't detect the cardinality as low cardinality,
+    /// but there are just 16 bucket ids, each bucket id will go to its own partition.
+    ///
+    /// We want to keep this cheap, because high cardinality aggregations can have a lot of
+    /// buckets, and they may be nothing to group.
+    partitions: [PartitionEntry; NUM_PARTITIONS],
+    pub(crate) sub_agg_collector: Box<dyn SegmentAggregationCollector>,
+    num_docs: usize,
+}
+
+const FLUSH_THRESHOLD: usize = 2048;
+const NUM_PARTITIONS: usize = 16;
+
+impl<const LOWCARD: bool> CachedSubAggs<LOWCARD> {
+    pub fn get_sub_agg_collector(&mut self) -> &mut Box<dyn SegmentAggregationCollector> {
+        &mut self.sub_agg_collector
+    }
+
+    pub fn new(sub_agg: Box<dyn SegmentAggregationCollector>) -> Self {
+        Self {
+            per_bucket_docs: Vec::new(),
+            num_docs: 0,
+            sub_agg_collector: sub_agg,
+            partitions: core::array::from_fn(|_| PartitionEntry::default()),
+        }
+    }
+
+    #[inline]
+    pub fn clear(&mut self) {
+        for v in &mut self.per_bucket_docs {
+            v.clear();
+        }
+        for partition in &mut self.partitions {
+            partition.clear();
+        }
+        self.num_docs = 0;
+    }
+
+    #[inline]
+    pub fn push(&mut self, bucket_id: BucketId, doc_id: DocId) {
+        if LOWCARD {
+            // TODO: We could flush single buckets here
+            let idx = bucket_id as usize;
+            if self.per_bucket_docs.len() <= idx {
+                self.per_bucket_docs.resize_with(idx + 1, Vec::new);
+            }
+            self.per_bucket_docs[idx].push(doc_id);
+        } else {
+            let idx = bucket_id % NUM_PARTITIONS as u32;
+            let slot = &mut self.partitions[idx as usize];
+            slot.bucket_ids.push(bucket_id);
+            slot.docs.push(doc_id);
+        }
+        self.num_docs += 1;
+    }
+
+    /// Check if we need to flush based on the number of documents cached.
+    /// If so, flushes the cache to the provided aggregation collector.
+    pub fn check_flush_local(
+        &mut self,
+        agg_data: &mut AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        if self.num_docs >= FLUSH_THRESHOLD {
+            self.flush_local(agg_data, false)?;
+        }
+        Ok(())
+    }
+
+    /// Note: this does _not_ flush the sub aggregations
+    fn flush_local(
+        &mut self,
+        agg_data: &mut AggregationsSegmentCtx,
+        force: bool,
+    ) -> crate::Result<()> {
+        if LOWCARD {
+            // Pre-aggregated: call collect per bucket.
+            let max_bucket = (self.per_bucket_docs.len() as BucketId).saturating_sub(1);
+            self.sub_agg_collector
+                .prepare_max_bucket(max_bucket, agg_data)?;
+            // The threshold above which we flush buckets individually.
+            // Note: We need to make sure that we don't lock ourselves into a situation where we hit
+            // the FLUSH_THRESHOLD, but never flush any buckets. (except the final flush)
+            let mut bucket_treshold = FLUSH_THRESHOLD / (self.per_bucket_docs.len().max(1) * 2);
+            const _: () = {
+                // MAX_NUM_TERMS_FOR_VEC == LOWCARD threshold
+                let bucket_treshold = FLUSH_THRESHOLD / (MAX_NUM_TERMS_FOR_VEC as usize * 2);
+                assert!(
+                    bucket_treshold > 0,
+                    "Bucket threshold must be greater than 0"
+                );
+            };
+            if force {
+                bucket_treshold = 0;
+            }
+            for (bucket_id, docs) in self
+                .per_bucket_docs
+                .iter()
+                .enumerate()
+                .filter(|(_, docs)| docs.len() > bucket_treshold)
+            {
+                self.sub_agg_collector
+                    .collect(bucket_id as BucketId, docs, agg_data)?;
+            }
+        } else {
+            let mut max_bucket = 0u32;
+            for partition in &self.partitions {
+                if let Some(&local_max) = partition.bucket_ids.iter().max() {
+                    max_bucket = max_bucket.max(local_max);
+                }
+            }
+
+            self.sub_agg_collector
+                .prepare_max_bucket(max_bucket, agg_data)?;
+
+            for slot in &self.partitions {
+                if !slot.bucket_ids.is_empty() {
+                    // Reduce dynamic dispatch overhead by collecting a full partition in one call.
+                    self.sub_agg_collector.collect_multiple(
+                        &slot.bucket_ids,
+                        &slot.docs,
+                        agg_data,
+                    )?;
+                }
+            }
+        }
+        self.clear();
+        Ok(())
+    }
+
+    /// Note: this _does_ flush the sub aggregations
+    pub fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
+        if self.num_docs != 0 {
+            self.flush_local(agg_data, true)?;
+        }
+        self.sub_agg_collector.flush(agg_data)?;
+        Ok(())
+    }
+}
+
+#[derive(Debug, Clone, Default)]
+struct PartitionEntry {
+    bucket_ids: Vec<BucketId>,
+    docs: Vec<DocId>,
+}
+
+impl PartitionEntry {
+    #[inline]
+    fn clear(&mut self) {
+        self.bucket_ids.clear();
+        self.docs.clear();
+    }
+}

src/aggregation/collector.rs

@@ -1,12 +1,12 @@
 use super::agg_req::Aggregations;
-use super::agg_req_with_accessor::AggregationsWithAccessor;
 use super::agg_result::AggregationResults;
-use super::buf_collector::BufAggregationCollector;
+use super::cached_sub_aggs::CachedSubAggs;
 use super::intermediate_agg_result::IntermediateAggregationResults;
-use super::segment_agg_result::{
-    build_segment_agg_collector, AggregationLimitsGuard, SegmentAggregationCollector,
+use super::AggContextParams;
+// group buffering strategy is chosen explicitly by callers; no need to hash-group on the fly.
+use crate::aggregation::agg_data::{
+    build_aggregations_data_from_req, build_segment_agg_collectors_root, AggregationsSegmentCtx,
 };
-use crate::aggregation::agg_req_with_accessor::get_aggs_with_segment_accessor_and_validate;
 use crate::collector::{Collector, SegmentCollector};
 use crate::index::SegmentReader;
 use crate::{DocId, SegmentOrdinal, TantivyError};
@@ -22,7 +22,7 @@ pub const DEFAULT_MEMORY_LIMIT: u64 = 500_000_000;
 /// The collector collects all aggregations by the underlying aggregation request.
 pub struct AggregationCollector {
     agg: Aggregations,
-    limits: AggregationLimitsGuard,
+    context: AggContextParams,
 }
 
 impl AggregationCollector {
@@ -30,8 +30,8 @@ impl AggregationCollector {
     ///
     /// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
     /// bucket limit)
-    pub fn from_aggs(agg: Aggregations, limits: AggregationLimitsGuard) -> Self {
-        Self { agg, limits }
+    pub fn from_aggs(agg: Aggregations, context: AggContextParams) -> Self {
+        Self { agg, context }
     }
 }
 
@@ -45,7 +45,7 @@ impl AggregationCollector {
 /// into the final `AggregationResults` via the `into_final_result()` method.
 pub struct DistributedAggregationCollector {
     agg: Aggregations,
-    limits: AggregationLimitsGuard,
+    context: AggContextParams,
 }
 
 impl DistributedAggregationCollector {
@@ -53,8 +53,8 @@ impl DistributedAggregationCollector {
     ///
     /// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
     /// bucket limit)
-    pub fn from_aggs(agg: Aggregations, limits: AggregationLimitsGuard) -> Self {
-        Self { agg, limits }
+    pub fn from_aggs(agg: Aggregations, context: AggContextParams) -> Self {
+        Self { agg, context }
     }
 }
 
@@ -72,7 +72,7 @@ impl Collector for DistributedAggregationCollector {
             &self.agg,
             reader,
             segment_local_id,
-            &self.limits,
+            &self.context,
         )
     }
 
@@ -102,7 +102,7 @@ impl Collector for AggregationCollector {
             &self.agg,
             reader,
             segment_local_id,
-            &self.limits,
+            &self.context,
         )
     }
 
@@ -115,7 +115,7 @@ impl Collector for AggregationCollector {
         segment_fruits: Vec<<Self::Child as SegmentCollector>::Fruit>,
     ) -> crate::Result<Self::Fruit> {
         let res = merge_fruits(segment_fruits)?;
-        res.into_final_result(self.agg.clone(), self.limits.clone())
+        res.into_final_result(self.agg.clone(), self.context.limits.clone())
     }
 }
 
@@ -135,8 +135,8 @@ fn merge_fruits(
 
 /// `AggregationSegmentCollector` does the aggregation collection on a segment.
 pub struct AggregationSegmentCollector {
-    aggs_with_accessor: AggregationsWithAccessor,
-    agg_collector: BufAggregationCollector,
+    aggs_with_accessor: AggregationsSegmentCtx,
+    agg_collector: CachedSubAggs<true>,
     error: Option<TantivyError>,
 }
 
@@ -147,14 +147,17 @@ impl AggregationSegmentCollector {
         agg: &Aggregations,
         reader: &SegmentReader,
         segment_ordinal: SegmentOrdinal,
-        limits: &AggregationLimitsGuard,
+        context: &AggContextParams,
     ) -> crate::Result<Self> {
-        let mut aggs_with_accessor =
-            get_aggs_with_segment_accessor_and_validate(agg, reader, segment_ordinal, limits)?;
-        let result =
-            BufAggregationCollector::new(build_segment_agg_collector(&mut aggs_with_accessor)?);
+        let mut agg_data =
+            build_aggregations_data_from_req(agg, reader, segment_ordinal, context.clone())?;
+        let mut result = CachedSubAggs::new(build_segment_agg_collectors_root(&mut agg_data)?);
+        result
+            .get_sub_agg_collector()
+            .prepare_max_bucket(0, &agg_data)?; // prepare for bucket zero
+
         Ok(AggregationSegmentCollector {
-            aggs_with_accessor,
+            aggs_with_accessor: agg_data,
             agg_collector: result,
             error: None,
         })
@@ -169,26 +172,31 @@ impl SegmentCollector for AggregationSegmentCollector {
         if self.error.is_some() {
             return;
         }
-        if let Err(err) = self
+        self.agg_collector.push(0, doc);
+        match self
             .agg_collector
-            .collect(doc, &mut self.aggs_with_accessor)
+            .check_flush_local(&mut self.aggs_with_accessor)
         {
-            self.error = Some(err);
+            Ok(_) => {}
+            Err(e) => {
+                self.error = Some(e);
+            }
         }
     }
-
-    /// The query pushes the documents to the collector via this method.
-    ///
-    /// Only valid for Collectors that ignore docs
     fn collect_block(&mut self, docs: &[DocId]) {
         if self.error.is_some() {
             return;
         }
-        if let Err(err) = self
-            .agg_collector
-            .collect_block(docs, &mut self.aggs_with_accessor)
-        {
-            self.error = Some(err);
+
+        match self.agg_collector.get_sub_agg_collector().collect(
+            0,
+            docs,
+            &mut self.aggs_with_accessor,
+        ) {
+            Ok(_) => {}
+            Err(e) => {
+                self.error = Some(e);
+            }
         }
     }
 
@@ -199,10 +207,13 @@ impl SegmentCollector for AggregationSegmentCollector {
         self.agg_collector.flush(&mut self.aggs_with_accessor)?;
 
         let mut sub_aggregation_res = IntermediateAggregationResults::default();
-        Box::new(self.agg_collector).add_intermediate_aggregation_result(
-            &self.aggs_with_accessor,
-            &mut sub_aggregation_res,
-        )?;
+        self.agg_collector
+            .get_sub_agg_collector()
+            .add_intermediate_aggregation_result(
+                &self.aggs_with_accessor,
+                &mut sub_aggregation_res,
+                0,
+            )?;
 
         Ok(sub_aggregation_res)
     }

src/aggregation/intermediate_agg_result.rs

@@ -24,7 +24,9 @@ use super::metric::{
 };
 use super::segment_agg_result::AggregationLimitsGuard;
 use super::{format_date, AggregationError, Key, SerializedKey};
-use crate::aggregation::agg_result::{AggregationResults, BucketEntries, BucketEntry};
+use crate::aggregation::agg_result::{
+    AggregationResults, BucketEntries, BucketEntry, FilterBucketResult,
+};
 use crate::aggregation::bucket::TermsAggregationInternal;
 use crate::aggregation::metric::CardinalityCollector;
 use crate::TantivyError;
@@ -179,12 +181,17 @@ impl IntermediateAggregationResults {
     }
 
     /// Merge another intermediate aggregation result into this result.
-    ///
-    /// The order of the values need to be the same on both results. This is ensured when the same
-    /// (key values) are present on the underlying `VecWithNames` struct.
-    pub fn merge_fruits(&mut self, other: IntermediateAggregationResults) -> crate::Result<()> {
-        for (left, right) in self.aggs_res.values_mut().zip(other.aggs_res.into_values()) {
-            left.merge_fruits(right)?;
+    pub fn merge_fruits(&mut self, mut other: IntermediateAggregationResults) -> crate::Result<()> {
+        for (key, left) in self.aggs_res.iter_mut() {
+            if let Some(key) = other.aggs_res.remove(key) {
+                left.merge_fruits(key)?;
+            }
+        }
+        // Move remainder of other aggs_res into self.
+        // Note: Currently we don't expect this to happen, as we create empty intermediate results
+        // via [IntermediateAggregationResults::empty_from_req].
+        for (key, value) in other.aggs_res {
+            self.aggs_res.insert(key, value);
         }
         Ok(())
     }
@@ -241,11 +248,16 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
         Cardinality(_) => IntermediateAggregationResult::Metric(
             IntermediateMetricResult::Cardinality(CardinalityCollector::default()),
         ),
+        Filter(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Filter {
+            doc_count: 0,
+            sub_aggregations: IntermediateAggregationResults::default(),
+        }),
     }
 }
 
 /// An aggregation is either a bucket or a metric.
 #[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
+#[allow(clippy::large_enum_variant)]
 pub enum IntermediateAggregationResult {
     /// Bucket variant
     Bucket(IntermediateBucketResult),
@@ -426,6 +438,13 @@ pub enum IntermediateBucketResult {
         /// The term buckets
         buckets: IntermediateTermBucketResult,
     },
+    /// Filter aggregation - a single bucket with sub-aggregations
+    Filter {
+        /// Document count in the filter bucket
+        doc_count: u64,
+        /// Sub-aggregation results
+        sub_aggregations: IntermediateAggregationResults,
+    },
 }
 
 impl IntermediateBucketResult {
@@ -509,6 +528,18 @@ impl IntermediateBucketResult {
                 req.sub_aggregation(),
                 limits,
             ),
+            IntermediateBucketResult::Filter {
+                doc_count,
+                sub_aggregations,
+            } => {
+                // Convert sub-aggregation results to final format
+                let final_sub_aggregations = sub_aggregations
+                    .into_final_result(req.sub_aggregation().clone(), limits.clone())?;
+                Ok(BucketResult::Filter(FilterBucketResult {
+                    doc_count,
+                    sub_aggregations: final_sub_aggregations,
+                }))
+            }
         }
     }
 
@@ -562,6 +593,19 @@ impl IntermediateBucketResult {
 
                 *buckets_left = buckets?;
             }
+            (
+                IntermediateBucketResult::Filter {
+                    doc_count: doc_count_left,
+                    sub_aggregations: sub_aggs_left,
+                },
+                IntermediateBucketResult::Filter {
+                    doc_count: doc_count_right,
+                    sub_aggregations: sub_aggs_right,
+                },
+            ) => {
+                *doc_count_left += doc_count_right;
+                sub_aggs_left.merge_fruits(sub_aggs_right)?;
+            }
             (IntermediateBucketResult::Range(_), _) => {
                 panic!("try merge on different types")
             }
@@ -571,6 +615,9 @@ impl IntermediateBucketResult {
             (IntermediateBucketResult::Terms { .. }, _) => {
                 panic!("try merge on different types")
             }
+            (IntermediateBucketResult::Filter { .. }, _) => {
+                panic!("try merge on different types")
+            }
         }
         Ok(())
     }
@@ -745,7 +792,7 @@ pub struct IntermediateRangeBucketEntry {
     /// The number of documents in the bucket.
     pub doc_count: u64,
     /// The sub_aggregation in this bucket.
-    pub sub_aggregation: IntermediateAggregationResults,
+    pub sub_aggregation_res: IntermediateAggregationResults,
     /// The from range of the bucket. Equals `f64::MIN` when `None`.
     pub from: Option<f64>,
     /// The to range of the bucket. Equals `f64::MAX` when `None`.
@@ -764,7 +811,7 @@ impl IntermediateRangeBucketEntry {
             key: self.key.into(),
             doc_count: self.doc_count,
             sub_aggregation: self
-                .sub_aggregation
+                .sub_aggregation_res
                 .into_final_result_internal(req, limits)?,
             to: self.to,
             from: self.from,
@@ -810,7 +857,8 @@ impl MergeFruits for IntermediateTermBucketEntry {
 impl MergeFruits for IntermediateRangeBucketEntry {
     fn merge_fruits(&mut self, other: IntermediateRangeBucketEntry) -> crate::Result<()> {
         self.doc_count += other.doc_count;
-        self.sub_aggregation.merge_fruits(other.sub_aggregation)?;
+        self.sub_aggregation_res
+            .merge_fruits(other.sub_aggregation_res)?;
         Ok(())
     }
 }
@@ -840,7 +888,7 @@ mod tests {
                 IntermediateRangeBucketEntry {
                     key: IntermediateKey::Str(key.to_string()),
                     doc_count: *doc_count,
-                    sub_aggregation: Default::default(),
+                    sub_aggregation_res: Default::default(),
                     from: None,
                     to: None,
                 },
@@ -873,7 +921,7 @@ mod tests {
                     doc_count: *doc_count,
                     from: None,
                     to: None,
-                    sub_aggregation: get_sub_test_tree(&[(
+                    sub_aggregation_res: get_sub_test_tree(&[(
                         sub_aggregation_key.to_string(),
                         *sub_aggregation_count,
                     )]),

src/aggregation/metric/average.rs

@@ -52,10 +52,8 @@ pub struct IntermediateAverage {
 
 impl IntermediateAverage {
     /// Creates a new [`IntermediateAverage`] instance from a [`SegmentStatsCollector`].
-    pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
-        Self {
-            stats: collector.stats,
-        }
+    pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
+        Self { stats }
     }
     /// Merges the other intermediate result into self.
     pub fn merge_fruits(&mut self, other: IntermediateAverage) {

src/aggregation/metric/cardinality.rs

@@ -2,15 +2,13 @@ use std::collections::hash_map::DefaultHasher;
 use std::hash::{BuildHasher, Hasher};
 
 use columnar::column_values::CompactSpaceU64Accessor;
-use columnar::Dictionary;
+use columnar::{Column, ColumnType, Dictionary, StrColumn};
 use common::f64_to_u64;
 use hyperloglogplus::{HyperLogLog, HyperLogLogPlus};
 use rustc_hash::FxHashSet;
 use serde::{Deserialize, Serialize};
 
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationWithAccessor, AggregationsWithAccessor,
-};
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
 };
@@ -97,6 +95,30 @@ pub struct CardinalityAggregationReq {
     pub missing: Option<Key>,
 }
 
+/// Contains all information required by the SegmentCardinalityCollector to perform the
+/// cardinality aggregation on a segment.
+pub struct CardinalityAggReqData {
+    /// The column accessor to access the fast field values.
+    pub accessor: Column<u64>,
+    /// The column_type of the field.
+    pub column_type: ColumnType,
+    /// The string dictionary column if the field is of type string.
+    pub str_dict_column: Option<StrColumn>,
+    /// The missing value normalized to the internal u64 representation of the field type.
+    pub missing_value_for_accessor: Option<u64>,
+    /// The name of the aggregation.
+    pub name: String,
+    /// The aggregation request.
+    pub req: CardinalityAggregationReq,
+}
+
+impl CardinalityAggReqData {
+    /// Estimate the memory consumption of this struct in bytes.
+    pub fn get_memory_consumption(&self) -> usize {
+        std::mem::size_of::<Self>()
+    }
+}
+
 impl CardinalityAggregationReq {
     /// Creates a new [`CardinalityAggregationReq`] instance from a field name.
     pub fn from_field_name(field_name: String) -> Self {
@@ -111,51 +133,37 @@ impl CardinalityAggregationReq {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Clone, Debug)]
 pub(crate) struct SegmentCardinalityCollector {
-    cardinality: CardinalityCollector,
-    entries: FxHashSet<u64>,
-    column_type: ColumnType,
+    buckets: Vec<SegmentCardinalityCollectorBucket>,
     accessor_idx: usize,
-    missing: Option<Key>,
+    /// The column accessor to access the fast field values.
+    accessor: Column<u64>,
+    /// The column_type of the field.
+    column_type: ColumnType,
+    /// The missing value normalized to the internal u64 representation of the field type.
+    missing_value_for_accessor: Option<u64>,
 }
 
-impl SegmentCardinalityCollector {
-    pub fn from_req(column_type: ColumnType, accessor_idx: usize, missing: &Option<Key>) -> Self {
+#[derive(Clone, Debug, PartialEq, Default)]
+pub(crate) struct SegmentCardinalityCollectorBucket {
+    cardinality: CardinalityCollector,
+    entries: FxHashSet<u64>,
+}
+impl SegmentCardinalityCollectorBucket {
+    pub fn new(column_type: ColumnType) -> Self {
         Self {
             cardinality: CardinalityCollector::new(column_type as u8),
-            entries: Default::default(),
-            column_type,
-            accessor_idx,
-            missing: missing.clone(),
+            entries: FxHashSet::default(),
         }
     }
-
-    fn fetch_block_with_field(
-        &mut self,
-        docs: &[crate::DocId],
-        agg_accessor: &mut AggregationWithAccessor,
-    ) {
-        if let Some(missing) = agg_accessor.missing_value_for_accessor {
-            agg_accessor.column_block_accessor.fetch_block_with_missing(
-                docs,
-                &agg_accessor.accessor,
-                missing,
-            );
-        } else {
-            agg_accessor
-                .column_block_accessor
-                .fetch_block(docs, &agg_accessor.accessor);
-        }
-    }
-
     fn into_intermediate_metric_result(
         mut self,
-        agg_with_accessor: &AggregationWithAccessor,
+        req_data: &CardinalityAggReqData,
     ) -> crate::Result<IntermediateMetricResult> {
-        if self.column_type == ColumnType::Str {
+        if req_data.column_type == ColumnType::Str {
             let fallback_dict = Dictionary::empty();
-            let dict = agg_with_accessor
+            let dict = req_data
                 .str_dict_column
                 .as_ref()
                 .map(|el| el.dictionary())
@@ -173,6 +181,7 @@ impl SegmentCardinalityCollector {
                     term_ids.push(term_ord as u32);
                 }
             }
+
             term_ids.sort_unstable();
             dict.sorted_ords_to_term_cb(term_ids.iter().map(|term| *term as u64), |term| {
                 self.cardinality.sketch.insert_any(&term);
@@ -180,10 +189,10 @@ impl SegmentCardinalityCollector {
             })?;
             if has_missing {
                 // Replace missing with the actual value provided
-                let missing_key = self
-                    .missing
-                    .as_ref()
-                    .expect("Found sentinel value u64::MAX for term_ord but `missing` is not set");
+                let missing_key =
+                    req_data.req.missing.as_ref().expect(
+                        "Found sentinel value u64::MAX for term_ord but `missing` is not set",
+                    );
                 match missing_key {
                     Key::Str(missing) => {
                         self.cardinality.sketch.insert_any(&missing);
@@ -206,16 +215,49 @@ impl SegmentCardinalityCollector {
     }
 }
 
+impl SegmentCardinalityCollector {
+    pub fn from_req(
+        column_type: ColumnType,
+        accessor_idx: usize,
+        accessor: Column<u64>,
+        missing_value_for_accessor: Option<u64>,
+    ) -> Self {
+        Self {
+            buckets: vec![SegmentCardinalityCollectorBucket::new(column_type); 1],
+            column_type,
+            accessor_idx,
+            accessor,
+            missing_value_for_accessor,
+        }
+    }
+
+    fn fetch_block_with_field(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_data: &mut AggregationsSegmentCtx,
+    ) {
+        agg_data.column_block_accessor.fetch_block_with_missing(
+            docs,
+            &self.accessor,
+            self.missing_value_for_accessor,
+        );
+    }
+}
+
 impl SegmentAggregationCollector for SegmentCardinalityCollector {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
-        let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
+        let req_data = &agg_data.get_cardinality_req_data(self.accessor_idx);
+        let name = req_data.name.to_string();
+        // take the bucket in buckets and replace it with a new empty one
+        let bucket = std::mem::take(&mut self.buckets[parent_bucket_id as usize]);
 
-        let intermediate_result = self.into_intermediate_metric_result(agg_with_accessor)?;
+        let intermediate_result = bucket.into_intermediate_metric_result(req_data)?;
         results.push(
             name,
             IntermediateAggregationResult::Metric(intermediate_result),
@@ -226,27 +268,20 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
 
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collect_block(&[doc], agg_with_accessor)
-    }
-
-    fn collect_block(
-        &mut self,
+        parent_bucket_id: BucketId,
         docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
-        self.fetch_block_with_field(docs, bucket_agg_accessor);
+        self.fetch_block_with_field(docs, agg_data);
+        let bucket = &mut self.buckets[parent_bucket_id as usize];
 
-        let col_block_accessor = &bucket_agg_accessor.column_block_accessor;
+        let col_block_accessor = &agg_data.column_block_accessor;
         if self.column_type == ColumnType::Str {
             for term_ord in col_block_accessor.iter_vals() {
-                self.entries.insert(term_ord);
+                bucket.entries.insert(term_ord);
             }
         } else if self.column_type == ColumnType::IpAddr {
-            let compact_space_accessor = bucket_agg_accessor
+            let compact_space_accessor = self
                 .accessor
                 .values
                 .clone()
@@ -261,16 +296,29 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
                 })?;
             for val in col_block_accessor.iter_vals() {
                 let val: u128 = compact_space_accessor.compact_to_u128(val as u32);
-                self.cardinality.sketch.insert_any(&val);
+                bucket.cardinality.sketch.insert_any(&val);
             }
         } else {
             for val in col_block_accessor.iter_vals() {
-                self.cardinality.sketch.insert_any(&val);
+                bucket.cardinality.sketch.insert_any(&val);
             }
         }
 
         Ok(())
     }
+
+    fn prepare_max_bucket(
+        &mut self,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        if max_bucket as usize >= self.buckets.len() {
+            self.buckets.resize_with(max_bucket as usize + 1, || {
+                SegmentCardinalityCollectorBucket::new(self.column_type)
+            });
+        }
+        Ok(())
+    }
 }
 
 #[derive(Clone, Debug, Serialize, Deserialize)]

src/aggregation/metric/count.rs

@@ -52,10 +52,8 @@ pub struct IntermediateCount {
 
 impl IntermediateCount {
     /// Creates a new [`IntermediateCount`] instance from a [`SegmentStatsCollector`].
-    pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
-        Self {
-            stats: collector.stats,
-        }
+    pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
+        Self { stats }
     }
     /// Merges the other intermediate result into self.
     pub fn merge_fruits(&mut self, other: IntermediateCount) {

src/aggregation/metric/extended_stats.rs

@@ -4,15 +4,13 @@ use std::mem;
 use serde::{Deserialize, Serialize};
 
 use super::*;
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationWithAccessor, AggregationsWithAccessor,
-};
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
 };
 use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
 use crate::aggregation::*;
-use crate::{DocId, TantivyError};
+use crate::TantivyError;
 
 /// A multi-value metric aggregation that computes a collection of extended statistics
 /// on numeric values that are extracted
@@ -63,7 +61,7 @@ impl ExtendedStatsAggregation {
 
 /// Extended stats contains a collection of statistics
 /// they extends stats adding variance, standard deviation
-/// and bound informations
+/// and bound information
 #[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
 pub struct ExtendedStats {
     /// The number of documents.
@@ -319,51 +317,28 @@ impl IntermediateExtendedStats {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Clone, Debug)]
 pub(crate) struct SegmentExtendedStatsCollector {
+    name: String,
     missing: Option<u64>,
     field_type: ColumnType,
-    pub(crate) extended_stats: IntermediateExtendedStats,
-    pub(crate) accessor_idx: usize,
-    val_cache: Vec<u64>,
+    accessor: columnar::Column<u64>,
+    buckets: Vec<IntermediateExtendedStats>,
+    sigma: Option<f64>,
 }
 
 impl SegmentExtendedStatsCollector {
-    pub fn from_req(
-        field_type: ColumnType,
-        sigma: Option<f64>,
-        accessor_idx: usize,
-        missing: Option<f64>,
-    ) -> Self {
-        let missing = missing.and_then(|val| f64_to_fastfield_u64(val, &field_type));
+    pub fn from_req(req: &MetricAggReqData, sigma: Option<f64>) -> Self {
+        let missing = req
+            .missing
+            .and_then(|val| f64_to_fastfield_u64(val, &req.field_type));
         Self {
-            field_type,
-            extended_stats: IntermediateExtendedStats::with_sigma(sigma),
-            accessor_idx,
+            name: req.name.clone(),
+            field_type: req.field_type,
+            accessor: req.accessor.clone(),
             missing,
-            val_cache: Default::default(),
-        }
-    }
-    #[inline]
-    pub(crate) fn collect_block_with_field(
-        &mut self,
-        docs: &[DocId],
-        agg_accessor: &mut AggregationWithAccessor,
-    ) {
-        if let Some(missing) = self.missing.as_ref() {
-            agg_accessor.column_block_accessor.fetch_block_with_missing(
-                docs,
-                &agg_accessor.accessor,
-                *missing,
-            );
-        } else {
-            agg_accessor
-                .column_block_accessor
-                .fetch_block(docs, &agg_accessor.accessor);
-        }
-        for val in agg_accessor.column_block_accessor.iter_vals() {
-            let val1 = f64_from_fastfield_u64(val, &self.field_type);
-            self.extended_stats.collect(val1);
+            buckets: vec![IntermediateExtendedStats::with_sigma(sigma); 16],
+            sigma,
         }
     }
 }
@@ -371,15 +346,18 @@ impl SegmentExtendedStatsCollector {
 impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
     #[inline]
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
+        let name = self.name.clone();
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
+        let extended_stats = std::mem::take(&mut self.buckets[parent_bucket_id as usize]);
         results.push(
             name,
             IntermediateAggregationResult::Metric(IntermediateMetricResult::ExtendedStats(
-                self.extended_stats,
+                extended_stats,
             )),
         )?;
 
@@ -389,39 +367,36 @@ impl SegmentAggregationCollector for SegmentExtendedStatsCollector {
     #[inline]
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        parent_bucket_id: BucketId,
+        docs: &[crate::DocId],
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
-        if let Some(missing) = self.missing {
-            let mut has_val = false;
-            for val in field.values_for_doc(doc) {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.extended_stats.collect(val1);
-                has_val = true;
-            }
-            if !has_val {
-                self.extended_stats
-                    .collect(f64_from_fastfield_u64(missing, &self.field_type));
-            }
-        } else {
-            for val in field.values_for_doc(doc) {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.extended_stats.collect(val1);
-            }
+        let mut extended_stats = self.buckets[parent_bucket_id as usize].clone();
+
+        agg_data
+            .column_block_accessor
+            .fetch_block_with_missing(docs, &self.accessor, self.missing);
+        for val in agg_data.column_block_accessor.iter_vals() {
+            let val1 = f64_from_fastfield_u64(val, self.field_type);
+            extended_stats.collect(val1);
         }
 
+        // store back
+        self.buckets[parent_bucket_id as usize] = extended_stats;
+
         Ok(())
     }
 
-    #[inline]
-    fn collect_block(
+    fn prepare_max_bucket(
         &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let field = &mut agg_with_accessor.aggs.values[self.accessor_idx];
-        self.collect_block_with_field(docs, field);
+        if self.buckets.len() <= max_bucket as usize {
+            self.buckets.resize_with(max_bucket as usize + 1, || {
+                IntermediateExtendedStats::with_sigma(self.sigma)
+            });
+        }
         Ok(())
     }
 }

src/aggregation/metric/max.rs

@@ -52,10 +52,8 @@ pub struct IntermediateMax {
 
 impl IntermediateMax {
     /// Creates a new [`IntermediateMax`] instance from a [`SegmentStatsCollector`].
-    pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
-        Self {
-            stats: collector.stats,
-        }
+    pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
+        Self { stats }
     }
     /// Merges the other intermediate result into self.
     pub fn merge_fruits(&mut self, other: IntermediateMax) {

src/aggregation/metric/min.rs

@@ -52,10 +52,8 @@ pub struct IntermediateMin {
 
 impl IntermediateMin {
     /// Creates a new [`IntermediateMin`] instance from a [`SegmentStatsCollector`].
-    pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
-        Self {
-            stats: collector.stats,
-        }
+    pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
+        Self { stats }
     }
     /// Merges the other intermediate result into self.
     pub fn merge_fruits(&mut self, other: IntermediateMin) {

src/aggregation/metric/mod.rs

@@ -31,6 +31,7 @@ use std::collections::HashMap;
 
 pub use average::*;
 pub use cardinality::*;
+use columnar::{Column, ColumnType};
 pub use count::*;
 pub use extended_stats::*;
 pub use max::*;
@@ -44,6 +45,33 @@ pub use top_hits::*;
 
 use crate::schema::OwnedValue;
 
+/// Contains all information required by metric aggregations like avg, min, max, sum, stats,
+/// extended_stats, count, percentiles.
+#[repr(C)]
+pub struct MetricAggReqData {
+    /// True if the field is of number or date type.
+    pub is_number_or_date_type: bool,
+    /// The type of the field.
+    pub field_type: ColumnType,
+    /// The missing value normalized to the internal u64 representation of the field type.
+    pub missing_u64: Option<u64>,
+    /// The column accessor to access the fast field values.
+    pub accessor: Column<u64>,
+    /// Used when converting to intermediate result
+    pub collecting_for: StatsType,
+    /// The missing value
+    pub missing: Option<f64>,
+    /// The name of the aggregation.
+    pub name: String,
+}
+
+impl MetricAggReqData {
+    /// Estimate the memory consumption of this struct in bytes.
+    pub fn get_memory_consumption(&self) -> usize {
+        std::mem::size_of::<Self>()
+    }
+}
+
 /// Single-metric aggregations use this common result structure.
 ///
 /// Main reason to wrap it in value is to match elasticsearch output structure.

src/aggregation/metric/percentiles.rs

@@ -3,15 +3,13 @@ use std::fmt::Debug;
 use serde::{Deserialize, Serialize};
 
 use super::*;
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationWithAccessor, AggregationsWithAccessor,
-};
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
 };
 use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
 use crate::aggregation::*;
-use crate::{DocId, TantivyError};
+use crate::TantivyError;
 
 /// # Percentiles
 ///
@@ -112,7 +110,8 @@ impl PercentilesAggregationReq {
         &self.field
     }
 
-    fn validate(&self) -> crate::Result<()> {
+    /// Validates the request parameters.
+    pub fn validate(&self) -> crate::Result<()> {
         if let Some(percents) = self.percents.as_ref() {
             let all_in_range = percents
                 .iter()
@@ -131,12 +130,16 @@ impl PercentilesAggregationReq {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Clone, Debug)]
 pub(crate) struct SegmentPercentilesCollector {
-    field_type: ColumnType,
-    pub(crate) percentiles: PercentilesCollector,
+    pub(crate) buckets: Vec<PercentilesCollector>,
     pub(crate) accessor_idx: usize,
-    missing: Option<u64>,
+    /// The type of the field.
+    pub field_type: ColumnType,
+    /// The missing value normalized to the internal u64 representation of the field type.
+    pub missing_u64: Option<u64>,
+    /// The column accessor to access the fast field values.
+    pub accessor: Column<u64>,
 }
 
 #[derive(Clone, Serialize, Deserialize)]
@@ -232,43 +235,17 @@ impl PercentilesCollector {
 
 impl SegmentPercentilesCollector {
     pub fn from_req_and_validate(
-        req: &PercentilesAggregationReq,
         field_type: ColumnType,
+        missing_u64: Option<u64>,
+        accessor: Column<u64>,
         accessor_idx: usize,
-    ) -> crate::Result<Self> {
-        req.validate()?;
-        let missing = req
-            .missing
-            .and_then(|val| f64_to_fastfield_u64(val, &field_type));
-
-        Ok(Self {
+    ) -> Self {
+        Self {
+            buckets: Vec::with_capacity(64),
             field_type,
-            percentiles: PercentilesCollector::new(),
+            missing_u64,
+            accessor,
             accessor_idx,
-            missing,
-        })
-    }
-    #[inline]
-    pub(crate) fn collect_block_with_field(
-        &mut self,
-        docs: &[DocId],
-        agg_accessor: &mut AggregationWithAccessor,
-    ) {
-        if let Some(missing) = self.missing.as_ref() {
-            agg_accessor.column_block_accessor.fetch_block_with_missing(
-                docs,
-                &agg_accessor.accessor,
-                *missing,
-            );
-        } else {
-            agg_accessor
-                .column_block_accessor
-                .fetch_block(docs, &agg_accessor.accessor);
-        }
-
-        for val in agg_accessor.column_block_accessor.iter_vals() {
-            let val1 = f64_from_fastfield_u64(val, &self.field_type);
-            self.percentiles.collect(val1);
         }
     }
 }
@@ -276,12 +253,18 @@ impl SegmentPercentilesCollector {
 impl SegmentAggregationCollector for SegmentPercentilesCollector {
     #[inline]
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
-        let intermediate_metric_result = IntermediateMetricResult::Percentiles(self.percentiles);
+        let name = agg_data.get_metric_req_data(self.accessor_idx).name.clone();
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
+        // Swap collector with an empty one to avoid cloning
+        let percentiles_collector = std::mem::take(&mut self.buckets[parent_bucket_id as usize]);
+
+        let intermediate_metric_result =
+            IntermediateMetricResult::Percentiles(percentiles_collector);
 
         results.push(
             name,
@@ -294,40 +277,33 @@ impl SegmentAggregationCollector for SegmentPercentilesCollector {
     #[inline]
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        parent_bucket_id: BucketId,
+        docs: &[crate::DocId],
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
+        let percentiles = &mut self.buckets[parent_bucket_id as usize];
+        agg_data.column_block_accessor.fetch_block_with_missing(
+            docs,
+            &self.accessor,
+            self.missing_u64,
+        );
 
-        if let Some(missing) = self.missing {
-            let mut has_val = false;
-            for val in field.values_for_doc(doc) {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.percentiles.collect(val1);
-                has_val = true;
-            }
-            if !has_val {
-                self.percentiles
-                    .collect(f64_from_fastfield_u64(missing, &self.field_type));
-            }
-        } else {
-            for val in field.values_for_doc(doc) {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.percentiles.collect(val1);
-            }
+        for val in agg_data.column_block_accessor.iter_vals() {
+            let val1 = f64_from_fastfield_u64(val, self.field_type);
+            percentiles.collect(val1);
         }
 
         Ok(())
     }
 
-    #[inline]
-    fn collect_block(
+    fn prepare_max_bucket(
         &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let field = &mut agg_with_accessor.aggs.values[self.accessor_idx];
-        self.collect_block_with_field(docs, field);
+        while self.buckets.len() <= max_bucket as usize {
+            self.buckets.push(PercentilesCollector::new());
+        }
         Ok(())
     }
 }

src/aggregation/metric/stats.rs

@@ -1,17 +1,16 @@
 use std::fmt::Debug;
 
+use columnar::{Column, ColumnType};
 use serde::{Deserialize, Serialize};
 
 use super::*;
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationWithAccessor, AggregationsWithAccessor,
-};
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
 };
 use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
 use crate::aggregation::*;
-use crate::{DocId, TantivyError};
+use crate::TantivyError;
 
 /// A multi-value metric aggregation that computes a collection of statistics on numeric values that
 /// are extracted from the aggregated documents.
@@ -84,7 +83,7 @@ impl Stats {
 
 /// Intermediate result of the stats aggregation that can be combined with other intermediate
 /// results.
-#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
+#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize)]
 pub struct IntermediateStats {
     /// The number of extracted values.
     pub(crate) count: u64,
@@ -166,106 +165,98 @@ impl IntermediateStats {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
-pub(crate) enum SegmentStatsType {
+/// The type of stats aggregation to perform.
+/// Note that not all stats types are supported in the stats aggregation.
+#[derive(Clone, Copy, Debug)]
+pub enum StatsType {
+    /// The average of the values.
     Average,
+    /// The count of the values.
     Count,
+    /// The maximum value.
     Max,
+    /// The minimum value.
     Min,
+    /// The stats (count, sum, min, max, avg) of the values.
     Stats,
+    /// The extended stats (count, sum, min, max, avg, sum_of_squares, variance, std_deviation,
+    ExtendedStats(Option<f64>), // sigma
+    /// The sum of the values.
     Sum,
+    /// The percentiles of the values.
+    Percentiles,
 }
 
-#[derive(Clone, Debug, PartialEq)]
-pub(crate) struct SegmentStatsCollector {
-    missing: Option<u64>,
-    field_type: ColumnType,
-    pub(crate) collecting_for: SegmentStatsType,
-    pub(crate) stats: IntermediateStats,
-    pub(crate) accessor_idx: usize,
-    val_cache: Vec<u64>,
+fn create_collector<const TYPE_ID: u8>(
+    req: &MetricAggReqData,
+) -> Box<dyn SegmentAggregationCollector> {
+    Box::new(SegmentStatsCollector::<TYPE_ID> {
+        name: req.name.clone(),
+        collecting_for: req.collecting_for,
+        is_number_or_date_type: req.is_number_or_date_type,
+        missing_u64: req.missing_u64,
+        accessor: req.accessor.clone(),
+        buckets: vec![IntermediateStats::default()],
+    })
 }
 
-impl SegmentStatsCollector {
-    pub fn from_req(
-        field_type: ColumnType,
-        collecting_for: SegmentStatsType,
-        accessor_idx: usize,
-        missing: Option<f64>,
-    ) -> Self {
-        let missing = missing.and_then(|val| f64_to_fastfield_u64(val, &field_type));
-        Self {
-            field_type,
-            collecting_for,
-            stats: IntermediateStats::default(),
-            accessor_idx,
-            missing,
-            val_cache: Default::default(),
-        }
-    }
-    #[inline]
-    pub(crate) fn collect_block_with_field(
-        &mut self,
-        docs: &[DocId],
-        agg_accessor: &mut AggregationWithAccessor,
-    ) {
-        if let Some(missing) = self.missing.as_ref() {
-            agg_accessor.column_block_accessor.fetch_block_with_missing(
-                docs,
-                &agg_accessor.accessor,
-                *missing,
-            );
-        } else {
-            agg_accessor
-                .column_block_accessor
-                .fetch_block(docs, &agg_accessor.accessor);
-        }
-        if [
-            ColumnType::I64,
-            ColumnType::U64,
-            ColumnType::F64,
-            ColumnType::DateTime,
-        ]
-        .contains(&self.field_type)
-        {
-            for val in agg_accessor.column_block_accessor.iter_vals() {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.stats.collect(val1);
-            }
-        } else {
-            for _val in agg_accessor.column_block_accessor.iter_vals() {
-                // we ignore the value and simply record that we got something
-                self.stats.collect(0.0);
-            }
-        }
+/// Build a concrete `SegmentStatsCollector` depending on the column type.
+pub(crate) fn build_segment_stats_collector(
+    req: &MetricAggReqData,
+) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
+    match req.field_type {
+        ColumnType::I64 => Ok(create_collector::<{ ColumnType::I64 as u8 }>(req)),
+        ColumnType::U64 => Ok(create_collector::<{ ColumnType::U64 as u8 }>(req)),
+        ColumnType::F64 => Ok(create_collector::<{ ColumnType::F64 as u8 }>(req)),
+        ColumnType::Bool => Ok(create_collector::<{ ColumnType::Bool as u8 }>(req)),
+        ColumnType::DateTime => Ok(create_collector::<{ ColumnType::DateTime as u8 }>(req)),
+        ColumnType::Bytes => Ok(create_collector::<{ ColumnType::Bytes as u8 }>(req)),
+        ColumnType::Str => Ok(create_collector::<{ ColumnType::Str as u8 }>(req)),
+        ColumnType::IpAddr => Ok(create_collector::<{ ColumnType::IpAddr as u8 }>(req)),
     }
 }
 
-impl SegmentAggregationCollector for SegmentStatsCollector {
+#[repr(C)]
+#[derive(Clone, Debug)]
+pub(crate) struct SegmentStatsCollector<const COLUMN_TYPE_ID: u8> {
+    pub(crate) missing_u64: Option<u64>,
+    pub(crate) accessor: Column<u64>,
+    pub(crate) is_number_or_date_type: bool,
+    pub(crate) buckets: Vec<IntermediateStats>,
+    pub(crate) name: String,
+    pub(crate) collecting_for: StatsType,
+}
+
+impl<const COLUMN_TYPE_ID: u8> SegmentAggregationCollector
+    for SegmentStatsCollector<COLUMN_TYPE_ID>
+{
     #[inline]
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
+        let name = self.name.clone();
 
+        self.prepare_max_bucket(parent_bucket_id, agg_data)?;
+        let stats = self.buckets[parent_bucket_id as usize];
         let intermediate_metric_result = match self.collecting_for {
-            SegmentStatsType::Average => {
-                IntermediateMetricResult::Average(IntermediateAverage::from_collector(*self))
+            StatsType::Average => {
+                IntermediateMetricResult::Average(IntermediateAverage::from_stats(stats))
             }
-            SegmentStatsType::Count => {
-                IntermediateMetricResult::Count(IntermediateCount::from_collector(*self))
+            StatsType::Count => {
+                IntermediateMetricResult::Count(IntermediateCount::from_stats(stats))
             }
-            SegmentStatsType::Max => {
-                IntermediateMetricResult::Max(IntermediateMax::from_collector(*self))
-            }
-            SegmentStatsType::Min => {
-                IntermediateMetricResult::Min(IntermediateMin::from_collector(*self))
-            }
-            SegmentStatsType::Stats => IntermediateMetricResult::Stats(self.stats),
-            SegmentStatsType::Sum => {
-                IntermediateMetricResult::Sum(IntermediateSum::from_collector(*self))
+            StatsType::Max => IntermediateMetricResult::Max(IntermediateMax::from_stats(stats)),
+            StatsType::Min => IntermediateMetricResult::Min(IntermediateMin::from_stats(stats)),
+            StatsType::Stats => IntermediateMetricResult::Stats(stats),
+            StatsType::Sum => IntermediateMetricResult::Sum(IntermediateSum::from_stats(stats)),
+            _ => {
+                return Err(TantivyError::InvalidArgument(format!(
+                    "Unsupported stats type for stats aggregation: {:?}",
+                    self.collecting_for
+                )))
             }
         };
 
@@ -280,41 +271,67 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
     #[inline]
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
-        if let Some(missing) = self.missing {
-            let mut has_val = false;
-            for val in field.values_for_doc(doc) {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.stats.collect(val1);
-                has_val = true;
-            }
-            if !has_val {
-                self.stats
-                    .collect(f64_from_fastfield_u64(missing, &self.field_type));
-            }
-        } else {
-            for val in field.values_for_doc(doc) {
-                let val1 = f64_from_fastfield_u64(val, &self.field_type);
-                self.stats.collect(val1);
-            }
-        }
-
-        Ok(())
-    }
-
-    #[inline]
-    fn collect_block(
-        &mut self,
+        parent_bucket_id: BucketId,
         docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let field = &mut agg_with_accessor.aggs.values[self.accessor_idx];
-        self.collect_block_with_field(docs, field);
+        // TODO: remove once we fetch all values for all bucket ids in one go
+        if docs.len() == 1 && self.missing_u64.is_none() {
+            collect_stats::<COLUMN_TYPE_ID>(
+                &mut self.buckets[parent_bucket_id as usize],
+                self.accessor.values_for_doc(docs[0]),
+                self.is_number_or_date_type,
+            )?;
+
+            return Ok(());
+        }
+        agg_data.column_block_accessor.fetch_block_with_missing(
+            docs,
+            &self.accessor,
+            self.missing_u64,
+        );
+        collect_stats::<COLUMN_TYPE_ID>(
+            &mut self.buckets[parent_bucket_id as usize],
+            agg_data.column_block_accessor.iter_vals(),
+            self.is_number_or_date_type,
+        )?;
+
         Ok(())
     }
+
+    fn prepare_max_bucket(
+        &mut self,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        let required_buckets = (max_bucket as usize) + 1;
+        if self.buckets.len() < required_buckets {
+            self.buckets
+                .resize_with(required_buckets, IntermediateStats::default);
+        }
+        Ok(())
+    }
+}
+
+#[inline]
+fn collect_stats<const COLUMN_TYPE_ID: u8>(
+    stats: &mut IntermediateStats,
+    vals: impl Iterator<Item = u64>,
+    is_number_or_date_type: bool,
+) -> crate::Result<()> {
+    if is_number_or_date_type {
+        for val in vals {
+            let val1 = convert_to_f64::<COLUMN_TYPE_ID>(val);
+            stats.collect(val1);
+        }
+    } else {
+        for _val in vals {
+            // we ignore the value and simply record that we got something
+            stats.collect(0.0);
+        }
+    }
+
+    Ok(())
 }
 
 #[cfg(test)]

src/aggregation/metric/sum.rs

@@ -52,10 +52,8 @@ pub struct IntermediateSum {
 
 impl IntermediateSum {
     /// Creates a new [`IntermediateSum`] instance from a [`SegmentStatsCollector`].
-    pub(crate) fn from_collector(collector: SegmentStatsCollector) -> Self {
-        Self {
-            stats: collector.stats,
-        }
+    pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
+        Self { stats }
     }
     /// Merges the other intermediate result into self.
     pub fn merge_fruits(&mut self, other: IntermediateSum) {

src/aggregation/metric/top_hits.rs

@@ -9,16 +9,41 @@ use serde::ser::SerializeMap;
 use serde::{Deserialize, Deserializer, Serialize, Serializer};
 
 use super::{TopHitsMetricResult, TopHitsVecEntry};
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
 use crate::aggregation::bucket::Order;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResult, IntermediateMetricResult,
 };
 use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
-use crate::aggregation::AggregationError;
+use crate::aggregation::{AggregationError, BucketId};
+use crate::collector::sort_key::ReverseComparator;
 use crate::collector::TopNComputer;
 use crate::schema::OwnedValue;
 use crate::{DocAddress, DocId, SegmentOrdinal};
 
+/// Contains all information required by the TopHitsSegmentCollector to perform the
+/// top_hits aggregation on a segment.
+#[derive(Default)]
+pub struct TopHitsAggReqData {
+    /// The accessors to access the fast field values.
+    pub accessors: Vec<(Column<u64>, ColumnType)>,
+    /// The accessors to access the fast field values for retrieving document fields.
+    pub value_accessors: HashMap<String, Vec<DynamicColumn>>,
+    /// The ordinal of the segment this request data is for.
+    pub segment_ordinal: SegmentOrdinal,
+    /// The name of the aggregation.
+    pub name: String,
+    /// The top_hits aggregation request.
+    pub req: TopHitsAggregationReq,
+}
+
+impl TopHitsAggReqData {
+    /// Estimate the memory consumption of this struct in bytes.
+    pub fn get_memory_consumption(&self) -> usize {
+        std::mem::size_of::<Self>()
+    }
+}
+
 /// # Top Hits
 ///
 /// The top hits aggregation is a useful tool to answer questions like:
@@ -433,7 +458,7 @@ impl Eq for DocSortValuesAndFields {}
 #[derive(Clone, Serialize, Deserialize, Debug)]
 pub struct TopHitsTopNComputer {
     req: TopHitsAggregationReq,
-    top_n: TopNComputer<DocSortValuesAndFields, DocAddress, false>,
+    top_n: TopNComputer<DocSortValuesAndFields, DocAddress, ReverseComparator>,
 }
 
 impl std::cmp::PartialEq for TopHitsTopNComputer {
@@ -446,7 +471,10 @@ impl TopHitsTopNComputer {
     /// Create a new TopHitsCollector
     pub fn new(req: &TopHitsAggregationReq) -> Self {
         Self {
-            top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
+            top_n: TopNComputer::new_with_comparator(
+                req.size + req.from.unwrap_or(0),
+                ReverseComparator,
+            ),
             req: req.clone(),
         }
     }
@@ -457,7 +485,7 @@ impl TopHitsTopNComputer {
 
     pub(crate) fn merge_fruits(&mut self, other_fruit: Self) -> crate::Result<()> {
         for doc in other_fruit.top_n.into_vec() {
-            self.collect(doc.feature, doc.doc);
+            self.collect(doc.sort_key, doc.doc);
         }
         Ok(())
     }
@@ -469,9 +497,9 @@ impl TopHitsTopNComputer {
             .into_sorted_vec()
             .into_iter()
             .map(|doc| TopHitsVecEntry {
-                sort: doc.feature.sorts.iter().map(|f| f.value).collect(),
+                sort: doc.sort_key.sorts.iter().map(|f| f.value).collect(),
                 doc_value_fields: doc
-                    .feature
+                    .sort_key
                     .doc_value_fields
                     .into_iter()
                     .map(|(k, v)| (k, v.into()))
@@ -492,7 +520,8 @@ impl TopHitsTopNComputer {
 pub(crate) struct TopHitsSegmentCollector {
     segment_ordinal: SegmentOrdinal,
     accessor_idx: usize,
-    top_n: TopNComputer<Vec<DocValueAndOrder>, DocAddress, false>,
+    buckets: Vec<TopNComputer<Vec<DocValueAndOrder>, DocAddress, ReverseComparator>>,
+    num_hits: usize,
 }
 
 impl TopHitsSegmentCollector {
@@ -501,25 +530,35 @@ impl TopHitsSegmentCollector {
         accessor_idx: usize,
         segment_ordinal: SegmentOrdinal,
     ) -> Self {
+        let num_hits = req.size + req.from.unwrap_or(0);
         Self {
-            top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
+            num_hits,
             segment_ordinal,
             accessor_idx,
+            buckets: vec![TopNComputer::new_with_comparator(num_hits, ReverseComparator); 1],
         }
     }
-    fn into_top_hits_collector(
-        self,
+    fn get_top_hits_computer(
+        &mut self,
+        parent_bucket_id: BucketId,
         value_accessors: &HashMap<String, Vec<DynamicColumn>>,
         req: &TopHitsAggregationReq,
     ) -> TopHitsTopNComputer {
+        if parent_bucket_id as usize >= self.buckets.len() {
+            return TopHitsTopNComputer::new(req);
+        }
+        let top_n = std::mem::replace(
+            &mut self.buckets[parent_bucket_id as usize],
+            TopNComputer::new(0),
+        );
         let mut top_hits_computer = TopHitsTopNComputer::new(req);
-        let top_results = self.top_n.into_vec();
+        let top_results = top_n.into_vec();
 
         for res in top_results {
             let doc_value_fields = req.get_document_field_data(value_accessors, res.doc.doc_id);
             top_hits_computer.collect(
                 DocSortValuesAndFields {
-                    sorts: res.feature,
+                    sorts: res.sort_key,
                     doc_value_fields,
                 },
                 res.doc,
@@ -528,61 +567,26 @@ impl TopHitsSegmentCollector {
 
         top_hits_computer
     }
-
-    /// TODO add a specialized variant for a single sort field
-    fn collect_with(
-        &mut self,
-        doc_id: crate::DocId,
-        req: &TopHitsAggregationReq,
-        accessors: &[(Column<u64>, ColumnType)],
-    ) -> crate::Result<()> {
-        let sorts: Vec<DocValueAndOrder> = req
-            .sort
-            .iter()
-            .enumerate()
-            .map(|(idx, KeyOrder { order, .. })| {
-                let order = *order;
-                let value = accessors
-                    .get(idx)
-                    .expect("could not find field in accessors")
-                    .0
-                    .values_for_doc(doc_id)
-                    .next();
-                DocValueAndOrder { value, order }
-            })
-            .collect();
-
-        self.top_n.push(
-            sorts,
-            DocAddress {
-                segment_ord: self.segment_ordinal,
-                doc_id,
-            },
-        );
-        Ok(())
-    }
 }
 
 impl SegmentAggregationCollector for TopHitsSegmentCollector {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
+        let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
 
-        let value_accessors = &agg_with_accessor.aggs.values[self.accessor_idx].value_accessors;
-        let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
-            .agg
-            .agg
-            .as_top_hits()
-            .expect("aggregation request must be of type top hits");
+        let value_accessors = &req_data.value_accessors;
 
-        let intermediate_result = IntermediateMetricResult::TopHits(
-            self.into_top_hits_collector(value_accessors, tophits_req),
-        );
+        let intermediate_result = IntermediateMetricResult::TopHits(self.get_top_hits_computer(
+            parent_bucket_id,
+            value_accessors,
+            &req_data.req,
+        ));
         results.push(
-            name,
+            req_data.name.to_string(),
             IntermediateAggregationResult::Metric(intermediate_result),
         )
     }
@@ -590,34 +594,55 @@ impl SegmentAggregationCollector for TopHitsSegmentCollector {
     /// TODO: Consider a caching layer to reduce the call overhead
     fn collect(
         &mut self,
-        doc_id: crate::DocId,
-        agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
+        parent_bucket_id: BucketId,
+        docs: &[crate::DocId],
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
-            .agg
-            .agg
-            .as_top_hits()
-            .expect("aggregation request must be of type top hits");
-        let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
-        self.collect_with(doc_id, tophits_req, accessors)?;
+        let top_n = &mut self.buckets[parent_bucket_id as usize];
+        let req_data = agg_data.get_top_hits_req_data(self.accessor_idx);
+        let req = &req_data.req;
+        let accessors = &req_data.accessors;
+        for doc_id in docs {
+            let doc_id = *doc_id;
+            // TODO: this is terrible, a new vec is allocated for every doc
+            // We can fetch blocks instead
+            // We don't need to store the order for every value
+            let sorts: Vec<DocValueAndOrder> = req
+                .sort
+                .iter()
+                .enumerate()
+                .map(|(idx, KeyOrder { order, .. })| {
+                    let order = *order;
+                    let value = accessors
+                        .get(idx)
+                        .expect("could not find field in accessors")
+                        .0
+                        .values_for_doc(doc_id)
+                        .next();
+                    DocValueAndOrder { value, order }
+                })
+                .collect();
+
+            top_n.push(
+                sorts,
+                DocAddress {
+                    segment_ord: self.segment_ordinal,
+                    doc_id,
+                },
+            );
+        }
         Ok(())
     }
 
-    fn collect_block(
+    fn prepare_max_bucket(
         &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
+        max_bucket: BucketId,
+        _agg_data: &AggregationsSegmentCtx,
     ) -> crate::Result<()> {
-        let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
-            .agg
-            .agg
-            .as_top_hits()
-            .expect("aggregation request must be of type top hits");
-        let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
-        // TODO: Consider getting fields with the column block accessor.
-        for doc in docs {
-            self.collect_with(*doc, tophits_req, accessors)?;
-        }
+        self.buckets.resize(
+            (max_bucket as usize) + 1,
+            TopNComputer::new_with_comparator(self.num_hits, ReverseComparator),
+        );
         Ok(())
     }
 }
@@ -635,6 +660,7 @@ mod tests {
     use crate::aggregation::bucket::tests::get_test_index_from_docs;
     use crate::aggregation::tests::get_test_index_from_values;
     use crate::aggregation::AggregationCollector;
+    use crate::collector::sort_key::ReverseComparator;
     use crate::collector::ComparableDoc;
     use crate::query::AllQuery;
     use crate::schema::OwnedValue;
@@ -650,7 +676,7 @@ mod tests {
 
     fn collector_with_capacity(capacity: usize) -> super::TopHitsTopNComputer {
         super::TopHitsTopNComputer {
-            top_n: super::TopNComputer::new(capacity),
+            top_n: super::TopNComputer::new_with_comparator(capacity, ReverseComparator),
             req: Default::default(),
         }
     }
@@ -734,7 +760,7 @@ mod tests {
                     ],
                     "from": 0,
                 }
-        }
+            }
         }))
         .unwrap();
 
@@ -764,12 +790,12 @@ mod tests {
     #[test]
     fn test_top_hits_collector_single_feature() -> crate::Result<()> {
         let docs = vec![
-            ComparableDoc::<_, _, false> {
+            ComparableDoc::<_, _> {
                 doc: crate::DocAddress {
                     segment_ord: 0,
                     doc_id: 0,
                 },
-                feature: DocSortValuesAndFields {
+                sort_key: DocSortValuesAndFields {
                     sorts: vec![DocValueAndOrder {
                         value: Some(1),
                         order: Order::Asc,
@@ -782,7 +808,7 @@ mod tests {
                     segment_ord: 0,
                     doc_id: 2,
                 },
-                feature: DocSortValuesAndFields {
+                sort_key: DocSortValuesAndFields {
                     sorts: vec![DocValueAndOrder {
                         value: Some(3),
                         order: Order::Asc,
@@ -795,7 +821,7 @@ mod tests {
                     segment_ord: 0,
                     doc_id: 1,
                 },
-                feature: DocSortValuesAndFields {
+                sort_key: DocSortValuesAndFields {
                     sorts: vec![DocValueAndOrder {
                         value: Some(5),
                         order: Order::Asc,
@@ -807,7 +833,7 @@ mod tests {
 
         let mut collector = collector_with_capacity(3);
         for doc in docs.clone() {
-            collector.collect(doc.feature, doc.doc);
+            collector.collect(doc.sort_key, doc.doc);
         }
 
         let res = collector.into_final_result();
@@ -817,15 +843,15 @@ mod tests {
             super::TopHitsMetricResult {
                 hits: vec![
                     super::TopHitsVecEntry {
-                        sort: vec![docs[0].feature.sorts[0].value],
+                        sort: vec![docs[0].sort_key.sorts[0].value],
                         doc_value_fields: Default::default(),
                     },
                     super::TopHitsVecEntry {
-                        sort: vec![docs[1].feature.sorts[0].value],
+                        sort: vec![docs[1].sort_key.sorts[0].value],
                         doc_value_fields: Default::default(),
                     },
                     super::TopHitsVecEntry {
-                        sort: vec![docs[2].feature.sorts[0].value],
+                        sort: vec![docs[2].sort_key.sorts[0].value],
                         doc_value_fields: Default::default(),
                     },
                 ]
@@ -863,7 +889,7 @@ mod tests {
                         "mixed.*",
                     ],
                 }
-        }
+            }
         }))?;
 
         let collector = AggregationCollector::from_aggs(d, Default::default());

src/aggregation/mod.rs

@@ -127,12 +127,13 @@
 //! [`AggregationResults`](agg_result::AggregationResults) via the
 //! [`into_final_result`](intermediate_agg_result::IntermediateAggregationResults::into_final_result) method.
 
+mod accessor_helpers;
+mod agg_data;
 mod agg_limits;
 pub mod agg_req;
-mod agg_req_with_accessor;
 pub mod agg_result;
 pub mod bucket;
-mod buf_collector;
+pub(crate) mod cached_sub_aggs;
 mod collector;
 mod date;
 mod error;
@@ -140,7 +141,6 @@ pub mod intermediate_agg_result;
 pub mod metric;
 
 mod segment_agg_result;
-use std::collections::HashMap;
 use std::fmt::Display;
 
 #[cfg(test)]
@@ -160,6 +160,41 @@ use itertools::Itertools;
 use serde::de::{self, Visitor};
 use serde::{Deserialize, Deserializer, Serialize};
 
+use crate::tokenizer::TokenizerManager;
+
+/// A bucket id is a dense identifier for a bucket within an aggregation.
+/// It is used to index into a Vec that hold per-bucket data.
+///
+/// For example, in a terms aggregation, each unique term will be assigned a incremental BucketId.
+/// This BucketId will be forwarded to sub-aggregations to identify the parent bucket.
+///
+/// This allows to have a single AggregationCollector instance per aggregation,
+/// that can handle multiple buckets efficiently.
+///
+/// The API to call sub-aggregations is therefore a &[(BucketId, &[DocId])].
+/// For that we'll need a buffer. One Vec per bucket aggregation is needed.
+pub type BucketId = u32;
+
+/// Context parameters for aggregation execution
+///
+/// This struct holds shared resources needed during aggregation execution:
+/// - `limits`: Memory and bucket limits for the aggregation
+/// - `tokenizers`: TokenizerManager for parsing query strings in filter aggregations
+#[derive(Clone, Default)]
+pub struct AggContextParams {
+    /// Aggregation limits (memory and bucket count)
+    pub limits: AggregationLimitsGuard,
+    /// Tokenizer manager for query string parsing
+    pub tokenizers: TokenizerManager,
+}
+
+impl AggContextParams {
+    /// Create new aggregation context parameters
+    pub fn new(limits: AggregationLimitsGuard, tokenizers: TokenizerManager) -> Self {
+        Self { limits, tokenizers }
+    }
+}
+
 fn parse_str_into_f64<E: de::Error>(value: &str) -> Result<f64, E> {
     let parsed = value
         .parse::<f64>()
@@ -257,80 +292,6 @@ where D: Deserializer<'de> {
     deserializer.deserialize_any(StringOrFloatVisitor)
 }
 
-/// Represents an associative array `(key => values)` in a very efficient manner.
-#[derive(PartialEq, Serialize, Deserialize)]
-pub(crate) struct VecWithNames<T> {
-    pub(crate) values: Vec<T>,
-    keys: Vec<String>,
-}
-
-impl<T: Clone> Clone for VecWithNames<T> {
-    fn clone(&self) -> Self {
-        Self {
-            values: self.values.clone(),
-            keys: self.keys.clone(),
-        }
-    }
-}
-
-impl<T> Default for VecWithNames<T> {
-    fn default() -> Self {
-        Self {
-            values: Default::default(),
-            keys: Default::default(),
-        }
-    }
-}
-
-impl<T: std::fmt::Debug> std::fmt::Debug for VecWithNames<T> {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        f.debug_map().entries(self.iter()).finish()
-    }
-}
-
-impl<T> From<HashMap<String, T>> for VecWithNames<T> {
-    fn from(map: HashMap<String, T>) -> Self {
-        VecWithNames::from_entries(map.into_iter().collect_vec())
-    }
-}
-
-impl<T> VecWithNames<T> {
-    fn from_entries(mut entries: Vec<(String, T)>) -> Self {
-        // Sort to ensure order of elements match across multiple instances
-        entries.sort_by(|left, right| left.0.cmp(&right.0));
-        let mut data = Vec::with_capacity(entries.len());
-        let mut data_names = Vec::with_capacity(entries.len());
-        for entry in entries {
-            data_names.push(entry.0);
-            data.push(entry.1);
-        }
-        VecWithNames {
-            values: data,
-            keys: data_names,
-        }
-    }
-    fn iter(&self) -> impl Iterator<Item = (&str, &T)> + '_ {
-        self.keys().zip(self.values.iter())
-    }
-    fn keys(&self) -> impl Iterator<Item = &str> + '_ {
-        self.keys.iter().map(|key| key.as_str())
-    }
-    fn values_mut(&mut self) -> impl Iterator<Item = &mut T> + '_ {
-        self.values.iter_mut()
-    }
-    fn is_empty(&self) -> bool {
-        self.keys.is_empty()
-    }
-    fn len(&self) -> usize {
-        self.keys.len()
-    }
-    fn get(&self, name: &str) -> Option<&T> {
-        self.keys()
-            .position(|key| key == name)
-            .map(|pos| &self.values[pos])
-    }
-}
-
 /// The serialized key is used in a `HashMap`.
 pub type SerializedKey = String;
 
@@ -387,19 +348,37 @@ impl Display for Key {
     }
 }
 
+pub(crate) fn convert_to_f64<const COLUMN_TYPE_ID: u8>(val: u64) -> f64 {
+    if COLUMN_TYPE_ID == ColumnType::U64 as u8 {
+        val as f64
+    } else if COLUMN_TYPE_ID == ColumnType::I64 as u8
+        || COLUMN_TYPE_ID == ColumnType::DateTime as u8
+    {
+        i64::from_u64(val) as f64
+    } else if COLUMN_TYPE_ID == ColumnType::F64 as u8 {
+        f64::from_u64(val)
+    } else if COLUMN_TYPE_ID == ColumnType::Bool as u8 {
+        val as f64
+    } else {
+        panic!(
+            "ColumnType ID {} cannot be converted to f64 metric",
+            COLUMN_TYPE_ID
+        )
+    }
+}
+
 /// Inverse of `to_fastfield_u64`. Used to convert to `f64` for metrics.
 ///
 /// # Panics
 /// Only `u64`, `f64`, `date`, and `i64` are supported.
-pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &ColumnType) -> f64 {
+pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: ColumnType) -> f64 {
     match field_type {
-        ColumnType::U64 => val as f64,
-        ColumnType::I64 | ColumnType::DateTime => i64::from_u64(val) as f64,
-        ColumnType::F64 => f64::from_u64(val),
-        ColumnType::Bool => val as f64,
-        _ => {
-            panic!("unexpected type {field_type:?}. This should not happen")
-        }
+        ColumnType::U64 => convert_to_f64::<{ ColumnType::U64 as u8 }>(val),
+        ColumnType::I64 => convert_to_f64::<{ ColumnType::I64 as u8 }>(val),
+        ColumnType::F64 => convert_to_f64::<{ ColumnType::F64 as u8 }>(val),
+        ColumnType::Bool => convert_to_f64::<{ ColumnType::Bool as u8 }>(val),
+        ColumnType::DateTime => convert_to_f64::<{ ColumnType::DateTime as u8 }>(val),
+        _ => panic!("unexpected type {field_type:?}. This should not happen"),
     }
 }
 
@@ -464,7 +443,10 @@ mod tests {
         query: Option<(&str, &str)>,
         limits: AggregationLimitsGuard,
     ) -> crate::Result<Value> {
-        let collector = AggregationCollector::from_aggs(agg_req, limits);
+        let collector = AggregationCollector::from_aggs(
+            agg_req,
+            AggContextParams::new(limits, index.tokenizers().clone()),
+        );
 
         let reader = index.reader()?;
         let searcher = reader.searcher();

src/aggregation/segment_agg_result.rs

@@ -6,179 +6,79 @@
 use std::fmt::Debug;
 
 pub(crate) use super::agg_limits::AggregationLimitsGuard;
-use super::agg_req::AggregationVariants;
-use super::agg_req_with_accessor::{AggregationWithAccessor, AggregationsWithAccessor};
-use super::bucket::{SegmentHistogramCollector, SegmentRangeCollector, SegmentTermCollector};
 use super::intermediate_agg_result::IntermediateAggregationResults;
-use super::metric::{
-    AverageAggregation, CountAggregation, ExtendedStatsAggregation, MaxAggregation, MinAggregation,
-    SegmentPercentilesCollector, SegmentStatsCollector, SegmentStatsType, StatsAggregation,
-    SumAggregation,
-};
-use crate::aggregation::bucket::TermMissingAgg;
-use crate::aggregation::metric::{
-    CardinalityAggregationReq, SegmentCardinalityCollector, SegmentExtendedStatsCollector,
-    TopHitsSegmentCollector,
-};
+use crate::aggregation::agg_data::AggregationsSegmentCtx;
+use crate::aggregation::BucketId;
 
-pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
+/// Monotonically increasing provider of BucketIds.
+#[derive(Debug, Clone, Default)]
+pub struct BucketIdProvider(u32);
+impl BucketIdProvider {
+    /// Get the next BucketId.
+    pub fn next_bucket_id(&mut self) -> BucketId {
+        let bucket_id = self.0;
+        self.0 += 1;
+        bucket_id
+    }
+}
+
+/// A SegmentAggregationCollector is used to collect aggregation results.
+pub trait SegmentAggregationCollector: Debug {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()>;
 
+    /// Note: The caller needs to call `prepare_max_bucket` before calling `collect`.
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        parent_bucket_id: BucketId,
+        docs: &[crate::DocId],
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()>;
 
-    fn collect_block(
+    /// Collect docs for multiple buckets in one call.
+    /// Minimizes dynamic dispatch overhead when collecting many buckets.
+    ///
+    /// Note: The caller needs to call `prepare_max_bucket` before calling `collect`.
+    fn collect_multiple(
         &mut self,
+        bucket_ids: &[BucketId],
         docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        debug_assert_eq!(bucket_ids.len(), docs.len());
+        let mut start = 0;
+        while start < bucket_ids.len() {
+            let bucket_id = bucket_ids[start];
+            let mut end = start + 1;
+            while end < bucket_ids.len() && bucket_ids[end] == bucket_id {
+                end += 1;
+            }
+            self.collect(bucket_id, &docs[start..end], agg_data)?;
+            start = end;
+        }
+        Ok(())
+    }
+
+    /// Prepare the collector for collecting up to BucketId `max_bucket`.
+    /// This is useful so we can split allocation ahead of time of collecting.
+    fn prepare_max_bucket(
+        &mut self,
+        max_bucket: BucketId,
+        agg_data: &AggregationsSegmentCtx,
     ) -> crate::Result<()>;
 
     /// Finalize method. Some Aggregator collect blocks of docs before calling `collect_block`.
     /// This method ensures those staged docs will be collected.
-    fn flush(&mut self, _agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
+    fn flush(&mut self, _agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
         Ok(())
     }
 }
 
-pub(crate) trait CollectorClone {
-    fn clone_box(&self) -> Box<dyn SegmentAggregationCollector>;
-}
-
-impl<T> CollectorClone for T
-where T: 'static + SegmentAggregationCollector + Clone
-{
-    fn clone_box(&self) -> Box<dyn SegmentAggregationCollector> {
-        Box::new(self.clone())
-    }
-}
-
-impl Clone for Box<dyn SegmentAggregationCollector> {
-    fn clone(&self) -> Box<dyn SegmentAggregationCollector> {
-        self.clone_box()
-    }
-}
-
-pub(crate) fn build_segment_agg_collector(
-    req: &mut AggregationsWithAccessor,
-) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
-    // Single collector special case
-    if req.aggs.len() == 1 {
-        let req = &mut req.aggs.values[0];
-        let accessor_idx = 0;
-        return build_single_agg_segment_collector(req, accessor_idx);
-    }
-
-    let agg = GenericSegmentAggregationResultsCollector::from_req_and_validate(req)?;
-    Ok(Box::new(agg))
-}
-
-pub(crate) fn build_single_agg_segment_collector(
-    req: &mut AggregationWithAccessor,
-    accessor_idx: usize,
-) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
-    use AggregationVariants::*;
-    match &req.agg.agg {
-        Terms(terms_req) => {
-            if req.accessors.is_empty() {
-                Ok(Box::new(SegmentTermCollector::from_req_and_validate(
-                    terms_req,
-                    &mut req.sub_aggregation,
-                    req.field_type,
-                    accessor_idx,
-                )?))
-            } else {
-                Ok(Box::new(TermMissingAgg::new(
-                    accessor_idx,
-                    &mut req.sub_aggregation,
-                )?))
-            }
-        }
-        Range(range_req) => Ok(Box::new(SegmentRangeCollector::from_req_and_validate(
-            range_req,
-            &mut req.sub_aggregation,
-            &mut req.limits,
-            req.field_type,
-            accessor_idx,
-        )?)),
-        Histogram(histogram) => Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
-            histogram.clone(),
-            &mut req.sub_aggregation,
-            req.field_type,
-            accessor_idx,
-        )?)),
-        DateHistogram(histogram) => Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
-            histogram.to_histogram_req()?,
-            &mut req.sub_aggregation,
-            req.field_type,
-            accessor_idx,
-        )?)),
-        Average(AverageAggregation { missing, .. }) => {
-            Ok(Box::new(SegmentStatsCollector::from_req(
-                req.field_type,
-                SegmentStatsType::Average,
-                accessor_idx,
-                *missing,
-            )))
-        }
-        Count(CountAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
-            req.field_type,
-            SegmentStatsType::Count,
-            accessor_idx,
-            *missing,
-        ))),
-        Max(MaxAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
-            req.field_type,
-            SegmentStatsType::Max,
-            accessor_idx,
-            *missing,
-        ))),
-        Min(MinAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
-            req.field_type,
-            SegmentStatsType::Min,
-            accessor_idx,
-            *missing,
-        ))),
-        Stats(StatsAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
-            req.field_type,
-            SegmentStatsType::Stats,
-            accessor_idx,
-            *missing,
-        ))),
-        ExtendedStats(ExtendedStatsAggregation { missing, sigma, .. }) => Ok(Box::new(
-            SegmentExtendedStatsCollector::from_req(req.field_type, *sigma, accessor_idx, *missing),
-        )),
-        Sum(SumAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
-            req.field_type,
-            SegmentStatsType::Sum,
-            accessor_idx,
-            *missing,
-        ))),
-        Percentiles(percentiles_req) => Ok(Box::new(
-            SegmentPercentilesCollector::from_req_and_validate(
-                percentiles_req,
-                req.field_type,
-                accessor_idx,
-            )?,
-        )),
-        TopHits(top_hits_req) => Ok(Box::new(TopHitsSegmentCollector::from_req(
-            top_hits_req,
-            accessor_idx,
-            req.segment_ordinal,
-        ))),
-        Cardinality(CardinalityAggregationReq { missing, .. }) => Ok(Box::new(
-            SegmentCardinalityCollector::from_req(req.field_type, accessor_idx, missing),
-        )),
-    }
-}
-
-#[derive(Clone, Default)]
+#[derive(Default)]
 /// The GenericSegmentAggregationResultsCollector is the generic version of the collector, which
 /// can handle arbitrary complexity of  sub-aggregations. Ideally we never have to pick this one
 /// and can provide specialized versions instead, that remove some of its overhead.
@@ -196,12 +96,13 @@ impl Debug for GenericSegmentAggregationResultsCollector {
 
 impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
     fn add_intermediate_aggregation_result(
-        self: Box<Self>,
-        agg_with_accessor: &AggregationsWithAccessor,
+        &mut self,
+        agg_data: &AggregationsSegmentCtx,
         results: &mut IntermediateAggregationResults,
+        parent_bucket_id: BucketId,
     ) -> crate::Result<()> {
-        for agg in self.aggs {
-            agg.add_intermediate_aggregation_result(agg_with_accessor, results)?;
+        for agg in &mut self.aggs {
+            agg.add_intermediate_aggregation_result(agg_data, results, parent_bucket_id)?;
         }
 
         Ok(())
@@ -209,43 +110,31 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
 
     fn collect(
         &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &mut AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collect_block(&[doc], agg_with_accessor)?;
-
-        Ok(())
-    }
-
-    fn collect_block(
-        &mut self,
+        parent_bucket_id: BucketId,
         docs: &[crate::DocId],
-        agg_with_accessor: &mut AggregationsWithAccessor,
+        agg_data: &mut AggregationsSegmentCtx,
     ) -> crate::Result<()> {
         for collector in &mut self.aggs {
-            collector.collect_block(docs, agg_with_accessor)?;
+            collector.collect(parent_bucket_id, docs, agg_data)?;
         }
-
         Ok(())
     }
 
-    fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
+    fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
         for collector in &mut self.aggs {
-            collector.flush(agg_with_accessor)?;
+            collector.flush(agg_data)?;
+        }
+        Ok(())
+    }
+
+    fn prepare_max_bucket(
+        &mut self,
+        max_bucket: BucketId,
+        agg_data: &AggregationsSegmentCtx,
+    ) -> crate::Result<()> {
+        for collector in &mut self.aggs {
+            collector.prepare_max_bucket(max_bucket, agg_data)?;
         }
         Ok(())
     }
 }
-
-impl GenericSegmentAggregationResultsCollector {
-    pub(crate) fn from_req_and_validate(req: &mut AggregationsWithAccessor) -> crate::Result<Self> {
-        let aggs = req
-            .aggs
-            .values_mut()
-            .enumerate()
-            .map(|(accessor_idx, req)| build_single_agg_segment_collector(req, accessor_idx))
-            .collect::<crate::Result<Vec<Box<dyn SegmentAggregationCollector>>>>()?;
-
-        Ok(GenericSegmentAggregationResultsCollector { aggs })
-    }
-}

src/collector/custom_score_top_collector.rs

@@ -1,121 +0,0 @@
-use crate::collector::top_collector::{TopCollector, TopSegmentCollector};
-use crate::collector::{Collector, SegmentCollector};
-use crate::{DocAddress, DocId, Score, SegmentReader};
-
-pub(crate) struct CustomScoreTopCollector<TCustomScorer, TScore = Score> {
-    custom_scorer: TCustomScorer,
-    collector: TopCollector<TScore>,
-}
-
-impl<TCustomScorer, TScore> CustomScoreTopCollector<TCustomScorer, TScore>
-where TScore: Clone + PartialOrd
-{
-    pub(crate) fn new(
-        custom_scorer: TCustomScorer,
-        collector: TopCollector<TScore>,
-    ) -> CustomScoreTopCollector<TCustomScorer, TScore> {
-        CustomScoreTopCollector {
-            custom_scorer,
-            collector,
-        }
-    }
-}
-
-/// A custom segment scorer makes it possible to define any kind of score
-/// for a given document belonging to a specific segment.
-///
-/// It is the segment local version of the [`CustomScorer`].
-pub trait CustomSegmentScorer<TScore>: 'static {
-    /// Computes the score of a specific `doc`.
-    fn score(&mut self, doc: DocId) -> TScore;
-}
-
-/// `CustomScorer` makes it possible to define any kind of score.
-///
-/// The `CustomerScorer` itself does not make much of the computation itself.
-/// Instead, it helps constructing `Self::Child` instances that will compute
-/// the score at a segment scale.
-pub trait CustomScorer<TScore>: Sync {
-    /// Type of the associated [`CustomSegmentScorer`].
-    type Child: CustomSegmentScorer<TScore>;
-    /// Builds a child scorer for a specific segment. The child scorer is associated with
-    /// a specific segment.
-    fn segment_scorer(&self, segment_reader: &SegmentReader) -> crate::Result<Self::Child>;
-}
-
-impl<TCustomScorer, TScore> Collector for CustomScoreTopCollector<TCustomScorer, TScore>
-where
-    TCustomScorer: CustomScorer<TScore> + Send + Sync,
-    TScore: 'static + PartialOrd + Clone + Send + Sync,
-{
-    type Fruit = Vec<(TScore, DocAddress)>;
-
-    type Child = CustomScoreTopSegmentCollector<TCustomScorer::Child, TScore>;
-
-    fn for_segment(
-        &self,
-        segment_local_id: u32,
-        segment_reader: &SegmentReader,
-    ) -> crate::Result<Self::Child> {
-        let segment_collector = self.collector.for_segment(segment_local_id, segment_reader);
-        let segment_scorer = self.custom_scorer.segment_scorer(segment_reader)?;
-        Ok(CustomScoreTopSegmentCollector {
-            segment_collector,
-            segment_scorer,
-        })
-    }
-
-    fn requires_scoring(&self) -> bool {
-        false
-    }
-
-    fn merge_fruits(&self, segment_fruits: Vec<Self::Fruit>) -> crate::Result<Self::Fruit> {
-        self.collector.merge_fruits(segment_fruits)
-    }
-}
-
-pub struct CustomScoreTopSegmentCollector<T, TScore>
-where
-    TScore: 'static + PartialOrd + Clone + Send + Sync + Sized,
-    T: CustomSegmentScorer<TScore>,
-{
-    segment_collector: TopSegmentCollector<TScore>,
-    segment_scorer: T,
-}
-
-impl<T, TScore> SegmentCollector for CustomScoreTopSegmentCollector<T, TScore>
-where
-    TScore: 'static + PartialOrd + Clone + Send + Sync,
-    T: 'static + CustomSegmentScorer<TScore>,
-{
-    type Fruit = Vec<(TScore, DocAddress)>;
-
-    fn collect(&mut self, doc: DocId, _score: Score) {
-        let score = self.segment_scorer.score(doc);
-        self.segment_collector.collect(doc, score);
-    }
-
-    fn harvest(self) -> Vec<(TScore, DocAddress)> {
-        self.segment_collector.harvest()
-    }
-}
-
-impl<F, TScore, T> CustomScorer<TScore> for F
-where
-    F: 'static + Send + Sync + Fn(&SegmentReader) -> T,
-    T: CustomSegmentScorer<TScore>,
-{
-    type Child = T;
-
-    fn segment_scorer(&self, segment_reader: &SegmentReader) -> crate::Result<Self::Child> {
-        Ok((self)(segment_reader))
-    }
-}
-
-impl<F, TScore> CustomSegmentScorer<TScore> for F
-where F: 'static + FnMut(DocId) -> TScore
-{
-    fn score(&mut self, doc: DocId) -> TScore {
-        (self)(doc)
-    }
-}

src/collector/facet_collector.rs

@@ -484,7 +484,6 @@ impl FacetCounts {
 #[cfg(test)]
 mod tests {
     use std::collections::BTreeSet;
-    use std::iter;
 
     use columnar::Dictionary;
     use rand::distributions::Uniform;

src/collector/filter_collector_wrapper.rs

@@ -12,6 +12,7 @@ use std::marker::PhantomData;
 use columnar::{BytesColumn, Column, DynamicColumn, HasAssociatedColumnType};
 
 use crate::collector::{Collector, SegmentCollector};
+use crate::schema::Schema;
 use crate::{DocId, Score, SegmentReader};
 
 /// The `FilterCollector` filters docs using a fast field value and a predicate.
@@ -49,13 +50,13 @@ use crate::{DocId, Score, SegmentReader};
 ///
 /// let query_parser = QueryParser::for_index(&index, vec![title]);
 /// let query = query_parser.parse_query("diary")?;
-/// let no_filter_collector = FilterCollector::new("price".to_string(), |value: u64| value > 20_120u64, TopDocs::with_limit(2));
+/// let no_filter_collector = FilterCollector::new("price".to_string(), |value: u64| value > 20_120u64, TopDocs::with_limit(2).order_by_score());
 /// let top_docs = searcher.search(&query, &no_filter_collector)?;
 ///
 /// assert_eq!(top_docs.len(), 1);
 /// assert_eq!(top_docs[0].1, DocAddress::new(0, 1));
 ///
-/// let filter_all_collector: FilterCollector<_, _, u64> = FilterCollector::new("price".to_string(), |value| value < 5u64, TopDocs::with_limit(2));
+/// let filter_all_collector: FilterCollector<_, _, u64> = FilterCollector::new("price".to_string(), |value| value < 5u64, TopDocs::with_limit(2).order_by_score());
 /// let filtered_top_docs = searcher.search(&query, &filter_all_collector)?;
 ///
 /// assert_eq!(filtered_top_docs.len(), 0);
@@ -104,6 +105,11 @@ where
 
     type Child = FilterSegmentCollector<TCollector::Child, TPredicate, TPredicateValue>;
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.collector.check_schema(schema)?;
+        Ok(())
+    }
+
     fn for_segment(
         &self,
         segment_local_id: u32,
@@ -120,6 +126,7 @@ where
             segment_collector,
             predicate: self.predicate.clone(),
             t_predicate_value: PhantomData,
+            filtered_docs: Vec::with_capacity(crate::COLLECT_BLOCK_BUFFER_LEN),
         })
     }
 
@@ -140,6 +147,7 @@ pub struct FilterSegmentCollector<TSegmentCollector, TPredicate, TPredicateValue
     segment_collector: TSegmentCollector,
     predicate: TPredicate,
     t_predicate_value: PhantomData<TPredicateValue>,
+    filtered_docs: Vec<DocId>,
 }
 
 impl<TSegmentCollector, TPredicate, TPredicateValue>
@@ -176,6 +184,20 @@ where
         }
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        self.filtered_docs.clear();
+        for &doc in docs {
+            // TODO: `accept_document` could be further optimized to do batch lookups of column
+            // values for single-valued columns.
+            if self.accept_document(doc) {
+                self.filtered_docs.push(doc);
+            }
+        }
+        if !self.filtered_docs.is_empty() {
+            self.segment_collector.collect_block(&self.filtered_docs);
+        }
+    }
+
     fn harvest(self) -> TSegmentCollector::Fruit {
         self.segment_collector.harvest()
     }
@@ -218,7 +240,7 @@ where
 ///
 /// let query_parser = QueryParser::for_index(&index, vec![title]);
 /// let query = query_parser.parse_query("diary")?;
-/// let filter_collector = BytesFilterCollector::new("barcode".to_string(), |bytes: &[u8]| bytes.starts_with(b"01"), TopDocs::with_limit(2));
+/// let filter_collector = BytesFilterCollector::new("barcode".to_string(), |bytes: &[u8]| bytes.starts_with(b"01"), TopDocs::with_limit(2).order_by_score());
 /// let top_docs = searcher.search(&query, &filter_collector)?;
 ///
 /// assert_eq!(top_docs.len(), 1);
@@ -258,6 +280,10 @@ where
 
     type Child = BytesFilterSegmentCollector<TCollector::Child, TPredicate>;
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.collector.check_schema(schema)
+    }
+
     fn for_segment(
         &self,
         segment_local_id: u32,
@@ -274,6 +300,7 @@ where
             segment_collector,
             predicate: self.predicate.clone(),
             buffer: Vec::new(),
+            filtered_docs: Vec::with_capacity(crate::COLLECT_BLOCK_BUFFER_LEN),
         })
     }
 
@@ -296,6 +323,7 @@ where TPredicate: 'static
     segment_collector: TSegmentCollector,
     predicate: TPredicate,
     buffer: Vec<u8>,
+    filtered_docs: Vec<DocId>,
 }
 
 impl<TSegmentCollector, TPredicate> BytesFilterSegmentCollector<TSegmentCollector, TPredicate>
@@ -334,6 +362,20 @@ where
         }
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        self.filtered_docs.clear();
+        for &doc in docs {
+            // TODO: `accept_document` could be further optimized to do batch lookups of column
+            // values for single-valued columns.
+            if self.accept_document(doc) {
+                self.filtered_docs.push(doc);
+            }
+        }
+        if !self.filtered_docs.is_empty() {
+            self.segment_collector.collect_block(&self.filtered_docs);
+        }
+    }
+
     fn harvest(self) -> TSegmentCollector::Fruit {
         self.segment_collector.harvest()
     }

src/collector/mod.rs

@@ -57,7 +57,7 @@
 //! #     let query_parser = QueryParser::for_index(&index, vec![title]);
 //! #     let query = query_parser.parse_query("diary")?;
 //! let (doc_count, top_docs): (usize, Vec<(Score, DocAddress)>) =
-//! searcher.search(&query, &(Count, TopDocs::with_limit(2)))?;
+//! searcher.search(&query, &(Count, TopDocs::with_limit(2).order_by_score()))?;
 //! #     Ok(())
 //! # }
 //! ```
@@ -83,11 +83,15 @@
 
 use downcast_rs::impl_downcast;
 
+use crate::schema::Schema;
 use crate::{DocId, Score, SegmentOrdinal, SegmentReader};
 
 mod count_collector;
 pub use self::count_collector::Count;
 
+/// Sort keys
+pub mod sort_key;
+
 mod histogram_collector;
 pub use histogram_collector::HistogramCollector;
 
@@ -95,16 +99,13 @@ mod multi_collector;
 pub use self::multi_collector::{FruitHandle, MultiCollector, MultiFruit};
 
 mod top_collector;
+pub use self::top_collector::ComparableDoc;
 
 mod top_score_collector;
-pub use self::top_collector::ComparableDoc;
 pub use self::top_score_collector::{TopDocs, TopNComputer};
 
-mod custom_score_top_collector;
-pub use self::custom_score_top_collector::{CustomScorer, CustomSegmentScorer};
-
-mod tweak_score_top_collector;
-pub use self::tweak_score_top_collector::{ScoreSegmentTweaker, ScoreTweaker};
+mod sort_key_top_collector;
+pub use self::sort_key::{SegmentSortKeyComputer, SortKeyComputer};
 mod facet_collector;
 pub use self::facet_collector::{FacetCollector, FacetCounts};
 use crate::query::Weight;
@@ -145,6 +146,11 @@ pub trait Collector: Sync + Send {
     /// Type of the `SegmentCollector` associated with this collector.
     type Child: SegmentCollector;
 
+    /// Returns an error if the schema is not compatible with the collector.
+    fn check_schema(&self, _schema: &Schema) -> crate::Result<()> {
+        Ok(())
+    }
+
     /// `set_segment` is called before beginning to enumerate
     /// on this segment.
     fn for_segment(
@@ -170,41 +176,50 @@ pub trait Collector: Sync + Send {
         segment_ord: u32,
         reader: &SegmentReader,
     ) -> crate::Result<<Self::Child as SegmentCollector>::Fruit> {
+        let with_scoring = self.requires_scoring();
         let mut segment_collector = self.for_segment(segment_ord, reader)?;
-
-        match (reader.alive_bitset(), self.requires_scoring()) {
-            (Some(alive_bitset), true) => {
-                weight.for_each(reader, &mut |doc, score| {
-                    if alive_bitset.is_alive(doc) {
-                        segment_collector.collect(doc, score);
-                    }
-                })?;
-            }
-            (Some(alive_bitset), false) => {
-                weight.for_each_no_score(reader, &mut |docs| {
-                    for doc in docs.iter().cloned() {
-                        if alive_bitset.is_alive(doc) {
-                            segment_collector.collect(doc, 0.0);
-                        }
-                    }
-                })?;
-            }
-            (None, true) => {
-                weight.for_each(reader, &mut |doc, score| {
-                    segment_collector.collect(doc, score);
-                })?;
-            }
-            (None, false) => {
-                weight.for_each_no_score(reader, &mut |docs| {
-                    segment_collector.collect_block(docs);
-                })?;
-            }
-        }
-
+        default_collect_segment_impl(&mut segment_collector, weight, reader, with_scoring)?;
         Ok(segment_collector.harvest())
     }
 }
 
+pub(crate) fn default_collect_segment_impl<TSegmentCollector: SegmentCollector>(
+    segment_collector: &mut TSegmentCollector,
+    weight: &dyn Weight,
+    reader: &SegmentReader,
+    with_scoring: bool,
+) -> crate::Result<()> {
+    match (reader.alive_bitset(), with_scoring) {
+        (Some(alive_bitset), true) => {
+            weight.for_each(reader, &mut |doc, score| {
+                if alive_bitset.is_alive(doc) {
+                    segment_collector.collect(doc, score);
+                }
+            })?;
+        }
+        (Some(alive_bitset), false) => {
+            weight.for_each_no_score(reader, &mut |docs| {
+                for doc in docs.iter().cloned() {
+                    if alive_bitset.is_alive(doc) {
+                        segment_collector.collect(doc, 0.0);
+                    }
+                }
+            })?;
+        }
+        (None, true) => {
+            weight.for_each(reader, &mut |doc, score| {
+                segment_collector.collect(doc, score);
+            })?;
+        }
+        (None, false) => {
+            weight.for_each_no_score(reader, &mut |docs| {
+                segment_collector.collect_block(docs);
+            })?;
+        }
+    }
+    Ok(())
+}
+
 impl<TSegmentCollector: SegmentCollector> SegmentCollector for Option<TSegmentCollector> {
     type Fruit = Option<TSegmentCollector::Fruit>;
 
@@ -214,6 +229,12 @@ impl<TSegmentCollector: SegmentCollector> SegmentCollector for Option<TSegmentCo
         }
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        if let Some(segment_collector) = self {
+            segment_collector.collect_block(docs);
+        }
+    }
+
     fn harvest(self) -> Self::Fruit {
         self.map(|segment_collector| segment_collector.harvest())
     }
@@ -224,6 +245,13 @@ impl<TCollector: Collector> Collector for Option<TCollector> {
 
     type Child = Option<<TCollector as Collector>::Child>;
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        if let Some(underlying_collector) = self {
+            underlying_collector.check_schema(schema)?;
+        }
+        Ok(())
+    }
+
     fn for_segment(
         &self,
         segment_local_id: SegmentOrdinal,
@@ -299,6 +327,12 @@ where
     type Fruit = (Left::Fruit, Right::Fruit);
     type Child = (Left::Child, Right::Child);
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)?;
+        self.1.check_schema(schema)?;
+        Ok(())
+    }
+
     fn for_segment(
         &self,
         segment_local_id: u32,
@@ -342,6 +376,11 @@ where
         self.1.collect(doc, score);
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        self.0.collect_block(docs);
+        self.1.collect_block(docs);
+    }
+
     fn harvest(self) -> <Self as SegmentCollector>::Fruit {
         (self.0.harvest(), self.1.harvest())
     }
@@ -358,6 +397,13 @@ where
     type Fruit = (One::Fruit, Two::Fruit, Three::Fruit);
     type Child = (One::Child, Two::Child, Three::Child);
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)?;
+        self.1.check_schema(schema)?;
+        self.2.check_schema(schema)?;
+        Ok(())
+    }
+
     fn for_segment(
         &self,
         segment_local_id: u32,
@@ -407,6 +453,12 @@ where
         self.2.collect(doc, score);
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        self.0.collect_block(docs);
+        self.1.collect_block(docs);
+        self.2.collect_block(docs);
+    }
+
     fn harvest(self) -> <Self as SegmentCollector>::Fruit {
         (self.0.harvest(), self.1.harvest(), self.2.harvest())
     }
@@ -424,6 +476,14 @@ where
     type Fruit = (One::Fruit, Two::Fruit, Three::Fruit, Four::Fruit);
     type Child = (One::Child, Two::Child, Three::Child, Four::Child);
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)?;
+        self.1.check_schema(schema)?;
+        self.2.check_schema(schema)?;
+        self.3.check_schema(schema)?;
+        Ok(())
+    }
+
     fn for_segment(
         &self,
         segment_local_id: u32,
@@ -482,6 +542,13 @@ where
         self.3.collect(doc, score);
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        self.0.collect_block(docs);
+        self.1.collect_block(docs);
+        self.2.collect_block(docs);
+        self.3.collect_block(docs);
+    }
+
     fn harvest(self) -> <Self as SegmentCollector>::Fruit {
         (
             self.0.harvest(),

src/collector/multi_collector.rs

@@ -3,6 +3,7 @@ use std::ops::Deref;
 
 use super::{Collector, SegmentCollector};
 use crate::collector::Fruit;
+use crate::schema::Schema;
 use crate::{DocId, Score, SegmentOrdinal, SegmentReader, TantivyError};
 
 /// MultiFruit keeps Fruits from every nested Collector
@@ -16,6 +17,10 @@ impl<TCollector: Collector> Collector for CollectorWrapper<TCollector> {
     type Fruit = Box<dyn Fruit>;
     type Child = Box<dyn BoxableSegmentCollector>;
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)
+    }
+
     fn for_segment(
         &self,
         segment_local_id: u32,
@@ -147,7 +152,7 @@ impl<TFruit: Fruit> FruitHandle<TFruit> {
 /// let searcher = reader.searcher();
 ///
 /// let mut collectors = MultiCollector::new();
-/// let top_docs_handle = collectors.add_collector(TopDocs::with_limit(2));
+/// let top_docs_handle = collectors.add_collector(TopDocs::with_limit(2).order_by_score());
 /// let count_handle = collectors.add_collector(Count);
 /// let query_parser = QueryParser::for_index(&index, vec![title]);
 /// let query = query_parser.parse_query("diary").unwrap();
@@ -194,6 +199,13 @@ impl Collector for MultiCollector<'_> {
     type Fruit = MultiFruit;
     type Child = MultiCollectorChild;
 
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        for collector in &self.collector_wrappers {
+            collector.check_schema(schema)?;
+        }
+        Ok(())
+    }
+
     fn for_segment(
         &self,
         segment_local_id: SegmentOrdinal,
@@ -250,6 +262,12 @@ impl SegmentCollector for MultiCollectorChild {
         }
     }
 
+    fn collect_block(&mut self, docs: &[DocId]) {
+        for child in &mut self.children {
+            child.collect_block(docs);
+        }
+    }
+
     fn harvest(self) -> MultiFruit {
         MultiFruit {
             sub_fruits: self
@@ -293,7 +311,7 @@ mod tests {
         let query = TermQuery::new(term, IndexRecordOption::Basic);
 
         let mut collectors = MultiCollector::new();
-        let topdocs_handler = collectors.add_collector(TopDocs::with_limit(2));
+        let topdocs_handler = collectors.add_collector(TopDocs::with_limit(2).order_by_score());
         let count_handler = collectors.add_collector(Count);
         let mut multifruits = searcher.search(&query, &collectors).unwrap();
 

src/collector/sort_key/mod.rs

@@ -0,0 +1,393 @@
+mod order;
+mod sort_by_score;
+mod sort_by_static_fast_value;
+mod sort_by_string;
+mod sort_key_computer;
+
+pub use order::*;
+pub use sort_by_score::SortBySimilarityScore;
+pub use sort_by_static_fast_value::SortByStaticFastValue;
+pub use sort_by_string::SortByString;
+pub use sort_key_computer::{SegmentSortKeyComputer, SortKeyComputer};
+
+#[cfg(test)]
+mod tests {
+    use std::collections::HashMap;
+    use std::ops::Range;
+
+    use crate::collector::sort_key::{SortBySimilarityScore, SortByStaticFastValue, SortByString};
+    use crate::collector::{ComparableDoc, DocSetCollector, TopDocs};
+    use crate::indexer::NoMergePolicy;
+    use crate::query::{AllQuery, QueryParser};
+    use crate::schema::{Schema, FAST, TEXT};
+    use crate::{DocAddress, Document, Index, Order, Score, Searcher};
+
+    fn make_index() -> crate::Result<Index> {
+        let mut schema_builder = Schema::builder();
+        let id = schema_builder.add_u64_field("id", FAST);
+        let city = schema_builder.add_text_field("city", TEXT | FAST);
+        let catchphrase = schema_builder.add_text_field("catchphrase", TEXT);
+        let altitude = schema_builder.add_f64_field("altitude", FAST);
+        let schema = schema_builder.build();
+        let index = Index::create_in_ram(schema);
+
+        fn create_segment(index: &Index, docs: Vec<impl Document>) -> crate::Result<()> {
+            let mut index_writer = index.writer_for_tests()?;
+            index_writer.set_merge_policy(Box::new(NoMergePolicy));
+            for doc in docs {
+                index_writer.add_document(doc)?;
+            }
+            index_writer.commit()?;
+            Ok(())
+        }
+
+        create_segment(
+            &index,
+            vec![
+                doc!(
+                    id => 0_u64,
+                    city => "austin",
+                    catchphrase => "Hills, Barbeque, Glow",
+                    altitude => 149.0,
+                ),
+                doc!(
+                    id => 1_u64,
+                    city => "greenville",
+                    catchphrase => "Grow, Glow, Glow",
+                    altitude => 27.0,
+                ),
+            ],
+        )?;
+        create_segment(
+            &index,
+            vec![doc!(
+                id => 2_u64,
+                city => "tokyo",
+                catchphrase => "Glow, Glow, Glow",
+                altitude => 40.0,
+            )],
+        )?;
+        create_segment(
+            &index,
+            vec![doc!(
+                id => 3_u64,
+                catchphrase => "No, No, No",
+                altitude => 0.0,
+            )],
+        )?;
+        Ok(index)
+    }
+
+    // NOTE: You cannot determine the SegmentIds that will be generated for Segments
+    // ahead of time, so DocAddresses must be mapped back to a unique id for each Searcher.
+    fn id_mapping(searcher: &Searcher) -> HashMap<DocAddress, u64> {
+        searcher
+            .search(&AllQuery, &DocSetCollector)
+            .unwrap()
+            .into_iter()
+            .map(|doc_address| {
+                let column = searcher.segment_readers()[doc_address.segment_ord as usize]
+                    .fast_fields()
+                    .u64("id")
+                    .unwrap();
+                (doc_address, column.first(doc_address.doc_id).unwrap())
+            })
+            .collect()
+    }
+
+    #[test]
+    fn test_order_by_string() -> crate::Result<()> {
+        let index = make_index()?;
+
+        #[track_caller]
+        fn assert_query(
+            index: &Index,
+            order: Order,
+            doc_range: Range<usize>,
+            expected: Vec<(Option<String>, u64)>,
+        ) -> crate::Result<()> {
+            let searcher = index.reader()?.searcher();
+            let ids = id_mapping(&searcher);
+
+            // Try as primitive.
+            let top_collector = TopDocs::for_doc_range(doc_range)
+                .order_by((SortByString::for_field("city"), order));
+            let actual = searcher
+                .search(&AllQuery, &top_collector)?
+                .into_iter()
+                .map(|(sort_key_opt, doc)| (sort_key_opt, ids[&doc]))
+                .collect::<Vec<_>>();
+            assert_eq!(actual, expected);
+            Ok(())
+        }
+
+        assert_query(
+            &index,
+            Order::Asc,
+            0..4,
+            vec![
+                (Some("austin".to_owned()), 0),
+                (Some("greenville".to_owned()), 1),
+                (Some("tokyo".to_owned()), 2),
+                (None, 3),
+            ],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Asc,
+            0..3,
+            vec![
+                (Some("austin".to_owned()), 0),
+                (Some("greenville".to_owned()), 1),
+                (Some("tokyo".to_owned()), 2),
+            ],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Asc,
+            0..2,
+            vec![
+                (Some("austin".to_owned()), 0),
+                (Some("greenville".to_owned()), 1),
+            ],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Asc,
+            0..1,
+            vec![(Some("austin".to_string()), 0)],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Asc,
+            1..3,
+            vec![
+                (Some("greenville".to_owned()), 1),
+                (Some("tokyo".to_owned()), 2),
+            ],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Desc,
+            0..4,
+            vec![
+                (Some("tokyo".to_owned()), 2),
+                (Some("greenville".to_owned()), 1),
+                (Some("austin".to_owned()), 0),
+                (None, 3),
+            ],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Desc,
+            1..3,
+            vec![
+                (Some("greenville".to_owned()), 1),
+                (Some("austin".to_owned()), 0),
+            ],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Desc,
+            0..1,
+            vec![(Some("tokyo".to_owned()), 2)],
+        )?;
+
+        Ok(())
+    }
+
+    #[test]
+    fn test_order_by_f64() -> crate::Result<()> {
+        let index = make_index()?;
+
+        fn assert_query(
+            index: &Index,
+            order: Order,
+            expected: Vec<(Option<f64>, u64)>,
+        ) -> crate::Result<()> {
+            let searcher = index.reader()?.searcher();
+            let ids = id_mapping(&searcher);
+
+            // Try as primitive.
+            let top_collector = TopDocs::with_limit(3)
+                .order_by((SortByStaticFastValue::<f64>::for_field("altitude"), order));
+            let actual = searcher
+                .search(&AllQuery, &top_collector)?
+                .into_iter()
+                .map(|(altitude_opt, doc)| (altitude_opt, ids[&doc]))
+                .collect::<Vec<_>>();
+            assert_eq!(actual, expected);
+
+            Ok(())
+        }
+
+        assert_query(
+            &index,
+            Order::Asc,
+            vec![(Some(0.0), 3), (Some(27.0), 1), (Some(40.0), 2)],
+        )?;
+
+        assert_query(
+            &index,
+            Order::Desc,
+            vec![(Some(149.0), 0), (Some(40.0), 2), (Some(27.0), 1)],
+        )?;
+
+        Ok(())
+    }
+
+    #[test]
+    fn test_order_by_score() -> crate::Result<()> {
+        let index = make_index()?;
+
+        fn query(index: &Index, order: Order) -> crate::Result<Vec<(Score, u64)>> {
+            let searcher = index.reader()?.searcher();
+            let ids = id_mapping(&searcher);
+
+            let top_collector = TopDocs::with_limit(4).order_by((SortBySimilarityScore, order));
+            let field = index.schema().get_field("catchphrase").unwrap();
+            let query_parser = QueryParser::for_index(index, vec![field]);
+            let text_query = query_parser.parse_query("glow")?;
+
+            Ok(searcher
+                .search(&text_query, &top_collector)?
+                .into_iter()
+                .map(|(score, doc)| (score, ids[&doc]))
+                .collect())
+        }
+
+        assert_eq!(
+            &query(&index, Order::Desc)?,
+            &[(0.5604893, 2), (0.4904281, 1), (0.35667497, 0),]
+        );
+
+        assert_eq!(
+            &query(&index, Order::Asc)?,
+            &[(0.35667497, 0), (0.4904281, 1), (0.5604893, 2),]
+        );
+
+        Ok(())
+    }
+
+    #[test]
+    fn test_order_by_score_then_string() -> crate::Result<()> {
+        let index = make_index()?;
+
+        type SortKey = (Score, Option<String>);
+
+        fn query(
+            index: &Index,
+            score_order: Order,
+            city_order: Order,
+        ) -> crate::Result<Vec<(SortKey, u64)>> {
+            let searcher = index.reader()?.searcher();
+            let ids = id_mapping(&searcher);
+
+            let top_collector = TopDocs::with_limit(4).order_by((
+                (SortBySimilarityScore, score_order),
+                (SortByString::for_field("city"), city_order),
+            ));
+            Ok(searcher
+                .search(&AllQuery, &top_collector)?
+                .into_iter()
+                .map(|(f, doc)| (f, ids[&doc]))
+                .collect())
+        }
+
+        assert_eq!(
+            &query(&index, Order::Asc, Order::Asc)?,
+            &[
+                ((1.0, Some("austin".to_owned())), 0),
+                ((1.0, Some("greenville".to_owned())), 1),
+                ((1.0, Some("tokyo".to_owned())), 2),
+                ((1.0, None), 3),
+            ]
+        );
+
+        assert_eq!(
+            &query(&index, Order::Asc, Order::Desc)?,
+            &[
+                ((1.0, Some("tokyo".to_owned())), 2),
+                ((1.0, Some("greenville".to_owned())), 1),
+                ((1.0, Some("austin".to_owned())), 0),
+                ((1.0, None), 3),
+            ]
+        );
+        Ok(())
+    }
+
+    use proptest::prelude::*;
+
+    proptest! {
+    #[test]
+    fn test_order_by_string_prop(
+          order in prop_oneof!(Just(Order::Desc), Just(Order::Asc)),
+          limit in 1..64_usize,
+          offset in 0..64_usize,
+          segments_terms in
+            proptest::collection::vec(
+                proptest::collection::vec(0..32_u8, 1..32_usize),
+                0..8_usize,
+            )
+        ) {
+            let mut schema_builder = Schema::builder();
+            let city = schema_builder.add_text_field("city", TEXT | FAST);
+            let schema = schema_builder.build();
+            let index = Index::create_in_ram(schema);
+            let mut index_writer = index.writer_for_tests()?;
+
+            // A Vec<Vec<u8>>, where the outer Vec represents segments, and the inner Vec
+            // represents terms.
+            for segment_terms in segments_terms.into_iter() {
+                for term in segment_terms.into_iter() {
+                    let term = format!("{term:0>3}");
+                    index_writer.add_document(doc!(
+                        city => term,
+                    ))?;
+                }
+                index_writer.commit()?;
+            }
+
+            let searcher = index.reader()?.searcher();
+            let top_n_results = searcher.search(&AllQuery, &TopDocs::with_limit(limit)
+                .and_offset(offset)
+                .order_by_string_fast_field("city", order))?;
+            let all_results = searcher.search(&AllQuery, &DocSetCollector)?.into_iter().map(|doc_address| {
+                // Get the term for this address.
+                let column = searcher.segment_readers()[doc_address.segment_ord as usize].fast_fields().str("city").unwrap().unwrap();
+                let value = column.term_ords(doc_address.doc_id).next().map(|term_ord| {
+                    let mut city = Vec::new();
+                    column.dictionary().ord_to_term(term_ord, &mut city).unwrap();
+                    String::try_from(city).unwrap()
+                });
+                (value, doc_address)
+            });
+
+            // Using the TopDocs collector should always be equivalent to sorting, skipping the
+            // offset, and then taking the limit.
+            let sorted_docs: Vec<_> = if order.is_desc() {
+                let mut comparable_docs: Vec<ComparableDoc<_, _, true>> =
+                    all_results.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc}).collect();
+                comparable_docs.sort();
+                comparable_docs.into_iter().map(|cd| (cd.sort_key, cd.doc)).collect()
+            } else {
+                let mut comparable_docs: Vec<ComparableDoc<_, _, false>> =
+                    all_results.into_iter().map(|(sort_key, doc)| ComparableDoc { sort_key, doc}).collect();
+                comparable_docs.sort();
+                comparable_docs.into_iter().map(|cd| (cd.sort_key, cd.doc)).collect()
+            };
+            let expected_docs = sorted_docs.into_iter().skip(offset).take(limit).collect::<Vec<_>>();
+            prop_assert_eq!(
+                expected_docs,
+                top_n_results
+            );
+        }
+    }
+}

src/collector/sort_key/order.rs

@@ -0,0 +1,348 @@
+use std::cmp::Ordering;
+
+use serde::{Deserialize, Serialize};
+
+use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
+use crate::schema::Schema;
+use crate::{DocId, Order, Score};
+
+/// Comparator trait defining the order in which documents should be ordered.
+pub trait Comparator<T>: Send + Sync + std::fmt::Debug + Default {
+    /// Return the order between two values.
+    fn compare(&self, lhs: &T, rhs: &T) -> Ordering;
+}
+
+/// With the natural comparator, the top k collector will return
+/// the top documents in decreasing order.
+#[derive(Debug, Copy, Clone, Default, Serialize, Deserialize)]
+pub struct NaturalComparator;
+
+impl<T: PartialOrd> Comparator<T> for NaturalComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &T, rhs: &T) -> Ordering {
+        lhs.partial_cmp(rhs).unwrap()
+    }
+}
+
+/// Sorts document in reverse order.
+///
+/// If the sort key is None, it will considered as the lowest value, and will therefore appear
+/// first.
+///
+/// The ReverseComparator does not necessarily imply that the sort order is reversed compared
+/// to the NaturalComparator. In presence of a tie, both version will retain the higher doc ids.
+#[derive(Debug, Copy, Clone, Default, Serialize, Deserialize)]
+pub struct ReverseComparator;
+
+impl<T> Comparator<T> for ReverseComparator
+where NaturalComparator: Comparator<T>
+{
+    #[inline(always)]
+    fn compare(&self, lhs: &T, rhs: &T) -> Ordering {
+        NaturalComparator.compare(rhs, lhs)
+    }
+}
+
+/// Sorts document in reverse order, but considers None as having the lowest value.
+///
+/// This is usually what is wanted when sorting by a field in an ascending order.
+/// For instance, in a e-commerce website, if I sort by price ascending, I most likely want the
+/// cheapest items first, and the items without a price at last.
+#[derive(Debug, Copy, Clone, Default)]
+pub struct ReverseNoneIsLowerComparator;
+
+impl<T> Comparator<Option<T>> for ReverseNoneIsLowerComparator
+where ReverseComparator: Comparator<T>
+{
+    #[inline(always)]
+    fn compare(&self, lhs_opt: &Option<T>, rhs_opt: &Option<T>) -> Ordering {
+        match (lhs_opt, rhs_opt) {
+            (None, None) => Ordering::Equal,
+            (None, Some(_)) => Ordering::Less,
+            (Some(_), None) => Ordering::Greater,
+            (Some(lhs), Some(rhs)) => ReverseComparator.compare(lhs, rhs),
+        }
+    }
+}
+
+impl Comparator<u32> for ReverseNoneIsLowerComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &u32, rhs: &u32) -> Ordering {
+        ReverseComparator.compare(lhs, rhs)
+    }
+}
+
+impl Comparator<u64> for ReverseNoneIsLowerComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &u64, rhs: &u64) -> Ordering {
+        ReverseComparator.compare(lhs, rhs)
+    }
+}
+
+impl Comparator<f64> for ReverseNoneIsLowerComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &f64, rhs: &f64) -> Ordering {
+        ReverseComparator.compare(lhs, rhs)
+    }
+}
+
+impl Comparator<f32> for ReverseNoneIsLowerComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &f32, rhs: &f32) -> Ordering {
+        ReverseComparator.compare(lhs, rhs)
+    }
+}
+
+impl Comparator<i64> for ReverseNoneIsLowerComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &i64, rhs: &i64) -> Ordering {
+        ReverseComparator.compare(lhs, rhs)
+    }
+}
+
+impl Comparator<String> for ReverseNoneIsLowerComparator {
+    #[inline(always)]
+    fn compare(&self, lhs: &String, rhs: &String) -> Ordering {
+        ReverseComparator.compare(lhs, rhs)
+    }
+}
+
+/// An enum representing the different sort orders.
+#[derive(Debug, Clone, Copy, Eq, PartialEq, Default)]
+pub enum ComparatorEnum {
+    /// Natural order (See [NaturalComparator])
+    #[default]
+    Natural,
+    /// Reverse order (See [ReverseComparator])
+    Reverse,
+    /// Reverse order by treating None as the lowest value.(See [ReverseNoneLowerComparator])
+    ReverseNoneLower,
+}
+
+impl From<Order> for ComparatorEnum {
+    fn from(order: Order) -> Self {
+        match order {
+            Order::Asc => ComparatorEnum::ReverseNoneLower,
+            Order::Desc => ComparatorEnum::Natural,
+        }
+    }
+}
+
+impl<T> Comparator<T> for ComparatorEnum
+where
+    ReverseNoneIsLowerComparator: Comparator<T>,
+    NaturalComparator: Comparator<T>,
+    ReverseComparator: Comparator<T>,
+{
+    #[inline(always)]
+    fn compare(&self, lhs: &T, rhs: &T) -> Ordering {
+        match self {
+            ComparatorEnum::Natural => NaturalComparator.compare(lhs, rhs),
+            ComparatorEnum::Reverse => ReverseComparator.compare(lhs, rhs),
+            ComparatorEnum::ReverseNoneLower => ReverseNoneIsLowerComparator.compare(lhs, rhs),
+        }
+    }
+}
+
+impl<Head, Tail, LeftComparator, RightComparator> Comparator<(Head, Tail)>
+    for (LeftComparator, RightComparator)
+where
+    LeftComparator: Comparator<Head>,
+    RightComparator: Comparator<Tail>,
+{
+    #[inline(always)]
+    fn compare(&self, lhs: &(Head, Tail), rhs: &(Head, Tail)) -> Ordering {
+        self.0
+            .compare(&lhs.0, &rhs.0)
+            .then_with(|| self.1.compare(&lhs.1, &rhs.1))
+    }
+}
+
+impl<Type1, Type2, Type3, Comparator1, Comparator2, Comparator3> Comparator<(Type1, (Type2, Type3))>
+    for (Comparator1, Comparator2, Comparator3)
+where
+    Comparator1: Comparator<Type1>,
+    Comparator2: Comparator<Type2>,
+    Comparator3: Comparator<Type3>,
+{
+    #[inline(always)]
+    fn compare(&self, lhs: &(Type1, (Type2, Type3)), rhs: &(Type1, (Type2, Type3))) -> Ordering {
+        self.0
+            .compare(&lhs.0, &rhs.0)
+            .then_with(|| self.1.compare(&lhs.1 .0, &rhs.1 .0))
+            .then_with(|| self.2.compare(&lhs.1 .1, &rhs.1 .1))
+    }
+}
+
+impl<Type1, Type2, Type3, Comparator1, Comparator2, Comparator3> Comparator<(Type1, Type2, Type3)>
+    for (Comparator1, Comparator2, Comparator3)
+where
+    Comparator1: Comparator<Type1>,
+    Comparator2: Comparator<Type2>,
+    Comparator3: Comparator<Type3>,
+{
+    #[inline(always)]
+    fn compare(&self, lhs: &(Type1, Type2, Type3), rhs: &(Type1, Type2, Type3)) -> Ordering {
+        self.0
+            .compare(&lhs.0, &rhs.0)
+            .then_with(|| self.1.compare(&lhs.1, &rhs.1))
+            .then_with(|| self.2.compare(&lhs.2, &rhs.2))
+    }
+}
+
+impl<Type1, Type2, Type3, Type4, Comparator1, Comparator2, Comparator3, Comparator4>
+    Comparator<(Type1, (Type2, (Type3, Type4)))>
+    for (Comparator1, Comparator2, Comparator3, Comparator4)
+where
+    Comparator1: Comparator<Type1>,
+    Comparator2: Comparator<Type2>,
+    Comparator3: Comparator<Type3>,
+    Comparator4: Comparator<Type4>,
+{
+    #[inline(always)]
+    fn compare(
+        &self,
+        lhs: &(Type1, (Type2, (Type3, Type4))),
+        rhs: &(Type1, (Type2, (Type3, Type4))),
+    ) -> Ordering {
+        self.0
+            .compare(&lhs.0, &rhs.0)
+            .then_with(|| self.1.compare(&lhs.1 .0, &rhs.1 .0))
+            .then_with(|| self.2.compare(&lhs.1 .1 .0, &rhs.1 .1 .0))
+            .then_with(|| self.3.compare(&lhs.1 .1 .1, &rhs.1 .1 .1))
+    }
+}
+
+impl<Type1, Type2, Type3, Type4, Comparator1, Comparator2, Comparator3, Comparator4>
+    Comparator<(Type1, Type2, Type3, Type4)>
+    for (Comparator1, Comparator2, Comparator3, Comparator4)
+where
+    Comparator1: Comparator<Type1>,
+    Comparator2: Comparator<Type2>,
+    Comparator3: Comparator<Type3>,
+    Comparator4: Comparator<Type4>,
+{
+    #[inline(always)]
+    fn compare(
+        &self,
+        lhs: &(Type1, Type2, Type3, Type4),
+        rhs: &(Type1, Type2, Type3, Type4),
+    ) -> Ordering {
+        self.0
+            .compare(&lhs.0, &rhs.0)
+            .then_with(|| self.1.compare(&lhs.1, &rhs.1))
+            .then_with(|| self.2.compare(&lhs.2, &rhs.2))
+            .then_with(|| self.3.compare(&lhs.3, &rhs.3))
+    }
+}
+
+impl<TSortKeyComputer> SortKeyComputer for (TSortKeyComputer, ComparatorEnum)
+where
+    TSortKeyComputer: SortKeyComputer,
+    ComparatorEnum: Comparator<TSortKeyComputer::SortKey>,
+    ComparatorEnum: Comparator<
+        <<TSortKeyComputer as SortKeyComputer>::Child as SegmentSortKeyComputer>::SegmentSortKey,
+    >,
+{
+    type SortKey = TSortKeyComputer::SortKey;
+
+    type Child = SegmentSortKeyComputerWithComparator<TSortKeyComputer::Child, Self::Comparator>;
+
+    type Comparator = ComparatorEnum;
+
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)
+    }
+
+    fn requires_scoring(&self) -> bool {
+        self.0.requires_scoring()
+    }
+
+    fn comparator(&self) -> Self::Comparator {
+        self.1
+    }
+
+    fn segment_sort_key_computer(
+        &self,
+        segment_reader: &crate::SegmentReader,
+    ) -> crate::Result<Self::Child> {
+        let child = self.0.segment_sort_key_computer(segment_reader)?;
+        Ok(SegmentSortKeyComputerWithComparator {
+            segment_sort_key_computer: child,
+            comparator: self.comparator(),
+        })
+    }
+}
+
+impl<TSortKeyComputer> SortKeyComputer for (TSortKeyComputer, Order)
+where
+    TSortKeyComputer: SortKeyComputer,
+    ComparatorEnum: Comparator<TSortKeyComputer::SortKey>,
+    ComparatorEnum: Comparator<
+        <<TSortKeyComputer as SortKeyComputer>::Child as SegmentSortKeyComputer>::SegmentSortKey,
+    >,
+{
+    type SortKey = TSortKeyComputer::SortKey;
+
+    type Child = SegmentSortKeyComputerWithComparator<TSortKeyComputer::Child, Self::Comparator>;
+
+    type Comparator = ComparatorEnum;
+
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)
+    }
+
+    fn requires_scoring(&self) -> bool {
+        self.0.requires_scoring()
+    }
+
+    fn comparator(&self) -> Self::Comparator {
+        self.1.into()
+    }
+
+    fn segment_sort_key_computer(
+        &self,
+        segment_reader: &crate::SegmentReader,
+    ) -> crate::Result<Self::Child> {
+        let child = self.0.segment_sort_key_computer(segment_reader)?;
+        Ok(SegmentSortKeyComputerWithComparator {
+            segment_sort_key_computer: child,
+            comparator: self.comparator(),
+        })
+    }
+}
+
+/// A segment sort key computer with a custom ordering.
+pub struct SegmentSortKeyComputerWithComparator<TSegmentSortKeyComputer, TComparator> {
+    segment_sort_key_computer: TSegmentSortKeyComputer,
+    comparator: TComparator,
+}
+
+impl<TSegmentSortKeyComputer, TSegmentSortKey, TComparator> SegmentSortKeyComputer
+    for SegmentSortKeyComputerWithComparator<TSegmentSortKeyComputer, TComparator>
+where
+    TSegmentSortKeyComputer: SegmentSortKeyComputer<SegmentSortKey = TSegmentSortKey>,
+    TSegmentSortKey: PartialOrd + Clone + 'static + Sync + Send,
+    TComparator: Comparator<TSegmentSortKey> + 'static + Sync + Send,
+{
+    type SortKey = TSegmentSortKeyComputer::SortKey;
+    type SegmentSortKey = TSegmentSortKey;
+
+    fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey {
+        self.segment_sort_key_computer.segment_sort_key(doc, score)
+    }
+
+    #[inline(always)]
+    fn compare_segment_sort_key(
+        &self,
+        left: &Self::SegmentSortKey,
+        right: &Self::SegmentSortKey,
+    ) -> Ordering {
+        self.comparator.compare(left, right)
+    }
+
+    fn convert_segment_sort_key(&self, sort_key: Self::SegmentSortKey) -> Self::SortKey {
+        self.segment_sort_key_computer
+            .convert_segment_sort_key(sort_key)
+    }
+}

src/collector/sort_key/sort_by_score.rs

@@ -0,0 +1,77 @@
+use crate::collector::sort_key::NaturalComparator;
+use crate::collector::{SegmentSortKeyComputer, SortKeyComputer, TopNComputer};
+use crate::{DocAddress, DocId, Score};
+
+/// Sort by similarity score.
+#[derive(Clone, Debug, Copy)]
+pub struct SortBySimilarityScore;
+
+impl SortKeyComputer for SortBySimilarityScore {
+    type SortKey = Score;
+
+    type Child = SortBySimilarityScore;
+
+    type Comparator = NaturalComparator;
+
+    fn requires_scoring(&self) -> bool {
+        true
+    }
+
+    fn segment_sort_key_computer(
+        &self,
+        _segment_reader: &crate::SegmentReader,
+    ) -> crate::Result<Self::Child> {
+        Ok(SortBySimilarityScore)
+    }
+
+    // Sorting by score is special in that it allows for the Block-Wand optimization.
+    fn collect_segment_top_k(
+        &self,
+        k: usize,
+        weight: &dyn crate::query::Weight,
+        reader: &crate::SegmentReader,
+        segment_ord: u32,
+    ) -> crate::Result<Vec<(Self::SortKey, DocAddress)>> {
+        let mut top_n: TopNComputer<Score, DocId, Self::Comparator> =
+            TopNComputer::new_with_comparator(k, self.comparator());
+
+        if let Some(alive_bitset) = reader.alive_bitset() {
+            let mut threshold = Score::MIN;
+            top_n.threshold = Some(threshold);
+            weight.for_each_pruning(Score::MIN, reader, &mut |doc, score| {
+                if alive_bitset.is_deleted(doc) {
+                    return threshold;
+                }
+                top_n.push(score, doc);
+                threshold = top_n.threshold.unwrap_or(Score::MIN);
+                threshold
+            })?;
+        } else {
+            weight.for_each_pruning(Score::MIN, reader, &mut |doc, score| {
+                top_n.push(score, doc);
+                top_n.threshold.unwrap_or(Score::MIN)
+            })?;
+        }
+
+        Ok(top_n
+            .into_vec()
+            .into_iter()
+            .map(|cid| (cid.sort_key, DocAddress::new(segment_ord, cid.doc)))
+            .collect())
+    }
+}
+
+impl SegmentSortKeyComputer for SortBySimilarityScore {
+    type SortKey = Score;
+
+    type SegmentSortKey = Score;
+
+    #[inline(always)]
+    fn segment_sort_key(&mut self, _doc: DocId, score: Score) -> Score {
+        score
+    }
+
+    fn convert_segment_sort_key(&self, score: Score) -> Score {
+        score
+    }
+}

src/collector/sort_key/sort_by_static_fast_value.rs

@@ -0,0 +1,98 @@
+use std::marker::PhantomData;
+
+use columnar::Column;
+
+use crate::collector::sort_key::NaturalComparator;
+use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
+use crate::fastfield::{FastFieldNotAvailableError, FastValue};
+use crate::{DocId, Score, SegmentReader};
+
+/// Sorts by a fast value (u64, i64, f64, bool).
+///
+/// The field must appear explicitly in the schema, with the right type, and declared as
+/// a fast field..
+///
+/// If the field is multivalued, only the first value is considered.
+///
+/// Documents that do not have this value are still considered.
+/// Their sort key will simply be `None`.
+#[derive(Debug, Clone)]
+pub struct SortByStaticFastValue<T: FastValue> {
+    field: String,
+    typ: PhantomData<T>,
+}
+
+impl<T: FastValue> SortByStaticFastValue<T> {
+    /// Creates a new `SortByStaticFastValue` instance for the given field.
+    pub fn for_field(column_name: impl ToString) -> SortByStaticFastValue<T> {
+        Self {
+            field: column_name.to_string(),
+            typ: PhantomData,
+        }
+    }
+}
+
+impl<T: FastValue> SortKeyComputer for SortByStaticFastValue<T> {
+    type Child = SortByFastValueSegmentSortKeyComputer<T>;
+
+    type SortKey = Option<T>;
+
+    type Comparator = NaturalComparator;
+
+    fn check_schema(&self, schema: &crate::schema::Schema) -> crate::Result<()> {
+        // At the segment sort key computer level, we rely on the u64 representation.
+        // The mapping is monotonic, so it is sufficient to compute our top-K docs.
+        let field = schema.get_field(&self.field)?;
+        let field_entry = schema.get_field_entry(field);
+        if !field_entry.is_fast() {
+            return Err(crate::TantivyError::SchemaError(format!(
+                "Field `{}` is not a fast field.",
+                self.field,
+            )));
+        }
+        let schema_type = field_entry.field_type().value_type();
+        if schema_type != T::to_type() {
+            return Err(crate::TantivyError::SchemaError(format!(
+                "Field `{}` is of type {schema_type:?}, not of the type {:?}.",
+                &self.field,
+                T::to_type()
+            )));
+        }
+        Ok(())
+    }
+
+    fn segment_sort_key_computer(
+        &self,
+        segment_reader: &SegmentReader,
+    ) -> crate::Result<Self::Child> {
+        let sort_column_opt = segment_reader.fast_fields().u64_lenient(&self.field)?;
+        let (sort_column, _sort_column_type) =
+            sort_column_opt.ok_or_else(|| FastFieldNotAvailableError {
+                field_name: self.field.clone(),
+            })?;
+        Ok(SortByFastValueSegmentSortKeyComputer {
+            sort_column,
+            typ: PhantomData,
+        })
+    }
+}
+
+pub struct SortByFastValueSegmentSortKeyComputer<T> {
+    sort_column: Column<u64>,
+    typ: PhantomData<T>,
+}
+
+impl<T: FastValue> SegmentSortKeyComputer for SortByFastValueSegmentSortKeyComputer<T> {
+    type SortKey = Option<T>;
+
+    type SegmentSortKey = Option<u64>;
+
+    #[inline(always)]
+    fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> Self::SegmentSortKey {
+        self.sort_column.first(doc)
+    }
+
+    fn convert_segment_sort_key(&self, sort_key: Self::SegmentSortKey) -> Self::SortKey {
+        sort_key.map(T::from_u64)
+    }
+}

src/collector/sort_key/sort_by_string.rs

@@ -0,0 +1,72 @@
+use columnar::StrColumn;
+
+use crate::collector::sort_key::NaturalComparator;
+use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
+use crate::termdict::TermOrdinal;
+use crate::{DocId, Score};
+
+/// Sort by the first value of a string column.
+///
+/// The string can be dynamic (coming from a json field)
+/// or static (being specificaly defined in the configuration).
+///
+/// If the field is multivalued, only the first value is considered.
+///
+/// Documents that do not have this value are still considered.
+/// Their sort key will simply be `None`.
+#[derive(Debug, Clone)]
+pub struct SortByString {
+    column_name: String,
+}
+
+impl SortByString {
+    /// Creates a new sort by string sort key computer.
+    pub fn for_field(column_name: impl ToString) -> Self {
+        SortByString {
+            column_name: column_name.to_string(),
+        }
+    }
+}
+
+impl SortKeyComputer for SortByString {
+    type SortKey = Option<String>;
+
+    type Child = ByStringColumnSegmentSortKeyComputer;
+
+    type Comparator = NaturalComparator;
+
+    fn segment_sort_key_computer(
+        &self,
+        segment_reader: &crate::SegmentReader,
+    ) -> crate::Result<Self::Child> {
+        let str_column_opt = segment_reader.fast_fields().str(&self.column_name)?;
+        Ok(ByStringColumnSegmentSortKeyComputer { str_column_opt })
+    }
+}
+
+pub struct ByStringColumnSegmentSortKeyComputer {
+    str_column_opt: Option<StrColumn>,
+}
+
+impl SegmentSortKeyComputer for ByStringColumnSegmentSortKeyComputer {
+    type SortKey = Option<String>;
+
+    type SegmentSortKey = Option<TermOrdinal>;
+
+    #[inline(always)]
+    fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> Option<TermOrdinal> {
+        let str_column = self.str_column_opt.as_ref()?;
+        str_column.ords().first(doc)
+    }
+
+    fn convert_segment_sort_key(&self, term_ord_opt: Option<TermOrdinal>) -> Option<String> {
+        let term_ord = term_ord_opt?;
+        let str_column = self.str_column_opt.as_ref()?;
+        let mut bytes = Vec::new();
+        str_column
+            .dictionary()
+            .ord_to_term(term_ord, &mut bytes)
+            .ok()?;
+        String::try_from(bytes).ok()
+    }
+}

src/collector/sort_key/sort_key_computer.rs

@@ -0,0 +1,631 @@
+use std::cmp::Ordering;
+
+use crate::collector::sort_key::{Comparator, NaturalComparator};
+use crate::collector::sort_key_top_collector::TopBySortKeySegmentCollector;
+use crate::collector::{default_collect_segment_impl, SegmentCollector as _, TopNComputer};
+use crate::schema::Schema;
+use crate::{DocAddress, DocId, Result, Score, SegmentReader};
+
+/// A `SegmentSortKeyComputer` makes it possible to modify the default score
+/// for a given document belonging to a specific segment.
+///
+/// It is the segment local version of the [`SortKeyComputer`].
+pub trait SegmentSortKeyComputer: 'static {
+    /// The final score being emitted.
+    type SortKey: 'static + PartialOrd + Send + Sync + Clone;
+
+    /// Sort key used by at the segment level by the `SegmentSortKeyComputer`.
+    ///
+    /// It is typically small like a `u64`, and is meant to be converted
+    /// to the final score at the end of the collection of the segment.
+    type SegmentSortKey: 'static + PartialOrd + Clone + Send + Sync + Clone;
+
+    /// Computes the sort key for the given document and score.
+    fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey;
+
+    /// Computes the sort key and pushes the document in a TopN Computer.
+    ///
+    /// When using a tuple as the sorting key, the sort key is evaluated in a lazy manner.
+    #[inline(always)]
+    fn compute_sort_key_and_collect<C: Comparator<Self::SegmentSortKey>>(
+        &mut self,
+        doc: DocId,
+        score: Score,
+        top_n_computer: &mut TopNComputer<Self::SegmentSortKey, DocId, C>,
+    ) {
+        let sort_key = self.segment_sort_key(doc, score);
+        top_n_computer.push(sort_key, doc);
+    }
+
+    /// A SegmentSortKeyComputer maps to a SegmentSortKey, but it can also decide on
+    /// its ordering.
+    ///
+    /// This method must be consistent with the `SortKey` ordering.
+    #[inline(always)]
+    fn compare_segment_sort_key(
+        &self,
+        left: &Self::SegmentSortKey,
+        right: &Self::SegmentSortKey,
+    ) -> Ordering {
+        NaturalComparator.compare(left, right)
+    }
+
+    /// Implementing this method makes it possible to avoid computing
+    /// a sort_key entirely if we can assess that it won't pass a threshold
+    /// with a partial computation.
+    ///
+    /// This is currently used for lexicographic sorting.
+    fn accept_sort_key_lazy(
+        &mut self,
+        doc_id: DocId,
+        score: Score,
+        threshold: &Self::SegmentSortKey,
+    ) -> Option<(Ordering, Self::SegmentSortKey)> {
+        let sort_key = self.segment_sort_key(doc_id, score);
+        let cmp = self.compare_segment_sort_key(&sort_key, threshold);
+        if cmp == Ordering::Less {
+            None
+        } else {
+            Some((cmp, sort_key))
+        }
+    }
+
+    /// Convert a segment level sort key into the global sort key.
+    fn convert_segment_sort_key(&self, sort_key: Self::SegmentSortKey) -> Self::SortKey;
+}
+
+/// `SortKeyComputer` defines the sort key to be used by a TopK Collector.
+///
+/// The `SortKeyComputer` itself does not make much of the computation itself.
+/// Instead, it helps constructing `Self::Child` instances that will compute
+/// the sort key at a segment scale.
+pub trait SortKeyComputer: Sync {
+    /// The sort key type.
+    type SortKey: 'static + Send + Sync + PartialOrd + Clone + std::fmt::Debug;
+    /// Type of the associated [`SegmentSortKeyComputer`].
+    type Child: SegmentSortKeyComputer<SortKey = Self::SortKey>;
+    /// Comparator type.
+    type Comparator: Comparator<Self::SortKey>
+        + Comparator<<Self::Child as SegmentSortKeyComputer>::SegmentSortKey>
+        + 'static;
+
+    /// Checks whether the schema is compatible with the sort key computer.
+    fn check_schema(&self, _schema: &Schema) -> crate::Result<()> {
+        Ok(())
+    }
+
+    /// Returns the sort key comparator.
+    fn comparator(&self) -> Self::Comparator {
+        Self::Comparator::default()
+    }
+
+    /// Indicates whether the sort key actually uses the similarity score (by default BM25).
+    /// If set to false, the similary score might not be computed (as an optimization),
+    /// and the score fed in the segment sort key computer could take any value.
+    fn requires_scoring(&self) -> bool {
+        false
+    }
+
+    /// Sorting by score has a overriding implementation for BM25 scores, using Block-WAND.
+    fn collect_segment_top_k(
+        &self,
+        k: usize,
+        weight: &dyn crate::query::Weight,
+        reader: &crate::SegmentReader,
+        segment_ord: u32,
+    ) -> crate::Result<Vec<(Self::SortKey, DocAddress)>> {
+        let with_scoring = self.requires_scoring();
+        let segment_sort_key_computer = self.segment_sort_key_computer(reader)?;
+        let topn_computer = TopNComputer::new_with_comparator(k, self.comparator());
+        let mut segment_top_key_collector = TopBySortKeySegmentCollector {
+            topn_computer,
+            segment_ord,
+            segment_sort_key_computer,
+        };
+        default_collect_segment_impl(&mut segment_top_key_collector, weight, reader, with_scoring)?;
+        Ok(segment_top_key_collector.harvest())
+    }
+
+    /// Builds a child sort key computer for a specific segment.
+    fn segment_sort_key_computer(&self, segment_reader: &SegmentReader) -> Result<Self::Child>;
+}
+
+impl<HeadSortKeyComputer, TailSortKeyComputer> SortKeyComputer
+    for (HeadSortKeyComputer, TailSortKeyComputer)
+where
+    HeadSortKeyComputer: SortKeyComputer,
+    TailSortKeyComputer: SortKeyComputer,
+{
+    type SortKey = (
+        <HeadSortKeyComputer::Child as SegmentSortKeyComputer>::SortKey,
+        <TailSortKeyComputer::Child as SegmentSortKeyComputer>::SortKey,
+    );
+    type Child = (HeadSortKeyComputer::Child, TailSortKeyComputer::Child);
+
+    type Comparator = (
+        HeadSortKeyComputer::Comparator,
+        TailSortKeyComputer::Comparator,
+    );
+
+    fn comparator(&self) -> Self::Comparator {
+        (self.0.comparator(), self.1.comparator())
+    }
+
+    fn segment_sort_key_computer(&self, segment_reader: &SegmentReader) -> Result<Self::Child> {
+        Ok((
+            self.0.segment_sort_key_computer(segment_reader)?,
+            self.1.segment_sort_key_computer(segment_reader)?,
+        ))
+    }
+
+    /// Checks whether the schema is compatible with the sort key computer.
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)?;
+        self.1.check_schema(schema)?;
+        Ok(())
+    }
+
+    /// Indicates whether the sort key actually uses the similarity score (by default BM25).
+    /// If set to false, the similary score might not be computed (as an optimization),
+    /// and the score fed in the segment sort key computer could take any value.
+    fn requires_scoring(&self) -> bool {
+        self.0.requires_scoring() || self.1.requires_scoring()
+    }
+}
+
+impl<HeadSegmentSortKeyComputer, TailSegmentSortKeyComputer> SegmentSortKeyComputer
+    for (HeadSegmentSortKeyComputer, TailSegmentSortKeyComputer)
+where
+    HeadSegmentSortKeyComputer: SegmentSortKeyComputer,
+    TailSegmentSortKeyComputer: SegmentSortKeyComputer,
+{
+    type SortKey = (
+        HeadSegmentSortKeyComputer::SortKey,
+        TailSegmentSortKeyComputer::SortKey,
+    );
+    type SegmentSortKey = (
+        HeadSegmentSortKeyComputer::SegmentSortKey,
+        TailSegmentSortKeyComputer::SegmentSortKey,
+    );
+
+    /// A SegmentSortKeyComputer maps to a SegmentSortKey, but it can also decide on
+    /// its ordering.
+    ///
+    /// By default, it uses the natural ordering.
+    #[inline]
+    fn compare_segment_sort_key(
+        &self,
+        left: &Self::SegmentSortKey,
+        right: &Self::SegmentSortKey,
+    ) -> Ordering {
+        self.0
+            .compare_segment_sort_key(&left.0, &right.0)
+            .then_with(|| self.1.compare_segment_sort_key(&left.1, &right.1))
+    }
+
+    #[inline(always)]
+    fn compute_sort_key_and_collect<C: Comparator<Self::SegmentSortKey>>(
+        &mut self,
+        doc: DocId,
+        score: Score,
+        top_n_computer: &mut TopNComputer<Self::SegmentSortKey, DocId, C>,
+    ) {
+        let sort_key: Self::SegmentSortKey;
+        if let Some(threshold) = &top_n_computer.threshold {
+            if let Some((_cmp, lazy_sort_key)) = self.accept_sort_key_lazy(doc, score, threshold) {
+                sort_key = lazy_sort_key;
+            } else {
+                return;
+            }
+        } else {
+            sort_key = self.segment_sort_key(doc, score);
+        };
+        top_n_computer.append_doc(doc, sort_key);
+    }
+
+    #[inline(always)]
+    fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey {
+        let head_sort_key = self.0.segment_sort_key(doc, score);
+        let tail_sort_key = self.1.segment_sort_key(doc, score);
+        (head_sort_key, tail_sort_key)
+    }
+
+    fn accept_sort_key_lazy(
+        &mut self,
+        doc_id: DocId,
+        score: Score,
+        threshold: &Self::SegmentSortKey,
+    ) -> Option<(Ordering, Self::SegmentSortKey)> {
+        let (head_threshold, tail_threshold) = threshold;
+        let (head_cmp, head_sort_key) =
+            self.0.accept_sort_key_lazy(doc_id, score, head_threshold)?;
+        if head_cmp == Ordering::Equal {
+            let (tail_cmp, tail_sort_key) =
+                self.1.accept_sort_key_lazy(doc_id, score, tail_threshold)?;
+            Some((tail_cmp, (head_sort_key, tail_sort_key)))
+        } else {
+            let tail_sort_key = self.1.segment_sort_key(doc_id, score);
+            Some((head_cmp, (head_sort_key, tail_sort_key)))
+        }
+    }
+
+    fn convert_segment_sort_key(&self, sort_key: Self::SegmentSortKey) -> Self::SortKey {
+        let (head_sort_key, tail_sort_key) = sort_key;
+        (
+            self.0.convert_segment_sort_key(head_sort_key),
+            self.1.convert_segment_sort_key(tail_sort_key),
+        )
+    }
+}
+
+/// This struct is used as an adapter to take a sort key computer and map its score to another
+/// new sort key.
+pub struct MappedSegmentSortKeyComputer<T, PreviousSortKey, NewSortKey> {
+    sort_key_computer: T,
+    map: fn(PreviousSortKey) -> NewSortKey,
+}
+
+impl<T, PreviousScore, NewScore> SegmentSortKeyComputer
+    for MappedSegmentSortKeyComputer<T, PreviousScore, NewScore>
+where
+    T: SegmentSortKeyComputer<SortKey = PreviousScore>,
+    PreviousScore: 'static + Clone + Send + Sync + PartialOrd,
+    NewScore: 'static + Clone + Send + Sync + PartialOrd,
+{
+    type SortKey = NewScore;
+    type SegmentSortKey = T::SegmentSortKey;
+
+    fn segment_sort_key(&mut self, doc: DocId, score: Score) -> Self::SegmentSortKey {
+        self.sort_key_computer.segment_sort_key(doc, score)
+    }
+
+    fn accept_sort_key_lazy(
+        &mut self,
+        doc_id: DocId,
+        score: Score,
+        threshold: &Self::SegmentSortKey,
+    ) -> Option<(Ordering, Self::SegmentSortKey)> {
+        self.sort_key_computer
+            .accept_sort_key_lazy(doc_id, score, threshold)
+    }
+
+    #[inline(always)]
+    fn compute_sort_key_and_collect<C: Comparator<Self::SegmentSortKey>>(
+        &mut self,
+        doc: DocId,
+        score: Score,
+        top_n_computer: &mut TopNComputer<Self::SegmentSortKey, DocId, C>,
+    ) {
+        self.sort_key_computer
+            .compute_sort_key_and_collect(doc, score, top_n_computer);
+    }
+
+    fn convert_segment_sort_key(&self, segment_sort_key: Self::SegmentSortKey) -> Self::SortKey {
+        (self.map)(
+            self.sort_key_computer
+                .convert_segment_sort_key(segment_sort_key),
+        )
+    }
+}
+
+// We then re-use our (head, tail) implement and our mapper by seeing mapping any tuple (a, b, c,
+// ...) as the chain (a, (b, (c, ...)))
+
+impl<SortKeyComputer1, SortKeyComputer2, SortKeyComputer3> SortKeyComputer
+    for (SortKeyComputer1, SortKeyComputer2, SortKeyComputer3)
+where
+    SortKeyComputer1: SortKeyComputer,
+    SortKeyComputer2: SortKeyComputer,
+    SortKeyComputer3: SortKeyComputer,
+{
+    type SortKey = (
+        SortKeyComputer1::SortKey,
+        SortKeyComputer2::SortKey,
+        SortKeyComputer3::SortKey,
+    );
+    type Child = MappedSegmentSortKeyComputer<
+        <(SortKeyComputer1, (SortKeyComputer2, SortKeyComputer3)) as SortKeyComputer>::Child,
+        (
+            SortKeyComputer1::SortKey,
+            (SortKeyComputer2::SortKey, SortKeyComputer3::SortKey),
+        ),
+        Self::SortKey,
+    >;
+
+    type Comparator = (
+        SortKeyComputer1::Comparator,
+        SortKeyComputer2::Comparator,
+        SortKeyComputer3::Comparator,
+    );
+
+    fn comparator(&self) -> Self::Comparator {
+        (
+            self.0.comparator(),
+            self.1.comparator(),
+            self.2.comparator(),
+        )
+    }
+
+    fn segment_sort_key_computer(&self, segment_reader: &SegmentReader) -> Result<Self::Child> {
+        let sort_key_computer1 = self.0.segment_sort_key_computer(segment_reader)?;
+        let sort_key_computer2 = self.1.segment_sort_key_computer(segment_reader)?;
+        let sort_key_computer3 = self.2.segment_sort_key_computer(segment_reader)?;
+        let map = |(sort_key1, (sort_key2, sort_key3))| (sort_key1, sort_key2, sort_key3);
+        Ok(MappedSegmentSortKeyComputer {
+            sort_key_computer: (sort_key_computer1, (sort_key_computer2, sort_key_computer3)),
+            map,
+        })
+    }
+
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)?;
+        self.1.check_schema(schema)?;
+        self.2.check_schema(schema)?;
+        Ok(())
+    }
+
+    fn requires_scoring(&self) -> bool {
+        self.0.requires_scoring() || self.1.requires_scoring() || self.2.requires_scoring()
+    }
+}
+
+impl<SortKeyComputer1, SortKeyComputer2, SortKeyComputer3, SortKeyComputer4> SortKeyComputer
+    for (
+        SortKeyComputer1,
+        SortKeyComputer2,
+        SortKeyComputer3,
+        SortKeyComputer4,
+    )
+where
+    SortKeyComputer1: SortKeyComputer,
+    SortKeyComputer2: SortKeyComputer,
+    SortKeyComputer3: SortKeyComputer,
+    SortKeyComputer4: SortKeyComputer,
+{
+    type Child = MappedSegmentSortKeyComputer<
+        <(
+            SortKeyComputer1,
+            (SortKeyComputer2, (SortKeyComputer3, SortKeyComputer4)),
+        ) as SortKeyComputer>::Child,
+        (
+            SortKeyComputer1::SortKey,
+            (
+                SortKeyComputer2::SortKey,
+                (SortKeyComputer3::SortKey, SortKeyComputer4::SortKey),
+            ),
+        ),
+        Self::SortKey,
+    >;
+    type SortKey = (
+        SortKeyComputer1::SortKey,
+        SortKeyComputer2::SortKey,
+        SortKeyComputer3::SortKey,
+        SortKeyComputer4::SortKey,
+    );
+    type Comparator = (
+        SortKeyComputer1::Comparator,
+        SortKeyComputer2::Comparator,
+        SortKeyComputer3::Comparator,
+        SortKeyComputer4::Comparator,
+    );
+
+    fn segment_sort_key_computer(&self, segment_reader: &SegmentReader) -> Result<Self::Child> {
+        let sort_key_computer1 = self.0.segment_sort_key_computer(segment_reader)?;
+        let sort_key_computer2 = self.1.segment_sort_key_computer(segment_reader)?;
+        let sort_key_computer3 = self.2.segment_sort_key_computer(segment_reader)?;
+        let sort_key_computer4 = self.3.segment_sort_key_computer(segment_reader)?;
+        Ok(MappedSegmentSortKeyComputer {
+            sort_key_computer: (
+                sort_key_computer1,
+                (sort_key_computer2, (sort_key_computer3, sort_key_computer4)),
+            ),
+            map: |(sort_key1, (sort_key2, (sort_key3, sort_key4)))| {
+                (sort_key1, sort_key2, sort_key3, sort_key4)
+            },
+        })
+    }
+
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.0.check_schema(schema)?;
+        self.1.check_schema(schema)?;
+        self.2.check_schema(schema)?;
+        self.3.check_schema(schema)?;
+        Ok(())
+    }
+
+    fn requires_scoring(&self) -> bool {
+        self.0.requires_scoring()
+            || self.1.requires_scoring()
+            || self.2.requires_scoring()
+            || self.3.requires_scoring()
+    }
+}
+
+impl<F, SegmentF, TSortKey> SortKeyComputer for F
+where
+    F: 'static + Send + Sync + Fn(&SegmentReader) -> SegmentF,
+    SegmentF: 'static + FnMut(DocId) -> TSortKey,
+    TSortKey: 'static + PartialOrd + Clone + Send + Sync + std::fmt::Debug,
+{
+    type SortKey = TSortKey;
+    type Child = SegmentF;
+    type Comparator = NaturalComparator;
+
+    fn segment_sort_key_computer(&self, segment_reader: &SegmentReader) -> Result<Self::Child> {
+        Ok((self)(segment_reader))
+    }
+}
+
+impl<F, TSortKey> SegmentSortKeyComputer for F
+where
+    F: 'static + FnMut(DocId) -> TSortKey,
+    TSortKey: 'static + PartialOrd + Clone + Send + Sync,
+{
+    type SortKey = TSortKey;
+    type SegmentSortKey = TSortKey;
+
+    fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> TSortKey {
+        (self)(doc)
+    }
+
+    /// Convert a segment level score into the global level score.
+    fn convert_segment_sort_key(&self, sort_key: Self::SegmentSortKey) -> Self::SortKey {
+        sort_key
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use std::cmp::Ordering;
+    use std::sync::atomic::{AtomicUsize, Ordering as AtomicOrdering};
+    use std::sync::Arc;
+
+    use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
+    use crate::schema::Schema;
+    use crate::{DocId, Index, Order, SegmentReader};
+
+    fn build_test_index() -> Index {
+        let schema = Schema::builder().build();
+        let index = Index::create_in_ram(schema);
+        let mut index_writer = index.writer_for_tests().unwrap();
+        index_writer
+            .add_document(crate::TantivyDocument::default())
+            .unwrap();
+        index_writer.commit().unwrap();
+        index
+    }
+
+    #[test]
+    fn test_lazy_score_computer() {
+        let score_computer_primary = |_segment_reader: &SegmentReader| |_doc: DocId| 200u32;
+        let call_count = Arc::new(AtomicUsize::new(0));
+        let call_count_clone = call_count.clone();
+        let score_computer_secondary = move |_segment_reader: &SegmentReader| {
+            let call_count_new_clone = call_count_clone.clone();
+            move |_doc: DocId| {
+                call_count_new_clone.fetch_add(1, AtomicOrdering::SeqCst);
+                "b"
+            }
+        };
+        let lazy_score_computer = (score_computer_primary, score_computer_secondary);
+        let index = build_test_index();
+        let searcher = index.reader().unwrap().searcher();
+        let mut segment_sort_key_computer = lazy_score_computer
+            .segment_sort_key_computer(searcher.segment_reader(0))
+            .unwrap();
+        let expected_sort_key = (200, "b");
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(100u32, "a"));
+            assert_eq!(sort_key_opt, Some((Ordering::Greater, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 1);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(100u32, "c"));
+            assert_eq!(sort_key_opt, Some((Ordering::Greater, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 2);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(200u32, "a"));
+            assert_eq!(sort_key_opt, Some((Ordering::Greater, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 3);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(200u32, "c"));
+            assert!(sort_key_opt.is_none());
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 4);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(300u32, "a"));
+            assert_eq!(sort_key_opt, None);
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 4);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(300u32, "c"));
+            assert_eq!(sort_key_opt, None);
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 4);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &expected_sort_key);
+            assert_eq!(sort_key_opt, Some((Ordering::Equal, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 5);
+        }
+    }
+
+    #[test]
+    fn test_lazy_score_computer_dynamic_ordering() {
+        let score_computer_primary = |_segment_reader: &SegmentReader| |_doc: DocId| 200u32;
+        let call_count = Arc::new(AtomicUsize::new(0));
+        let call_count_clone = call_count.clone();
+        let score_computer_secondary = move |_segment_reader: &SegmentReader| {
+            let call_count_new_clone = call_count_clone.clone();
+            move |_doc: DocId| {
+                call_count_new_clone.fetch_add(1, AtomicOrdering::SeqCst);
+                2u32
+            }
+        };
+        let lazy_score_computer = (
+            (score_computer_primary, Order::Desc),
+            (score_computer_secondary, Order::Asc),
+        );
+        let index = build_test_index();
+        let searcher = index.reader().unwrap().searcher();
+        let mut segment_sort_key_computer = lazy_score_computer
+            .segment_sort_key_computer(searcher.segment_reader(0))
+            .unwrap();
+        let expected_sort_key = (200, 2u32);
+
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(100u32, 1u32));
+            assert_eq!(sort_key_opt, Some((Ordering::Greater, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 1);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(100u32, 3u32));
+            assert_eq!(sort_key_opt, Some((Ordering::Greater, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 2);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(200u32, 1u32));
+            assert!(sort_key_opt.is_none());
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 3);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(200u32, 3u32));
+            assert_eq!(sort_key_opt, Some((Ordering::Greater, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 4);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(300u32, 1u32));
+            assert_eq!(sort_key_opt, None);
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 4);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &(300u32, 3u32));
+            assert_eq!(sort_key_opt, None);
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 4);
+        }
+        {
+            let sort_key_opt =
+                segment_sort_key_computer.accept_sort_key_lazy(0u32, 1f32, &expected_sort_key);
+            assert_eq!(sort_key_opt, Some((Ordering::Equal, expected_sort_key)));
+            assert_eq!(call_count.load(AtomicOrdering::SeqCst), 5);
+        }
+        assert_eq!(
+            segment_sort_key_computer.convert_segment_sort_key(expected_sort_key),
+            (200u32, 2u32)
+        );
+    }
+}

src/collector/sort_key_top_collector.rs

@@ -0,0 +1,193 @@
+use std::ops::Range;
+
+use crate::collector::sort_key::{Comparator, SegmentSortKeyComputer, SortKeyComputer};
+use crate::collector::{Collector, SegmentCollector, TopNComputer};
+use crate::query::Weight;
+use crate::schema::Schema;
+use crate::{DocAddress, DocId, Result, Score, SegmentReader};
+
+pub(crate) struct TopBySortKeyCollector<TSortKeyComputer> {
+    sort_key_computer: TSortKeyComputer,
+    doc_range: Range<usize>,
+}
+
+impl<TSortKeyComputer> TopBySortKeyCollector<TSortKeyComputer> {
+    pub fn new(sort_key_computer: TSortKeyComputer, doc_range: Range<usize>) -> Self {
+        TopBySortKeyCollector {
+            sort_key_computer,
+            doc_range,
+        }
+    }
+}
+
+impl<TSortKeyComputer> Collector for TopBySortKeyCollector<TSortKeyComputer>
+where TSortKeyComputer: SortKeyComputer + Send + Sync + 'static
+{
+    type Fruit = Vec<(TSortKeyComputer::SortKey, DocAddress)>;
+
+    type Child =
+        TopBySortKeySegmentCollector<TSortKeyComputer::Child, TSortKeyComputer::Comparator>;
+
+    fn check_schema(&self, schema: &Schema) -> crate::Result<()> {
+        self.sort_key_computer.check_schema(schema)
+    }
+
+    fn for_segment(&self, segment_ord: u32, segment_reader: &SegmentReader) -> Result<Self::Child> {
+        let segment_sort_key_computer = self
+            .sort_key_computer
+            .segment_sort_key_computer(segment_reader)?;
+        let topn_computer = TopNComputer::new_with_comparator(
+            self.doc_range.end,
+            self.sort_key_computer.comparator(),
+        );
+        Ok(TopBySortKeySegmentCollector {
+            topn_computer,
+            segment_ord,
+            segment_sort_key_computer,
+        })
+    }
+
+    fn requires_scoring(&self) -> bool {
+        self.sort_key_computer.requires_scoring()
+    }
+
+    fn merge_fruits(&self, segment_fruits: Vec<Self::Fruit>) -> Result<Self::Fruit> {
+        Ok(merge_top_k(
+            segment_fruits.into_iter().flatten(),
+            self.doc_range.clone(),
+            self.sort_key_computer.comparator(),
+        ))
+    }
+
+    fn collect_segment(
+        &self,
+        weight: &dyn Weight,
+        segment_ord: u32,
+        reader: &SegmentReader,
+    ) -> crate::Result<Vec<(TSortKeyComputer::SortKey, DocAddress)>> {
+        let k = self.doc_range.end;
+        let docs = self
+            .sort_key_computer
+            .collect_segment_top_k(k, weight, reader, segment_ord)?;
+        Ok(docs)
+    }
+}
+
+fn merge_top_k<D: Ord, TSortKey: Clone + std::fmt::Debug, C: Comparator<TSortKey>>(
+    sort_key_docs: impl Iterator<Item = (TSortKey, D)>,
+    doc_range: Range<usize>,
+    comparator: C,
+) -> Vec<(TSortKey, D)> {
+    if doc_range.is_empty() {
+        return Vec::new();
+    }
+    let mut top_collector: TopNComputer<TSortKey, D, C> =
+        TopNComputer::new_with_comparator(doc_range.end, comparator);
+    for (sort_key, doc) in sort_key_docs {
+        top_collector.push(sort_key, doc);
+    }
+    top_collector
+        .into_sorted_vec()
+        .into_iter()
+        .skip(doc_range.start)
+        .map(|cdoc| (cdoc.sort_key, cdoc.doc))
+        .collect()
+}
+
+pub struct TopBySortKeySegmentCollector<TSegmentSortKeyComputer, C>
+where
+    TSegmentSortKeyComputer: SegmentSortKeyComputer,
+    C: Comparator<TSegmentSortKeyComputer::SegmentSortKey>,
+{
+    pub(crate) topn_computer: TopNComputer<TSegmentSortKeyComputer::SegmentSortKey, DocId, C>,
+    pub(crate) segment_ord: u32,
+    pub(crate) segment_sort_key_computer: TSegmentSortKeyComputer,
+}
+
+impl<TSegmentSortKeyComputer, C> SegmentCollector
+    for TopBySortKeySegmentCollector<TSegmentSortKeyComputer, C>
+where
+    TSegmentSortKeyComputer: 'static + SegmentSortKeyComputer,
+    C: Comparator<TSegmentSortKeyComputer::SegmentSortKey> + 'static,
+{
+    type Fruit = Vec<(TSegmentSortKeyComputer::SortKey, DocAddress)>;
+
+    fn collect(&mut self, doc: DocId, score: Score) {
+        self.segment_sort_key_computer.compute_sort_key_and_collect(
+            doc,
+            score,
+            &mut self.topn_computer,
+        );
+    }
+
+    fn harvest(self) -> Self::Fruit {
+        let segment_ord = self.segment_ord;
+        let segment_hits: Vec<(TSegmentSortKeyComputer::SortKey, DocAddress)> = self
+            .topn_computer
+            .into_vec()
+            .into_iter()
+            .map(|comparable_doc| {
+                let sort_key = self
+                    .segment_sort_key_computer
+                    .convert_segment_sort_key(comparable_doc.sort_key);
+                (
+                    sort_key,
+                    DocAddress {
+                        segment_ord,
+                        doc_id: comparable_doc.doc,
+                    },
+                )
+            })
+            .collect();
+        segment_hits
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use std::ops::Range;
+
+    use rand;
+    use rand::seq::SliceRandom as _;
+
+    use super::merge_top_k;
+    use crate::collector::sort_key::ComparatorEnum;
+    use crate::Order;
+
+    fn test_merge_top_k_aux(
+        order: Order,
+        doc_range: Range<usize>,
+        expected: &[(crate::Score, usize)],
+    ) {
+        let mut vals: Vec<(crate::Score, usize)> = (0..10).map(|val| (val as f32, val)).collect();
+        vals.shuffle(&mut rand::thread_rng());
+        let vals_merged = merge_top_k(vals.into_iter(), doc_range, ComparatorEnum::from(order));
+        assert_eq!(&vals_merged, expected);
+    }
+
+    #[test]
+    fn test_merge_top_k() {
+        test_merge_top_k_aux(Order::Asc, 0..0, &[]);
+        test_merge_top_k_aux(Order::Asc, 3..3, &[]);
+        test_merge_top_k_aux(Order::Asc, 0..3, &[(0.0f32, 0), (1.0f32, 1), (2.0f32, 2)]);
+        test_merge_top_k_aux(
+            Order::Asc,
+            0..11,
+            &[
+                (0.0f32, 0),
+                (1.0f32, 1),
+                (2.0f32, 2),
+                (3.0f32, 3),
+                (4.0f32, 4),
+                (5.0f32, 5),
+                (6.0f32, 6),
+                (7.0f32, 7),
+                (8.0f32, 8),
+                (9.0f32, 9),
+            ],
+        );
+        test_merge_top_k_aux(Order::Asc, 1..3, &[(1.0f32, 1), (2.0f32, 2)]);
+        test_merge_top_k_aux(Order::Desc, 0..2, &[(9.0f32, 9), (8.0f32, 8)]);
+        test_merge_top_k_aux(Order::Desc, 2..4, &[(7.0f32, 7), (6.0f32, 6)]);
+    }
+}

src/collector/tests.rs

@@ -40,7 +40,7 @@ pub fn test_filter_collector() -> crate::Result<()> {
     let filter_some_collector = FilterCollector::new(
         "price".to_string(),
         &|value: u64| value > 20_120u64,
-        TopDocs::with_limit(2),
+        TopDocs::with_limit(2).order_by_score(),
     );
     let top_docs = searcher.search(&query, &filter_some_collector)?;
 
@@ -50,7 +50,7 @@ pub fn test_filter_collector() -> crate::Result<()> {
     let filter_all_collector: FilterCollector<_, _, u64> = FilterCollector::new(
         "price".to_string(),
         &|value| value < 5u64,
-        TopDocs::with_limit(2),
+        TopDocs::with_limit(2).order_by_score(),
     );
     let filtered_top_docs = searcher.search(&query, &filter_all_collector).unwrap();
 
@@ -62,8 +62,11 @@ pub fn test_filter_collector() -> crate::Result<()> {
             > 0
     }
 
-    let filter_dates_collector =
-        FilterCollector::new("date".to_string(), &date_filter, TopDocs::with_limit(5));
+    let filter_dates_collector = FilterCollector::new(
+        "date".to_string(),
+        &date_filter,
+        TopDocs::with_limit(5).order_by_score(),
+    );
     let filtered_date_docs = searcher.search(&query, &filter_dates_collector)?;
 
     assert_eq!(filtered_date_docs.len(), 2);

src/collector/top_collector.rs

@@ -1,12 +1,7 @@
 use std::cmp::Ordering;
-use std::marker::PhantomData;
 
 use serde::{Deserialize, Serialize};
 
-use super::top_score_collector::TopNComputer;
-use crate::index::SegmentReader;
-use crate::{DocAddress, DocId, SegmentOrdinal};
-
 /// Contains a feature (field, score, etc.) of a document along with the document address.
 ///
 /// It guarantees stable sorting: in case of a tie on the feature, the document
@@ -19,7 +14,7 @@ use crate::{DocAddress, DocId, SegmentOrdinal};
 pub struct ComparableDoc<T, D, const REVERSE_ORDER: bool = false> {
     /// The feature of the document. In practice, this is
     /// is any type that implements `PartialOrd`.
-    pub feature: T,
+    pub sort_key: T,
     /// The document address. In practice, this is any
     /// type that implements `PartialOrd`, and is guaranteed
     /// to be unique for each document.
@@ -28,9 +23,9 @@ pub struct ComparableDoc<T, D, const REVERSE_ORDER: bool = false> {
 impl<T: std::fmt::Debug, D: std::fmt::Debug, const R: bool> std::fmt::Debug
     for ComparableDoc<T, D, R>
 {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
+    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
         f.debug_struct(format!("ComparableDoc<_, _ {R}").as_str())
-            .field("feature", &self.feature)
+            .field("feature", &self.sort_key)
             .field("doc", &self.doc)
             .finish()
     }
@@ -46,8 +41,8 @@ impl<T: PartialOrd, D: PartialOrd, const R: bool> Ord for ComparableDoc<T, D, R>
     #[inline]
     fn cmp(&self, other: &Self) -> Ordering {
         let by_feature = self
-            .feature
-            .partial_cmp(&other.feature)
+            .sort_key
+            .partial_cmp(&other.sort_key)
             .map(|ord| if R { ord.reverse() } else { ord })
             .unwrap_or(Ordering::Equal);
 
@@ -67,308 +62,3 @@ impl<T: PartialOrd, D: PartialOrd, const R: bool> PartialEq for ComparableDoc<T,
 }
 
 impl<T: PartialOrd, D: PartialOrd, const R: bool> Eq for ComparableDoc<T, D, R> {}
-
-pub(crate) struct TopCollector<T> {
-    pub limit: usize,
-    pub offset: usize,
-    _marker: PhantomData<T>,
-}
-
-impl<T> TopCollector<T>
-where T: PartialOrd + Clone
-{
-    /// Creates a top collector, with a number of documents equal to "limit".
-    ///
-    /// # Panics
-    /// The method panics if limit is 0
-    pub fn with_limit(limit: usize) -> TopCollector<T> {
-        assert!(limit >= 1, "Limit must be strictly greater than 0.");
-        Self {
-            limit,
-            offset: 0,
-            _marker: PhantomData,
-        }
-    }
-
-    /// Skip the first "offset" documents when collecting.
-    ///
-    /// This is equivalent to `OFFSET` in MySQL or PostgreSQL and `start` in
-    /// Lucene's TopDocsCollector.
-    pub fn and_offset(mut self, offset: usize) -> TopCollector<T> {
-        self.offset = offset;
-        self
-    }
-
-    pub fn merge_fruits(
-        &self,
-        children: Vec<Vec<(T, DocAddress)>>,
-    ) -> crate::Result<Vec<(T, DocAddress)>> {
-        if self.limit == 0 {
-            return Ok(Vec::new());
-        }
-        let mut top_collector: TopNComputer<_, _> = TopNComputer::new(self.limit + self.offset);
-        for child_fruit in children {
-            for (feature, doc) in child_fruit {
-                top_collector.push(feature, doc);
-            }
-        }
-
-        Ok(top_collector
-            .into_sorted_vec()
-            .into_iter()
-            .skip(self.offset)
-            .map(|cdoc| (cdoc.feature, cdoc.doc))
-            .collect())
-    }
-
-    pub(crate) fn for_segment<F: PartialOrd + Clone>(
-        &self,
-        segment_id: SegmentOrdinal,
-        _: &SegmentReader,
-    ) -> TopSegmentCollector<F> {
-        TopSegmentCollector::new(segment_id, self.limit + self.offset)
-    }
-
-    /// Create a new TopCollector with the same limit and offset.
-    ///
-    /// Ideally we would use Into but the blanket implementation seems to cause the Scorer traits
-    /// to fail.
-    #[doc(hidden)]
-    pub(crate) fn into_tscore<TScore: PartialOrd + Clone>(self) -> TopCollector<TScore> {
-        TopCollector {
-            limit: self.limit,
-            offset: self.offset,
-            _marker: PhantomData,
-        }
-    }
-}
-
-/// The Top Collector keeps track of the K documents
-/// sorted by type `T`.
-///
-/// The implementation is based on a repeatedly truncating on the median after K * 2 documents
-/// The theoretical complexity for collecting the top `K` out of `n` documents
-/// is `O(n + K)`.
-pub(crate) struct TopSegmentCollector<T> {
-    /// We reverse the order of the feature in order to
-    /// have top-semantics instead of bottom semantics.
-    topn_computer: TopNComputer<T, DocId>,
-    segment_ord: u32,
-}
-
-impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
-    fn new(segment_ord: SegmentOrdinal, limit: usize) -> TopSegmentCollector<T> {
-        TopSegmentCollector {
-            topn_computer: TopNComputer::new(limit),
-            segment_ord,
-        }
-    }
-}
-
-impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
-    pub fn harvest(self) -> Vec<(T, DocAddress)> {
-        let segment_ord = self.segment_ord;
-        self.topn_computer
-            .into_sorted_vec()
-            .into_iter()
-            .map(|comparable_doc| {
-                (
-                    comparable_doc.feature,
-                    DocAddress {
-                        segment_ord,
-                        doc_id: comparable_doc.doc,
-                    },
-                )
-            })
-            .collect()
-    }
-
-    /// Collects a document scored by the given feature
-    ///
-    /// It collects documents until it has reached the max capacity. Once it reaches capacity, it
-    /// will compare the lowest scoring item with the given one and keep whichever is greater.
-    #[inline]
-    pub fn collect(&mut self, doc: DocId, feature: T) {
-        self.topn_computer.push(feature, doc);
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::{TopCollector, TopSegmentCollector};
-    use crate::DocAddress;
-
-    #[test]
-    fn test_top_collector_not_at_capacity() {
-        let mut top_collector = TopSegmentCollector::new(0, 4);
-        top_collector.collect(1, 0.8);
-        top_collector.collect(3, 0.2);
-        top_collector.collect(5, 0.3);
-        assert_eq!(
-            top_collector.harvest(),
-            vec![
-                (0.8, DocAddress::new(0, 1)),
-                (0.3, DocAddress::new(0, 5)),
-                (0.2, DocAddress::new(0, 3))
-            ]
-        );
-    }
-
-    #[test]
-    fn test_top_collector_at_capacity() {
-        let mut top_collector = TopSegmentCollector::new(0, 4);
-        top_collector.collect(1, 0.8);
-        top_collector.collect(3, 0.2);
-        top_collector.collect(5, 0.3);
-        top_collector.collect(7, 0.9);
-        top_collector.collect(9, -0.2);
-        assert_eq!(
-            top_collector.harvest(),
-            vec![
-                (0.9, DocAddress::new(0, 7)),
-                (0.8, DocAddress::new(0, 1)),
-                (0.3, DocAddress::new(0, 5)),
-                (0.2, DocAddress::new(0, 3))
-            ]
-        );
-    }
-
-    #[test]
-    fn test_top_segment_collector_stable_ordering_for_equal_feature() {
-        // given that the documents are collected in ascending doc id order,
-        // when harvesting we have to guarantee stable sorting in case of a tie
-        // on the score
-        let doc_ids_collection = [4, 5, 6];
-        let score = 3.3f32;
-
-        let mut top_collector_limit_2 = TopSegmentCollector::new(0, 2);
-        for id in &doc_ids_collection {
-            top_collector_limit_2.collect(*id, score);
-        }
-
-        let mut top_collector_limit_3 = TopSegmentCollector::new(0, 3);
-        for id in &doc_ids_collection {
-            top_collector_limit_3.collect(*id, score);
-        }
-
-        assert_eq!(
-            top_collector_limit_2.harvest(),
-            top_collector_limit_3.harvest()[..2].to_vec(),
-        );
-    }
-
-    #[test]
-    fn test_top_collector_with_limit_and_offset() {
-        let collector = TopCollector::with_limit(2).and_offset(1);
-
-        let results = collector
-            .merge_fruits(vec![vec![
-                (0.9, DocAddress::new(0, 1)),
-                (0.8, DocAddress::new(0, 2)),
-                (0.7, DocAddress::new(0, 3)),
-                (0.6, DocAddress::new(0, 4)),
-                (0.5, DocAddress::new(0, 5)),
-            ]])
-            .unwrap();
-
-        assert_eq!(
-            results,
-            vec![(0.8, DocAddress::new(0, 2)), (0.7, DocAddress::new(0, 3)),]
-        );
-    }
-
-    #[test]
-    fn test_top_collector_with_limit_larger_than_set_and_offset() {
-        let collector = TopCollector::with_limit(2).and_offset(1);
-
-        let results = collector
-            .merge_fruits(vec![vec![
-                (0.9, DocAddress::new(0, 1)),
-                (0.8, DocAddress::new(0, 2)),
-            ]])
-            .unwrap();
-
-        assert_eq!(results, vec![(0.8, DocAddress::new(0, 2)),]);
-    }
-
-    #[test]
-    fn test_top_collector_with_limit_and_offset_larger_than_set() {
-        let collector = TopCollector::with_limit(2).and_offset(20);
-
-        let results = collector
-            .merge_fruits(vec![vec![
-                (0.9, DocAddress::new(0, 1)),
-                (0.8, DocAddress::new(0, 2)),
-            ]])
-            .unwrap();
-
-        assert_eq!(results, vec![]);
-    }
-}
-
-#[cfg(all(test, feature = "unstable"))]
-mod bench {
-    use test::Bencher;
-
-    use super::TopSegmentCollector;
-
-    #[bench]
-    fn bench_top_segment_collector_collect_not_at_capacity(b: &mut Bencher) {
-        let mut top_collector = TopSegmentCollector::new(0, 400);
-
-        b.iter(|| {
-            for i in 0..100 {
-                top_collector.collect(i, 0.8);
-            }
-        });
-    }
-
-    #[bench]
-    fn bench_top_segment_collector_collect_at_capacity(b: &mut Bencher) {
-        let mut top_collector = TopSegmentCollector::new(0, 100);
-
-        for i in 0..100 {
-            top_collector.collect(i, 0.8);
-        }
-
-        b.iter(|| {
-            for i in 0..100 {
-                top_collector.collect(i, 0.8);
-            }
-        });
-    }
-
-    #[bench]
-    fn bench_top_segment_collector_collect_and_harvest_many_ties(b: &mut Bencher) {
-        b.iter(|| {
-            let mut top_collector = TopSegmentCollector::new(0, 100);
-
-            for i in 0..100 {
-                top_collector.collect(i, 0.8);
-            }
-
-            // it would be nice to be able to do the setup N times but still
-            // measure only harvest(). We can't since harvest() consumes
-            // the top_collector.
-            top_collector.harvest()
-        });
-    }
-
-    #[bench]
-    fn bench_top_segment_collector_collect_and_harvest_no_tie(b: &mut Bencher) {
-        b.iter(|| {
-            let mut top_collector = TopSegmentCollector::new(0, 100);
-            let mut score = 1.0;
-
-            for i in 0..100 {
-                score += 1.0;
-                top_collector.collect(i, score);
-            }
-
-            // it would be nice to be able to do the setup N times but still
-            // measure only harvest(). We can't since harvest() consumes
-            // the top_collector.
-            top_collector.harvest()
-        });
-    }
-}

src/collector/tweak_score_top_collector.rs

@@ -1,124 +0,0 @@
-use crate::collector::top_collector::{TopCollector, TopSegmentCollector};
-use crate::collector::{Collector, SegmentCollector};
-use crate::{DocAddress, DocId, Result, Score, SegmentReader};
-
-pub(crate) struct TweakedScoreTopCollector<TScoreTweaker, TScore = Score> {
-    score_tweaker: TScoreTweaker,
-    collector: TopCollector<TScore>,
-}
-
-impl<TScoreTweaker, TScore> TweakedScoreTopCollector<TScoreTweaker, TScore>
-where TScore: Clone + PartialOrd
-{
-    pub fn new(
-        score_tweaker: TScoreTweaker,
-        collector: TopCollector<TScore>,
-    ) -> TweakedScoreTopCollector<TScoreTweaker, TScore> {
-        TweakedScoreTopCollector {
-            score_tweaker,
-            collector,
-        }
-    }
-}
-
-/// A `ScoreSegmentTweaker` makes it possible to modify the default score
-/// for a given document belonging to a specific segment.
-///
-/// It is the segment local version of the [`ScoreTweaker`].
-pub trait ScoreSegmentTweaker<TScore>: 'static {
-    /// Tweak the given `score` for the document `doc`.
-    fn score(&mut self, doc: DocId, score: Score) -> TScore;
-}
-
-/// `ScoreTweaker` makes it possible to tweak the score
-/// emitted  by the scorer into another one.
-///
-/// The `ScoreTweaker` itself does not make much of the computation itself.
-/// Instead, it helps constructing `Self::Child` instances that will compute
-/// the score at a segment scale.
-pub trait ScoreTweaker<TScore>: Sync {
-    /// Type of the associated [`ScoreSegmentTweaker`].
-    type Child: ScoreSegmentTweaker<TScore>;
-
-    /// Builds a child tweaker for a specific segment. The child scorer is associated with
-    /// a specific segment.
-    fn segment_tweaker(&self, segment_reader: &SegmentReader) -> Result<Self::Child>;
-}
-
-impl<TScoreTweaker, TScore> Collector for TweakedScoreTopCollector<TScoreTweaker, TScore>
-where
-    TScoreTweaker: ScoreTweaker<TScore> + Send + Sync,
-    TScore: 'static + PartialOrd + Clone + Send + Sync,
-{
-    type Fruit = Vec<(TScore, DocAddress)>;
-
-    type Child = TopTweakedScoreSegmentCollector<TScoreTweaker::Child, TScore>;
-
-    fn for_segment(
-        &self,
-        segment_local_id: u32,
-        segment_reader: &SegmentReader,
-    ) -> Result<Self::Child> {
-        let segment_scorer = self.score_tweaker.segment_tweaker(segment_reader)?;
-        let segment_collector = self.collector.for_segment(segment_local_id, segment_reader);
-        Ok(TopTweakedScoreSegmentCollector {
-            segment_collector,
-            segment_scorer,
-        })
-    }
-
-    fn requires_scoring(&self) -> bool {
-        true
-    }
-
-    fn merge_fruits(&self, segment_fruits: Vec<Self::Fruit>) -> Result<Self::Fruit> {
-        self.collector.merge_fruits(segment_fruits)
-    }
-}
-
-pub struct TopTweakedScoreSegmentCollector<TSegmentScoreTweaker, TScore>
-where
-    TScore: 'static + PartialOrd + Clone + Send + Sync + Sized,
-    TSegmentScoreTweaker: ScoreSegmentTweaker<TScore>,
-{
-    segment_collector: TopSegmentCollector<TScore>,
-    segment_scorer: TSegmentScoreTweaker,
-}
-
-impl<TSegmentScoreTweaker, TScore> SegmentCollector
-    for TopTweakedScoreSegmentCollector<TSegmentScoreTweaker, TScore>
-where
-    TScore: 'static + PartialOrd + Clone + Send + Sync,
-    TSegmentScoreTweaker: 'static + ScoreSegmentTweaker<TScore>,
-{
-    type Fruit = Vec<(TScore, DocAddress)>;
-
-    fn collect(&mut self, doc: DocId, score: Score) {
-        let score = self.segment_scorer.score(doc, score);
-        self.segment_collector.collect(doc, score);
-    }
-
-    fn harvest(self) -> Vec<(TScore, DocAddress)> {
-        self.segment_collector.harvest()
-    }
-}
-
-impl<F, TScore, TSegmentScoreTweaker> ScoreTweaker<TScore> for F
-where
-    F: 'static + Send + Sync + Fn(&SegmentReader) -> TSegmentScoreTweaker,
-    TSegmentScoreTweaker: ScoreSegmentTweaker<TScore>,
-{
-    type Child = TSegmentScoreTweaker;
-
-    fn segment_tweaker(&self, segment_reader: &SegmentReader) -> Result<Self::Child> {
-        Ok((self)(segment_reader))
-    }
-}
-
-impl<F, TScore> ScoreSegmentTweaker<TScore> for F
-where F: 'static + FnMut(DocId, Score) -> TScore
-{
-    fn score(&mut self, doc: DocId, score: Score) -> TScore {
-        (self)(doc, score)
-    }
-}

src/compat_tests.rs

@@ -69,7 +69,7 @@ fn assert_date_time_precision(index: &Index, doc_store_precision: DateTimePrecis
         .parse_query("dateformat")
         .expect("Failed to parse query");
     let top_docs = searcher
-        .search(&query, &TopDocs::with_limit(1))
+        .search(&query, &TopDocs::with_limit(1).order_by_score())
         .expect("Search failed");
 
     assert_eq!(top_docs.len(), 1, "Expected 1 search result");

src/core/executor.rs

@@ -48,7 +48,15 @@ impl Executor {
         F: Sized + Sync + Fn(A) -> crate::Result<R>,
     {
         match self {
-            Executor::SingleThread => args.map(f).collect::<crate::Result<_>>(),
+            Executor::SingleThread => {
+                // Avoid `collect`, since the stacktrace is blown up by it, which makes profiling
+                // harder.
+                let mut result = Vec::with_capacity(args.size_hint().0);
+                for arg in args {
+                    result.push(f(arg)?);
+                }
+                Ok(result)
+            }
             Executor::ThreadPool(pool) => {
                 let args: Vec<A> = args.collect();
                 let num_fruits = args.len();

src/core/json_utils.rs

@@ -1,7 +1,9 @@
+use columnar::NumericalValue;
 use common::json_path_writer::{JSON_END_OF_PATH, JSON_PATH_SEGMENT_SEP};
 use common::{replace_in_place, JsonPathWriter};
 use rustc_hash::FxHashMap;
 
+use crate::indexer::indexing_term::IndexingTerm;
 use crate::postings::{IndexingContext, IndexingPosition, PostingsWriter};
 use crate::schema::document::{ReferenceValue, ReferenceValueLeaf, Value};
 use crate::schema::{Type, DATE_TIME_PRECISION_INDEXED};
@@ -76,7 +78,7 @@ fn index_json_object<'a, V: Value<'a>>(
     doc: DocId,
     json_visitor: V::ObjectIter,
     text_analyzer: &mut TextAnalyzer,
-    term_buffer: &mut Term,
+    term_buffer: &mut IndexingTerm,
     json_path_writer: &mut JsonPathWriter,
     postings_writer: &mut dyn PostingsWriter,
     ctx: &mut IndexingContext,
@@ -106,17 +108,17 @@ pub(crate) fn index_json_value<'a, V: Value<'a>>(
     doc: DocId,
     json_value: V,
     text_analyzer: &mut TextAnalyzer,
-    term_buffer: &mut Term,
+    term_buffer: &mut IndexingTerm,
     json_path_writer: &mut JsonPathWriter,
     postings_writer: &mut dyn PostingsWriter,
     ctx: &mut IndexingContext,
     positions_per_path: &mut IndexingPositionsPerPath,
 ) {
-    let set_path_id = |term_buffer: &mut Term, unordered_id: u32| {
+    let set_path_id = |term_buffer: &mut IndexingTerm, unordered_id: u32| {
         term_buffer.truncate_value_bytes(0);
         term_buffer.append_bytes(&unordered_id.to_be_bytes());
     };
-    let set_type = |term_buffer: &mut Term, typ: Type| {
+    let set_type = |term_buffer: &mut IndexingTerm, typ: Type| {
         term_buffer.append_bytes(&[typ.to_code()]);
     };
 
@@ -152,7 +154,7 @@ pub(crate) fn index_json_value<'a, V: Value<'a>>(
                 if let Ok(i64_val) = val.try_into() {
                     term_buffer.append_type_and_fast_value::<i64>(i64_val);
                 } else {
-                    term_buffer.append_type_and_fast_value(val);
+                    term_buffer.append_type_and_fast_value::<u64>(val);
                 }
                 postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
             }
@@ -166,12 +168,30 @@ pub(crate) fn index_json_value<'a, V: Value<'a>>(
                 postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
             }
             ReferenceValueLeaf::F64(val) => {
+                if !val.is_finite() {
+                    return;
+                };
                 set_path_id(
                     term_buffer,
                     ctx.path_to_unordered_id
                         .get_or_allocate_unordered_id(json_path_writer.as_str()),
                 );
-                term_buffer.append_type_and_fast_value(val);
+                // Normalize here is important.
+                // In the inverted index, we coerce all numerical values to their canonical
+                // representation.
+                //
+                // (We do the same thing on the query side)
+                match NumericalValue::F64(val).normalize() {
+                    NumericalValue::I64(val_i64) => {
+                        term_buffer.append_type_and_fast_value::<i64>(val_i64);
+                    }
+                    NumericalValue::U64(val_u64) => {
+                        term_buffer.append_type_and_fast_value::<u64>(val_u64);
+                    }
+                    NumericalValue::F64(val_f64) => {
+                        term_buffer.append_type_and_fast_value::<f64>(val_f64);
+                    }
+                }
                 postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
             }
             ReferenceValueLeaf::Bool(val) => {
@@ -241,8 +261,8 @@ pub(crate) fn index_json_value<'a, V: Value<'a>>(
 ///
 /// The term must be json + JSON path.
 pub fn convert_to_fast_value_and_append_to_json_term(
-    mut term: Term,
-    phrase: &str,
+    term: &Term,
+    text: &str,
     truncate_date_for_search: bool,
 ) -> Option<Term> {
     assert_eq!(
@@ -254,31 +274,50 @@ pub fn convert_to_fast_value_and_append_to_json_term(
         0,
         "JSON value bytes should be empty"
     );
-    if let Ok(dt) = OffsetDateTime::parse(phrase, &Rfc3339) {
-        let mut dt = DateTime::from_utc(dt.to_offset(UtcOffset::UTC));
-        if truncate_date_for_search {
-            dt = dt.truncate(DATE_TIME_PRECISION_INDEXED);
+    try_convert_to_datetime_and_append_to_json_term(term, text, truncate_date_for_search)
+        .or_else(|| try_convert_to_number_and_append_to_json_term(term, text))
+        .or_else(|| try_convert_to_bool_and_append_to_json_term_typed(term, text))
+}
+
+fn try_convert_to_datetime_and_append_to_json_term(
+    term: &Term,
+    text: &str,
+    truncate_date_for_search: bool,
+) -> Option<Term> {
+    let dt = OffsetDateTime::parse(text, &Rfc3339).ok()?;
+    let mut dt = DateTime::from_utc(dt.to_offset(UtcOffset::UTC));
+    if truncate_date_for_search {
+        dt = dt.truncate(DATE_TIME_PRECISION_INDEXED);
+    }
+    let mut term_clone = term.clone();
+    term_clone.append_type_and_fast_value(dt);
+    Some(term_clone)
+}
+
+fn try_convert_to_number_and_append_to_json_term(term: &Term, text: &str) -> Option<Term> {
+    let numerical_value: NumericalValue = str::parse::<NumericalValue>(text).ok()?;
+    let mut term_clone = term.clone();
+    // Parse is actually returning normalized values already today, but let's not
+    // not rely on that hidden contract.
+    match numerical_value.normalize() {
+        NumericalValue::I64(i64_value) => {
+            term_clone.append_type_and_fast_value::<i64>(i64_value);
+        }
+        NumericalValue::U64(u64_value) => {
+            term_clone.append_type_and_fast_value::<u64>(u64_value);
+        }
+        NumericalValue::F64(f64_value) => {
+            term_clone.append_type_and_fast_value::<f64>(f64_value);
         }
-        term.append_type_and_fast_value(dt);
-        return Some(term);
     }
-    if let Ok(i64_val) = str::parse::<i64>(phrase) {
-        term.append_type_and_fast_value(i64_val);
-        return Some(term);
-    }
-    if let Ok(u64_val) = str::parse::<u64>(phrase) {
-        term.append_type_and_fast_value(u64_val);
-        return Some(term);
-    }
-    if let Ok(f64_val) = str::parse::<f64>(phrase) {
-        term.append_type_and_fast_value(f64_val);
-        return Some(term);
-    }
-    if let Ok(bool_val) = str::parse::<bool>(phrase) {
-        term.append_type_and_fast_value(bool_val);
-        return Some(term);
-    }
-    None
+    Some(term_clone)
+}
+
+fn try_convert_to_bool_and_append_to_json_term_typed(term: &Term, text: &str) -> Option<Term> {
+    let val = str::parse::<bool>(text).ok()?;
+    let mut term_clone = term.clone();
+    term_clone.append_type_and_fast_value(val);
+    Some(term_clone)
 }
 
 /// Splits a json path supplied to the query parser in such a way that

src/core/searcher.rs

@@ -225,6 +225,7 @@ impl Searcher {
         enabled_scoring: EnableScoring,
     ) -> crate::Result<C::Fruit> {
         let weight = query.weight(enabled_scoring)?;
+        collector.check_schema(self.schema())?;
         let segment_readers = self.segment_readers();
         let fruits = executor.map(
             |(segment_ord, segment_reader)| {

src/directory/directory.rs

@@ -108,7 +108,7 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
     /// Opens a file and returns a boxed `FileHandle`.
     ///
     /// Users of `Directory` should typically call `Directory::open_read(...)`,
-    /// while `Directory` implementor should implement `get_file_handle()`.
+    /// while `Directory` implementer should implement `get_file_handle()`.
     fn get_file_handle(&self, path: &Path) -> Result<Arc<dyn FileHandle>, OpenReadError>;
 
     /// Once a virtual file is open, its data may not