remove dynamic dispatch in collect_segment

* add date_histogram

* add return result

Cargo.toml

@@ -58,7 +58,7 @@ arc-swap = "1.5.0"
 columnar = { version="0.1", path="./columnar", package ="tantivy-columnar" }
 sstable = { version="0.1", path="./sstable", package ="tantivy-sstable", optional = true }
 stacker = { version="0.1", path="./stacker", package ="tantivy-stacker" }
-tantivy-query-grammar = { version= "0.19.0", path="./query-grammar" }
+query-grammar = { version= "0.19.0", path="./query-grammar", package = "tantivy-query-grammar" }
 tantivy-bitpacker = { version= "0.3", path="./bitpacker" }
 common = { version= "0.5", path = "./common/", package = "tantivy-common" }
 tokenizer-api = { version="0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
@@ -77,6 +77,7 @@ test-log = "0.2.10"
 env_logger = "0.10.0"
 pprof = { version = "0.11.0", features = ["flamegraph", "criterion"] }
 futures = "0.3.21"
+paste = "1.0.11"
 
 [dev-dependencies.fail]
 version = "0.5.0"

columnar/Cargo.toml

@@ -17,6 +17,7 @@ stacker = { path = "../stacker", package="tantivy-stacker"}
 sstable = { path = "../sstable", package = "tantivy-sstable" }
 common = { path = "../common", package = "tantivy-common" }
 tantivy-bitpacker = { version= "0.3", path = "../bitpacker/" }
+serde = "1.0.152"
 
 [dev-dependencies]
 proptest = "1"

columnar/src/TODO.md

@@ -1,7 +1,6 @@
 # zero to one
 
 * revisit line codec
-* removal of all rows of a column in the schema due to deletes
 * add columns from schema on merge
 * Plugging JSON
 * replug examples

columnar/src/column/dictionary_encoded.rs

@@ -36,7 +36,7 @@ impl BytesColumn {
     }
 
     pub fn term_ords(&self, row_id: RowId) -> impl Iterator<Item = u64> + '_ {
-        self.term_ord_column.values(row_id)
+        self.term_ord_column.values_for_doc(row_id)
     }
 
     /// Returns the column of ordinals

columnar/src/column/mod.rs

@@ -38,13 +38,15 @@ impl<T: MonotonicallyMappableToU64> Column<T> {
 }
 
 impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
+    #[inline]
     pub fn get_cardinality(&self) -> Cardinality {
         self.idx.get_cardinality()
     }
 
     pub fn num_docs(&self) -> RowId {
         match &self.idx {
-            ColumnIndex::Full => self.values.num_vals() as u32,
+            ColumnIndex::Empty { num_docs } => *num_docs,
+            ColumnIndex::Full => self.values.num_vals(),
             ColumnIndex::Optional(optional_index) => optional_index.num_docs(),
             ColumnIndex::Multivalued(col_index) => {
                 // The multivalued index contains all value start row_id,
@@ -63,10 +65,10 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
     }
 
     pub fn first(&self, row_id: RowId) -> Option<T> {
-        self.values(row_id).next()
+        self.values_for_doc(row_id).next()
     }
 
-    pub fn values(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
+    pub fn values_for_doc(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
         self.value_row_ids(row_id)
             .map(|value_row_id: RowId| self.values.get_val(value_row_id))
     }
@@ -77,17 +79,17 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
         &self,
         value_range: RangeInclusive<T>,
         selected_docid_range: Range<u32>,
-        docids: &mut Vec<u32>,
+        doc_ids: &mut Vec<u32>,
     ) {
         // convert passed docid range to row id range
         let rowid_range = self.idx.docid_range_to_rowids(selected_docid_range.clone());
 
         // Load rows
         self.values
-            .get_row_ids_for_value_range(value_range, rowid_range, docids);
+            .get_row_ids_for_value_range(value_range, rowid_range, doc_ids);
         // Convert rows to docids
         self.idx
-            .select_batch_in_place(docids, selected_docid_range.start);
+            .select_batch_in_place(selected_docid_range.start, doc_ids);
     }
 
     /// Fils the output vector with the (possibly multiple values that are associated_with
@@ -96,7 +98,7 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
     /// This method clears the `output` vector.
     pub fn fill_vals(&self, row_id: RowId, output: &mut Vec<T>) {
         output.clear();
-        output.extend(self.values(row_id));
+        output.extend(self.values_for_doc(row_id));
     }
 
     pub fn first_or_default_col(self, default_value: T) -> Arc<dyn ColumnValues<T>> {
@@ -150,6 +152,7 @@ impl<T: PartialOrd + Debug + Send + Sync + Copy + 'static> ColumnValues<T>
 
     fn num_vals(&self) -> u32 {
         match &self.column.idx {
+            ColumnIndex::Empty { .. } => 0u32,
             ColumnIndex::Full => self.column.values.num_vals(),
             ColumnIndex::Optional(optional_idx) => optional_idx.num_docs(),
             ColumnIndex::Multivalued(multivalue_idx) => multivalue_idx.num_docs(),

columnar/src/column/serialize.rs

@@ -7,9 +7,10 @@ use sstable::Dictionary;
 
 use crate::column::{BytesColumn, Column};
 use crate::column_index::{serialize_column_index, SerializableColumnIndex};
-use crate::column_values::serialize::serialize_column_values_u128;
-use crate::column_values::u64_based::{serialize_u64_based_column_values, CodecType};
-use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
+use crate::column_values::{
+    load_u64_based_column_values, serialize_column_values_u128, serialize_u64_based_column_values,
+    CodecType, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
+};
 use crate::iterable::Iterable;
 use crate::StrColumn;
 
@@ -49,8 +50,7 @@ pub fn open_column_u64<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::
     );
     let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
     let column_index = crate::column_index::open_column_index(column_index_data)?;
-    let column_values =
-        crate::column_values::u64_based::load_u64_based_column_values(column_values_data)?;
+    let column_values = load_u64_based_column_values(column_values_data)?;
     Ok(Column {
         idx: column_index,
         values: column_values,

columnar/src/column_index/merge/shuffled.rs

@@ -91,6 +91,7 @@ fn iter_num_values<'a>(
                     return 0u32;
                 };
         match column_index {
+            ColumnIndex::Empty { .. } => 0u32,
             ColumnIndex::Full => 1,
             ColumnIndex::Optional(optional_index) => {
                 u32::from(optional_index.contains(row_addr.row_id))

columnar/src/column_index/merge/stacked.rs

@@ -55,7 +55,7 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
                         Some(ColumnIndex::Multivalued(_)) => {
                             panic!("No multivalued index is allowed when stacking column index");
                         }
-                        None => Box::new(std::iter::empty()),
+                        None | Some(ColumnIndex::Empty { .. }) => Box::new(std::iter::empty()),
                     };
                     rows_it
                 }),
@@ -74,7 +74,9 @@ fn convert_column_opt_to_multivalued_index<'a>(
     num_rows: RowId,
 ) -> Box<dyn Iterator<Item = RowId> + 'a> {
     match column_index_opt {
-        None => Box::new(iter::repeat(0u32).take(num_rows as usize + 1)),
+        None | Some(ColumnIndex::Empty { .. }) => {
+            Box::new(iter::repeat(0u32).take(num_rows as usize + 1))
+        }
         Some(ColumnIndex::Full) => Box::new(0..num_rows + 1),
         Some(ColumnIndex::Optional(optional_index)) => {
             Box::new(

columnar/src/column_index/mod.rs

@@ -14,6 +14,9 @@ use crate::{Cardinality, DocId, RowId};
 
 #[derive(Clone)]
 pub enum ColumnIndex {
+    Empty {
+        num_docs: u32,
+    },
     Full,
     Optional(OptionalIndex),
     /// In addition, at index num_rows, an extra value is added
@@ -34,8 +37,10 @@ impl From<MultiValueIndex> for ColumnIndex {
 }
 
 impl ColumnIndex {
+    #[inline]
     pub fn get_cardinality(&self) -> Cardinality {
         match self {
+            ColumnIndex::Empty { .. } => Cardinality::Optional,
             ColumnIndex::Full => Cardinality::Full,
             ColumnIndex::Optional(_) => Cardinality::Optional,
             ColumnIndex::Multivalued(_) => Cardinality::Multivalued,
@@ -45,6 +50,7 @@ impl ColumnIndex {
     /// Returns true if and only if there are at least one value associated to the row.
     pub fn has_value(&self, doc_id: DocId) -> bool {
         match self {
+            ColumnIndex::Empty { .. } => false,
             ColumnIndex::Full => true,
             ColumnIndex::Optional(optional_index) => optional_index.contains(doc_id),
             ColumnIndex::Multivalued(multivalued_index) => {
@@ -55,6 +61,7 @@ impl ColumnIndex {
 
     pub fn value_row_ids(&self, doc_id: DocId) -> Range<RowId> {
         match self {
+            ColumnIndex::Empty { .. } => 0..0,
             ColumnIndex::Full => doc_id..doc_id + 1,
             ColumnIndex::Optional(optional_index) => {
                 if let Some(val) = optional_index.rank_if_exists(doc_id) {
@@ -69,6 +76,7 @@ impl ColumnIndex {
 
     pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
         match self {
+            ColumnIndex::Empty { .. } => 0..0,
             ColumnIndex::Full => doc_id,
             ColumnIndex::Optional(optional_index) => {
                 let row_start = optional_index.rank(doc_id.start);
@@ -87,8 +95,11 @@ impl ColumnIndex {
         }
     }
 
-    pub fn select_batch_in_place(&self, rank_ids: &mut Vec<RowId>, doc_id_start: DocId) {
+    pub fn select_batch_in_place(&self, doc_id_start: DocId, rank_ids: &mut Vec<RowId>) {
         match self {
+            ColumnIndex::Empty { .. } => {
+                rank_ids.clear();
+            }
             ColumnIndex::Full => {
                 // No need to do anything:
                 // value_idx and row_idx are the same.

columnar/src/column_index/multivalued_index.rs

@@ -5,8 +5,9 @@ use std::sync::Arc;
 
 use common::OwnedBytes;
 
-use crate::column_values::u64_based::CodecType;
-use crate::column_values::ColumnValues;
+use crate::column_values::{
+    load_u64_based_column_values, serialize_u64_based_column_values, CodecType, ColumnValues,
+};
 use crate::iterable::Iterable;
 use crate::{DocId, RowId};
 
@@ -14,7 +15,7 @@ pub fn serialize_multivalued_index(
     multivalued_index: &dyn Iterable<RowId>,
     output: &mut impl Write,
 ) -> io::Result<()> {
-    crate::column_values::u64_based::serialize_u64_based_column_values(
+    serialize_u64_based_column_values(
         multivalued_index,
         &[CodecType::Bitpacked, CodecType::Linear],
         output,
@@ -23,8 +24,7 @@ pub fn serialize_multivalued_index(
 }
 
 pub fn open_multivalued_index(bytes: OwnedBytes) -> io::Result<MultiValueIndex> {
-    let start_index_column: Arc<dyn ColumnValues<RowId>> =
-        crate::column_values::u64_based::load_u64_based_column_values(bytes)?;
+    let start_index_column: Arc<dyn ColumnValues<RowId>> = load_u64_based_column_values(bytes)?;
     Ok(MultiValueIndex { start_index_column })
 }
 
@@ -83,13 +83,13 @@ impl MultiValueIndex {
         let mut cur_doc = docid_start;
         let mut last_doc = None;
 
-        assert!(self.start_index_column.get_val(docid_start) as u32 <= ranks[0]);
+        assert!(self.start_index_column.get_val(docid_start) <= ranks[0]);
 
         let mut write_doc_pos = 0;
         for i in 0..ranks.len() {
             let pos = ranks[i];
             loop {
-                let end = self.start_index_column.get_val(cur_doc + 1) as u32;
+                let end = self.start_index_column.get_val(cur_doc + 1);
                 if end > pos {
                     ranks[write_doc_pos] = cur_doc;
                     write_doc_pos += if last_doc == Some(cur_doc) { 0 } else { 1 };

columnar/src/column_index/optional_index/mod.rs

@@ -440,7 +440,7 @@ impl SerializedBlockMeta {
 
 #[inline]
 fn is_sparse(num_rows_in_block: u32) -> bool {
-    num_rows_in_block < DENSE_BLOCK_THRESHOLD as u32
+    num_rows_in_block < DENSE_BLOCK_THRESHOLD
 }
 
 fn deserialize_optional_index_block_metadatas(
@@ -448,7 +448,7 @@ fn deserialize_optional_index_block_metadatas(
     num_rows: u32,
 ) -> (Box<[BlockMeta]>, u32) {
     let num_blocks = data.len() / SERIALIZED_BLOCK_META_NUM_BYTES;
-    let mut block_metas = Vec::with_capacity(num_blocks as usize + 1);
+    let mut block_metas = Vec::with_capacity(num_blocks + 1);
     let mut start_byte_offset = 0;
     let mut non_null_rows_before_block = 0;
     for block_meta_bytes in data.chunks_exact(SERIALIZED_BLOCK_META_NUM_BYTES) {
@@ -479,7 +479,7 @@ fn deserialize_optional_index_block_metadatas(
             block_variant,
         });
         start_byte_offset += block_variant.num_bytes_in_block();
-        non_null_rows_before_block += num_non_null_rows as u32;
+        non_null_rows_before_block += num_non_null_rows;
     }
     block_metas.resize(
         ((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,

columnar/src/column_index/optional_index/set_block/dense.rs

@@ -32,7 +32,7 @@ pub const MINI_BLOCK_NUM_BYTES: usize = MINI_BLOCK_BITVEC_NUM_BYTES + MINI_BLOCK
 
 /// Number of bytes in a dense block.
 pub const DENSE_BLOCK_NUM_BYTES: u32 =
-    (ELEMENTS_PER_BLOCK as u32 / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
+    (ELEMENTS_PER_BLOCK / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
 
 pub struct DenseBlockCodec;
 
@@ -229,7 +229,7 @@ pub fn serialize_dense_codec(
         while block_id > current_block_id {
             let dense_mini_block = DenseMiniBlock {
                 bitvec: block,
-                rank: non_null_rows_before as u16,
+                rank: non_null_rows_before,
             };
             output.write_all(&dense_mini_block.to_bytes())?;
             non_null_rows_before += block.count_ones() as u16;

columnar/src/column_index/optional_index/tests.rs

@@ -37,7 +37,7 @@ proptest! {
 fn test_with_random_sets_simple() {
     let vals = 10..BLOCK_SIZE * 2;
     let mut out: Vec<u8> = Vec::new();
-    serialize_optional_index(&vals.clone(), 100, &mut out).unwrap();
+    serialize_optional_index(&vals, 100, &mut out).unwrap();
     let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
     let ranks: Vec<u32> = (65_472u32..65_473u32).collect();
     let els: Vec<u32> = ranks.iter().copied().map(|rank| rank + 10).collect();

columnar/src/column_values/bench.rs

@@ -0,0 +1,135 @@
+use std::sync::Arc;
+
+use common::OwnedBytes;
+use rand::rngs::StdRng;
+use rand::{Rng, SeedableRng};
+use test::{self, Bencher};
+
+use super::*;
+use crate::column_values::u64_based::*;
+
+fn get_data() -> Vec<u64> {
+    let mut rng = StdRng::seed_from_u64(2u64);
+    let mut data: Vec<_> = (100..55000_u64)
+        .map(|num| num + rng.gen::<u8>() as u64)
+        .collect();
+    data.push(99_000);
+    data.insert(1000, 2000);
+    data.insert(2000, 100);
+    data.insert(3000, 4100);
+    data.insert(4000, 100);
+    data.insert(5000, 800);
+    data
+}
+
+fn compute_stats(vals: impl Iterator<Item = u64>) -> ColumnStats {
+    let mut stats_collector = StatsCollector::default();
+    for val in vals {
+        stats_collector.collect(val);
+    }
+    stats_collector.stats()
+}
+
+#[inline(never)]
+fn value_iter() -> impl Iterator<Item = u64> {
+    0..20_000
+}
+fn get_reader_for_bench<Codec: ColumnCodec>(data: &[u64]) -> Codec::ColumnValues {
+    let mut bytes = Vec::new();
+    let stats = compute_stats(data.iter().cloned());
+    let mut codec_serializer = Codec::estimator();
+    for val in data {
+        codec_serializer.collect(*val);
+    }
+    codec_serializer.serialize(&stats, Box::new(data.iter().copied()).as_mut(), &mut bytes);
+
+    Codec::load(OwnedBytes::new(bytes)).unwrap()
+}
+fn bench_get<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
+    let col = get_reader_for_bench::<Codec>(data);
+    b.iter(|| {
+        let mut sum = 0u64;
+        for pos in value_iter() {
+            let val = col.get_val(pos as u32);
+            sum = sum.wrapping_add(val);
+        }
+        sum
+    });
+}
+
+#[inline(never)]
+fn bench_get_dynamic_helper(b: &mut Bencher, col: Arc<dyn ColumnValues>) {
+    b.iter(|| {
+        let mut sum = 0u64;
+        for pos in value_iter() {
+            let val = col.get_val(pos as u32);
+            sum = sum.wrapping_add(val);
+        }
+        sum
+    });
+}
+
+fn bench_get_dynamic<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
+    let col = Arc::new(get_reader_for_bench::<Codec>(data));
+    bench_get_dynamic_helper(b, col);
+}
+fn bench_create<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
+    let stats = compute_stats(data.iter().cloned());
+
+    let mut bytes = Vec::new();
+    b.iter(|| {
+        bytes.clear();
+        let mut codec_serializer = Codec::estimator();
+        for val in data.iter().take(1024) {
+            codec_serializer.collect(*val);
+        }
+
+        codec_serializer.serialize(&stats, Box::new(data.iter().copied()).as_mut(), &mut bytes)
+    });
+}
+
+#[bench]
+fn bench_fastfield_bitpack_create(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_create::<BitpackedCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_linearinterpol_create(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_create::<LinearCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_multilinearinterpol_create(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_create::<BlockwiseLinearCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_bitpack_get(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_get::<BitpackedCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_bitpack_get_dynamic(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_get_dynamic::<BitpackedCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_linearinterpol_get(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_get::<LinearCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_linearinterpol_get_dynamic(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_get_dynamic::<LinearCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_multilinearinterpol_get(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_get::<BlockwiseLinearCodec>(b, &data);
+}
+#[bench]
+fn bench_fastfield_multilinearinterpol_get_dynamic(b: &mut Bencher) {
+    let data: Vec<_> = get_data();
+    bench_get_dynamic::<BlockwiseLinearCodec>(b, &data);
+}

columnar/src/column_values/column.rs

@@ -1,367 +0,0 @@
-use std::fmt::Debug;
-use std::marker::PhantomData;
-use std::ops::{Range, RangeInclusive};
-use std::sync::Arc;
-
-use tantivy_bitpacker::minmax;
-
-use crate::column_values::monotonic_mapping::StrictlyMonotonicFn;
-use crate::RowId;
-
-/// `ColumnValues` provides access to a dense field column.
-///
-/// `Column` are just a wrapper over `ColumnValues` and a `ColumnIndex`.
-pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
-    /// Return the value associated with the given idx.
-    ///
-    /// This accessor should return as fast as possible.
-    ///
-    /// # Panics
-    ///
-    /// May panic if `idx` is greater than the column length.
-    fn get_val(&self, idx: u32) -> T;
-
-    /// Fills an output buffer with the fast field values
-    /// associated with the `DocId` going from
-    /// `start` to `start + output.len()`.
-    ///
-    /// # Panics
-    ///
-    /// Must panic if `start + output.len()` is greater than
-    /// the segment's `maxdoc`.
-    #[inline(always)]
-    fn get_range(&self, start: u64, output: &mut [T]) {
-        for (out, idx) in output.iter_mut().zip(start..) {
-            *out = self.get_val(idx as u32);
-        }
-    }
-
-    /// Get the row ids of values which are in the provided value range.
-    ///
-    /// Note that position == docid for single value fast fields
-    #[inline(always)]
-    fn get_row_ids_for_value_range(
-        &self,
-        value_range: RangeInclusive<T>,
-        row_id_range: Range<RowId>,
-        row_id_hits: &mut Vec<RowId>,
-    ) {
-        let row_id_range = row_id_range.start..row_id_range.end.min(self.num_vals());
-        for idx in row_id_range.start..row_id_range.end {
-            let val = self.get_val(idx);
-            if value_range.contains(&val) {
-                row_id_hits.push(idx);
-            }
-        }
-    }
-
-    /// Returns the minimum value for this fast field.
-    ///
-    /// This min_value may not be exact.
-    /// For instance, the min value does not take in account of possible
-    /// deleted document. All values are however guaranteed to be higher than
-    /// `.min_value()`.
-    fn min_value(&self) -> T;
-
-    /// Returns the maximum value for this fast field.
-    ///
-    /// This max_value may not be exact.
-    /// For instance, the max value does not take in account of possible
-    /// deleted document. All values are however guaranteed to be higher than
-    /// `.max_value()`.
-    fn max_value(&self) -> T;
-
-    /// The number of values in the column.
-    fn num_vals(&self) -> u32;
-
-    /// Returns a iterator over the data
-    fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = T> + 'a> {
-        Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
-    }
-}
-
-impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
-    #[inline(always)]
-    fn get_val(&self, idx: u32) -> T {
-        self.as_ref().get_val(idx)
-    }
-
-    #[inline(always)]
-    fn min_value(&self) -> T {
-        self.as_ref().min_value()
-    }
-
-    #[inline(always)]
-    fn max_value(&self) -> T {
-        self.as_ref().max_value()
-    }
-
-    #[inline(always)]
-    fn num_vals(&self) -> u32 {
-        self.as_ref().num_vals()
-    }
-
-    #[inline(always)]
-    fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
-        self.as_ref().iter()
-    }
-
-    #[inline(always)]
-    fn get_range(&self, start: u64, output: &mut [T]) {
-        self.as_ref().get_range(start, output)
-    }
-
-    fn get_row_ids_for_value_range(
-        &self,
-        value_range: RangeInclusive<T>,
-        row_id_range: Range<RowId>,
-        row_id_hits: &mut Vec<RowId>,
-    ) {
-        self.as_ref().get_row_ids_for_value_range(value_range, row_id_range, row_id_hits)
-    }
-}
-
-/// VecColumn provides `Column` over a slice.
-pub struct VecColumn<'a, T = u64> {
-    pub(crate) values: &'a [T],
-    pub(crate) min_value: T,
-    pub(crate) max_value: T,
-}
-
-impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
-    fn get_val(&self, position: u32) -> T {
-        self.values[position as usize]
-    }
-
-    fn iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
-        Box::new(self.values.iter().copied())
-    }
-
-    fn min_value(&self) -> T {
-        self.min_value
-    }
-
-    fn max_value(&self) -> T {
-        self.max_value
-    }
-
-    fn num_vals(&self) -> u32 {
-        self.values.len() as u32
-    }
-
-    fn get_range(&self, start: u64, output: &mut [T]) {
-        output.copy_from_slice(&self.values[start as usize..][..output.len()])
-    }
-}
-
-impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
-where V: AsRef<[T]> + ?Sized
-{
-    fn from(values: &'a V) -> Self {
-        let values = values.as_ref();
-        let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
-        Self {
-            values,
-            min_value,
-            max_value,
-        }
-    }
-}
-
-struct MonotonicMappingColumn<C, T, Input> {
-    from_column: C,
-    monotonic_mapping: T,
-    _phantom: PhantomData<Input>,
-}
-
-/// Creates a view of a column transformed by a strictly monotonic mapping. See
-/// [`StrictlyMonotonicFn`].
-///
-/// E.g. apply a gcd monotonic_mapping([100, 200, 300]) == [1, 2, 3]
-/// monotonic_mapping.mapping() is expected to be injective, and we should always have
-/// monotonic_mapping.inverse(monotonic_mapping.mapping(el)) == el
-///
-/// The inverse of the mapping is required for:
-/// `fn get_positions_for_value_range(&self, range: RangeInclusive<T>) -> Vec<u64> `
-/// The user provides the original value range and we need to monotonic map them in the same way the
-/// serialization does before calling the underlying column.
-///
-/// Note that when opening a codec, the monotonic_mapping should be the inverse of the mapping
-/// during serialization. And therefore the monotonic_mapping_inv when opening is the same as
-/// monotonic_mapping during serialization.
-pub fn monotonic_map_column<C, T, Input, Output>(
-    from_column: C,
-    monotonic_mapping: T,
-) -> impl ColumnValues<Output>
-where
-    C: ColumnValues<Input>,
-    T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
-    Input: PartialOrd + Debug + Send + Sync + Clone,
-    Output: PartialOrd + Debug + Send + Sync + Clone,
-{
-    MonotonicMappingColumn {
-        from_column,
-        monotonic_mapping,
-        _phantom: PhantomData,
-    }
-}
-
-impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
-where
-    C: ColumnValues<Input>,
-    T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
-    Input: PartialOrd + Send + Debug + Sync + Clone,
-    Output: PartialOrd + Send + Debug + Sync + Clone,
-{
-    #[inline]
-    fn get_val(&self, idx: u32) -> Output {
-        let from_val = self.from_column.get_val(idx);
-        self.monotonic_mapping.mapping(from_val)
-    }
-
-    fn min_value(&self) -> Output {
-        let from_min_value = self.from_column.min_value();
-        self.monotonic_mapping.mapping(from_min_value)
-    }
-
-    fn max_value(&self) -> Output {
-        let from_max_value = self.from_column.max_value();
-        self.monotonic_mapping.mapping(from_max_value)
-    }
-
-    fn num_vals(&self) -> u32 {
-        self.from_column.num_vals()
-    }
-
-    fn iter(&self) -> Box<dyn Iterator<Item = Output> + '_> {
-        Box::new(
-            self.from_column
-                .iter()
-                .map(|el| self.monotonic_mapping.mapping(el)),
-        )
-    }
-
-    fn get_row_ids_for_value_range(
-        &self,
-        range: RangeInclusive<Output>,
-        doc_id_range: Range<u32>,
-        positions: &mut Vec<u32>,
-    ) {
-        self.from_column.get_row_ids_for_value_range(
-            self.monotonic_mapping.inverse(range.start().clone())
-                ..=self.monotonic_mapping.inverse(range.end().clone()),
-            doc_id_range,
-            positions,
-        )
-    }
-
-    // We voluntarily do not implement get_range as it yields a regression,
-    // and we do not have any specialized implementation anyway.
-}
-
-/// Wraps an iterator into a `Column`.
-pub struct IterColumn<T>(T);
-
-impl<T> From<T> for IterColumn<T>
-where T: Iterator + Clone + ExactSizeIterator
-{
-    fn from(iter: T) -> Self {
-        IterColumn(iter)
-    }
-}
-
-impl<T> ColumnValues<T::Item> for IterColumn<T>
-where
-    T: Iterator + Clone + ExactSizeIterator + Send + Sync,
-    T::Item: PartialOrd + Debug,
-{
-    fn get_val(&self, idx: u32) -> T::Item {
-        self.0.clone().nth(idx as usize).unwrap()
-    }
-
-    fn min_value(&self) -> T::Item {
-        self.0.clone().next().unwrap()
-    }
-
-    fn max_value(&self) -> T::Item {
-        self.0.clone().last().unwrap()
-    }
-
-    fn num_vals(&self) -> u32 {
-        self.0.len() as u32
-    }
-
-    fn iter(&self) -> Box<dyn Iterator<Item = T::Item> + '_> {
-        Box::new(self.0.clone())
-    }
-}
-
-#[cfg(test)]
-mod tests {
-    use super::*;
-    use crate::column_values::monotonic_mapping::{
-        StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternalBaseval,
-        StrictlyMonotonicMappingToInternalGCDBaseval,
-    };
-
-    #[test]
-    fn test_monotonic_mapping() {
-        let vals = &[3u64, 5u64][..];
-        let col = VecColumn::from(vals);
-        let mapped = monotonic_map_column(col, StrictlyMonotonicMappingToInternalBaseval::new(2));
-        assert_eq!(mapped.min_value(), 1u64);
-        assert_eq!(mapped.max_value(), 3u64);
-        assert_eq!(mapped.num_vals(), 2);
-        assert_eq!(mapped.num_vals(), 2);
-        assert_eq!(mapped.get_val(0), 1);
-        assert_eq!(mapped.get_val(1), 3);
-    }
-
-    #[test]
-    fn test_range_as_col() {
-        let col = IterColumn::from(10..100);
-        assert_eq!(col.num_vals(), 90);
-        assert_eq!(col.max_value(), 99);
-    }
-
-    #[test]
-    fn test_monotonic_mapping_iter() {
-        let vals: Vec<u64> = (10..110u64).map(|el| el * 10).collect();
-        let col = VecColumn::from(&vals);
-        let mapped = monotonic_map_column(
-            col,
-            StrictlyMonotonicMappingInverter::from(
-                StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 100),
-            ),
-        );
-        let val_i64s: Vec<u64> = mapped.iter().collect();
-        for i in 0..100 {
-            assert_eq!(val_i64s[i as usize], mapped.get_val(i));
-        }
-    }
-
-    #[test]
-    fn test_monotonic_mapping_get_range() {
-        let vals: Vec<u64> = (0..100u64).map(|el| el * 10).collect();
-        let col = VecColumn::from(&vals);
-        let mapped = monotonic_map_column(
-            col,
-            StrictlyMonotonicMappingInverter::from(
-                StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 0),
-            ),
-        );
-
-        assert_eq!(mapped.min_value(), 0u64);
-        assert_eq!(mapped.max_value(), 9900u64);
-        assert_eq!(mapped.num_vals(), 100);
-        let val_u64s: Vec<u64> = mapped.iter().collect();
-        assert_eq!(val_u64s.len(), 100);
-        for i in 0..100 {
-            assert_eq!(val_u64s[i as usize], mapped.get_val(i));
-            assert_eq!(val_u64s[i as usize], vals[i as usize] * 10);
-        }
-        let mut buf = [0u64; 20];
-        mapped.get_range(7, &mut buf[..]);
-        assert_eq!(&val_u64s[7..][..20], &buf);
-    }
-}

columnar/src/column_values/merge.rs

@@ -0,0 +1,41 @@
+use std::fmt::Debug;
+use std::sync::Arc;
+
+use crate::iterable::Iterable;
+use crate::{ColumnIndex, ColumnValues, MergeRowOrder};
+
+pub(crate) struct MergedColumnValues<'a, T> {
+    pub(crate) column_indexes: &'a [Option<ColumnIndex>],
+    pub(crate) column_values: &'a [Option<Arc<dyn ColumnValues<T>>>],
+    pub(crate) merge_row_order: &'a MergeRowOrder,
+}
+
+impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T> {
+    fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
+        match self.merge_row_order {
+            MergeRowOrder::Stack(_) => Box::new(
+                self.column_values
+                    .iter()
+                    .flatten()
+                    .flat_map(|column_value| column_value.iter()),
+            ),
+            MergeRowOrder::Shuffled(shuffle_merge_order) => Box::new(
+                shuffle_merge_order
+                    .iter_new_to_old_row_addrs()
+                    .flat_map(|row_addr| {
+                        let column_index =
+                            self.column_indexes[row_addr.segment_ord as usize].as_ref()?;
+                        let column_values =
+                            self.column_values[row_addr.segment_ord as usize].as_ref()?;
+                        let value_range = column_index.value_row_ids(row_addr.row_id);
+                        Some((value_range, column_values))
+                    })
+                    .flat_map(|(value_range, column_values)| {
+                        value_range
+                            .into_iter()
+                            .map(|val| column_values.get_val(val))
+                    }),
+            ),
+        }
+    }
+}

columnar/src/column_values/mod.rs

@@ -7,260 +7,214 @@
 //! - Monotonically map values to u64/u128
 
 use std::fmt::Debug;
-use std::io;
-use std::io::Write;
+use std::ops::{Range, RangeInclusive};
 use std::sync::Arc;
 
-use common::{BinarySerializable, OwnedBytes};
-use compact_space::CompactSpaceDecompressor;
 pub use monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
-use monotonic_mapping::{StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal};
 pub use monotonic_mapping_u128::MonotonicallyMappableToU128;
-use serialize::U128Header;
 
-mod compact_space;
+mod merge;
 pub(crate) mod monotonic_mapping;
 pub(crate) mod monotonic_mapping_u128;
 mod stats;
-pub(crate) mod u64_based;
+mod u128_based;
+mod u64_based;
+mod vec_column;
 
-mod column;
-pub(crate) mod serialize;
+mod monotonic_column;
 
-pub use serialize::serialize_column_values_u128;
+pub(crate) use merge::MergedColumnValues;
 pub use stats::ColumnStats;
+pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
 pub use u64_based::{
     load_u64_based_column_values, serialize_and_load_u64_based_column_values,
     serialize_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
 };
+pub use vec_column::VecColumn;
 
-pub use self::column::{monotonic_map_column, ColumnValues, IterColumn, VecColumn};
-use crate::iterable::Iterable;
-use crate::{ColumnIndex, MergeRowOrder};
+pub use self::monotonic_column::monotonic_map_column;
+use crate::RowId;
 
-pub(crate) struct MergedColumnValues<'a, T> {
-    pub(crate) column_indexes: &'a [Option<ColumnIndex>],
-    pub(crate) column_values: &'a [Option<Arc<dyn ColumnValues<T>>>],
-    pub(crate) merge_row_order: &'a MergeRowOrder,
-}
+/// `ColumnValues` provides access to a dense field column.
+///
+/// `Column` are just a wrapper over `ColumnValues` and a `ColumnIndex`.
+///
+/// Any methods with a default and specialized implementation need to be called in the
+/// wrappers that implement the trait: Arc and MonotonicMappingColumn
+pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
+    /// Return the value associated with the given idx.
+    ///
+    /// This accessor should return as fast as possible.
+    ///
+    /// # Panics
+    ///
+    /// May panic if `idx` is greater than the column length.
+    fn get_val(&self, idx: u32) -> T;
 
-impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T> {
-    fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
-        match self.merge_row_order {
-            MergeRowOrder::Stack(_) => {
-                Box::new(self
-                    .column_values
-                    .iter()
-                    .flatten()
-                    .flat_map(|column_value| column_value.iter()))
-            },
-            MergeRowOrder::Shuffled(shuffle_merge_order) => {
-                Box::new(shuffle_merge_order
-                    .iter_new_to_old_row_addrs()
-                    .flat_map(|row_addr| {
-                        let Some(column_index) = self.column_indexes[row_addr.segment_ord as usize].as_ref() else {
-                            return None;
-                        };
-                        let Some(column_values) = self.column_values[row_addr.segment_ord as usize].as_ref() else {
-                            return None;
-                        };
-                        let value_range = column_index.value_row_ids(row_addr.row_id);
-                        Some((value_range, column_values))
-                    })
-                    .flat_map(|(value_range, column_values)| {
-                        value_range
-                            .into_iter()
-                            .map(|val| column_values.get_val(val))
-                    })
-                )
-            },
+    /// Allows to push down multiple fetch calls, to avoid dynamic dispatch overhead.
+    ///
+    /// idx and output should have the same length
+    ///
+    /// # Panics
+    ///
+    /// May panic if `idx` is greater than the column length.
+    fn get_vals(&self, idx: &[u32], output: &mut [T]) {
+        assert!(idx.len() == output.len());
+        for (out, idx) in output.iter_mut().zip(idx.iter()) {
+            *out = self.get_val(*idx as u32);
         }
     }
-}
 
-#[derive(PartialEq, Eq, PartialOrd, Ord, Debug, Clone, Copy)]
-#[repr(u8)]
-/// Available codecs to use to encode the u128 (via [`MonotonicallyMappableToU128`]) converted data.
-pub enum U128FastFieldCodecType {
-    /// This codec takes a large number space (u128) and reduces it to a compact number space, by
-    /// removing the holes.
-    CompactSpace = 1,
-}
-
-impl BinarySerializable for U128FastFieldCodecType {
-    fn serialize<W: Write + ?Sized>(&self, wrt: &mut W) -> io::Result<()> {
-        self.to_code().serialize(wrt)
-    }
-
-    fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
-        let code = u8::deserialize(reader)?;
-        let codec_type: Self = Self::from_code(code)
-            .ok_or_else(|| io::Error::new(io::ErrorKind::InvalidData, "Unknown code `{code}.`"))?;
-        Ok(codec_type)
-    }
-}
-
-impl U128FastFieldCodecType {
-    pub(crate) fn to_code(self) -> u8 {
-        self as u8
-    }
-
-    pub(crate) fn from_code(code: u8) -> Option<Self> {
-        match code {
-            1 => Some(Self::CompactSpace),
-            _ => None,
+    /// Fills an output buffer with the fast field values
+    /// associated with the `DocId` going from
+    /// `start` to `start + output.len()`.
+    ///
+    /// # Panics
+    ///
+    /// Must panic if `start + output.len()` is greater than
+    /// the segment's `maxdoc`.
+    #[inline(always)]
+    fn get_range(&self, start: u64, output: &mut [T]) {
+        for (out, idx) in output.iter_mut().zip(start..) {
+            *out = self.get_val(idx as u32);
         }
     }
+
+    /// Get the row ids of values which are in the provided value range.
+    ///
+    /// Note that position == docid for single value fast fields
+    #[inline(always)]
+    fn get_row_ids_for_value_range(
+        &self,
+        value_range: RangeInclusive<T>,
+        row_id_range: Range<RowId>,
+        row_id_hits: &mut Vec<RowId>,
+    ) {
+        let row_id_range = row_id_range.start..row_id_range.end.min(self.num_vals());
+        for idx in row_id_range.start..row_id_range.end {
+            let val = self.get_val(idx);
+            if value_range.contains(&val) {
+                row_id_hits.push(idx);
+            }
+        }
+    }
+
+    /// Returns the minimum value for this fast field.
+    ///
+    /// This min_value may not be exact.
+    /// For instance, the min value does not take in account of possible
+    /// deleted document. All values are however guaranteed to be higher than
+    /// `.min_value()`.
+    fn min_value(&self) -> T;
+
+    /// Returns the maximum value for this fast field.
+    ///
+    /// This max_value may not be exact.
+    /// For instance, the max value does not take in account of possible
+    /// deleted document. All values are however guaranteed to be higher than
+    /// `.max_value()`.
+    fn max_value(&self) -> T;
+
+    /// The number of values in the column.
+    fn num_vals(&self) -> u32;
+
+    /// Returns a iterator over the data
+    fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = T> + 'a> {
+        Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
+    }
 }
 
-/// Returns the correct codec reader wrapped in the `Arc` for the data.
-pub fn open_u128_mapped<T: MonotonicallyMappableToU128 + Debug>(
-    mut bytes: OwnedBytes,
-) -> io::Result<Arc<dyn ColumnValues<T>>> {
-    let header = U128Header::deserialize(&mut bytes)?;
-    assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
-    let reader = CompactSpaceDecompressor::open(bytes)?;
+impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
+    #[inline(always)]
+    fn get_val(&self, idx: u32) -> T {
+        self.as_ref().get_val(idx)
+    }
 
-    let inverted: StrictlyMonotonicMappingInverter<StrictlyMonotonicMappingToInternal<T>> =
-        StrictlyMonotonicMappingToInternal::<T>::new().into();
-    Ok(Arc::new(monotonic_map_column(reader, inverted)))
+    #[inline(always)]
+    fn min_value(&self) -> T {
+        self.as_ref().min_value()
+    }
+
+    #[inline(always)]
+    fn max_value(&self) -> T {
+        self.as_ref().max_value()
+    }
+
+    #[inline(always)]
+    fn num_vals(&self) -> u32 {
+        self.as_ref().num_vals()
+    }
+
+    #[inline(always)]
+    fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
+        self.as_ref().iter()
+    }
+
+    #[inline(always)]
+    fn get_range(&self, start: u64, output: &mut [T]) {
+        self.as_ref().get_range(start, output)
+    }
+
+    #[inline(always)]
+    fn get_row_ids_for_value_range(
+        &self,
+        range: RangeInclusive<T>,
+        doc_id_range: Range<u32>,
+        positions: &mut Vec<u32>,
+    ) {
+        self.as_ref()
+            .get_row_ids_for_value_range(range, doc_id_range, positions)
+    }
+}
+
+/// Wraps an cloneable iterator into a `Column`.
+pub struct IterColumn<T>(T);
+
+impl<T> From<T> for IterColumn<T>
+where T: Iterator + Clone + ExactSizeIterator
+{
+    fn from(iter: T) -> Self {
+        IterColumn(iter)
+    }
+}
+
+impl<T> ColumnValues<T::Item> for IterColumn<T>
+where
+    T: Iterator + Clone + ExactSizeIterator + Send + Sync,
+    T::Item: PartialOrd + Debug,
+{
+    fn get_val(&self, idx: u32) -> T::Item {
+        self.0.clone().nth(idx as usize).unwrap()
+    }
+
+    fn min_value(&self) -> T::Item {
+        self.0.clone().next().unwrap()
+    }
+
+    fn max_value(&self) -> T::Item {
+        self.0.clone().last().unwrap()
+    }
+
+    fn num_vals(&self) -> u32 {
+        self.0.len() as u32
+    }
+
+    fn iter(&self) -> Box<dyn Iterator<Item = T::Item> + '_> {
+        Box::new(self.0.clone())
+    }
 }
 
 #[cfg(all(test, feature = "unstable"))]
-mod bench {
-    use std::sync::Arc;
-
-    use common::OwnedBytes;
-    use rand::rngs::StdRng;
-    use rand::{Rng, SeedableRng};
-    use test::{self, Bencher};
+mod bench;
 
+#[cfg(test)]
+mod tests {
     use super::*;
-    use crate::column_values::u64_based::*;
 
-    fn get_data() -> Vec<u64> {
-        let mut rng = StdRng::seed_from_u64(2u64);
-        let mut data: Vec<_> = (100..55000_u64)
-            .map(|num| num + rng.gen::<u8>() as u64)
-            .collect();
-        data.push(99_000);
-        data.insert(1000, 2000);
-        data.insert(2000, 100);
-        data.insert(3000, 4100);
-        data.insert(4000, 100);
-        data.insert(5000, 800);
-        data
-    }
-
-    fn compute_stats(vals: impl Iterator<Item = u64>) -> ColumnStats {
-        let mut stats_collector = StatsCollector::default();
-        for val in vals {
-            stats_collector.collect(val);
-        }
-        stats_collector.stats()
-    }
-
-    #[inline(never)]
-    fn value_iter() -> impl Iterator<Item = u64> {
-        0..20_000
-    }
-    fn get_reader_for_bench<Codec: ColumnCodec>(data: &[u64]) -> Codec::ColumnValues {
-        let mut bytes = Vec::new();
-        let stats = compute_stats(data.iter().cloned());
-        let mut codec_serializer = Codec::estimator();
-        for val in data {
-            codec_serializer.collect(*val);
-        }
-        codec_serializer.serialize(&stats, Box::new(data.iter().copied()).as_mut(), &mut bytes);
-
-        Codec::load(OwnedBytes::new(bytes)).unwrap()
-    }
-    fn bench_get<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
-        let col = get_reader_for_bench::<Codec>(data);
-        b.iter(|| {
-            let mut sum = 0u64;
-            for pos in value_iter() {
-                let val = col.get_val(pos as u32);
-                sum = sum.wrapping_add(val);
-            }
-            sum
-        });
-    }
-
-    #[inline(never)]
-    fn bench_get_dynamic_helper(b: &mut Bencher, col: Arc<dyn ColumnValues>) {
-        b.iter(|| {
-            let mut sum = 0u64;
-            for pos in value_iter() {
-                let val = col.get_val(pos as u32);
-                sum = sum.wrapping_add(val);
-            }
-            sum
-        });
-    }
-
-    fn bench_get_dynamic<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
-        let col = Arc::new(get_reader_for_bench::<Codec>(data));
-        bench_get_dynamic_helper(b, col);
-    }
-    fn bench_create<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
-        let stats = compute_stats(data.iter().cloned());
-
-        let mut bytes = Vec::new();
-        b.iter(|| {
-            bytes.clear();
-            let mut codec_serializer = Codec::estimator();
-            for val in data.iter().take(1024) {
-                codec_serializer.collect(*val);
-            }
-
-            codec_serializer.serialize(&stats, Box::new(data.iter().copied()).as_mut(), &mut bytes)
-        });
-    }
-
-    #[bench]
-    fn bench_fastfield_bitpack_create(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_create::<BitpackedCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_linearinterpol_create(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_create::<LinearCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_multilinearinterpol_create(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_create::<BlockwiseLinearCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_bitpack_get(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_get::<BitpackedCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_bitpack_get_dynamic(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_get_dynamic::<BitpackedCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_linearinterpol_get(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_get::<LinearCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_linearinterpol_get_dynamic(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_get_dynamic::<LinearCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_multilinearinterpol_get(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_get::<BlockwiseLinearCodec>(b, &data);
-    }
-    #[bench]
-    fn bench_fastfield_multilinearinterpol_get_dynamic(b: &mut Bencher) {
-        let data: Vec<_> = get_data();
-        bench_get_dynamic::<BlockwiseLinearCodec>(b, &data);
+    #[test]
+    fn test_range_as_col() {
+        let col = IterColumn::from(10..100);
+        assert_eq!(col.num_vals(), 90);
+        assert_eq!(col.max_value(), 99);
     }
 }

columnar/src/column_values/monotonic_column.rs

@@ -0,0 +1,120 @@
+use std::fmt::Debug;
+use std::marker::PhantomData;
+use std::ops::{Range, RangeInclusive};
+
+use crate::column_values::monotonic_mapping::StrictlyMonotonicFn;
+use crate::ColumnValues;
+
+struct MonotonicMappingColumn<C, T, Input> {
+    from_column: C,
+    monotonic_mapping: T,
+    _phantom: PhantomData<Input>,
+}
+
+/// Creates a view of a column transformed by a strictly monotonic mapping. See
+/// [`StrictlyMonotonicFn`].
+///
+/// E.g. apply a gcd monotonic_mapping([100, 200, 300]) == [1, 2, 3]
+/// monotonic_mapping.mapping() is expected to be injective, and we should always have
+/// monotonic_mapping.inverse(monotonic_mapping.mapping(el)) == el
+///
+/// The inverse of the mapping is required for:
+/// `fn get_positions_for_value_range(&self, range: RangeInclusive<T>) -> Vec<u64> `
+/// The user provides the original value range and we need to monotonic map them in the same way the
+/// serialization does before calling the underlying column.
+///
+/// Note that when opening a codec, the monotonic_mapping should be the inverse of the mapping
+/// during serialization. And therefore the monotonic_mapping_inv when opening is the same as
+/// monotonic_mapping during serialization.
+pub fn monotonic_map_column<C, T, Input, Output>(
+    from_column: C,
+    monotonic_mapping: T,
+) -> impl ColumnValues<Output>
+where
+    C: ColumnValues<Input>,
+    T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
+    Input: PartialOrd + Debug + Send + Sync + Clone,
+    Output: PartialOrd + Debug + Send + Sync + Clone,
+{
+    MonotonicMappingColumn {
+        from_column,
+        monotonic_mapping,
+        _phantom: PhantomData,
+    }
+}
+
+impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
+where
+    C: ColumnValues<Input>,
+    T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
+    Input: PartialOrd + Send + Debug + Sync + Clone,
+    Output: PartialOrd + Send + Debug + Sync + Clone,
+{
+    #[inline]
+    fn get_val(&self, idx: u32) -> Output {
+        let from_val = self.from_column.get_val(idx);
+        self.monotonic_mapping.mapping(from_val)
+    }
+
+    fn min_value(&self) -> Output {
+        let from_min_value = self.from_column.min_value();
+        self.monotonic_mapping.mapping(from_min_value)
+    }
+
+    fn max_value(&self) -> Output {
+        let from_max_value = self.from_column.max_value();
+        self.monotonic_mapping.mapping(from_max_value)
+    }
+
+    fn num_vals(&self) -> u32 {
+        self.from_column.num_vals()
+    }
+
+    fn iter(&self) -> Box<dyn Iterator<Item = Output> + '_> {
+        Box::new(
+            self.from_column
+                .iter()
+                .map(|el| self.monotonic_mapping.mapping(el)),
+        )
+    }
+
+    fn get_row_ids_for_value_range(
+        &self,
+        range: RangeInclusive<Output>,
+        doc_id_range: Range<u32>,
+        positions: &mut Vec<u32>,
+    ) {
+        self.from_column.get_row_ids_for_value_range(
+            self.monotonic_mapping.inverse(range.start().clone())
+                ..=self.monotonic_mapping.inverse(range.end().clone()),
+            doc_id_range,
+            positions,
+        )
+    }
+
+    // We voluntarily do not implement get_range as it yields a regression,
+    // and we do not have any specialized implementation anyway.
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::column_values::monotonic_mapping::{
+        StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
+    };
+    use crate::column_values::VecColumn;
+
+    #[test]
+    fn test_monotonic_mapping_iter() {
+        let vals: Vec<u64> = (0..100u64).map(|el| el * 10).collect();
+        let col = VecColumn::from(&vals);
+        let mapped = monotonic_map_column(
+            col,
+            StrictlyMonotonicMappingInverter::from(StrictlyMonotonicMappingToInternal::<i64>::new()),
+        );
+        let val_i64s: Vec<u64> = mapped.iter().collect();
+        for i in 0..100 {
+            assert_eq!(val_i64s[i as usize], mapped.get_val(i));
+        }
+    }
+}

columnar/src/column_values/monotonic_mapping.rs

@@ -2,7 +2,6 @@ use std::fmt::Debug;
 use std::marker::PhantomData;
 
 use common::DateTime;
-use fastdivide::DividerU64;
 
 use super::MonotonicallyMappableToU128;
 use crate::RowId;
@@ -113,68 +112,6 @@ where T: MonotonicallyMappableToU64
     }
 }
 
-/// Mapping dividing by  gcd and a base value.
-///
-/// The function is assumed to be only called on values divided by passed
-/// gcd value. (It is necessary for the function to be monotonic.)
-pub(crate) struct StrictlyMonotonicMappingToInternalGCDBaseval {
-    gcd_divider: DividerU64,
-    gcd: u64,
-    min_value: u64,
-}
-impl StrictlyMonotonicMappingToInternalGCDBaseval {
-    /// Creates a linear mapping `x -> gcd*x + min_value`.
-    pub(crate) fn new(gcd: u64, min_value: u64) -> Self {
-        let gcd_divider = DividerU64::divide_by(gcd);
-        Self {
-            gcd_divider,
-            gcd,
-            min_value,
-        }
-    }
-}
-impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
-    for StrictlyMonotonicMappingToInternalGCDBaseval
-{
-    #[inline(always)]
-    fn mapping(&self, inp: External) -> u64 {
-        self.gcd_divider
-            .divide(External::to_u64(inp) - self.min_value)
-    }
-
-    #[inline(always)]
-    fn inverse(&self, out: u64) -> External {
-        External::from_u64(self.min_value + out * self.gcd)
-    }
-}
-
-/// Strictly monotonic mapping with a base value.
-pub(crate) struct StrictlyMonotonicMappingToInternalBaseval {
-    min_value: u64,
-}
-
-impl StrictlyMonotonicMappingToInternalBaseval {
-    /// Creates a linear mapping `x -> x + min_value`.
-    #[inline(always)]
-    pub(crate) fn new(min_value: u64) -> Self {
-        Self { min_value }
-    }
-}
-
-impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
-    for StrictlyMonotonicMappingToInternalBaseval
-{
-    #[inline(always)]
-    fn mapping(&self, val: External) -> u64 {
-        External::to_u64(val) - self.min_value
-    }
-
-    #[inline(always)]
-    fn inverse(&self, val: u64) -> External {
-        External::from_u64(self.min_value + val)
-    }
-}
-
 impl MonotonicallyMappableToU64 for u64 {
     #[inline(always)]
     fn to_u64(self) -> u64 {
@@ -263,13 +200,6 @@ mod tests {
         // TODO
         // identity mapping
         // test_round_trip(&StrictlyMonotonicMappingToInternal::<u128>::new(), 100u128);
-
-        // base value to i64 round trip
-        let mapping = StrictlyMonotonicMappingToInternalBaseval::new(100);
-        test_round_trip::<_, _, u64>(&mapping, 100i64);
-        // base value and gcd to u64 round trip
-        let mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 100);
-        test_round_trip::<_, _, u64>(&mapping, 100u64);
     }
 
     fn test_round_trip<T: StrictlyMonotonicFn<K, L>, K: std::fmt::Debug + Eq + Copy, L>(

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

@@ -17,16 +17,16 @@ use std::{
     ops::{Range, RangeInclusive},
 };
 
+mod blank_range;
+mod build_compact_space;
+
+use build_compact_space::get_compact_space;
 use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt, VIntU128};
 use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
 
-use crate::column_values::compact_space::build_compact_space::get_compact_space;
 use crate::column_values::ColumnValues;
 use crate::RowId;
 
-mod blank_range;
-mod build_compact_space;
-
 /// The cost per blank is quite hard actually, since blanks are delta encoded, the actual cost of
 /// blanks depends on the number of blanks.
 ///
@@ -464,7 +464,7 @@ mod tests {
     use itertools::Itertools;
 
     use super::*;
-    use crate::column_values::serialize::U128Header;
+    use crate::column_values::u128_based::U128Header;
     use crate::column_values::{open_u128_mapped, serialize_column_values_u128};
 
     #[test]

columnar/src/column_values/u128_based/mod.rs

@@ -1,12 +1,19 @@
 use std::fmt::Debug;
 use std::io;
+use std::io::Write;
+use std::sync::Arc;
 
-use common::{BinarySerializable, VInt};
+mod compact_space;
 
-use crate::column_values::compact_space::CompactSpaceCompressor;
-use crate::column_values::U128FastFieldCodecType;
+use common::{BinarySerializable, OwnedBytes, VInt};
+use compact_space::{CompactSpaceCompressor, CompactSpaceDecompressor};
+
+use crate::column_values::monotonic_map_column;
+use crate::column_values::monotonic_mapping::{
+    StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
+};
 use crate::iterable::Iterable;
-use crate::MonotonicallyMappableToU128;
+use crate::{ColumnValues, MonotonicallyMappableToU128};
 
 #[derive(Debug, Copy, Clone, PartialEq, Eq)]
 pub(crate) struct U128Header {
@@ -55,6 +62,52 @@ pub fn serialize_column_values_u128<T: MonotonicallyMappableToU128>(
     Ok(())
 }
 
+#[derive(PartialEq, Eq, PartialOrd, Ord, Debug, Clone, Copy)]
+#[repr(u8)]
+/// Available codecs to use to encode the u128 (via [`MonotonicallyMappableToU128`]) converted data.
+pub(crate) enum U128FastFieldCodecType {
+    /// This codec takes a large number space (u128) and reduces it to a compact number space, by
+    /// removing the holes.
+    CompactSpace = 1,
+}
+
+impl BinarySerializable for U128FastFieldCodecType {
+    fn serialize<W: Write + ?Sized>(&self, wrt: &mut W) -> io::Result<()> {
+        self.to_code().serialize(wrt)
+    }
+
+    fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
+        let code = u8::deserialize(reader)?;
+        let codec_type: Self = Self::from_code(code)
+            .ok_or_else(|| io::Error::new(io::ErrorKind::InvalidData, "Unknown code `{code}.`"))?;
+        Ok(codec_type)
+    }
+}
+
+impl U128FastFieldCodecType {
+    pub(crate) fn to_code(self) -> u8 {
+        self as u8
+    }
+
+    pub(crate) fn from_code(code: u8) -> Option<Self> {
+        match code {
+            1 => Some(Self::CompactSpace),
+            _ => None,
+        }
+    }
+}
+
+/// Returns the correct codec reader wrapped in the `Arc` for the data.
+pub fn open_u128_mapped<T: MonotonicallyMappableToU128 + Debug>(
+    mut bytes: OwnedBytes,
+) -> io::Result<Arc<dyn ColumnValues<T>>> {
+    let header = U128Header::deserialize(&mut bytes)?;
+    assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
+    let reader = CompactSpaceDecompressor::open(bytes)?;
+    let inverted: StrictlyMonotonicMappingInverter<StrictlyMonotonicMappingToInternal<T>> =
+        StrictlyMonotonicMappingToInternal::<T>::new().into();
+    Ok(Arc::new(monotonic_map_column(reader, inverted)))
+}
 #[cfg(test)]
 pub mod tests {
     use super::*;

columnar/src/column_values/u64_based/blockwise_linear.rs

@@ -201,8 +201,8 @@ pub struct BlockwiseLinearReader {
 impl ColumnValues for BlockwiseLinearReader {
     #[inline(always)]
     fn get_val(&self, idx: u32) -> u64 {
-        let block_id = (idx / BLOCK_SIZE as u32) as usize;
-        let idx_within_block = idx % (BLOCK_SIZE as u32);
+        let block_id = (idx / BLOCK_SIZE) as usize;
+        let idx_within_block = idx % BLOCK_SIZE;
         let block = &self.blocks[block_id];
         let interpoled_val: u64 = block.line.eval(idx_within_block);
         let block_bytes = &self.data[block.data_start_offset..];

columnar/src/column_values/u64_based/tests.rs

@@ -1,6 +1,6 @@
 use proptest::prelude::*;
 use proptest::strategy::Strategy;
-use proptest::{prop_oneof, proptest};
+use proptest::{num, prop_oneof, proptest};
 
 #[test]
 fn test_serialize_and_load_simple() {
@@ -19,6 +19,62 @@ fn test_serialize_and_load_simple() {
     assert_eq!(col.get_val(1), 2);
     assert_eq!(col.get_val(2), 5);
 }
+
+#[test]
+fn test_empty_column_i64() {
+    let vals: [i64; 0] = [];
+    let mut num_acceptable_codecs = 0;
+    for codec in ALL_U64_CODEC_TYPES {
+        let mut buffer = Vec::new();
+        if serialize_u64_based_column_values(&&vals[..], &[codec], &mut buffer).is_err() {
+            continue;
+        }
+        num_acceptable_codecs += 1;
+        let col = load_u64_based_column_values::<i64>(OwnedBytes::new(buffer)).unwrap();
+        assert_eq!(col.num_vals(), 0);
+        assert_eq!(col.min_value(), i64::MIN);
+        assert_eq!(col.max_value(), i64::MIN);
+    }
+    assert!(num_acceptable_codecs > 0);
+}
+
+#[test]
+fn test_empty_column_u64() {
+    let vals: [u64; 0] = [];
+    let mut num_acceptable_codecs = 0;
+    for codec in ALL_U64_CODEC_TYPES {
+        let mut buffer = Vec::new();
+        if serialize_u64_based_column_values(&&vals[..], &[codec], &mut buffer).is_err() {
+            continue;
+        }
+        num_acceptable_codecs += 1;
+        let col = load_u64_based_column_values::<u64>(OwnedBytes::new(buffer)).unwrap();
+        assert_eq!(col.num_vals(), 0);
+        assert_eq!(col.min_value(), u64::MIN);
+        assert_eq!(col.max_value(), u64::MIN);
+    }
+    assert!(num_acceptable_codecs > 0);
+}
+
+#[test]
+fn test_empty_column_f64() {
+    let vals: [f64; 0] = [];
+    let mut num_acceptable_codecs = 0;
+    for codec in ALL_U64_CODEC_TYPES {
+        let mut buffer = Vec::new();
+        if serialize_u64_based_column_values(&&vals[..], &[codec], &mut buffer).is_err() {
+            continue;
+        }
+        num_acceptable_codecs += 1;
+        let col = load_u64_based_column_values::<f64>(OwnedBytes::new(buffer)).unwrap();
+        assert_eq!(col.num_vals(), 0);
+        // FIXME. f64::MIN would be better!
+        assert!(col.min_value().is_nan());
+        assert!(col.max_value().is_nan());
+    }
+    assert!(num_acceptable_codecs > 0);
+}
+
 pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
     vals: &[u64],
     name: &str,

columnar/src/column_values/vec_column.rs

@@ -0,0 +1,52 @@
+use std::fmt::Debug;
+
+use tantivy_bitpacker::minmax;
+
+use crate::ColumnValues;
+
+/// VecColumn provides `Column` over a slice.
+pub struct VecColumn<'a, T = u64> {
+    pub(crate) values: &'a [T],
+    pub(crate) min_value: T,
+    pub(crate) max_value: T,
+}
+
+impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
+    fn get_val(&self, position: u32) -> T {
+        self.values[position as usize]
+    }
+
+    fn iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
+        Box::new(self.values.iter().copied())
+    }
+
+    fn min_value(&self) -> T {
+        self.min_value
+    }
+
+    fn max_value(&self) -> T {
+        self.max_value
+    }
+
+    fn num_vals(&self) -> u32 {
+        self.values.len() as u32
+    }
+
+    fn get_range(&self, start: u64, output: &mut [T]) {
+        output.copy_from_slice(&self.values[start as usize..][..output.len()])
+    }
+}
+
+impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
+where V: AsRef<[T]> + ?Sized
+{
+    fn from(values: &'a V) -> Self {
+        let values = values.as_ref();
+        let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
+        Self {
+            values,
+            min_value,
+            max_value,
+        }
+    }
+}

columnar/src/columnar/column_type.rs

@@ -1,12 +1,14 @@
 use std::fmt::Debug;
 use std::net::Ipv6Addr;
 
+use serde::{Deserialize, Serialize};
+
 use crate::value::NumericalType;
 use crate::InvalidData;
 
 /// The column type represents the column type.
 /// Any changes need to be propagated to `COLUMN_TYPES`.
-#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy, Ord, PartialOrd)]
+#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy, Ord, PartialOrd, Serialize, Deserialize)]
 #[repr(u8)]
 pub enum ColumnType {
     I64 = 0u8,
@@ -143,7 +145,7 @@ mod tests {
             }
         }
         for code in COLUMN_TYPES.len() as u8..=u8::MAX {
-            assert!(ColumnType::try_from_code(code as u8).is_err());
+            assert!(ColumnType::try_from_code(code).is_err());
         }
     }
 

columnar/src/columnar/merge/merge_dict_column.rs

@@ -96,7 +96,7 @@ fn compute_term_bitset(column: &BytesColumn, row_bitset: &ReadOnlyBitSet) -> Bit
     let num_terms = column.dictionary().num_terms();
     let mut term_bitset = BitSet::with_max_value(num_terms as u32);
     for row_id in row_bitset.iter() {
-        for term_ord in column.term_ord_column.values(row_id) {
+        for term_ord in column.term_ord_column.values_for_doc(row_id) {
             term_bitset.insert(term_ord as u32);
         }
     }
@@ -191,7 +191,7 @@ struct TermOrdinalMapping {
 impl TermOrdinalMapping {
     fn add_segment(&mut self, max_term_ord: usize) {
         self.per_segment_new_term_ordinals
-            .push(vec![TermOrdinal::default(); max_term_ord as usize]);
+            .push(vec![TermOrdinal::default(); max_term_ord]);
     }
 
     fn register_from_to(&mut self, segment_ord: usize, from_ord: TermOrdinal, to_ord: TermOrdinal) {

columnar/src/columnar/merge/mod.rs

@@ -2,8 +2,6 @@ mod merge_dict_column;
 mod merge_mapping;
 mod term_merger;
 
-// mod sorted_doc_id_column;
-
 use std::collections::{BTreeMap, HashMap, HashSet};
 use std::io;
 use std::net::Ipv6Addr;
@@ -54,14 +52,34 @@ impl From<ColumnType> for ColumnTypeCategory {
     }
 }
 
+/// Merge several columnar table together.
+///
+/// If several columns with the same name are conflicting with the numerical types in the
+/// input columnars, the first type compatible out of i64, u64, f64 in that order will be used.
+///
+/// `require_columns` makes it possible to ensure that some columns will be present in the
+/// resulting columnar. When a required column is a numerical column type, one of two things can
+/// happen:
+/// - If the required column type is compatible with all of the input columnar, the resulsting
+///   merged
+/// columnar will simply coerce the input column and use the required column type.
+/// - If the required column type is incompatible with one of the input columnar, the merged
+/// will fail with an InvalidData error.
+///
+/// `merge_row_order` makes it possible to remove or reorder row in the resulting
+/// `Columnar` table.
+///
+/// Reminder: a string and a numerical column may bare the same column name. This is not
+/// considered a conflict.
 pub fn merge_columnar(
     columnar_readers: &[&ColumnarReader],
+    required_columns: &[(String, ColumnType)],
     merge_row_order: MergeRowOrder,
     output: &mut impl io::Write,
 ) -> io::Result<()> {
     let mut serializer = ColumnarSerializer::new(output);
 
-    let columns_to_merge = group_columns_for_merge(columnar_readers)?;
+    let columns_to_merge = group_columns_for_merge(columnar_readers, required_columns)?;
     for ((column_name, column_type), columns) in columns_to_merge {
         let mut column_serializer =
             serializer.serialize_column(column_name.as_bytes(), column_type);
@@ -174,98 +192,183 @@ fn merge_column(
     Ok(())
 }
 
+struct GroupedColumns {
+    required_column_type: Option<ColumnType>,
+    columns: Vec<Option<DynamicColumn>>,
+    column_category: ColumnTypeCategory,
+}
+
+impl GroupedColumns {
+    fn for_category(column_category: ColumnTypeCategory, num_columnars: usize) -> Self {
+        GroupedColumns {
+            required_column_type: None,
+            columns: vec![None; num_columnars],
+            column_category,
+        }
+    }
+
+    /// Set the dynamic column for a given columnar.
+    fn set_column(&mut self, columnar_id: usize, column: DynamicColumn) {
+        self.columns[columnar_id] = Some(column);
+    }
+
+    /// Force the existence of a column, as well as its type.
+    fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
+        if let Some(existing_required_type) = self.required_column_type {
+            if existing_required_type == required_type {
+                // This was just a duplicate in the `required_columns`.
+                // Nothing to do.
+                return Ok(());
+            } else {
+                return Err(io::Error::new(
+                    io::ErrorKind::InvalidInput,
+                    "Required column conflicts with another required column of the same type \
+                     category.",
+                ));
+            }
+        }
+        self.required_column_type = Some(required_type);
+        Ok(())
+    }
+
+    /// Returns the column type after merge.
+    ///
+    /// This method does not check if the column types can actually be coerced to
+    /// this type.
+    fn column_type_after_merge(&self) -> ColumnType {
+        if let Some(required_type) = self.required_column_type {
+            return required_type;
+        }
+        let column_type: HashSet<ColumnType> = self
+            .columns
+            .iter()
+            .flatten()
+            .map(|column| column.column_type())
+            .collect();
+        if column_type.len() == 1 {
+            return column_type.into_iter().next().unwrap();
+        }
+        // At the moment, only the numerical categorical column type has more than one possible
+        // column type.
+        assert_eq!(self.column_category, ColumnTypeCategory::Numerical);
+        merged_numerical_columns_type(self.columns.iter().flatten()).into()
+    }
+}
+
+/// Returns the type of the merged numerical column.
+///
+/// This function picks the first numerical type out of i64, u64, f64 (order matters
+/// here), that is compatible with all the `columns`.
+///
+/// # Panics
+/// Panics if one of the column is not numerical.
+fn merged_numerical_columns_type<'a>(
+    columns: impl Iterator<Item = &'a DynamicColumn>,
+) -> NumericalType {
+    let mut compatible_numerical_types = CompatibleNumericalTypes::default();
+    for column in columns {
+        let (min_value, max_value) =
+            min_max_if_numerical(column).expect("All columns re required to be numerical");
+        compatible_numerical_types.accept_value(min_value);
+        compatible_numerical_types.accept_value(max_value);
+    }
+    compatible_numerical_types.to_numerical_type()
+}
+
 #[allow(clippy::type_complexity)]
 fn group_columns_for_merge(
     columnar_readers: &[&ColumnarReader],
+    required_columns: &[(String, ColumnType)],
 ) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
     // Each column name may have multiple types of column associated.
     // For merging we are interested in the same column type category since they can be merged.
-    let mut columns_grouped: HashMap<(String, ColumnTypeCategory), Vec<Option<DynamicColumn>>> =
-        HashMap::new();
+    let mut columns_grouped: HashMap<(String, ColumnTypeCategory), GroupedColumns> = HashMap::new();
 
-    let num_columnars = columnar_readers.len();
+    for &(ref column_name, column_type) in required_columns {
+        columns_grouped
+            .entry((column_name.clone(), column_type.into()))
+            .or_insert_with(|| {
+                GroupedColumns::for_category(column_type.into(), columnar_readers.len())
+            })
+            .require_type(column_type)?;
+    }
 
     for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
         let column_name_and_handle = columnar_reader.list_columns()?;
         for (column_name, handle) in column_name_and_handle {
-            let column_type_category: ColumnTypeCategory = handle.column_type().into();
-            let columns = columns_grouped
-                .entry((column_name, column_type_category))
-                .or_insert_with(|| vec![None; num_columnars]);
+            let column_category: ColumnTypeCategory = handle.column_type().into();
             let column = handle.open()?;
-            columns[columnar_id] = Some(column);
+            columns_grouped
+                .entry((column_name, column_category))
+                .or_insert_with(|| {
+                    GroupedColumns::for_category(column_category, columnar_readers.len())
+                })
+                .set_column(columnar_id, column);
         }
     }
 
     let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        BTreeMap::default();
+        Default::default();
 
-    for ((column_name, col_category), mut columns) in columns_grouped {
-        if col_category == ColumnTypeCategory::Numerical {
-            coerce_numerical_columns_to_same_type(&mut columns);
-        }
-        let column_type = columns
-            .iter()
-            .flatten()
-            .map(|col| col.column_type())
-            .next()
-            .unwrap();
-        merge_columns.insert((column_name, column_type), columns);
+    for ((column_name, _), mut grouped_columns) in columns_grouped {
+        let column_type = grouped_columns.column_type_after_merge();
+        coerce_columns(column_type, &mut grouped_columns.columns)?;
+        merge_columns.insert((column_name, column_type), grouped_columns.columns);
     }
 
     Ok(merge_columns)
 }
 
-/// Coerce a set of numerical columns to the same type.
-///
-/// If all columns are already from the same type, keep this type
-/// (even if they could all be coerced to i64).
-fn coerce_numerical_columns_to_same_type(columns: &mut [Option<DynamicColumn>]) {
-    let mut column_types: HashSet<NumericalType> = HashSet::default();
-    let mut compatible_numerical_types = CompatibleNumericalTypes::default();
-    for column in columns.iter().flatten() {
-        let min_value: NumericalValue;
-        let max_value: NumericalValue;
-        match column {
-            DynamicColumn::I64(column) => {
-                min_value = column.min_value().into();
-                max_value = column.max_value().into();
-            }
-            DynamicColumn::U64(column) => {
-                min_value = column.min_value().into();
-                max_value = column.min_value().into();
-            }
-            DynamicColumn::F64(column) => {
-                min_value = column.min_value().into();
-                max_value = column.min_value().into();
-            }
-            DynamicColumn::Bool(_)
-            | DynamicColumn::IpAddr(_)
-            | DynamicColumn::DateTime(_)
-            | DynamicColumn::Bytes(_)
-            | DynamicColumn::Str(_) => {
-                panic!("We expected only numerical columns.");
-            }
-        }
-        column_types.insert(column.column_type().numerical_type().unwrap());
-        compatible_numerical_types.accept_value(min_value);
-        compatible_numerical_types.accept_value(max_value);
-    }
-    if column_types.len() <= 1 {
-        // No need to do anything. The columns are already all from the same type.
-        // This is necessary to let use force a given type.
-
-        // TODO This works in a world where we do not allow a change of schema,
-        // but in the future, we will have to pass some kind of schema to enforce
-        // the logic.
-        return;
-    }
-    let coerce_type = compatible_numerical_types.to_numerical_type();
+fn coerce_columns(
+    column_type: ColumnType,
+    columns: &mut [Option<DynamicColumn>],
+) -> io::Result<()> {
     for column_opt in columns.iter_mut() {
         if let Some(column) = column_opt.take() {
-            *column_opt = column.coerce_numerical(coerce_type);
+            *column_opt = Some(coerce_column(column_type, column)?);
         }
     }
+    Ok(())
+}
+
+fn coerce_column(column_type: ColumnType, column: DynamicColumn) -> io::Result<DynamicColumn> {
+    if let Some(numerical_type) = column_type.numerical_type() {
+        column
+            .coerce_numerical(numerical_type)
+            .ok_or_else(|| io::Error::new(io::ErrorKind::InvalidInput, ""))
+    } else {
+        if column.column_type() != column_type {
+            return Err(io::Error::new(
+                io::ErrorKind::InvalidInput,
+                format!(
+                    "Cannot coerce column of type `{:?}` to `{column_type:?}`",
+                    column.column_type()
+                ),
+            ));
+        }
+        Ok(column)
+    }
+}
+
+/// Returns the (min, max) of a column provided it is numerical (i64, u64. f64).
+///
+/// The min and the max are simply the numerical value as defined by `ColumnValue::min_value()`,
+/// and `ColumnValue::max_value()`.
+///
+/// It is important to note that these values are only guaranteed to be lower/upper bound
+/// (as opposed to min/max value).
+/// If a column is empty, the min and max values are currently set to 0.
+fn min_max_if_numerical(column: &DynamicColumn) -> Option<(NumericalValue, NumericalValue)> {
+    match column {
+        DynamicColumn::I64(column) => Some((column.min_value().into(), column.max_value().into())),
+        DynamicColumn::U64(column) => Some((column.min_value().into(), column.min_value().into())),
+        DynamicColumn::F64(column) => Some((column.min_value().into(), column.min_value().into())),
+        DynamicColumn::Bool(_)
+        | DynamicColumn::IpAddr(_)
+        | DynamicColumn::DateTime(_)
+        | DynamicColumn::Bytes(_)
+        | DynamicColumn::Str(_) => None,
+    }
 }
 
 #[cfg(test)]

columnar/src/columnar/merge/sorted_doc_id_column.rs

@@ -1,107 +0,0 @@
-use std::sync::Arc;
-
-use fastfield_codecs::Column;
-use itertools::Itertools;
-
-use crate::indexer::doc_id_mapping::SegmentDocIdMapping;
-use crate::SegmentReader;
-
-pub(crate) struct RemappedDocIdColumn<'a> {
-    doc_id_mapping: &'a SegmentDocIdMapping,
-    fast_field_readers: Vec<Arc<dyn Column<u64>>>,
-    min_value: u64,
-    max_value: u64,
-    num_vals: u32,
-}
-
-fn compute_min_max_val(
-    u64_reader: &dyn Column<u64>,
-    segment_reader: &SegmentReader,
-) -> Option<(u64, u64)> {
-    if segment_reader.max_doc() == 0 {
-        return None;
-    }
-
-    if segment_reader.alive_bitset().is_none() {
-        // no deleted documents,
-        // we can use the previous min_val, max_val.
-        return Some((u64_reader.min_value(), u64_reader.max_value()));
-    }
-    // some deleted documents,
-    // we need to recompute the max / min
-    segment_reader
-        .doc_ids_alive()
-        .map(|doc_id| u64_reader.get_val(doc_id))
-        .minmax()
-        .into_option()
-}
-
-impl<'a> RemappedDocIdColumn<'a> {
-    pub(crate) fn new(
-        readers: &'a [SegmentReader],
-        doc_id_mapping: &'a SegmentDocIdMapping,
-        field: &str,
-    ) -> Self {
-        let (min_value, max_value) = readers
-            .iter()
-            .filter_map(|reader| {
-                let u64_reader: Arc<dyn Column<u64>> =
-                    reader.fast_fields().typed_fast_field_reader(field).expect(
-                        "Failed to find a reader for single fast field. This is a tantivy bug and \
-                         it should never happen.",
-                    );
-                compute_min_max_val(&*u64_reader, reader)
-            })
-            .reduce(|a, b| (a.0.min(b.0), a.1.max(b.1)))
-            .expect("Unexpected error, empty readers in IndexMerger");
-
-        let fast_field_readers = readers
-            .iter()
-            .map(|reader| {
-                let u64_reader: Arc<dyn Column<u64>> =
-                    reader.fast_fields().typed_fast_field_reader(field).expect(
-                        "Failed to find a reader for single fast field. This is a tantivy bug and \
-                         it should never happen.",
-                    );
-                u64_reader
-            })
-            .collect::<Vec<_>>();
-
-        RemappedDocIdColumn {
-            doc_id_mapping,
-            fast_field_readers,
-            min_value,
-            max_value,
-            num_vals: doc_id_mapping.len() as u32,
-        }
-    }
-}
-
-impl<'a> Column for RemappedDocIdColumn<'a> {
-    fn get_val(&self, _doc: u32) -> u64 {
-        unimplemented!()
-    }
-
-    fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
-        Box::new(
-            self.doc_id_mapping
-                .iter_old_doc_addrs()
-                .map(|old_doc_addr| {
-                    let fast_field_reader =
-                        &self.fast_field_readers[old_doc_addr.segment_ord as usize];
-                    fast_field_reader.get_val(old_doc_addr.doc_id)
-                }),
-        )
-    }
-    fn min_value(&self) -> u64 {
-        self.min_value
-    }
-
-    fn max_value(&self) -> u64 {
-        self.max_value
-    }
-
-    fn num_vals(&self) -> u32 {
-        self.num_vals
-    }
-}

columnar/src/columnar/merge/tests.rs

@@ -24,7 +24,7 @@ fn test_column_coercion_to_u64() {
     // u64 type
     let columnar2 = make_columnar("numbers", &[u64::MAX]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 1);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
 }
@@ -34,7 +34,7 @@ fn test_column_no_coercion_if_all_the_same() {
     let columnar1 = make_columnar("numbers", &[1u64]);
     let columnar2 = make_columnar("numbers", &[2u64]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 1);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
 }
@@ -44,17 +44,74 @@ fn test_column_coercion_to_i64() {
     let columnar1 = make_columnar("numbers", &[-1i64]);
     let columnar2 = make_columnar("numbers", &[2u64]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 1);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
 }
 
+#[test]
+fn test_impossible_coercion_returns_an_error() {
+    let columnar1 = make_columnar("numbers", &[u64::MAX]);
+    let group_error =
+        group_columns_for_merge(&[&columnar1], &[("numbers".to_string(), ColumnType::I64)])
+            .map(|_| ())
+            .unwrap_err();
+    assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
+}
+
+#[test]
+fn test_group_columns_with_required_column() {
+    let columnar1 = make_columnar("numbers", &[1i64]);
+    let columnar2 = make_columnar("numbers", &[2u64]);
+    let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
+        group_columns_for_merge(
+            &[&columnar1, &columnar2],
+            &[("numbers".to_string(), ColumnType::U64)],
+        )
+        .unwrap();
+    assert_eq!(column_map.len(), 1);
+    assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
+}
+
+#[test]
+fn test_group_columns_required_column_with_no_existing_columns() {
+    let columnar1 = make_columnar("numbers", &[2u64]);
+    let columnar2 = make_columnar("numbers", &[2u64]);
+    let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
+        group_columns_for_merge(
+            &[&columnar1, &columnar2],
+            &[("required_col".to_string(), ColumnType::Str)],
+        )
+        .unwrap();
+    assert_eq!(column_map.len(), 2);
+    let columns = column_map
+        .get(&("required_col".to_string(), ColumnType::Str))
+        .unwrap();
+    assert_eq!(columns.len(), 2);
+    assert!(columns[0].is_none());
+    assert!(columns[1].is_none());
+}
+
+#[test]
+fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_rule() {
+    let columnar1 = make_columnar("numbers", &[2i64]);
+    let columnar2 = make_columnar("numbers", &[2i64]);
+    let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
+        group_columns_for_merge(
+            &[&columnar1, &columnar2],
+            &[("numbers".to_string(), ColumnType::U64)],
+        )
+        .unwrap();
+    assert_eq!(column_map.len(), 1);
+    assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
+}
+
 #[test]
 fn test_missing_column() {
     let columnar1 = make_columnar("numbers", &[-1i64]);
     let columnar2 = make_columnar("numbers2", &[2u64]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 2);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
     {
@@ -101,7 +158,7 @@ fn make_byte_columnar_multiple_columns(columns: &[(&str, &[&[&[u8]]])]) -> Colum
     for (column_name, column_values) in columns {
         for (row_id, vals) in column_values.iter().enumerate() {
             for val in vals.iter() {
-                dataframe_writer.record_bytes(row_id as u32, column_name, *val);
+                dataframe_writer.record_bytes(row_id as u32, column_name, val);
             }
         }
     }
@@ -122,7 +179,7 @@ fn make_text_columnar_multiple_columns(columns: &[(&str, &[&[&str]])]) -> Column
     for (column_name, column_values) in columns {
         for (row_id, vals) in column_values.iter().enumerate() {
             for val in vals.iter() {
-                dataframe_writer.record_str(row_id as u32, column_name, *val);
+                dataframe_writer.record_str(row_id as u32, column_name, val);
             }
         }
     }
@@ -151,6 +208,7 @@ fn test_merge_columnar_numbers() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
+        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -176,6 +234,7 @@ fn test_merge_columnar_texts() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
+        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -220,6 +279,7 @@ fn test_merge_columnar_byte() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
+        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )

columnar/src/columnar/merge_index.rs

@@ -1 +0,0 @@
-

columnar/src/columnar/mod.rs

@@ -1,7 +1,6 @@
 mod column_type;
 mod format_version;
 mod merge;
-mod merge_index;
 mod reader;
 mod writer;
 

columnar/src/columnar/reader/mod.rs

@@ -21,6 +21,32 @@ pub struct ColumnarReader {
     num_rows: RowId,
 }
 
+/// Functions by both the async/sync code listing columns.
+/// It takes a stream from the column sstable and return the list of
+/// `DynamicColumn` available in it.
+fn read_all_columns_in_stream(
+    mut stream: sstable::Streamer<'_, RangeSSTable>,
+    column_data: &FileSlice,
+) -> io::Result<Vec<DynamicColumnHandle>> {
+    let mut results = Vec::new();
+    while stream.advance() {
+        let key_bytes: &[u8] = stream.key();
+        let Some(column_code) = key_bytes.last().copied() else {
+            return Err(io_invalid_data("Empty column name.".to_string()));
+        };
+        let column_type = ColumnType::try_from_code(column_code)
+            .map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
+        let range = stream.value();
+        let file_slice = column_data.slice(range.start as usize..range.end as usize);
+        let dynamic_column_handle = DynamicColumnHandle {
+            file_slice,
+            column_type,
+        };
+        results.push(dynamic_column_handle);
+    }
+    Ok(results)
+}
+
 impl ColumnarReader {
     /// Opens a new Columnar file.
     pub fn open<F>(file_slice: F) -> io::Result<ColumnarReader>
@@ -76,11 +102,7 @@ impl ColumnarReader {
         Ok(results)
     }
 
-    /// Get all columns for the given column name.
-    ///
-    /// There can be more than one column associated to a given column name, provided they have
-    /// different types.
-    pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
+    fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {
         // Each column is a associated to a given `column_key`,
         // that starts by `column_name\0column_header`.
         //
@@ -89,36 +111,35 @@ impl ColumnarReader {
         //
         // This is in turn equivalent to searching for the range
         // `[column_name,\0`..column_name\1)`.
-
-        // TODO can we get some more generic `prefix(..)` logic in the dictioanry.
+        // TODO can we get some more generic `prefix(..)` logic in the dictionary.
         let mut start_key = column_name.to_string();
         start_key.push('\0');
         let mut end_key = column_name.to_string();
         end_key.push(1u8 as char);
-        let mut stream = self
-            .column_dictionary
+        self.column_dictionary
             .range()
             .ge(start_key.as_bytes())
             .lt(end_key.as_bytes())
-            .into_stream()?;
-        let mut results = Vec::new();
-        while stream.advance() {
-            let key_bytes: &[u8] = stream.key();
-            assert!(key_bytes.starts_with(start_key.as_bytes()));
-            let column_code: u8 = key_bytes.last().cloned().unwrap();
-            let column_type = ColumnType::try_from_code(column_code)
-                .map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
-            let range = stream.value().clone();
-            let file_slice = self
-                .column_data
-                .slice(range.start as usize..range.end as usize);
-            let dynamic_column_handle = DynamicColumnHandle {
-                file_slice,
-                column_type,
-            };
-            results.push(dynamic_column_handle);
-        }
-        Ok(results)
+    }
+
+    pub async fn read_columns_async(
+        &self,
+        column_name: &str,
+    ) -> io::Result<Vec<DynamicColumnHandle>> {
+        let stream = self
+            .stream_for_column_range(column_name)
+            .into_stream_async()
+            .await?;
+        read_all_columns_in_stream(stream, &self.column_data)
+    }
+
+    /// Get all columns for the given column name.
+    ///
+    /// There can be more than one column associated to a given column name, provided they have
+    /// different types.
+    pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
+        let stream = self.stream_for_column_range(column_name).into_stream()?;
+        read_all_columns_in_stream(stream, &self.column_data)
     }
 
     /// Return the number of columns in the columnar.

columnar/src/columnar/writer/column_operation.rs

@@ -310,7 +310,7 @@ mod tests {
         buffer.extend_from_slice(b"234234");
         let mut bytes = &buffer[..];
         let serdeser_symbol = ColumnOperation::deserialize(&mut bytes).unwrap();
-        assert_eq!(bytes.len() + buf.as_ref().len() as usize, buffer.len());
+        assert_eq!(bytes.len() + buf.as_ref().len(), buffer.len());
         assert_eq!(column_op, serdeser_symbol);
     }
 
@@ -341,7 +341,7 @@ mod tests {
     fn test_column_operation_unordered_aux(val: u32, expected_len: usize) {
         let column_op = ColumnOperation::Value(UnorderedId(val));
         let minibuf = column_op.serialize();
-        assert_eq!(minibuf.as_ref().len() as usize, expected_len);
+        assert_eq!({ minibuf.as_ref().len() }, expected_len);
         let mut buf = minibuf.as_ref().to_vec();
         buf.extend_from_slice(&[2, 2, 2, 2, 2, 2]);
         let mut cursor = &buf[..];

columnar/src/columnar/writer/mod.rs

@@ -761,7 +761,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(3), Cardinality::Full);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, None, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 6);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -790,7 +790,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(3), Cardinality::Optional);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, None, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 4);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
@@ -813,7 +813,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(2), Cardinality::Optional);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, None, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 2);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -832,7 +832,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(1), Cardinality::Multivalued);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, None, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 3);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));

columnar/src/columnar/writer/value_index.rs

@@ -150,11 +150,7 @@ mod tests {
         multivalued_value_index_builder.record_row(2u32);
         multivalued_value_index_builder.record_value();
         assert_eq!(
-            multivalued_value_index_builder
-                .finish(4u32)
-                .iter()
-                .copied()
-                .collect::<Vec<u32>>(),
+            multivalued_value_index_builder.finish(4u32).to_vec(),
             vec![0, 0, 2, 3, 3]
         );
         multivalued_value_index_builder.reset();
@@ -162,11 +158,7 @@ mod tests {
         multivalued_value_index_builder.record_value();
         multivalued_value_index_builder.record_value();
         assert_eq!(
-            multivalued_value_index_builder
-                .finish(4u32)
-                .iter()
-                .copied()
-                .collect::<Vec<u32>>(),
+            multivalued_value_index_builder.finish(4u32).to_vec(),
             vec![0, 0, 0, 2, 2]
         );
     }

columnar/src/dynamic_column.rs

@@ -206,10 +206,9 @@ impl DynamicColumnHandle {
         self.open_internal(column_bytes)
     }
 
-    // TODO rename load_async
-    pub async fn open_async(&self) -> io::Result<DynamicColumn> {
-        let column_bytes: OwnedBytes = self.file_slice.read_bytes_async().await?;
-        self.open_internal(column_bytes)
+    #[doc(hidden)]
+    pub fn file_slice(&self) -> &FileSlice {
+        &self.file_slice
     }
 
     /// Returns the `u64` fast field reader reader associated with `fields` of types

common/src/datetime.rs

@@ -29,7 +29,7 @@ pub enum DatePrecision {
 /// All constructors and conversions are provided as explicit
 /// functions and not by implementing any `From`/`Into` traits
 /// to prevent unintended usage.
-#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord)]
+#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
 pub struct DateTime {
     // Timestamp in microseconds.
     pub(crate) timestamp_micros: i64,

common/src/lib.rs

@@ -109,6 +109,21 @@ pub fn u64_to_f64(val: u64) -> f64 {
     })
 }
 
+/// Replaces a given byte in the `bytes` slice of bytes.
+///
+/// This function assumes that the needle is rarely contained in the bytes string
+/// and offers a fast path if the needle is not present.
+pub fn replace_in_place(needle: u8, replacement: u8, bytes: &mut [u8]) {
+    if !bytes.contains(&needle) {
+        return;
+    }
+    for b in bytes {
+        if *b == needle {
+            *b = replacement;
+        }
+    }
+}
+
 #[cfg(test)]
 pub mod test {
 
@@ -173,4 +188,20 @@ pub mod test {
         assert!(f64_to_u64(-2.0) < f64_to_u64(1.0));
         assert!(f64_to_u64(-2.0) < f64_to_u64(-1.5));
     }
+
+    #[test]
+    fn test_replace_in_place() {
+        let test_aux = |before_replacement: &[u8], expected: &[u8]| {
+            let mut bytes: Vec<u8> = before_replacement.to_vec();
+            super::replace_in_place(b'b', b'c', &mut bytes);
+            assert_eq!(&bytes[..], expected);
+        };
+        test_aux(b"", b"");
+        test_aux(b"b", b"c");
+        test_aux(b"baaa", b"caaa");
+        test_aux(b"aaab", b"aaac");
+        test_aux(b"aaabaa", b"aaacaa");
+        test_aux(b"aaaaaa", b"aaaaaa");
+        test_aux(b"bbbb", b"cccc");
+    }
 }

examples/aggregation.rs

@@ -1,129 +1,319 @@
 // # Aggregation example
 //
 // This example shows how you can use built-in aggregations.
-// We will use range buckets and compute the average in each bucket.
-//
+// We will use nested aggregations with buckets and metrics:
+// - Range buckets and compute the average in each bucket.
+// - Term aggregation and compute the min price in each bucket
+// ---
 
-use serde_json::Value;
+use serde_json::{Deserializer, Value};
 use tantivy::aggregation::agg_req::{
     Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
     RangeAggregation,
 };
 use tantivy::aggregation::agg_result::AggregationResults;
+use tantivy::aggregation::bucket::RangeAggregationRange;
 use tantivy::aggregation::metric::AverageAggregation;
 use tantivy::aggregation::AggregationCollector;
-use tantivy::query::TermQuery;
-use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing};
-use tantivy::{doc, Index, Term};
+use tantivy::query::AllQuery;
+use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing, FAST};
+use tantivy::Index;
 
 fn main() -> tantivy::Result<()> {
+    // # Create Schema
+    //
+    // Lets create a schema for a footwear shop, with 4 fields: name, category, stock and price.
+    // category, stock and price will be fast fields as that's the requirement
+    // for aggregation queries.
+    //
+
     let mut schema_builder = Schema::builder();
+    // In preparation of the `TermsAggregation`, the category field is configured with:
+    // - `set_fast`
+    // - `raw` tokenizer
+    //
+    // The tokenizer is set to "raw", because the fast field uses the same dictionary as the
+    // inverted index. (This behaviour will change in tantivy 0.20, where the fast field will
+    // always be raw tokenized independent from the regular tokenizing)
+    //
     let text_fieldtype = schema::TextOptions::default()
         .set_indexing_options(
-            TextFieldIndexing::default().set_index_option(IndexRecordOption::WithFreqs),
+            TextFieldIndexing::default()
+                .set_index_option(IndexRecordOption::WithFreqs)
+                .set_tokenizer("raw"),
         )
+        .set_fast()
         .set_stored();
-    let text_field = schema_builder.add_text_field("text", text_fieldtype);
-    let score_fieldtype = crate::schema::NumericOptions::default().set_fast();
-    let highscore_field = schema_builder.add_f64_field("highscore", score_fieldtype.clone());
-    let price_field = schema_builder.add_f64_field("price", score_fieldtype);
+    schema_builder.add_text_field("category", text_fieldtype);
+    schema_builder.add_f64_field("stock", FAST);
+    schema_builder.add_f64_field("price", FAST);
 
     let schema = schema_builder.build();
 
     // # Indexing documents
     //
     // Lets index a bunch of documents for this example.
-    let index = Index::create_in_ram(schema);
+    let index = Index::create_in_ram(schema.clone());
+
+    let data = r#"{
+        "name": "Almond Toe Court Shoes, Patent Black",
+        "category": "Womens Footwear",
+        "price": 99.00,
+        "stock": 5
+    }
+    {
+        "name": "Suede Shoes, Blue",
+        "category": "Womens Footwear",
+        "price": 42.00,
+        "stock": 4
+    }
+    {
+        "name": "Leather Driver Saddle Loafers, Tan",
+        "category": "Mens Footwear",
+        "price": 34.00,
+        "stock": 12
+    }
+    {
+        "name": "Flip Flops, Red",
+        "category": "Mens Footwear",
+        "price": 19.00,
+        "stock": 6
+    }
+    {
+        "name": "Flip Flops, Blue",
+        "category": "Mens Footwear",
+        "price": 19.00,
+        "stock": 0
+    }
+    {
+        "name": "Gold Button Cardigan, Black",
+        "category": "Womens Casualwear",
+        "price": 167.00,
+        "stock": 6
+    }
+    {
+        "name": "Cotton Shorts, Medium Red",
+        "category": "Womens Casualwear",
+        "price": 30.00,
+        "stock": 5
+    }
+    {
+        "name": "Fine Stripe Short SleeveShirt, Grey",
+        "category": "Mens Casualwear",
+        "price": 49.99,
+        "stock": 9
+    }
+    {
+        "name": "Fine Stripe Short SleeveShirt, Green",
+        "category": "Mens Casualwear",
+        "price": 49.99,
+        "offer": 39.99,
+        "stock": 9
+    }
+    {
+        "name": "Sharkskin Waistcoat, Charcoal",
+        "category": "Mens Formalwear",
+        "price": 75.00,
+        "stock": 2
+    }
+    {
+        "name": "Lightweight Patch PocketBlazer, Deer",
+        "category": "Mens Formalwear",
+        "price": 175.50,
+        "stock": 1
+    }
+    {
+        "name": "Bird Print Dress, Black",
+        "category": "Womens Formalwear",
+        "price": 270.00,
+        "stock": 10
+    }
+    {
+        "name": "Mid Twist Cut-Out Dress, Pink",
+        "category": "Womens Formalwear",
+        "price": 540.00,
+        "stock": 5
+    }"#;
+
+    let stream = Deserializer::from_str(data).into_iter::<Value>();
 
     let mut index_writer = index.writer(50_000_000)?;
-    // writing the segment
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 1f64,
-        price_field => 0f64,
-    ))?;
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 3f64,
-        price_field => 1f64,
-    ))?;
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 5f64,
-        price_field => 1f64,
-    ))?;
-    index_writer.add_document(doc!(
-        text_field => "nohit",
-        highscore_field => 6f64,
-        price_field => 2f64,
-    ))?;
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 7f64,
-        price_field => 2f64,
-    ))?;
-    index_writer.commit()?;
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 11f64,
-        price_field => 10f64,
-    ))?;
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 14f64,
-        price_field => 15f64,
-    ))?;
-
-    index_writer.add_document(doc!(
-        text_field => "cool",
-        highscore_field => 15f64,
-        price_field => 20f64,
-    ))?;
+    let mut num_indexed = 0;
+    for value in stream {
+        let doc = schema.parse_document(&serde_json::to_string(&value.unwrap())?)?;
+        index_writer.add_document(doc)?;
+        num_indexed += 1;
+        if num_indexed > 4 {
+            // Writing the first segment
+            index_writer.commit()?;
+        }
+    }
 
+    // Writing the second segment
     index_writer.commit()?;
 
+    // We have two segments now. The `AggregationCollector` will run the aggregation on each
+    // segment and then merge the results into an `IntermediateAggregationResult`.
+
     let reader = index.reader()?;
-    let text_field = reader.searcher().schema().get_field("text").unwrap();
+    let searcher = reader.searcher();
+    // ---
+    // # Aggregation Query
+    //
+    //
+    // We can construct the query by building the request structure or by deserializing from JSON.
+    // The JSON API is more stable and therefore recommended.
+    //
+    // ## Request 1
 
-    let term_query = TermQuery::new(
-        Term::from_field_text(text_field, "cool"),
-        IndexRecordOption::Basic,
-    );
+    let agg_req_str = r#"
+    {
+      "group_by_stock": {
+        "aggs": {
+          "average_price": { "avg": { "field": "price" } }
+        },
+        "range": {
+          "field": "stock",
+          "ranges": [
+            { "key": "few", "to": 1.0 },
+            { "key": "some", "from": 1.0, "to": 10.0 },
+            { "key": "many", "from": 10.0 }
+          ]
+        }
+      }
+    } "#;
 
-    let sub_agg_req_1: Aggregations = vec![(
-        "average_price".to_string(),
-        Aggregation::Metric(MetricAggregation::Average(
-            AverageAggregation::from_field_name("price".to_string()),
-        )),
-    )]
-    .into_iter()
-    .collect();
+    // In this Aggregation we want to get the average price for different groups, depending on how
+    // many items are in stock. We define custom ranges `few`, `some`, `many` via the
+    // range aggregation.
+    // For every bucket we want the average price, so we create a nested metric aggregation on the
+    // range bucket aggregation. Only buckets support nested aggregations.
+    // ### Request JSON API
+    //
 
-    let agg_req_1: Aggregations = vec![(
-        "score_ranges".to_string(),
+    let agg_req: Aggregations = serde_json::from_str(agg_req_str)?;
+    let collector = AggregationCollector::from_aggs(agg_req, None);
+
+    let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
+    let res2: Value = serde_json::to_value(agg_res)?;
+
+    // ### Request Rust API
+    //
+    // This is exactly the same request as above, but via the rust structures.
+    //
+
+    let agg_req: Aggregations = vec![(
+        "group_by_stock".to_string(),
         Aggregation::Bucket(BucketAggregation {
             bucket_agg: BucketAggregationType::Range(RangeAggregation {
-                field: "highscore".to_string(),
+                field: "stock".to_string(),
                 ranges: vec![
-                    (-1f64..9f64).into(),
-                    (9f64..14f64).into(),
-                    (14f64..20f64).into(),
+                    RangeAggregationRange {
+                        key: Some("few".into()),
+                        from: None,
+                        to: Some(1f64),
+                    },
+                    RangeAggregationRange {
+                        key: Some("some".into()),
+                        from: Some(1f64),
+                        to: Some(10f64),
+                    },
+                    RangeAggregationRange {
+                        key: Some("many".into()),
+                        from: Some(10f64),
+                        to: None,
+                    },
                 ],
                 ..Default::default()
             }),
-            sub_aggregation: sub_agg_req_1,
+            sub_aggregation: vec![(
+                "average_price".to_string(),
+                Aggregation::Metric(MetricAggregation::Average(
+                    AverageAggregation::from_field_name("price".to_string()),
+                )),
+            )]
+            .into_iter()
+            .collect(),
         }),
     )]
     .into_iter()
     .collect();
 
-    let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
+    let collector = AggregationCollector::from_aggs(agg_req, None);
+    // We use the `AllQuery` which will pass all documents to the AggregationCollector.
+    let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
 
-    let searcher = reader.searcher();
-    let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();
+    let res1: Value = serde_json::to_value(agg_res)?;
 
+    // ### Aggregation Result
+    //
+    // The resulting structure deserializes in the same JSON format as elastic search.
+    //
+    let expected_res = r#"
+    {
+        "group_by_stock":{
+            "buckets":[
+                {"average_price":{"value":19.0},"doc_count":1,"key":"few","to":1.0},
+                {"average_price":{"value":124.748},"doc_count":10,"from":1.0,"key":"some","to":10.0},
+                {"average_price":{"value":152.0},"doc_count":2,"from":10.0,"key":"many"}
+            ]
+        }
+    }
+    "#;
+    let expected_json: Value = serde_json::from_str(expected_res)?;
+    assert_eq!(expected_json, res1);
+    assert_eq!(expected_json, res2);
+
+    // ### Request 2
+    //
+    // Now we are interested in the minimum price per category, so we create a bucket per
+    // category via `TermsAggregation`. We are interested in the highest minimum prices, and set the
+    // order of the buckets `"order": { "min_price": "desc" }` to be sorted by the the metric of
+    // the sub aggregation. (awesome)
+    //
+    let agg_req_str = r#"
+    {
+      "min_price_per_category": {
+        "aggs": {
+          "min_price": { "min": { "field": "price" } }
+        },
+        "terms": {
+          "field": "category",
+          "min_doc_count": 1,
+          "order": { "min_price": "desc" }
+        }
+      }
+    } "#;
+
+    let agg_req: Aggregations = serde_json::from_str(agg_req_str)?;
+
+    let collector = AggregationCollector::from_aggs(agg_req, None);
+
+    let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
     let res: Value = serde_json::to_value(agg_res)?;
-    println!("{}", serde_json::to_string_pretty(&res)?);
+
+    // Minimum price per category, sorted by minimum price descending
+    //
+    // As you can see, the starting prices for `Formalwear` are higher than `Casualwear`.
+    //
+    let expected_res = r#"
+    {
+      "min_price_per_category": {
+        "buckets": [
+          { "doc_count": 2, "key": "Womens Formalwear", "min_price": { "value": 270.0 } },
+          { "doc_count": 2, "key": "Mens Formalwear", "min_price": { "value": 75.0 } },
+          { "doc_count": 2, "key": "Mens Casualwear", "min_price": { "value": 49.99 } },
+          { "doc_count": 2, "key": "Womens Footwear", "min_price": { "value": 42.0 } },
+          { "doc_count": 2, "key": "Womens Casualwear", "min_price": { "value": 30.0 } },
+          { "doc_count": 3, "key": "Mens Footwear", "min_price": { "value": 19.0 } }
+        ],
+        "sum_other_doc_count": 0
+      }
+    }
+    "#;
+    let expected_json: Value = serde_json::from_str(expected_res)?;
+
+    assert_eq!(expected_json, res);
 
     Ok(())
 }

examples/custom_collector.rs

@@ -105,7 +105,7 @@ impl SegmentCollector for StatsSegmentCollector {
     fn collect(&mut self, doc: u32, _score: Score) {
         // Since we know the values are single value, we could call `first_or_default_col` on the
         // column and fetch single values.
-        for value in self.fast_field_reader.values(doc) {
+        for value in self.fast_field_reader.values_for_doc(doc) {
             let value = value as f64;
             self.stats.count += 1;
             self.stats.sum += value;
@@ -171,7 +171,7 @@ fn main() -> tantivy::Result<()> {
     let searcher = reader.searcher();
     let query_parser = QueryParser::for_index(&index, vec![product_name, product_description]);
 
-    // here we want to get a hit on the 'ken' in Frankenstein
+    // here we want to search for `broom` and use `StatsCollector` on the hits.
     let query = query_parser.parse_query("broom")?;
     if let Some(stats) =
         searcher.search(&query, &StatsCollector::with_field("price".to_string()))?

examples/custom_tokenizer.rs

@@ -1,7 +1,7 @@
 // # Defining a tokenizer pipeline
 //
-// In this example, we'll see how to define a tokenizer pipeline
-// by aligning a bunch of `TokenFilter`.
+// In this example, we'll see how to define a tokenizer
+// by creating a custom `NgramTokenizer`.
 use tantivy::collector::TopDocs;
 use tantivy::query::QueryParser;
 use tantivy::schema::*;

examples/date_time_field.rs

@@ -14,6 +14,7 @@ fn main() -> tantivy::Result<()> {
         .set_stored()
         .set_fast()
         .set_precision(tantivy::DatePrecision::Seconds);
+    // Add `occurred_at` date field type
     let occurred_at = schema_builder.add_date_field("occurred_at", opts);
     let event_type = schema_builder.add_text_field("event", STRING | STORED);
     let schema = schema_builder.build();
@@ -22,6 +23,7 @@ fn main() -> tantivy::Result<()> {
     let index = Index::create_in_ram(schema.clone());
 
     let mut index_writer = index.writer(50_000_000)?;
+    // The dates are passed as string in the RFC3339 format
     let doc = schema.parse_document(
         r#"{
         "occurred_at": "2022-06-22T12:53:50.53Z",
@@ -41,14 +43,16 @@ fn main() -> tantivy::Result<()> {
     let reader = index.reader()?;
     let searcher = reader.searcher();
 
-    // # Default fields: event_type
+    // # Search
     let query_parser = QueryParser::for_index(&index, vec![event_type]);
     {
-        let query = query_parser.parse_query("event:comment")?;
+        // 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))?;
         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))?;

examples/faceted_search_with_tweaked_score.rs

@@ -1,3 +1,12 @@
+// # Faceted Search With Tweak Score
+//
+// This example covers the faceted search functionalities of
+// tantivy.
+//
+// We will :
+// - define a text field "name" in our schema
+// - define a facet field "classification" in our schema
+
 use std::collections::HashSet;
 
 use tantivy::collector::TopDocs;
@@ -55,6 +64,7 @@ fn main() -> tantivy::Result<()> {
                 .collect(),
         );
         let top_docs_by_custom_score =
+            // Call TopDocs with a custom tweak score
             TopDocs::with_limit(2).tweak_score(move |segment_reader: &SegmentReader| {
                 let ingredient_reader = segment_reader.facet_reader("ingredient").unwrap();
                 let facet_dict = ingredient_reader.facet_dict();
@@ -65,6 +75,7 @@ fn main() -> tantivy::Result<()> {
                     .collect();
 
                 move |doc: DocId, original_score: Score| {
+                    // Update the original score with a tweaked score
                     let missing_ingredients = ingredient_reader
                         .facet_ords(doc)
                         .filter(|ord| !query_ords.contains(ord))

examples/fuzzy_search.rs

@@ -0,0 +1,167 @@
+// # Basic Example
+//
+// This example covers the basic functionalities of
+// tantivy.
+//
+// We will :
+// - define our schema
+// - create an index in a directory
+// - index a few documents into our index
+// - search for the best document matching a basic query
+// - retrieve the best document's original content.
+// ---
+// Importing tantivy...
+use tantivy::collector::{Count, TopDocs};
+use tantivy::query::FuzzyTermQuery;
+use tantivy::schema::*;
+use tantivy::{doc, Index, ReloadPolicy};
+use tempfile::TempDir;
+
+fn main() -> tantivy::Result<()> {
+    // Let's create a temporary directory for the
+    // sake of this example
+    let index_path = TempDir::new()?;
+
+    // # Defining the schema
+    //
+    // The Tantivy index requires a very strict schema.
+    // The schema declares which fields are in the index,
+    // and for each field, its type and "the way it should
+    // be indexed".
+
+    // First we need to define a schema ...
+    let mut schema_builder = Schema::builder();
+
+    // Our first field is title.
+    // We want full-text search for it, and we also want
+    // to be able to retrieve the document after the search.
+    //
+    // `TEXT | STORED` is some syntactic sugar to describe
+    // that.
+    //
+    // `TEXT` means the field should be tokenized and indexed,
+    // along with its term frequency and term positions.
+    //
+    // `STORED` means that the field will also be saved
+    // in a compressed, row-oriented key-value store.
+    // This store is useful for reconstructing the
+    // documents that were selected during the search phase.
+    let title = schema_builder.add_text_field("title", TEXT | STORED);
+
+    let schema = schema_builder.build();
+
+    // # Indexing documents
+    //
+    // Let's create a brand new index.
+    //
+    // This will actually just save a meta.json
+    // with our schema in the directory.
+    let index = Index::create_in_dir(&index_path, schema.clone())?;
+
+    // To insert a document we will need an index writer.
+    // There must be only one writer at a time.
+    // This single `IndexWriter` is already
+    // multithreaded.
+    //
+    // Here we give tantivy a budget of `50MB`.
+    // Using a bigger memory_arena for the indexer may increase
+    // throughput, but 50 MB is already plenty.
+    let mut index_writer = index.writer(50_000_000)?;
+
+    // Let's index our documents!
+    // We first need a handle on the title and the body field.
+
+    // ### Adding documents
+    //
+    index_writer.add_document(doc!(
+        title => "The Name of the Wind",
+    ))?;
+    index_writer.add_document(doc!(
+        title => "The Diary of Muadib",
+    ))?;
+    index_writer.add_document(doc!(
+        title => "A Dairy Cow",
+    ))?;
+    index_writer.add_document(doc!(
+        title => "The Diary of a Young Girl",
+    ))?;
+    index_writer.commit()?;
+
+    // ### Committing
+    //
+    // At this point our documents are not searchable.
+    //
+    //
+    // We need to call `.commit()` explicitly to force the
+    // `index_writer` to finish processing the documents in the queue,
+    // flush the current index to the disk, and advertise
+    // the existence of new documents.
+    //
+    // This call is blocking.
+    index_writer.commit()?;
+
+    // If `.commit()` returns correctly, then all of the
+    // documents that have been added are guaranteed to be
+    // persistently indexed.
+    //
+    // In the scenario of a crash or a power failure,
+    // tantivy behaves as if it has rolled back to its last
+    // commit.
+
+    // # Searching
+    //
+    // ### Searcher
+    //
+    // A reader is required first in order to search an index.
+    // It acts as a `Searcher` pool that reloads itself,
+    // depending on a `ReloadPolicy`.
+    //
+    // For a search server you will typically create one reader for the entire lifetime of your
+    // program, and acquire a new searcher for every single request.
+    //
+    // In the code below, we rely on the 'ON_COMMIT' policy: the reader
+    // will reload the index automatically after each commit.
+    let reader = index
+        .reader_builder()
+        .reload_policy(ReloadPolicy::OnCommit)
+        .try_into()?;
+
+    // We now need to acquire a searcher.
+    //
+    // A searcher points to a snapshotted, immutable version of the index.
+    //
+    // Some search experience might require more than
+    // one query. Using the same searcher ensures that all of these queries will run on the
+    // same version of the index.
+    //
+    // Acquiring a `searcher` is very cheap.
+    //
+    // You should acquire a searcher every time you start processing a request and
+    // and release it right after your query is finished.
+    let searcher = reader.searcher();
+
+    // ### FuzzyTermQuery
+    {
+        let term = Term::from_field_text(title, "Diary");
+        let query = FuzzyTermQuery::new(term, 2, true);
+
+        let (top_docs, count) = searcher
+            .search(&query, &(TopDocs::with_limit(5), Count))
+            .unwrap();
+        assert_eq!(count, 3);
+        assert_eq!(top_docs.len(), 3);
+        for (score, doc_address) in top_docs {
+            let retrieved_doc = searcher.doc(doc_address)?;
+            // Note that the score is not lower for the fuzzy hit.
+            // There's an issue open for that: https://github.com/quickwit-oss/tantivy/issues/563
+            println!("score {score:?} doc {}", schema.to_json(&retrieved_doc));
+            // score 1.0 doc {"title":["The Diary of Muadib"]}
+            //
+            // score 1.0 doc {"title":["The Diary of a Young Girl"]}
+            //
+            // score 1.0 doc {"title":["A Dairy Cow"]}
+        }
+    }
+
+    Ok(())
+}

examples/ip_field.rs

@@ -10,6 +10,10 @@ use tantivy::Index;
 
 fn main() -> tantivy::Result<()> {
     // # Defining the schema
+    // We set the IP field as `INDEXED`, so it can be searched
+    // `FAST` will create a fast field. The fast field will be used to execute search queries.
+    // `FAST` is not a requirement for range queries, it can also be executed on the inverted index
+    // which is created by `INDEXED`.
     let mut schema_builder = Schema::builder();
     let event_type = schema_builder.add_text_field("event_type", STRING | STORED);
     let ip = schema_builder.add_ip_addr_field("ip", STORED | INDEXED | FAST);
@@ -19,51 +23,81 @@ fn main() -> tantivy::Result<()> {
     let index = Index::create_in_ram(schema.clone());
 
     let mut index_writer = index.writer(50_000_000)?;
+
+    // ### IPv4
+    // Adding documents that contain an IPv4 address. Notice that the IP addresses are passed as
+    // `String`. Since the field is of type ip, we parse the IP address from the string and store it
+    // internally as IPv6.
     let doc = schema.parse_document(
         r#"{
-        "ip": "192.168.0.33",
-        "event_type": "login"
-    }"#,
+            "ip": "192.168.0.33",
+            "event_type": "login"
+        }"#,
     )?;
     index_writer.add_document(doc)?;
     let doc = schema.parse_document(
         r#"{
-        "ip": "192.168.0.80",
-        "event_type": "checkout"
-    }"#,
+            "ip": "192.168.0.80",
+            "event_type": "checkout"
+        }"#,
     )?;
     index_writer.add_document(doc)?;
+    // ### IPv6
+    // Adding a document that contains an IPv6 address.
     let doc = schema.parse_document(
         r#"{
-        "ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334",
-        "event_type": "checkout"
-    }"#,
+            "ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334",
+            "event_type": "checkout"
+        }"#,
     )?;
 
     index_writer.add_document(doc)?;
+    // Commit will create a segment containing our documents.
     index_writer.commit()?;
 
     let reader = index.reader()?;
     let searcher = reader.searcher();
 
+    // # Search
+    // Range queries on IPv4. Since we created a fast field, the fast field will be used to execute
+    // the search.
+    // ### Range Queries
     let query_parser = QueryParser::for_index(&index, vec![event_type, ip]);
     {
-        let query = query_parser.parse_query("ip:[192.168.0.0 TO 192.168.0.100]")?;
+        // 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))?;
-        assert_eq!(count_docs.len(), 2);
+        assert_eq!(count_docs.len(), 1);
     }
     {
-        let query = query_parser.parse_query("ip:[192.168.1.0 TO 192.168.1.100]")?;
+        // 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))?;
         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))?;
+        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))?;
+        assert_eq!(count_docs.len(), 2);
+    }
+
+    // ### Exact Queries
+    // Exact search on IPv4.
     {
         let query = query_parser.parse_query("ip:192.168.0.80")?;
         let count_docs = searcher.search(&*query, &Count)?;
         assert_eq!(count_docs, 1);
     }
+    // Exact search on IPv6.
+    // IpV6 addresses need to be quoted because they contain `:`
     {
-        // IpV6 needs to be escaped because it contains `:`
         let query = query_parser.parse_query("ip:\"2001:0db8:85a3:0000:0000:8a2e:0370:7334\"")?;
         let count_docs = searcher.search(&*query, &Count)?;
         assert_eq!(count_docs, 1);

examples/warmer.rs

@@ -17,7 +17,6 @@ use tantivy::{
 
 type ProductId = u64;
 
-/// Price
 type Price = u32;
 
 pub trait PriceFetcher: Send + Sync + 'static {
@@ -90,10 +89,10 @@ impl Warmer for DynamicPriceColumn {
     }
 }
 
-/// For the sake of this example, the table is just an editable HashMap behind a RwLock.
-/// This map represents a map (ProductId -> Price)
-///
-/// In practise, it could be fetching things from an external service, like a SQL table.
+// For the sake of this example, the table is just an editable HashMap behind a RwLock.
+// This map represents a map (ProductId -> Price)
+//
+// In practise, it could be fetching things from an external service, like a SQL table.
 #[derive(Default, Clone)]
 pub struct ExternalPriceTable {
     prices: Arc<RwLock<HashMap<ProductId, Price>>>,

src/aggregation/agg_req.rs

@@ -50,7 +50,7 @@ use std::collections::{HashMap, HashSet};
 use serde::{Deserialize, Serialize};
 
 pub use super::bucket::RangeAggregation;
-use super::bucket::{HistogramAggregation, TermsAggregation};
+use super::bucket::{DateHistogramAggregationReq, HistogramAggregation, TermsAggregation};
 use super::metric::{
     AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
     SumAggregation,
@@ -110,10 +110,13 @@ impl BucketAggregationInternal {
             _ => None,
         }
     }
-    pub(crate) fn as_histogram(&self) -> Option<&HistogramAggregation> {
+    pub(crate) fn as_histogram(&self) -> crate::Result<Option<HistogramAggregation>> {
         match &self.bucket_agg {
-            BucketAggregationType::Histogram(histogram) => Some(histogram),
-            _ => None,
+            BucketAggregationType::Histogram(histogram) => Ok(Some(histogram.clone())),
+            BucketAggregationType::DateHistogram(histogram) => {
+                Ok(Some(histogram.to_histogram_req()?))
+            }
+            _ => Ok(None),
         }
     }
     pub(crate) fn as_term(&self) -> Option<&TermsAggregation> {
@@ -124,15 +127,6 @@ impl BucketAggregationInternal {
     }
 }
 
-/// Extract all fields, where the term directory is used in the tree.
-pub fn get_term_dict_field_names(aggs: &Aggregations) -> HashSet<String> {
-    let mut term_dict_field_names = Default::default();
-    for el in aggs.values() {
-        el.get_term_dict_field_names(&mut term_dict_field_names)
-    }
-    term_dict_field_names
-}
-
 /// Extract all fast field names used in the tree.
 pub fn get_fast_field_names(aggs: &Aggregations) -> HashSet<String> {
     let mut fast_field_names = Default::default();
@@ -155,16 +149,12 @@ pub enum Aggregation {
 }
 
 impl Aggregation {
-    fn get_term_dict_field_names(&self, term_field_names: &mut HashSet<String>) {
-        if let Aggregation::Bucket(bucket) = self {
-            bucket.get_term_dict_field_names(term_field_names)
-        }
-    }
-
     fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
         match self {
             Aggregation::Bucket(bucket) => bucket.get_fast_field_names(fast_field_names),
-            Aggregation::Metric(metric) => metric.get_fast_field_names(fast_field_names),
+            Aggregation::Metric(metric) => {
+                fast_field_names.insert(metric.get_fast_field_name().to_string());
+            }
         }
     }
 }
@@ -193,14 +183,9 @@ pub struct BucketAggregation {
 }
 
 impl BucketAggregation {
-    fn get_term_dict_field_names(&self, term_dict_field_names: &mut HashSet<String>) {
-        if let BucketAggregationType::Terms(terms) = &self.bucket_agg {
-            term_dict_field_names.insert(terms.field.to_string());
-        }
-        term_dict_field_names.extend(get_term_dict_field_names(&self.sub_aggregation));
-    }
     fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
-        self.bucket_agg.get_fast_field_names(fast_field_names);
+        let fast_field_name = self.bucket_agg.get_fast_field_name();
+        fast_field_names.insert(fast_field_name.to_string());
         fast_field_names.extend(get_fast_field_names(&self.sub_aggregation));
     }
 }
@@ -214,20 +199,22 @@ pub enum BucketAggregationType {
     /// Put data into buckets of user-defined ranges.
     #[serde(rename = "histogram")]
     Histogram(HistogramAggregation),
+    /// Put data into buckets of user-defined ranges.
+    #[serde(rename = "date_histogram")]
+    DateHistogram(DateHistogramAggregationReq),
     /// Put data into buckets of terms.
     #[serde(rename = "terms")]
     Terms(TermsAggregation),
 }
 
 impl BucketAggregationType {
-    fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
+    fn get_fast_field_name(&self) -> &str {
         match self {
-            BucketAggregationType::Terms(terms) => fast_field_names.insert(terms.field.to_string()),
-            BucketAggregationType::Range(range) => fast_field_names.insert(range.field.to_string()),
-            BucketAggregationType::Histogram(histogram) => {
-                fast_field_names.insert(histogram.field.to_string())
-            }
-        };
+            BucketAggregationType::Terms(terms) => terms.field.as_str(),
+            BucketAggregationType::Range(range) => range.field.as_str(),
+            BucketAggregationType::Histogram(histogram) => histogram.field.as_str(),
+            BucketAggregationType::DateHistogram(histogram) => histogram.field.as_str(),
+        }
     }
 }
 
@@ -262,16 +249,15 @@ pub enum MetricAggregation {
 }
 
 impl MetricAggregation {
-    fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
-        let fast_field_name = match self {
+    fn get_fast_field_name(&self) -> &str {
+        match self {
             MetricAggregation::Average(avg) => avg.field_name(),
             MetricAggregation::Count(count) => count.field_name(),
             MetricAggregation::Max(max) => max.field_name(),
             MetricAggregation::Min(min) => min.field_name(),
             MetricAggregation::Stats(stats) => stats.field_name(),
             MetricAggregation::Sum(sum) => sum.field_name(),
-        };
-        fast_field_names.insert(fast_field_name.to_string());
+        }
     }
 }
 

src/aggregation/agg_req_with_accessor.rs

@@ -3,17 +3,18 @@
 use std::rc::Rc;
 use std::sync::atomic::AtomicU32;
 
-use columnar::{Column, StrColumn};
+use columnar::{Column, ColumnType, StrColumn};
 
 use super::agg_req::{Aggregation, Aggregations, BucketAggregationType, MetricAggregation};
-use super::bucket::{HistogramAggregation, RangeAggregation, TermsAggregation};
+use super::bucket::{
+    DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
+};
 use super::metric::{
     AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
     SumAggregation,
 };
 use super::segment_agg_result::BucketCount;
 use super::VecWithNames;
-use crate::schema::Type;
 use crate::{SegmentReader, TantivyError};
 
 #[derive(Clone, Default)]
@@ -41,7 +42,7 @@ pub struct BucketAggregationWithAccessor {
     /// based on search terms. So eventually this needs to be Option or moved.
     pub(crate) accessor: Column<u64>,
     pub(crate) str_dict_column: Option<StrColumn>,
-    pub(crate) field_type: Type,
+    pub(crate) field_type: ColumnType,
     pub(crate) bucket_agg: BucketAggregationType,
     pub(crate) sub_aggregation: AggregationsWithAccessor,
     pub(crate) bucket_count: BucketCount,
@@ -63,6 +64,10 @@ impl BucketAggregationWithAccessor {
             BucketAggregationType::Histogram(HistogramAggregation {
                 field: field_name, ..
             }) => get_ff_reader_and_validate(reader, field_name)?,
+            BucketAggregationType::DateHistogram(DateHistogramAggregationReq {
+                field: field_name,
+                ..
+            }) => get_ff_reader_and_validate(reader, field_name)?,
             BucketAggregationType::Terms(TermsAggregation {
                 field: field_name, ..
             }) => {
@@ -94,7 +99,7 @@ impl BucketAggregationWithAccessor {
 #[derive(Clone)]
 pub struct MetricAggregationWithAccessor {
     pub metric: MetricAggregation,
-    pub field_type: Type,
+    pub field_type: ColumnType,
     pub accessor: Column<u64>,
 }
 
@@ -158,22 +163,12 @@ pub(crate) fn get_aggs_with_accessor_and_validate(
 fn get_ff_reader_and_validate(
     reader: &SegmentReader,
     field_name: &str,
-) -> crate::Result<(columnar::Column<u64>, Type)> {
-    let field = reader.schema().get_field(field_name)?;
-    // TODO we should get type metadata from columnar
-    let field_type = reader
-        .schema()
-        .get_field_entry(field)
-        .field_type()
-        .value_type();
-    // TODO Do validation
-
+) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
     let ff_fields = reader.fast_fields();
-    let ff_field = ff_fields.u64_lenient(field_name)?.ok_or_else(|| {
-        TantivyError::InvalidArgument(format!(
-            "No numerical fast field found for field: {}",
-            field_name
-        ))
-    })?;
-    Ok((ff_field, field_type))
+    let ff_field_with_type = ff_fields
+        .u64_lenient_with_type(field_name)?
+        .ok_or_else(|| {
+            TantivyError::InvalidArgument(format!("No fast field found for field: {}", field_name))
+        })?;
+    Ok(ff_field_with_type)
 }

src/aggregation/agg_result.rs

@@ -12,7 +12,6 @@ use super::bucket::GetDocCount;
 use super::intermediate_agg_result::{IntermediateBucketResult, IntermediateMetricResult};
 use super::metric::{SingleMetricResult, Stats};
 use super::Key;
-use crate::schema::Schema;
 use crate::TantivyError;
 
 #[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
@@ -154,12 +153,9 @@ pub enum BucketResult {
 }
 
 impl BucketResult {
-    pub(crate) fn empty_from_req(
-        req: &BucketAggregationInternal,
-        schema: &Schema,
-    ) -> crate::Result<Self> {
+    pub(crate) fn empty_from_req(req: &BucketAggregationInternal) -> crate::Result<Self> {
         let empty_bucket = IntermediateBucketResult::empty_from_req(&req.bucket_agg);
-        empty_bucket.into_final_bucket_result(req, schema)
+        empty_bucket.into_final_bucket_result(req)
     }
 }
 

src/aggregation/bucket/histogram/date_histogram.rs

@@ -1,5 +1,8 @@
 use serde::{Deserialize, Serialize};
 
+use super::{HistogramAggregation, HistogramBounds};
+use crate::aggregation::AggregationError;
+
 /// DateHistogramAggregation is similar to `HistogramAggregation`, but it can only be used with date
 /// type.
 ///
@@ -29,8 +32,16 @@ use serde::{Deserialize, Serialize};
 /// See [`BucketEntry`](crate::aggregation::agg_result::BucketEntry)
 #[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
 pub struct DateHistogramAggregationReq {
+    #[doc(hidden)]
+    /// Only for validation
+    interval: Option<String>,
+    #[doc(hidden)]
+    /// Only for validation
+    date_interval: Option<String>,
     /// The field to aggregate on.
     pub field: String,
+    /// The format to format dates.
+    pub format: Option<String>,
     /// The interval to chunk your data range. Each bucket spans a value range of
     /// [0..fixed_interval). Accepted values
     ///
@@ -55,29 +66,132 @@ pub struct DateHistogramAggregationReq {
     /// Intervals implicitly defines an absolute grid of buckets `[interval * k, interval * (k +
     /// 1))`.
     pub offset: Option<String>,
+    /// The minimum number of documents in a bucket to be returned. Defaults to 0.
+    pub min_doc_count: Option<u64>,
+    /// Limits the data range to `[min, max]` closed interval.
+    ///
+    /// This can be used to filter values if they are not in the data range.
+    ///
+    /// hard_bounds only limits the buckets, to force a range set both extended_bounds and
+    /// hard_bounds to the same range.
+    ///
+    /// Needs to be provided as timestamp in microseconds precision.
+    ///
+    /// ## Example
+    /// ```json
+    /// {
+    ///     "sales_over_time": {
+    ///        "date_histogram": {
+    ///            "field": "dates",
+    ///            "interval": "1d",
+    ///            "hard_bounds": {
+    ///                "min": 0,
+    ///                "max": 1420502400000000
+    ///            }
+    ///        }
+    ///    }
+    /// }
+    /// ```
+    pub hard_bounds: Option<HistogramBounds>,
+    /// Can be set to extend your bounds. The range of the buckets is by default defined by the
+    /// data range of the values of the documents. As the name suggests, this can only be used to
+    /// extend the value range. If the bounds for min or max are not extending the range, the value
+    /// has no effect on the returned buckets.
+    ///
+    /// Cannot be set in conjunction with min_doc_count > 0, since the empty buckets from extended
+    /// bounds would not be returned.
+    pub extended_bounds: Option<HistogramBounds>,
+
     /// Whether to return the buckets as a hash map
     #[serde(default)]
     pub keyed: bool,
 }
 
 impl DateHistogramAggregationReq {
+    pub(crate) fn to_histogram_req(&self) -> crate::Result<HistogramAggregation> {
+        self.validate()?;
+        Ok(HistogramAggregation {
+            field: self.field.to_string(),
+            interval: parse_into_microseconds(&self.fixed_interval)? as f64,
+            offset: self
+                .offset
+                .as_ref()
+                .map(|offset| parse_offset_into_microseconds(offset))
+                .transpose()?
+                .map(|el| el as f64),
+            min_doc_count: self.min_doc_count,
+            hard_bounds: None,
+            extended_bounds: None,
+            keyed: self.keyed,
+        })
+    }
+
     fn validate(&self) -> crate::Result<()> {
+        if self.interval.is_some() {
+            return Err(crate::TantivyError::InvalidArgument(format!(
+                "`interval` parameter {:?} in date histogram is unsupported, only \
+                 `fixed_interval` is supported",
+                self.interval
+            )));
+        }
+        if self.format.is_some() {
+            return Err(crate::TantivyError::InvalidArgument(
+                "format parameter on date_histogram is unsupported".to_string(),
+            ));
+        }
+
+        if self.date_interval.is_some() {
+            return Err(crate::TantivyError::InvalidArgument(
+                "date_interval in date histogram is unsupported, only `fixed_interval` is \
+                 supported"
+                    .to_string(),
+            ));
+        }
+
+        parse_into_microseconds(&self.fixed_interval)?;
+
         Ok(())
     }
 }
 
-#[derive(Debug, PartialEq, Eq)]
+#[derive(Debug, Clone, PartialEq, Eq, Error)]
 /// Errors when parsing the fixed interval for `DateHistogramAggregationReq`.
 pub enum DateHistogramParseError {
     /// Unit not recognized in passed String
+    #[error("Unit not recognized in passed String {0:?}")]
     UnitNotRecognized(String),
     /// Number not found in passed String
+    #[error("Number not found in passed String {0:?}")]
     NumberMissing(String),
     /// Unit not found in passed String
+    #[error("Unit not found in passed String {0:?}")]
     UnitMissing(String),
+    /// Offset invalid
+    #[error("passed offset is invalid {0:?}")]
+    InvalidOffset(String),
 }
 
-fn parse_into_milliseconds(input: &str) -> Result<u64, DateHistogramParseError> {
+fn parse_offset_into_microseconds(input: &str) -> Result<i64, AggregationError> {
+    let is_sign = |byte| &[byte] == b"-" || &[byte] == b"+";
+    if input.is_empty() {
+        return Err(DateHistogramParseError::InvalidOffset(input.to_string()).into());
+    }
+
+    let has_sign = is_sign(input.as_bytes()[0]);
+    if has_sign {
+        let (sign, input) = input.split_at(1);
+        let val = parse_into_microseconds(input)?;
+        if sign == "-" {
+            Ok(-val)
+        } else {
+            Ok(val)
+        }
+    } else {
+        parse_into_microseconds(input)
+    }
+}
+
+fn parse_into_microseconds(input: &str) -> Result<i64, AggregationError> {
     let split_boundary = input
         .as_bytes()
         .iter()
@@ -85,12 +199,12 @@ fn parse_into_milliseconds(input: &str) -> Result<u64, DateHistogramParseError>
         .count();
     let (number, unit) = input.split_at(split_boundary);
     if number.is_empty() {
-        return Err(DateHistogramParseError::NumberMissing(input.to_string()));
+        return Err(DateHistogramParseError::NumberMissing(input.to_string()).into());
     }
     if unit.is_empty() {
-        return Err(DateHistogramParseError::UnitMissing(input.to_string()));
+        return Err(DateHistogramParseError::UnitMissing(input.to_string()).into());
     }
-    let number: u64 = number
+    let number: i64 = number
         .parse()
         // Technically this should never happen, but there was a bug
         // here and being defensive does not hurt.
@@ -102,36 +216,260 @@ fn parse_into_milliseconds(input: &str) -> Result<u64, DateHistogramParseError>
         "m" => 60 * 1000,
         "h" => 60 * 60 * 1000,
         "d" => 24 * 60 * 60 * 1000,
-        _ => return Err(DateHistogramParseError::UnitNotRecognized(unit.to_string())),
+        _ => return Err(DateHistogramParseError::UnitNotRecognized(unit.to_string()).into()),
     };
 
-    Ok(number * multiplier_from_unit)
+    Ok(number * multiplier_from_unit * 1000)
 }
 
 #[cfg(test)]
 mod tests {
+    use pretty_assertions::assert_eq;
+
     use super::*;
+    use crate::aggregation::agg_req::Aggregations;
+    use crate::aggregation::tests::exec_request;
+    use crate::indexer::NoMergePolicy;
+    use crate::schema::{Schema, FAST};
+    use crate::Index;
 
     #[test]
-    fn test_parse_into_milliseconds() {
-        assert_eq!(parse_into_milliseconds("1m").unwrap(), 60_000);
-        assert_eq!(parse_into_milliseconds("2m").unwrap(), 120_000);
+    fn test_parse_into_microseconds() {
+        assert_eq!(parse_into_microseconds("1m").unwrap(), 60_000_000);
+        assert_eq!(parse_into_microseconds("2m").unwrap(), 120_000_000);
         assert_eq!(
-            parse_into_milliseconds("2y").unwrap_err(),
-            DateHistogramParseError::UnitNotRecognized("y".to_string())
+            parse_into_microseconds("2y").unwrap_err(),
+            DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
         );
         assert_eq!(
-            parse_into_milliseconds("2000").unwrap_err(),
-            DateHistogramParseError::UnitMissing("2000".to_string())
+            parse_into_microseconds("2000").unwrap_err(),
+            DateHistogramParseError::UnitMissing("2000".to_string()).into()
         );
         assert_eq!(
-            parse_into_milliseconds("ms").unwrap_err(),
-            DateHistogramParseError::NumberMissing("ms".to_string())
+            parse_into_microseconds("ms").unwrap_err(),
+            DateHistogramParseError::NumberMissing("ms".to_string()).into()
+        );
+    }
+
+    #[test]
+    fn test_parse_offset_into_microseconds() {
+        assert_eq!(parse_offset_into_microseconds("1m").unwrap(), 60_000_000);
+        assert_eq!(parse_offset_into_microseconds("+1m").unwrap(), 60_000_000);
+        assert_eq!(parse_offset_into_microseconds("-1m").unwrap(), -60_000_000);
+        assert_eq!(parse_offset_into_microseconds("2m").unwrap(), 120_000_000);
+        assert_eq!(parse_offset_into_microseconds("+2m").unwrap(), 120_000_000);
+        assert_eq!(parse_offset_into_microseconds("-2m").unwrap(), -120_000_000);
+        assert_eq!(parse_offset_into_microseconds("-2ms").unwrap(), -2_000);
+        assert_eq!(
+            parse_offset_into_microseconds("2y").unwrap_err(),
+            DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
+        );
+        assert_eq!(
+            parse_offset_into_microseconds("2000").unwrap_err(),
+            DateHistogramParseError::UnitMissing("2000".to_string()).into()
+        );
+        assert_eq!(
+            parse_offset_into_microseconds("ms").unwrap_err(),
+            DateHistogramParseError::NumberMissing("ms".to_string()).into()
         );
     }
 
     #[test]
     fn test_parse_into_milliseconds_do_not_accept_non_ascii() {
-        assert!(parse_into_milliseconds("１m").is_err());
+        assert!(parse_into_microseconds("１m").is_err());
+    }
+
+    pub fn get_test_index_from_docs(
+        merge_segments: bool,
+        segment_and_docs: &[Vec<&str>],
+    ) -> crate::Result<Index> {
+        let mut schema_builder = Schema::builder();
+        schema_builder.add_date_field("date", FAST);
+        schema_builder.add_text_field("text", FAST);
+        let schema = schema_builder.build();
+        let index = Index::create_in_ram(schema.clone());
+        {
+            let mut index_writer = index.writer_with_num_threads(1, 30_000_000)?;
+            index_writer.set_merge_policy(Box::new(NoMergePolicy));
+            for values in segment_and_docs {
+                for doc_str in values {
+                    let doc = schema.parse_document(doc_str)?;
+                    index_writer.add_document(doc)?;
+                }
+                // writing the segment
+                index_writer.commit()?;
+            }
+        }
+        if merge_segments {
+            let segment_ids = index
+                .searchable_segment_ids()
+                .expect("Searchable segments failed.");
+            if segment_ids.len() > 1 {
+                let mut index_writer = index.writer_for_tests()?;
+                index_writer.merge(&segment_ids).wait()?;
+                index_writer.wait_merging_threads()?;
+            }
+        }
+
+        Ok(index)
+    }
+
+    #[test]
+    fn histogram_test_date_force_merge_segments() -> crate::Result<()> {
+        histogram_test_date_merge_segments(true)
+    }
+
+    #[test]
+    fn histogram_test_date() -> crate::Result<()> {
+        histogram_test_date_merge_segments(false)
+    }
+    fn histogram_test_date_merge_segments(merge_segments: bool) -> crate::Result<()> {
+        let docs = vec![
+            vec![r#"{ "date": "2015-01-01T12:10:30Z", "text": "aaa" }"#],
+            vec![r#"{ "date": "2015-01-01T11:11:30Z", "text": "bbb" }"#],
+            vec![r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb" }"#],
+            vec![r#"{ "date": "2015-01-06T00:00:00Z", "text": "ccc" }"#],
+        ];
+
+        let index = get_test_index_from_docs(merge_segments, &docs)?;
+        // 30day + offset
+        let elasticsearch_compatible_json = json!(
+            {
+              "sales_over_time": {
+                "date_histogram": {
+                  "field": "date",
+                  "fixed_interval": "30d",
+                  "offset": "-4d"
+                }
+              }
+            }
+        );
+
+        let agg_req: Aggregations =
+            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
+                .unwrap();
+        let res = exec_request(agg_req, &index)?;
+        let expected_res = json!({
+          "sales_over_time" : {
+          "buckets" : [
+            {
+              "key_as_string" : "2015-01-01T00:00:00Z",
+              "key" : 1420070400000000.0,
+              "doc_count" : 4
+            }
+          ]
+        }
+        });
+        assert_eq!(res, expected_res);
+
+        // 30day + offset + sub_agg
+        let elasticsearch_compatible_json = json!(
+            {
+              "sales_over_time": {
+                "date_histogram": {
+                  "field": "date",
+                  "fixed_interval": "30d",
+                  "offset": "-4d"
+                },
+                "aggs": {
+                    "texts": {
+                        "terms": {"field": "text"}
+                    }
+                }
+              }
+            }
+        );
+
+        let agg_req: Aggregations =
+            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
+                .unwrap();
+        let res = exec_request(agg_req, &index)?;
+        println!("{}", serde_json::to_string_pretty(&res).unwrap());
+        let expected_res = json!({
+          "sales_over_time" : {
+          "buckets" : [
+            {
+              "key_as_string" : "2015-01-01T00:00:00Z",
+              "key" : 1420070400000000.0,
+              "doc_count" : 4,
+              "texts": {
+                  "buckets": [
+                    {
+                      "doc_count": 2,
+                      "key": "bbb"
+                    },
+                    {
+                      "doc_count": 1,
+                      "key": "ccc"
+                    },
+                    {
+                      "doc_count": 1,
+                      "key": "aaa"
+                    }
+                  ],
+                  "doc_count_error_upper_bound": 0,
+                  "sum_other_doc_count": 0
+                }
+            }
+          ]
+        }
+        });
+        assert_eq!(res, expected_res);
+
+        // 1day
+        let elasticsearch_compatible_json = json!(
+            {
+              "sales_over_time": {
+                "date_histogram": {
+                  "field": "date",
+                  "fixed_interval": "1d"
+                }
+              }
+            }
+        );
+
+        let agg_req: Aggregations =
+            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
+                .unwrap();
+        let res = exec_request(agg_req, &index)?;
+        let expected_res = json!( {
+          "sales_over_time": {
+            "buckets": [
+              {
+                "doc_count": 2,
+                "key": 1420070400000000.0,
+                "key_as_string": "2015-01-01T00:00:00Z"
+              },
+              {
+                "doc_count": 1,
+                "key": 1420156800000000.0,
+                "key_as_string": "2015-01-02T00:00:00Z"
+              },
+              {
+                "doc_count": 0,
+                "key": 1420243200000000.0,
+                "key_as_string": "2015-01-03T00:00:00Z"
+              },
+              {
+                "doc_count": 0,
+                "key": 1420329600000000.0,
+                "key_as_string": "2015-01-04T00:00:00Z"
+              },
+              {
+                "doc_count": 0,
+                "key": 1420416000000000.0,
+                "key_as_string": "2015-01-05T00:00:00Z"
+              },
+              {
+                "doc_count": 1,
+                "key": 1420502400000000.0,
+                "key_as_string": "2015-01-06T00:00:00Z"
+              }
+            ]
+          }
+        });
+        assert_eq!(res, expected_res);
+
+        Ok(())
     }
 }

src/aggregation/bucket/histogram/histogram.rs

@@ -1,9 +1,11 @@
 use std::cmp::Ordering;
 use std::fmt::Display;
 
-use columnar::Column;
+use columnar::ColumnType;
 use itertools::Itertools;
+use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
+use tantivy_bitpacker::minmax;
 
 use crate::aggregation::agg_req::AggregationsInternal;
 use crate::aggregation::agg_req_with_accessor::{
@@ -14,10 +16,9 @@ use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResults, IntermediateBucketResult, IntermediateHistogramBucketEntry,
 };
 use crate::aggregation::segment_agg_result::{
-    GenericSegmentAggregationResultsCollector, SegmentAggregationCollector,
+    build_segment_agg_collector, SegmentAggregationCollector,
 };
-use crate::aggregation::{f64_from_fastfield_u64, format_date};
-use crate::schema::{Schema, Type};
+use crate::aggregation::{f64_from_fastfield_u64, format_date, VecWithNames};
 use crate::{DocId, TantivyError};
 
 /// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
@@ -176,7 +177,7 @@ impl HistogramBounds {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Default, Clone, Debug, PartialEq)]
 pub(crate) struct SegmentHistogramBucketEntry {
     pub key: f64,
     pub doc_count: u64,
@@ -185,7 +186,7 @@ pub(crate) struct SegmentHistogramBucketEntry {
 impl SegmentHistogramBucketEntry {
     pub(crate) fn into_intermediate_bucket_entry(
         self,
-        sub_aggregation: GenericSegmentAggregationResultsCollector,
+        sub_aggregation: Box<dyn SegmentAggregationCollector>,
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<IntermediateHistogramBucketEntry> {
         Ok(IntermediateHistogramBucketEntry {
@@ -202,14 +203,85 @@ impl SegmentHistogramBucketEntry {
 #[derive(Clone, Debug)]
 pub struct SegmentHistogramCollector {
     /// The buckets containing the aggregation data.
-    buckets: Vec<SegmentHistogramBucketEntry>,
-    sub_aggregations: Option<Vec<GenericSegmentAggregationResultsCollector>>,
-    field_type: Type,
+    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,
-    min_doc_count: u64,
-    first_bucket_num: i64,
     bounds: HistogramBounds,
+    accessor_idx: usize,
+}
+
+impl SegmentAggregationCollector for SegmentHistogramCollector {
+    fn into_intermediate_aggregations_result(
+        self: Box<Self>,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<IntermediateAggregationResults> {
+        let name = agg_with_accessor.buckets.keys[self.accessor_idx].to_string();
+        let agg_with_accessor = &agg_with_accessor.buckets.values[self.accessor_idx];
+
+        let bucket = self.into_intermediate_bucket_result(agg_with_accessor)?;
+        let buckets = Some(VecWithNames::from_entries(vec![(name, bucket)]));
+
+        Ok(IntermediateAggregationResults {
+            metrics: None,
+            buckets,
+        })
+    }
+
+    fn collect(
+        &mut self,
+        doc: crate::DocId,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        self.collect_block(&[doc], agg_with_accessor)
+    }
+
+    fn collect_block(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        let accessor = &agg_with_accessor.buckets.values[self.accessor_idx].accessor;
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        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);
+
+        for doc in docs {
+            for val in accessor.values_for_doc(*doc) {
+                let val = self.f64_from_fastfield_u64(val);
+
+                let bucket_pos = get_bucket_pos(val);
+
+                if bounds.contains(val) {
+                    self.increment_bucket(
+                        bucket_pos,
+                        *doc,
+                        sub_aggregation_accessor,
+                        interval,
+                        offset,
+                    )?;
+                }
+            }
+        }
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        for sub_aggregation in self.sub_aggregations.values_mut() {
+            sub_aggregation.flush(sub_aggregation_accessor)?;
+        }
+
+        Ok(())
+    }
 }
 
 impl SegmentHistogramCollector {
@@ -217,210 +289,96 @@ impl SegmentHistogramCollector {
         self,
         agg_with_accessor: &BucketAggregationWithAccessor,
     ) -> crate::Result<IntermediateBucketResult> {
-        // Compute the number of buckets to validate against max num buckets
-        // Note: We use min_doc_count here, but it's only an lowerbound here, since were are on the
-        // intermediate level and after merging the number of documents of a bucket could exceed
-        // `min_doc_count`.
-        {
-            let cut_off_buckets_front = self
-                .buckets
-                .iter()
-                .take_while(|bucket| bucket.doc_count <= self.min_doc_count)
-                .count();
-            let cut_off_buckets_back = self.buckets[cut_off_buckets_front..]
-                .iter()
-                .rev()
-                .take_while(|bucket| bucket.doc_count <= self.min_doc_count)
-                .count();
-            let estimate_num_buckets =
-                self.buckets.len() - cut_off_buckets_front - cut_off_buckets_back;
+        let mut buckets = Vec::with_capacity(self.buckets.len());
 
-            agg_with_accessor
-                .bucket_count
-                .add_count(estimate_num_buckets as u32);
-            agg_with_accessor.bucket_count.validate_bucket_count()?;
-        }
+        if self.sub_aggregation_blueprint.is_some() {
+            for (bucket_pos, bucket) in self.buckets.into_iter() {
+                let bucket_res = bucket.into_intermediate_bucket_entry(
+                    self.sub_aggregations.get(&bucket_pos).unwrap().clone(),
+                    &agg_with_accessor.sub_aggregation,
+                );
 
-        let mut buckets = Vec::with_capacity(
-            self.buckets
-                .iter()
-                .filter(|bucket| bucket.doc_count != 0)
-                .count(),
-        );
-
-        // Below we remove empty buckets for two reasons
-        // 1. To reduce the size of the intermediate result, which may be passed on the wire.
-        // 2. To mimic elasticsearch, there are no empty buckets at the start and end.
-        //
-        // Empty buckets may be added later again in the final result, depending on the request.
-        if let Some(sub_aggregations) = self.sub_aggregations {
-            for bucket_res in self
-                .buckets
-                .into_iter()
-                .zip(sub_aggregations.into_iter())
-                .filter(|(bucket, _sub_aggregation)| bucket.doc_count != 0)
-                .map(|(bucket, sub_aggregation)| {
-                    bucket.into_intermediate_bucket_entry(
-                        sub_aggregation,
-                        &agg_with_accessor.sub_aggregation,
-                    )
-                })
-            {
                 buckets.push(bucket_res?);
             }
         } else {
-            buckets.extend(
-                self.buckets
-                    .into_iter()
-                    .filter(|bucket| bucket.doc_count != 0)
-                    .map(|bucket| bucket.into()),
-            );
+            buckets.extend(self.buckets.into_values().map(|bucket| bucket.into()));
         };
+        buckets.sort_unstable_by(|b1, b2| b1.key.partial_cmp(&b2.key).unwrap_or(Ordering::Equal));
 
-        Ok(IntermediateBucketResult::Histogram { buckets })
+        Ok(IntermediateBucketResult::Histogram {
+            buckets,
+            column_type: Some(self.column_type),
+        })
     }
 
     pub(crate) fn from_req_and_validate(
         req: &HistogramAggregation,
         sub_aggregation: &AggregationsWithAccessor,
-        field_type: Type,
-        accessor: &Column<u64>,
+        field_type: ColumnType,
+        accessor_idx: usize,
     ) -> crate::Result<Self> {
         req.validate()?;
-        let min = f64_from_fastfield_u64(accessor.min_value(), &field_type);
-        let max = f64_from_fastfield_u64(accessor.max_value(), &field_type);
 
-        let (min, max) = get_req_min_max(req, Some((min, max)));
-
-        // We compute and generate the buckets range (min, max) based on the request and the min
-        // max in the fast field, but this is likely not ideal when this is a subbucket, where many
-        // unnecessary buckets may be generated.
-        let buckets = generate_buckets(req, min, max);
-
-        let sub_aggregations = if sub_aggregation.is_empty() {
+        let sub_aggregation_blueprint = if sub_aggregation.is_empty() {
             None
         } else {
-            let sub_aggregation =
-                GenericSegmentAggregationResultsCollector::from_req_and_validate(sub_aggregation)?;
-            Some(buckets.iter().map(|_| sub_aggregation.clone()).collect())
+            let sub_aggregation = build_segment_agg_collector(sub_aggregation)?;
+            Some(sub_aggregation)
         };
 
-        let buckets = buckets
-            .iter()
-            .map(|bucket| SegmentHistogramBucketEntry {
-                key: *bucket,
-                doc_count: 0,
-            })
-            .collect();
-
-        let first_bucket_num =
-            get_bucket_num_f64(min, req.interval, req.offset.unwrap_or(0.0)) as i64;
-
         let bounds = req.hard_bounds.unwrap_or(HistogramBounds {
             min: f64::MIN,
             max: f64::MAX,
         });
 
         Ok(Self {
-            buckets,
-            field_type,
+            buckets: Default::default(),
+            column_type: field_type,
             interval: req.interval,
             offset: req.offset.unwrap_or(0.0),
-            first_bucket_num,
             bounds,
-            sub_aggregations,
-            min_doc_count: req.min_doc_count(),
+            sub_aggregations: Default::default(),
+            sub_aggregation_blueprint,
+            accessor_idx,
         })
     }
 
-    #[inline]
-    pub(crate) fn collect_block(
-        &mut self,
-        docs: &[DocId],
-        bucket_with_accessor: &BucketAggregationWithAccessor,
-        force_flush: bool,
-    ) -> crate::Result<()> {
-        let bounds = self.bounds;
-        let interval = self.interval;
-        let offset = self.offset;
-        let first_bucket_num = self.first_bucket_num;
-        let get_bucket_num =
-            |val| (get_bucket_num_f64(val, interval, offset) as i64 - first_bucket_num) as usize;
-
-        let accessor = &bucket_with_accessor.accessor;
-        for doc in docs {
-            for val in accessor.values(*doc) {
-                let val = self.f64_from_fastfield_u64(val);
-
-                let bucket_pos = get_bucket_num(val);
-                self.increment_bucket_if_in_bounds(
-                    val,
-                    &bounds,
-                    bucket_pos,
-                    *doc,
-                    &bucket_with_accessor.sub_aggregation,
-                )?;
-            }
-        }
-        if force_flush {
-            if let Some(sub_aggregations) = self.sub_aggregations.as_mut() {
-                for sub_aggregation in sub_aggregations {
-                    sub_aggregation
-                        .flush_staged_docs(&bucket_with_accessor.sub_aggregation, force_flush)?;
-                }
-            }
-        }
-        Ok(())
-    }
-
-    #[inline]
-    fn increment_bucket_if_in_bounds(
-        &mut self,
-        val: f64,
-        bounds: &HistogramBounds,
-        bucket_pos: usize,
-        doc: DocId,
-        bucket_with_accessor: &AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        if bounds.contains(val) {
-            debug_assert_eq!(
-                self.buckets[bucket_pos].key,
-                get_bucket_val(val, self.interval, self.offset)
-            );
-
-            self.increment_bucket(bucket_pos, doc, bucket_with_accessor)?;
-        }
-        Ok(())
-    }
-
     #[inline]
     fn increment_bucket(
         &mut self,
-        bucket_pos: usize,
+        bucket_pos: i64,
         doc: DocId,
         bucket_with_accessor: &AggregationsWithAccessor,
+        interval: f64,
+        offset: f64,
     ) -> crate::Result<()> {
-        let bucket = &mut self.buckets[bucket_pos];
+        let bucket = self.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 }
+        });
         bucket.doc_count += 1;
-        if let Some(sub_aggregation) = self.sub_aggregations.as_mut() {
-            sub_aggregation[bucket_pos].collect(doc, bucket_with_accessor)?;
+        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, bucket_with_accessor)?;
         }
         Ok(())
     }
 
+    #[inline]
     fn f64_from_fastfield_u64(&self, val: u64) -> f64 {
-        f64_from_fastfield_u64(val, &self.field_type)
+        f64_from_fastfield_u64(val, &self.column_type)
     }
 }
 
 #[inline]
-fn get_bucket_num_f64(val: f64, interval: f64, offset: f64) -> f64 {
+fn get_bucket_pos_f64(val: f64, interval: f64, offset: f64) -> f64 {
     ((val - offset) / interval).floor()
 }
 
 #[inline]
-fn get_bucket_val(val: f64, interval: f64, offset: f64) -> f64 {
-    let bucket_pos = get_bucket_num_f64(val, interval, offset);
+fn get_bucket_key_from_pos(bucket_pos: f64, interval: f64, offset: f64) -> f64 {
     bucket_pos * interval + offset
 }
 
@@ -429,19 +387,14 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
     buckets: Vec<IntermediateHistogramBucketEntry>,
     histogram_req: &HistogramAggregation,
     sub_aggregation: &AggregationsInternal,
-    schema: &Schema,
 ) -> crate::Result<Vec<BucketEntry>> {
     // Generate the full list of buckets without gaps.
     //
     // The bounds are the min max from the current buckets, optionally extended by
     // extended_bounds from the request
-    let min_max = if buckets.is_empty() {
-        None
-    } else {
-        let min = buckets[0].key;
-        let max = buckets[buckets.len() - 1].key;
-        Some((min, max))
-    };
+    let min_max = minmax(buckets.iter().map(|bucket| bucket.key));
+
+    // TODO add memory check
     let fill_gaps_buckets = generate_buckets_with_opt_minmax(histogram_req, min_max);
 
     let empty_sub_aggregation = IntermediateAggregationResults::empty_from_req(sub_aggregation);
@@ -470,43 +423,33 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
                 sub_aggregation: empty_sub_aggregation.clone(),
             },
         })
-        .map(|intermediate_bucket| {
-            intermediate_bucket.into_final_bucket_entry(sub_aggregation, schema)
-        })
+        .map(|intermediate_bucket| intermediate_bucket.into_final_bucket_entry(sub_aggregation))
         .collect::<crate::Result<Vec<_>>>()
 }
 
 // Convert to BucketEntry
 pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
     buckets: Vec<IntermediateHistogramBucketEntry>,
+    column_type: Option<ColumnType>,
     histogram_req: &HistogramAggregation,
     sub_aggregation: &AggregationsInternal,
-    schema: &Schema,
 ) -> crate::Result<Vec<BucketEntry>> {
     let mut buckets = if histogram_req.min_doc_count() == 0 {
         // With min_doc_count != 0, we may need to add buckets, so that there are no
         // gaps, since intermediate result does not contain empty buckets (filtered to
         // reduce serialization size).
 
-        intermediate_buckets_to_final_buckets_fill_gaps(
-            buckets,
-            histogram_req,
-            sub_aggregation,
-            schema,
-        )?
+        intermediate_buckets_to_final_buckets_fill_gaps(buckets, histogram_req, sub_aggregation)?
     } else {
         buckets
             .into_iter()
             .filter(|histogram_bucket| histogram_bucket.doc_count >= histogram_req.min_doc_count())
-            .map(|histogram_bucket| {
-                histogram_bucket.into_final_bucket_entry(sub_aggregation, schema)
-            })
+            .map(|histogram_bucket| histogram_bucket.into_final_bucket_entry(sub_aggregation))
             .collect::<crate::Result<Vec<_>>>()?
     };
 
     // If we have a date type on the histogram buckets, we add the `key_as_string` field as rfc339
-    let field = schema.get_field(&histogram_req.field)?;
-    if schema.get_field_entry(field).field_type().is_date() {
+    if column_type == Some(ColumnType::DateTime) {
         for bucket in buckets.iter_mut() {
             if let crate::aggregation::Key::F64(val) = bucket.key {
                 let key_as_string = format_date(val as i64)?;
@@ -537,12 +480,6 @@ fn get_req_min_max(req: &HistogramAggregation, min_max: Option<(f64, f64)>) -> (
     (min, max)
 }
 
-/// Generates buckets with req.interval
-/// range is computed for provided min_max and request extended_bounds/hard_bounds
-pub(crate) fn generate_buckets(req: &HistogramAggregation, min: f64, max: f64) -> Vec<f64> {
-    generate_buckets_with_opt_minmax(req, Some((min, max)))
-}
-
 /// Generates buckets with req.interval
 /// Range is computed for provided min_max and request extended_bounds/hard_bounds
 /// returns empty vec when there is no range to span
@@ -553,8 +490,8 @@ pub(crate) fn generate_buckets_with_opt_minmax(
     let (min, max) = get_req_min_max(req, min_max);
 
     let offset = req.offset.unwrap_or(0.0);
-    let first_bucket_num = get_bucket_num_f64(min, req.interval, offset) as i64;
-    let last_bucket_num = get_bucket_num_f64(max, req.interval, offset) as i64;
+    let first_bucket_num = get_bucket_pos_f64(min, req.interval, offset) as i64;
+    let last_bucket_num = get_bucket_pos_f64(max, req.interval, offset) as i64;
     let mut buckets = Vec::with_capacity((first_bucket_num..=last_bucket_num).count());
     for bucket_pos in first_bucket_num..=last_bucket_num {
         let bucket_key = bucket_pos as f64 * req.interval + offset;
@@ -564,118 +501,6 @@ pub(crate) fn generate_buckets_with_opt_minmax(
     buckets
 }
 
-#[test]
-fn generate_buckets_test() {
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![2.0, 4.0]);
-
-    // Single bucket
-    let buckets = generate_buckets(&histogram_req, 0.5, 0.75);
-    assert_eq!(buckets, vec![0.0]);
-
-    // With offset
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        offset: Some(0.5),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![-1.5, 0.5, 2.5, 4.5, 6.5, 8.5]);
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![2.5, 4.5]);
-
-    // Single bucket
-    let buckets = generate_buckets(&histogram_req, 0.5, 0.75);
-    assert_eq!(buckets, vec![0.5]);
-
-    // no bucket
-    let buckets = generate_buckets(&histogram_req, f64::MAX, f64::MIN);
-    assert_eq!(buckets, vec![] as Vec<f64>);
-
-    // With extended_bounds
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        extended_bounds: Some(HistogramBounds {
-            min: 0.0,
-            max: 10.0,
-        }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // Single bucket, but extended_bounds
-    let buckets = generate_buckets(&histogram_req, 0.5, 0.75);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // no bucket, but extended_bounds
-    let buckets = generate_buckets(&histogram_req, f64::MAX, f64::MIN);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // With invalid extended_bounds
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        extended_bounds: Some(HistogramBounds { min: 3.0, max: 5.0 }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // With hard_bounds reducing
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        hard_bounds: Some(HistogramBounds { min: 3.0, max: 5.0 }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![2.0, 4.0]);
-
-    // With hard_bounds, extending has no effect
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        hard_bounds: Some(HistogramBounds {
-            min: 0.0,
-            max: 10.0,
-        }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![2.0, 4.0]);
-
-    // Blubber
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 4.0, 10.0);
-    assert_eq!(buckets, vec![4.0, 6.0, 8.0, 10.0]);
-}
-
 #[cfg(test)]
 mod tests {
 
@@ -1496,36 +1321,4 @@ mod tests {
 
         Ok(())
     }
-
-    #[test]
-    fn histogram_test_max_buckets_segments() -> crate::Result<()> {
-        let values = vec![0.0, 70000.0];
-
-        let index = get_test_index_from_values(true, &values)?;
-
-        let agg_req: Aggregations = vec![(
-            "my_interval".to_string(),
-            Aggregation::Bucket(BucketAggregation {
-                bucket_agg: BucketAggregationType::Histogram(HistogramAggregation {
-                    field: "score_f64".to_string(),
-                    interval: 1.0,
-                    ..Default::default()
-                }),
-                sub_aggregation: Default::default(),
-            }),
-        )]
-        .into_iter()
-        .collect();
-
-        let res = exec_request(agg_req, &index);
-
-        assert_eq!(
-            res.unwrap_err().to_string(),
-            "An invalid argument was passed: 'Aborting aggregation because too many buckets were \
-             created'"
-                .to_string()
-        );
-
-        Ok(())
-    }
 }

src/aggregation/bucket/histogram/mod.rs

@@ -1,4 +1,4 @@
-// mod date_histogram;
+mod date_histogram;
 mod histogram;
-// pub use date_histogram::*;
+pub use date_histogram::*;
 pub use histogram::*;

src/aggregation/bucket/mod.rs

@@ -21,28 +21,25 @@ use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
 pub use term_agg::*;
 
 /// Order for buckets in a bucket aggregation.
-#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize)]
+#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize, Default)]
 pub enum Order {
     /// Asc order
     #[serde(rename = "asc")]
     Asc,
     /// Desc order
     #[serde(rename = "desc")]
+    #[default]
     Desc,
 }
 
-impl Default for Order {
-    fn default() -> Self {
-        Order::Desc
-    }
-}
-
 #[derive(Clone, Debug, PartialEq)]
 /// Order property by which to apply the order
+#[derive(Default)]
 pub enum OrderTarget {
     /// The key of the bucket
     Key,
     /// The doc count of the bucket
+    #[default]
     Count,
     /// Order by value of the sub aggregation metric with identified by given `String`.
     ///
@@ -50,11 +47,6 @@ pub enum OrderTarget {
     SubAggregation(String),
 }
 
-impl Default for OrderTarget {
-    fn default() -> Self {
-        OrderTarget::Count
-    }
-}
 impl From<&str> for OrderTarget {
     fn from(val: &str) -> Self {
         match val {

src/aggregation/bucket/range.rs

@@ -1,24 +1,22 @@
 use std::fmt::Debug;
 use std::ops::Range;
 
-use columnar::MonotonicallyMappableToU64;
+use columnar::{ColumnType, MonotonicallyMappableToU64};
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationsWithAccessor, BucketAggregationWithAccessor,
-};
+use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
 use crate::aggregation::intermediate_agg_result::{
-    IntermediateBucketResult, IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
+    IntermediateAggregationResults, IntermediateBucketResult, IntermediateRangeBucketEntry,
+    IntermediateRangeBucketResult,
 };
 use crate::aggregation::segment_agg_result::{
-    BucketCount, GenericSegmentAggregationResultsCollector, SegmentAggregationCollector,
+    build_segment_agg_collector, BucketCount, SegmentAggregationCollector,
 };
 use crate::aggregation::{
-    f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
+    f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey, VecWithNames,
 };
-use crate::schema::Type;
-use crate::{DocId, TantivyError};
+use crate::TantivyError;
 
 /// Provide user-defined buckets to aggregate on.
 /// Two special buckets will automatically be created to cover the whole range of values.
@@ -128,14 +126,15 @@ pub(crate) struct SegmentRangeAndBucketEntry {
 pub struct SegmentRangeCollector {
     /// The buckets containing the aggregation data.
     buckets: Vec<SegmentRangeAndBucketEntry>,
-    field_type: Type,
+    column_type: ColumnType,
+    pub(crate) accessor_idx: usize,
 }
 
 #[derive(Clone)]
 pub(crate) struct SegmentRangeBucketEntry {
     pub key: Key,
     pub doc_count: u64,
-    pub sub_aggregation: Option<GenericSegmentAggregationResultsCollector>,
+    pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
     /// 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
@@ -174,12 +173,14 @@ impl SegmentRangeBucketEntry {
     }
 }
 
-impl SegmentRangeCollector {
-    pub fn into_intermediate_bucket_result(
-        self,
-        agg_with_accessor: &BucketAggregationWithAccessor,
-    ) -> crate::Result<IntermediateBucketResult> {
-        let field_type = self.field_type;
+impl SegmentAggregationCollector for SegmentRangeCollector {
+    fn into_intermediate_aggregations_result(
+        self: Box<Self>,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<IntermediateAggregationResults> {
+        let field_type = self.column_type;
+        let name = agg_with_accessor.buckets.keys[self.accessor_idx].to_string();
+        let sub_agg = &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
 
         let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
             .buckets
@@ -189,21 +190,77 @@ impl SegmentRangeCollector {
                     range_to_string(&range_bucket.range, &field_type)?,
                     range_bucket
                         .bucket
-                        .into_intermediate_bucket_entry(&agg_with_accessor.sub_aggregation)?,
+                        .into_intermediate_bucket_entry(sub_agg)?,
                 ))
             })
             .collect::<crate::Result<_>>()?;
 
-        Ok(IntermediateBucketResult::Range(
-            IntermediateRangeBucketResult { buckets },
-        ))
+        let bucket = IntermediateBucketResult::Range(IntermediateRangeBucketResult {
+            buckets,
+            column_type: Some(self.column_type),
+        });
+
+        let buckets = Some(VecWithNames::from_entries(vec![(name, bucket)]));
+
+        Ok(IntermediateAggregationResults {
+            metrics: None,
+            buckets,
+        })
     }
 
+    fn collect(
+        &mut self,
+        doc: crate::DocId,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        self.collect_block(&[doc], agg_with_accessor)
+    }
+
+    fn collect_block(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        let accessor = &agg_with_accessor.buckets.values[self.accessor_idx].accessor;
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+        for doc in docs {
+            for val in accessor.values_for_doc(*doc) {
+                let bucket_pos = self.get_bucket_pos(val);
+
+                let bucket = &mut self.buckets[bucket_pos];
+
+                bucket.bucket.doc_count += 1;
+                if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
+                    sub_aggregation.collect(*doc, sub_aggregation_accessor)?;
+                }
+            }
+        }
+
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        for bucket in self.buckets.iter_mut() {
+            if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
+                sub_agg.flush(sub_aggregation_accessor)?;
+            }
+        }
+
+        Ok(())
+    }
+}
+
+impl SegmentRangeCollector {
     pub(crate) fn from_req_and_validate(
         req: &RangeAggregation,
         sub_aggregation: &AggregationsWithAccessor,
         bucket_count: &BucketCount,
-        field_type: Type,
+        field_type: ColumnType,
+        accessor_idx: usize,
     ) -> crate::Result<Self> {
         // The range input on the request is f64.
         // We need to convert to u64 ranges, because we read the values as u64.
@@ -229,11 +286,7 @@ impl SegmentRangeCollector {
                 let sub_aggregation = if sub_aggregation.is_empty() {
                     None
                 } else {
-                    Some(
-                        GenericSegmentAggregationResultsCollector::from_req_and_validate(
-                            sub_aggregation,
-                        )?,
-                    )
+                    Some(build_segment_agg_collector(sub_aggregation)?)
                 };
 
                 Ok(SegmentRangeAndBucketEntry {
@@ -254,52 +307,11 @@ impl SegmentRangeCollector {
 
         Ok(SegmentRangeCollector {
             buckets,
-            field_type,
+            column_type: field_type,
+            accessor_idx,
         })
     }
 
-    #[inline]
-    pub(crate) fn collect_block(
-        &mut self,
-        docs: &[DocId],
-        bucket_with_accessor: &BucketAggregationWithAccessor,
-        force_flush: bool,
-    ) -> crate::Result<()> {
-        let accessor = &bucket_with_accessor.accessor;
-        for doc in docs {
-            for val in accessor.values(*doc) {
-                let bucket_pos = self.get_bucket_pos(val);
-                self.increment_bucket(bucket_pos, *doc, &bucket_with_accessor.sub_aggregation)?;
-            }
-        }
-
-        if force_flush {
-            for bucket in &mut self.buckets {
-                if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
-                    sub_aggregation
-                        .flush_staged_docs(&bucket_with_accessor.sub_aggregation, force_flush)?;
-                }
-            }
-        }
-        Ok(())
-    }
-
-    #[inline]
-    fn increment_bucket(
-        &mut self,
-        bucket_pos: usize,
-        doc: DocId,
-        bucket_with_accessor: &AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        let bucket = &mut self.buckets[bucket_pos];
-
-        bucket.bucket.doc_count += 1;
-        if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
-            sub_aggregation.collect(doc, bucket_with_accessor)?;
-        }
-        Ok(())
-    }
-
     #[inline]
     fn get_bucket_pos(&self, val: u64) -> usize {
         let pos = self
@@ -325,7 +337,7 @@ impl SegmentRangeCollector {
 /// more computational expensive when many documents are hit.
 fn to_u64_range(
     range: &RangeAggregationRange,
-    field_type: &Type,
+    field_type: &ColumnType,
 ) -> crate::Result<InternalRangeAggregationRange> {
     let start = if let Some(from) = range.from {
         f64_to_fastfield_u64(from, field_type)
@@ -351,7 +363,7 @@ fn to_u64_range(
 /// beginning and end and filling gaps.
 fn extend_validate_ranges(
     buckets: &[RangeAggregationRange],
-    field_type: &Type,
+    field_type: &ColumnType,
 ) -> crate::Result<Vec<InternalRangeAggregationRange>> {
     let mut converted_buckets = buckets
         .iter()
@@ -393,13 +405,16 @@ fn extend_validate_ranges(
     Ok(converted_buckets)
 }
 
-pub(crate) fn range_to_string(range: &Range<u64>, field_type: &Type) -> crate::Result<String> {
+pub(crate) fn range_to_string(
+    range: &Range<u64>,
+    field_type: &ColumnType,
+) -> crate::Result<String> {
     // is_start is there for malformed requests, e.g. ig the user passes the range u64::MIN..0.0,
     // it should be rendered as "*-0" and not "*-*"
     let to_str = |val: u64, is_start: bool| {
         if (is_start && val == u64::MIN) || (!is_start && val == u64::MAX) {
             Ok("*".to_string())
-        } else if *field_type == Type::Date {
+        } else if *field_type == ColumnType::DateTime {
             let val = i64::from_u64(val);
             format_date(val)
         } else {
@@ -414,7 +429,7 @@ pub(crate) fn range_to_string(range: &Range<u64>, field_type: &Type) -> crate::R
     ))
 }
 
-pub(crate) fn range_to_key(range: &Range<u64>, field_type: &Type) -> crate::Result<Key> {
+pub(crate) fn range_to_key(range: &Range<u64>, field_type: &ColumnType) -> crate::Result<Key> {
     Ok(Key::Str(range_to_string(range, field_type)?))
 }
 
@@ -426,8 +441,9 @@ mod tests {
 
     use super::*;
     use crate::aggregation::agg_req::{
-        Aggregation, Aggregations, BucketAggregation, BucketAggregationType,
+        Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
     };
+    use crate::aggregation::metric::AverageAggregation;
     use crate::aggregation::tests::{
         exec_request, exec_request_with_query, get_test_index_2_segments,
         get_test_index_with_num_docs,
@@ -435,7 +451,7 @@ mod tests {
 
     pub fn get_collector_from_ranges(
         ranges: Vec<RangeAggregationRange>,
-        field_type: Type,
+        field_type: ColumnType,
     ) -> SegmentRangeCollector {
         let req = RangeAggregation {
             field: "dummy".to_string(),
@@ -448,6 +464,7 @@ mod tests {
             &Default::default(),
             &Default::default(),
             field_type,
+            0,
         )
         .expect("unexpected error")
     }
@@ -484,6 +501,47 @@ mod tests {
         Ok(())
     }
 
+    #[test]
+    fn range_fraction_test_with_sub_agg() -> crate::Result<()> {
+        let index = get_test_index_with_num_docs(false, 100)?;
+
+        let sub_agg_req: Aggregations = vec![(
+            "score_f64".to_string(),
+            Aggregation::Metric(MetricAggregation::Average(
+                AverageAggregation::from_field_name("score_f64".to_string()),
+            )),
+        )]
+        .into_iter()
+        .collect();
+
+        let agg_req: Aggregations = vec![(
+            "range".to_string(),
+            Aggregation::Bucket(BucketAggregation {
+                bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                    field: "fraction_f64".to_string(),
+                    ranges: vec![(0f64..0.1f64).into(), (0.1f64..0.2f64).into()],
+                    ..Default::default()
+                }),
+                sub_aggregation: sub_agg_req,
+            }),
+        )]
+        .into_iter()
+        .collect();
+
+        let res = exec_request_with_query(agg_req, &index, None)?;
+
+        assert_eq!(res["range"]["buckets"][0]["key"], "*-0");
+        assert_eq!(res["range"]["buckets"][0]["doc_count"], 0);
+        assert_eq!(res["range"]["buckets"][1]["key"], "0-0.1");
+        assert_eq!(res["range"]["buckets"][1]["doc_count"], 10);
+        assert_eq!(res["range"]["buckets"][2]["key"], "0.1-0.2");
+        assert_eq!(res["range"]["buckets"][2]["doc_count"], 10);
+        assert_eq!(res["range"]["buckets"][3]["key"], "0.2-*");
+        assert_eq!(res["range"]["buckets"][3]["doc_count"], 80);
+
+        Ok(())
+    }
+
     #[test]
     fn range_keyed_buckets_test() -> crate::Result<()> {
         let index = get_test_index_with_num_docs(false, 100)?;
@@ -683,7 +741,7 @@ mod tests {
     #[test]
     fn bucket_test_extend_range_hole() {
         let buckets = vec![(10f64..20f64).into(), (30f64..40f64).into()];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(buckets[0].range.start, u64::MIN);
@@ -706,7 +764,7 @@ mod tests {
             (10f64..20f64).into(),
             (20f64..f64::MAX).into(),
         ];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(buckets[0].range.start, u64::MIN);
@@ -721,7 +779,7 @@ mod tests {
     #[test]
     fn bucket_range_test_negative_vals() {
         let buckets = vec![(-10f64..-1f64).into()];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(&buckets[0].bucket.key.to_string(), "*--10");
@@ -730,7 +788,7 @@ mod tests {
     #[test]
     fn bucket_range_test_positive_vals() {
         let buckets = vec![(0f64..10f64).into()];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(&buckets[0].bucket.key.to_string(), "*-0");
@@ -740,7 +798,7 @@ mod tests {
     #[test]
     fn range_binary_search_test_u64() {
         let check_ranges = |ranges: Vec<RangeAggregationRange>| {
-            let collector = get_collector_from_ranges(ranges, Type::U64);
+            let collector = get_collector_from_ranges(ranges, ColumnType::U64);
             let search = |val: u64| collector.get_bucket_pos(val);
 
             assert_eq!(search(u64::MIN), 0);
@@ -786,7 +844,7 @@ mod tests {
     fn range_binary_search_test_f64() {
         let ranges = vec![(10.0..100.0).into()];
 
-        let collector = get_collector_from_ranges(ranges, Type::F64);
+        let collector = get_collector_from_ranges(ranges, ColumnType::F64);
         let search = |val: u64| collector.get_bucket_pos(val);
 
         assert_eq!(search(u64::MIN), 0);
@@ -821,7 +879,7 @@ mod bench {
             buckets.push((bucket_start..bucket_start + bucket_size as f64).into())
         }
 
-        get_collector_from_ranges(buckets, Type::U64)
+        get_collector_from_ranges(buckets, ColumnType::U64)
     }
 
     fn get_rand_docs(total_docs: u64, num_docs_returned: u64) -> Vec<u64> {

src/aggregation/bucket/term_agg.rs

@@ -1,5 +1,6 @@
 use std::fmt::Debug;
 
+use columnar::{Cardinality, ColumnType};
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 
@@ -8,13 +9,15 @@ use crate::aggregation::agg_req_with_accessor::{
     AggregationsWithAccessor, BucketAggregationWithAccessor,
 };
 use crate::aggregation::intermediate_agg_result::{
-    IntermediateBucketResult, IntermediateTermBucketEntry, IntermediateTermBucketResult,
+    IntermediateAggregationResults, IntermediateBucketResult, IntermediateTermBucketEntry,
+    IntermediateTermBucketResult,
 };
 use crate::aggregation::segment_agg_result::{
     build_segment_agg_collector, SegmentAggregationCollector,
 };
+use crate::aggregation::{f64_from_fastfield_u64, Key, VecWithNames};
 use crate::error::DataCorruption;
-use crate::{DocId, TantivyError};
+use crate::TantivyError;
 
 /// Creates a bucket for every unique term and counts the number of occurences.
 /// Note that doc_count in the response buckets equals term count here.
@@ -22,6 +25,10 @@ use crate::{DocId, TantivyError};
 /// If the text is untokenized and single value, that means one term per document and therefore it
 /// is in fact doc count.
 ///
+/// ## Prerequisite
+/// Term aggregations work only on [fast fields](`crate::fastfield`) of type `u64`, `f64`, `i64` and
+/// text.
+///
 /// ### Terminology
 /// Shard parameters are supposed to be equivalent to elasticsearch shard parameter.
 /// Since they are
@@ -196,9 +203,9 @@ impl TermsAggregationInternal {
 }
 
 #[derive(Clone, Debug, Default)]
-/// Container to store term_ids and their buckets.
+/// Container to store term_ids/or u64 values and their buckets.
 struct TermBuckets {
-    pub(crate) entries: FxHashMap<u32, TermBucketEntry>,
+    pub(crate) entries: FxHashMap<u64, TermBucketEntry>,
 }
 
 #[derive(Clone, Default)]
@@ -244,7 +251,7 @@ impl TermBuckets {
     fn force_flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
         for entry in &mut self.entries.values_mut() {
             if let Some(sub_aggregations) = entry.sub_aggregations.as_mut() {
-                sub_aggregations.flush_staged_docs(agg_with_accessor, false)?;
+                sub_aggregations.flush(agg_with_accessor)?;
             }
         }
         Ok(())
@@ -259,6 +266,8 @@ pub struct SegmentTermCollector {
     term_buckets: TermBuckets,
     req: TermsAggregationInternal,
     blueprint: Option<Box<dyn SegmentAggregationCollector>>,
+    field_type: ColumnType,
+    accessor_idx: usize,
 }
 
 pub(crate) fn get_agg_name_and_property(name: &str) -> (&str, &str) {
@@ -266,10 +275,86 @@ pub(crate) fn get_agg_name_and_property(name: &str) -> (&str, &str) {
     (agg_name, agg_property)
 }
 
+impl SegmentAggregationCollector for SegmentTermCollector {
+    fn into_intermediate_aggregations_result(
+        self: Box<Self>,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<IntermediateAggregationResults> {
+        let name = agg_with_accessor.buckets.keys[self.accessor_idx].to_string();
+        let agg_with_accessor = &agg_with_accessor.buckets.values[self.accessor_idx];
+
+        let bucket = self.into_intermediate_bucket_result(agg_with_accessor)?;
+        let buckets = Some(VecWithNames::from_entries(vec![(name, bucket)]));
+
+        Ok(IntermediateAggregationResults {
+            metrics: None,
+            buckets,
+        })
+    }
+
+    fn collect(
+        &mut self,
+        doc: crate::DocId,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        self.collect_block(&[doc], agg_with_accessor)
+    }
+
+    fn collect_block(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        let accessor = &agg_with_accessor.buckets.values[self.accessor_idx].accessor;
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        if accessor.get_cardinality() == Cardinality::Full {
+            for doc in docs {
+                let term_id = accessor.values.get_val(*doc);
+                let entry = self
+                    .term_buckets
+                    .entries
+                    .entry(term_id)
+                    .or_insert_with(|| TermBucketEntry::from_blueprint(&self.blueprint));
+                entry.doc_count += 1;
+                if let Some(sub_aggregations) = entry.sub_aggregations.as_mut() {
+                    sub_aggregations.collect(*doc, sub_aggregation_accessor)?;
+                }
+            }
+        } else {
+            for doc in docs {
+                for term_id in accessor.values_for_doc(*doc) {
+                    let entry = self
+                        .term_buckets
+                        .entries
+                        .entry(term_id)
+                        .or_insert_with(|| TermBucketEntry::from_blueprint(&self.blueprint));
+                    entry.doc_count += 1;
+                    if let Some(sub_aggregations) = entry.sub_aggregations.as_mut() {
+                        sub_aggregations.collect(*doc, sub_aggregation_accessor)?;
+                    }
+                }
+            }
+        }
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        self.term_buckets.force_flush(sub_aggregation_accessor)?;
+        Ok(())
+    }
+}
+
 impl SegmentTermCollector {
     pub(crate) fn from_req_and_validate(
         req: &TermsAggregation,
         sub_aggregations: &AggregationsWithAccessor,
+        field_type: ColumnType,
+        accessor_idx: usize,
     ) -> crate::Result<Self> {
         let term_buckets = TermBuckets::default();
 
@@ -299,6 +384,8 @@ impl SegmentTermCollector {
             req: TermsAggregationInternal::from_req(req),
             term_buckets,
             blueprint,
+            field_type,
+            accessor_idx,
         })
     }
 
@@ -306,7 +393,7 @@ impl SegmentTermCollector {
         self,
         agg_with_accessor: &BucketAggregationWithAccessor,
     ) -> crate::Result<IntermediateBucketResult> {
-        let mut entries: Vec<(u32, TermBucketEntry)> =
+        let mut entries: Vec<(u64, TermBucketEntry)> =
             self.term_buckets.entries.into_iter().collect();
 
         let order_by_sub_aggregation =
@@ -343,41 +430,52 @@ impl SegmentTermCollector {
             cut_off_buckets(&mut entries, self.req.segment_size as usize)
         };
 
-        let inverted_index = agg_with_accessor
-            .str_dict_column
-            .as_ref()
-            .expect("internal error: inverted index not loaded for term aggregation");
-        let term_dict = inverted_index;
+        let mut dict: FxHashMap<Key, IntermediateTermBucketEntry> = Default::default();
+        dict.reserve(entries.len());
+        if self.field_type == ColumnType::Str {
+            let term_dict = agg_with_accessor
+                .str_dict_column
+                .as_ref()
+                .expect("internal error: term dictionary not found for term aggregation");
 
-        let mut dict: FxHashMap<String, IntermediateTermBucketEntry> = Default::default();
-        let mut buffer = String::new();
-        for (term_id, entry) in entries {
-            if !term_dict.ord_to_str(term_id as u64, &mut buffer)? {
-                return Err(TantivyError::InternalError(format!(
-                    "Couldn't find term_id {} in dict",
-                    term_id
-                )));
-            }
-            dict.insert(
-                buffer.to_string(),
-                entry.into_intermediate_bucket_entry(&agg_with_accessor.sub_aggregation)?,
-            );
-        }
-        if self.req.min_doc_count == 0 {
-            // TODO: Handle rev streaming for descending sorting by keys
-            let mut stream = term_dict.dictionary().stream()?;
-            while let Some((key, _ord)) = stream.next() {
-                if dict.len() >= self.req.segment_size as usize {
-                    break;
+            let mut buffer = String::new();
+            for (term_id, entry) in entries {
+                if !term_dict.ord_to_str(term_id, &mut buffer)? {
+                    return Err(TantivyError::InternalError(format!(
+                        "Couldn't find term_id {} in dict",
+                        term_id
+                    )));
                 }
+                dict.insert(
+                    Key::Str(buffer.to_string()),
+                    entry.into_intermediate_bucket_entry(&agg_with_accessor.sub_aggregation)?,
+                );
+            }
+            if self.req.min_doc_count == 0 {
+                // TODO: Handle rev streaming for descending sorting by keys
+                let mut stream = term_dict.dictionary().stream()?;
+                while let Some((key, _ord)) = stream.next() {
+                    if dict.len() >= self.req.segment_size as usize {
+                        break;
+                    }
 
-                let key = std::str::from_utf8(key)
-                    .map_err(|utf8_err| DataCorruption::comment_only(utf8_err.to_string()))?;
-                if !dict.contains_key(key) {
-                    dict.insert(key.to_owned(), Default::default());
+                    let key = Key::Str(
+                        std::str::from_utf8(key)
+                            .map_err(|utf8_err| DataCorruption::comment_only(utf8_err.to_string()))?
+                            .to_string(),
+                    );
+                    dict.entry(key).or_default();
                 }
             }
-        }
+        } else {
+            for (val, entry) in entries {
+                let val = f64_from_fastfield_u64(val, &self.field_type);
+                dict.insert(
+                    Key::F64(val),
+                    entry.into_intermediate_bucket_entry(&agg_with_accessor.sub_aggregation)?,
+                );
+            }
+        };
 
         Ok(IntermediateBucketResult::Terms(
             IntermediateTermBucketResult {
@@ -387,36 +485,6 @@ impl SegmentTermCollector {
             },
         ))
     }
-
-    #[inline]
-    pub(crate) fn collect_block(
-        &mut self,
-        docs: &[DocId],
-        bucket_with_accessor: &BucketAggregationWithAccessor,
-        force_flush: bool,
-    ) -> crate::Result<()> {
-        let accessor = &bucket_with_accessor.accessor;
-
-        for doc in docs {
-            for term_id in accessor.values(*doc) {
-                let entry = self
-                    .term_buckets
-                    .entries
-                    .entry(term_id as u32)
-                    .or_insert_with(|| TermBucketEntry::from_blueprint(&self.blueprint));
-                entry.doc_count += 1;
-                if let Some(sub_aggregations) = entry.sub_aggregations.as_mut() {
-                    sub_aggregations.collect(*doc, &bucket_with_accessor.sub_aggregation)?;
-                }
-            }
-        }
-
-        if force_flush {
-            self.term_buckets
-                .force_flush(&bucket_with_accessor.sub_aggregation)?;
-        }
-        Ok(())
-    }
 }
 
 pub(crate) trait GetDocCount {
@@ -427,6 +495,11 @@ impl GetDocCount for (u32, TermBucketEntry) {
         self.1.doc_count
     }
 }
+impl GetDocCount for (u64, TermBucketEntry) {
+    fn doc_count(&self) -> u64 {
+        self.1.doc_count
+    }
+}
 impl GetDocCount for (String, IntermediateTermBucketEntry) {
     fn doc_count(&self) -> u64 {
         self.1.doc_count
@@ -455,8 +528,7 @@ pub(crate) fn cut_off_buckets<T: GetDocCount + Debug>(
 mod tests {
     use super::*;
     use crate::aggregation::agg_req::{
-        get_term_dict_field_names, Aggregation, Aggregations, BucketAggregation,
-        BucketAggregationType, MetricAggregation,
+        Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
     };
     use crate::aggregation::metric::{AverageAggregation, StatsAggregation};
     use crate::aggregation::tests::{
@@ -557,12 +629,6 @@ mod tests {
             serde_json::Value::Null
         );
         assert_eq!(res["my_texts"]["sum_other_doc_count"], 0); // TODO sum_other_doc_count with min_doc_count
-
-        assert_eq!(
-            get_term_dict_field_names(&agg_req),
-            vec!["string_id".to_string(),].into_iter().collect()
-        );
-
         Ok(())
     }
 
@@ -577,7 +643,8 @@ mod tests {
     fn terms_aggregation_test_order_count_merge_segment(merge_segments: bool) -> crate::Result<()> {
         let segment_and_terms = vec![
             vec![(5.0, "terma".to_string())],
-            vec![(4.0, "termb".to_string())],
+            vec![(2.0, "termb".to_string())],
+            vec![(2.0, "terma".to_string())],
             vec![(1.0, "termc".to_string())],
             vec![(1.0, "termc".to_string())],
             vec![(1.0, "termc".to_string())],
@@ -618,7 +685,7 @@ mod tests {
                     }),
                     ..Default::default()
                 }),
-                sub_aggregation: sub_agg,
+                sub_aggregation: sub_agg.clone(),
             }),
         )]
         .into_iter()
@@ -627,15 +694,114 @@ mod tests {
         let res = exec_request(agg_req, &index)?;
         assert_eq!(res["my_texts"]["buckets"][0]["key"], "termb");
         assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
+        assert_eq!(res["my_texts"]["buckets"][0]["avg_score"]["value"], 5.0);
 
         assert_eq!(res["my_texts"]["buckets"][1]["key"], "termc");
         assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 3);
+        assert_eq!(res["my_texts"]["buckets"][1]["avg_score"]["value"], 1.0);
 
         assert_eq!(res["my_texts"]["buckets"][2]["key"], "terma");
-        assert_eq!(res["my_texts"]["buckets"][2]["doc_count"], 5);
+        assert_eq!(res["my_texts"]["buckets"][2]["doc_count"], 6);
+        assert_eq!(res["my_texts"]["buckets"][2]["avg_score"]["value"], 4.5);
 
         assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
 
+        // Agg on non string
+        //
+        let agg_req: Aggregations = vec![
+            (
+                "my_scores1".to_string(),
+                Aggregation::Bucket(BucketAggregation {
+                    bucket_agg: BucketAggregationType::Terms(TermsAggregation {
+                        field: "score".to_string(),
+                        order: Some(CustomOrder {
+                            order: Order::Asc,
+                            target: OrderTarget::Count,
+                        }),
+                        ..Default::default()
+                    }),
+                    sub_aggregation: sub_agg.clone(),
+                }),
+            ),
+            (
+                "my_scores2".to_string(),
+                Aggregation::Bucket(BucketAggregation {
+                    bucket_agg: BucketAggregationType::Terms(TermsAggregation {
+                        field: "score_f64".to_string(),
+                        order: Some(CustomOrder {
+                            order: Order::Asc,
+                            target: OrderTarget::Count,
+                        }),
+                        ..Default::default()
+                    }),
+                    sub_aggregation: sub_agg.clone(),
+                }),
+            ),
+            (
+                "my_scores3".to_string(),
+                Aggregation::Bucket(BucketAggregation {
+                    bucket_agg: BucketAggregationType::Terms(TermsAggregation {
+                        field: "score_i64".to_string(),
+                        order: Some(CustomOrder {
+                            order: Order::Asc,
+                            target: OrderTarget::Count,
+                        }),
+                        ..Default::default()
+                    }),
+                    sub_aggregation: sub_agg,
+                }),
+            ),
+        ]
+        .into_iter()
+        .collect();
+
+        let res = exec_request(agg_req, &index)?;
+        assert_eq!(res["my_scores1"]["buckets"][0]["key"], 8.0);
+        assert_eq!(res["my_scores1"]["buckets"][0]["doc_count"], 1);
+        assert_eq!(res["my_scores1"]["buckets"][0]["avg_score"]["value"], 8.0);
+
+        assert_eq!(res["my_scores1"]["buckets"][1]["key"], 2.0);
+        assert_eq!(res["my_scores1"]["buckets"][1]["doc_count"], 2);
+        assert_eq!(res["my_scores1"]["buckets"][1]["avg_score"]["value"], 2.0);
+
+        assert_eq!(res["my_scores1"]["buckets"][2]["key"], 1.0);
+        assert_eq!(res["my_scores1"]["buckets"][2]["doc_count"], 3);
+        assert_eq!(res["my_scores1"]["buckets"][2]["avg_score"]["value"], 1.0);
+
+        assert_eq!(res["my_scores1"]["buckets"][3]["key"], 5.0);
+        assert_eq!(res["my_scores1"]["buckets"][3]["doc_count"], 5);
+        assert_eq!(res["my_scores1"]["buckets"][3]["avg_score"]["value"], 5.0);
+
+        assert_eq!(res["my_scores1"]["sum_other_doc_count"], 0);
+
+        assert_eq!(res["my_scores2"]["buckets"][0]["key"], 8.0);
+        assert_eq!(res["my_scores2"]["buckets"][0]["doc_count"], 1);
+        assert_eq!(res["my_scores2"]["buckets"][0]["avg_score"]["value"], 8.0);
+
+        assert_eq!(res["my_scores2"]["buckets"][1]["key"], 2.0);
+        assert_eq!(res["my_scores2"]["buckets"][1]["doc_count"], 2);
+        assert_eq!(res["my_scores2"]["buckets"][1]["avg_score"]["value"], 2.0);
+
+        assert_eq!(res["my_scores2"]["buckets"][2]["key"], 1.0);
+        assert_eq!(res["my_scores2"]["buckets"][2]["doc_count"], 3);
+        assert_eq!(res["my_scores2"]["buckets"][2]["avg_score"]["value"], 1.0);
+
+        assert_eq!(res["my_scores2"]["sum_other_doc_count"], 0);
+
+        assert_eq!(res["my_scores3"]["buckets"][0]["key"], 8.0);
+        assert_eq!(res["my_scores3"]["buckets"][0]["doc_count"], 1);
+        assert_eq!(res["my_scores3"]["buckets"][0]["avg_score"]["value"], 8.0);
+
+        assert_eq!(res["my_scores3"]["buckets"][1]["key"], 2.0);
+        assert_eq!(res["my_scores3"]["buckets"][1]["doc_count"], 2);
+        assert_eq!(res["my_scores3"]["buckets"][1]["avg_score"]["value"], 2.0);
+
+        assert_eq!(res["my_scores3"]["buckets"][2]["key"], 1.0);
+        assert_eq!(res["my_scores3"]["buckets"][2]["doc_count"], 3);
+        assert_eq!(res["my_scores3"]["buckets"][2]["avg_score"]["value"], 1.0);
+
+        assert_eq!(res["my_scores3"]["sum_other_doc_count"], 0);
+
         Ok(())
     }
 

src/aggregation/buf_collector.rs

@@ -0,0 +1,79 @@
+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 {
+    fn into_intermediate_aggregations_result(
+        self: Box<Self>,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<IntermediateAggregationResults> {
+        Box::new(self.collector).into_intermediate_aggregations_result(agg_with_accessor)
+    }
+
+    fn collect(
+        &mut self,
+        doc: crate::DocId,
+        agg_with_accessor: &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(())
+    }
+
+    fn collect_block(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        for doc in docs {
+            self.collect(*doc, agg_with_accessor)?;
+        }
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &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/collector.rs

@@ -3,11 +3,11 @@ use std::rc::Rc;
 use super::agg_req::Aggregations;
 use super::agg_req_with_accessor::AggregationsWithAccessor;
 use super::agg_result::AggregationResults;
+use super::buf_collector::BufAggregationCollector;
 use super::intermediate_agg_result::IntermediateAggregationResults;
 use super::segment_agg_result::{build_segment_agg_collector, SegmentAggregationCollector};
 use crate::aggregation::agg_req_with_accessor::get_aggs_with_accessor_and_validate;
 use crate::collector::{Collector, SegmentCollector};
-use crate::schema::Schema;
 use crate::{SegmentReader, TantivyError};
 
 /// The default max bucket count, before the aggregation fails.
@@ -17,7 +17,6 @@ pub const MAX_BUCKET_COUNT: u32 = 65000;
 ///
 /// The collector collects all aggregations by the underlying aggregation request.
 pub struct AggregationCollector {
-    schema: Schema,
     agg: Aggregations,
     max_bucket_count: u32,
 }
@@ -27,9 +26,8 @@ impl AggregationCollector {
     ///
     /// Aggregation fails when the total bucket count is higher than max_bucket_count.
     /// max_bucket_count will default to `MAX_BUCKET_COUNT` (65000) when unset
-    pub fn from_aggs(agg: Aggregations, max_bucket_count: Option<u32>, schema: Schema) -> Self {
+    pub fn from_aggs(agg: Aggregations, max_bucket_count: Option<u32>) -> Self {
         Self {
-            schema,
             agg,
             max_bucket_count: max_bucket_count.unwrap_or(MAX_BUCKET_COUNT),
         }
@@ -116,7 +114,7 @@ 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_bucket_result(self.agg.clone(), &self.schema)
+        res.into_final_bucket_result(self.agg.clone())
     }
 }
 
@@ -137,7 +135,7 @@ fn merge_fruits(
 /// `AggregationSegmentCollector` does the aggregation collection on a segment.
 pub struct AggregationSegmentCollector {
     aggs_with_accessor: AggregationsWithAccessor,
-    result: Box<dyn SegmentAggregationCollector>,
+    result: BufAggregationCollector,
     error: Option<TantivyError>,
 }
 
@@ -151,7 +149,8 @@ impl AggregationSegmentCollector {
     ) -> crate::Result<Self> {
         let aggs_with_accessor =
             get_aggs_with_accessor_and_validate(agg, reader, Rc::default(), max_bucket_count)?;
-        let result = build_segment_agg_collector(&aggs_with_accessor)?;
+        let result =
+            BufAggregationCollector::new(build_segment_agg_collector(&aggs_with_accessor)?);
         Ok(AggregationSegmentCollector {
             aggs_with_accessor,
             result,
@@ -177,9 +176,7 @@ impl SegmentCollector for AggregationSegmentCollector {
         if let Some(err) = self.error {
             return Err(err);
         }
-        self.result
-            .flush_staged_docs(&self.aggs_with_accessor, true)?;
-        self.result
-            .into_intermediate_aggregations_result(&self.aggs_with_accessor)
+        self.result.flush(&self.aggs_with_accessor)?;
+        Box::new(self.result).into_intermediate_aggregations_result(&self.aggs_with_accessor)
     }
 }

src/aggregation/error.rs

@@ -0,0 +1,9 @@
+use super::bucket::DateHistogramParseError;
+
+/// Error that may occur when opening a directory
+#[derive(Debug, Clone, PartialEq, Eq, Error)]
+pub enum AggregationError {
+    /// Failed to open the directory.
+    #[error("Date histogram parse error: {0:?}")]
+    DateHistogramParseError(#[from] DateHistogramParseError),
+}

src/aggregation/intermediate_agg_result.rs

@@ -4,6 +4,7 @@
 
 use std::cmp::Ordering;
 
+use columnar::ColumnType;
 use itertools::Itertools;
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
@@ -21,11 +22,9 @@ use super::metric::{
     IntermediateAverage, IntermediateCount, IntermediateMax, IntermediateMin, IntermediateStats,
     IntermediateSum,
 };
-use super::segment_agg_result::SegmentMetricResultCollector;
 use super::{format_date, Key, SerializedKey, VecWithNames};
 use crate::aggregation::agg_result::{AggregationResults, BucketEntries, BucketEntry};
 use crate::aggregation::bucket::TermsAggregationInternal;
-use crate::schema::Schema;
 
 /// Contains the intermediate aggregation result, which is optimized to be merged with other
 /// intermediate results.
@@ -39,12 +38,8 @@ pub struct IntermediateAggregationResults {
 
 impl IntermediateAggregationResults {
     /// Convert intermediate result and its aggregation request to the final result.
-    pub fn into_final_bucket_result(
-        self,
-        req: Aggregations,
-        schema: &Schema,
-    ) -> crate::Result<AggregationResults> {
-        self.into_final_bucket_result_internal(&(req.into()), schema)
+    pub fn into_final_bucket_result(self, req: Aggregations) -> crate::Result<AggregationResults> {
+        self.into_final_bucket_result_internal(&(req.into()))
     }
 
     /// Convert intermediate result and its aggregation request to the final result.
@@ -54,7 +49,6 @@ impl IntermediateAggregationResults {
     pub(crate) fn into_final_bucket_result_internal(
         self,
         req: &AggregationsInternal,
-        schema: &Schema,
     ) -> crate::Result<AggregationResults> {
         // Important assumption:
         // When the tree contains buckets/metric, we expect it to have all buckets/metrics from the
@@ -62,11 +56,11 @@ impl IntermediateAggregationResults {
         let mut results: FxHashMap<String, AggregationResult> = FxHashMap::default();
 
         if let Some(buckets) = self.buckets {
-            convert_and_add_final_buckets_to_result(&mut results, buckets, &req.buckets, schema)?
+            convert_and_add_final_buckets_to_result(&mut results, buckets, &req.buckets)?
         } else {
             // When there are no buckets, we create empty buckets, so that the serialized json
             // format is constant
-            add_empty_final_buckets_to_result(&mut results, &req.buckets, schema)?
+            add_empty_final_buckets_to_result(&mut results, &req.buckets)?
         };
 
         if let Some(metrics) = self.metrics {
@@ -167,12 +161,10 @@ fn add_empty_final_metrics_to_result(
 fn add_empty_final_buckets_to_result(
     results: &mut FxHashMap<String, AggregationResult>,
     req_buckets: &VecWithNames<BucketAggregationInternal>,
-    schema: &Schema,
 ) -> crate::Result<()> {
     let requested_buckets = req_buckets.iter();
     for (key, req) in requested_buckets {
-        let empty_bucket =
-            AggregationResult::BucketResult(BucketResult::empty_from_req(req, schema)?);
+        let empty_bucket = AggregationResult::BucketResult(BucketResult::empty_from_req(req)?);
         results.insert(key.to_string(), empty_bucket);
     }
     Ok(())
@@ -182,13 +174,12 @@ fn convert_and_add_final_buckets_to_result(
     results: &mut FxHashMap<String, AggregationResult>,
     buckets: VecWithNames<IntermediateBucketResult>,
     req_buckets: &VecWithNames<BucketAggregationInternal>,
-    schema: &Schema,
 ) -> crate::Result<()> {
     assert_eq!(buckets.len(), req_buckets.len());
 
     let buckets_with_request = buckets.into_iter().zip(req_buckets.values());
     for ((key, bucket), req) in buckets_with_request {
-        let result = AggregationResult::BucketResult(bucket.into_final_bucket_result(req, schema)?);
+        let result = AggregationResult::BucketResult(bucket.into_final_bucket_result(req)?);
         results.insert(key, result);
     }
     Ok(())
@@ -220,32 +211,6 @@ pub enum IntermediateMetricResult {
     Sum(IntermediateSum),
 }
 
-impl From<SegmentMetricResultCollector> for IntermediateMetricResult {
-    fn from(tree: SegmentMetricResultCollector) -> Self {
-        use super::metric::SegmentStatsType;
-        match tree {
-            SegmentMetricResultCollector::Stats(collector) => match collector.collecting_for {
-                SegmentStatsType::Average => IntermediateMetricResult::Average(
-                    IntermediateAverage::from_collector(collector),
-                ),
-                SegmentStatsType::Count => {
-                    IntermediateMetricResult::Count(IntermediateCount::from_collector(collector))
-                }
-                SegmentStatsType::Max => {
-                    IntermediateMetricResult::Max(IntermediateMax::from_collector(collector))
-                }
-                SegmentStatsType::Min => {
-                    IntermediateMetricResult::Min(IntermediateMin::from_collector(collector))
-                }
-                SegmentStatsType::Stats => IntermediateMetricResult::Stats(collector.stats),
-                SegmentStatsType::Sum => {
-                    IntermediateMetricResult::Sum(IntermediateSum::from_collector(collector))
-                }
-            },
-        }
-    }
-}
-
 impl IntermediateMetricResult {
     pub(crate) fn empty_from_req(req: &MetricAggregation) -> Self {
         match req {
@@ -309,6 +274,8 @@ pub enum IntermediateBucketResult {
     /// This is the histogram entry for a bucket, which contains a key, count, and optionally
     /// sub_aggregations.
     Histogram {
+        /// The column_type of the underlying `Column`
+        column_type: Option<ColumnType>,
         /// The buckets
         buckets: Vec<IntermediateHistogramBucketEntry>,
     },
@@ -320,7 +287,6 @@ impl IntermediateBucketResult {
     pub(crate) fn into_final_bucket_result(
         self,
         req: &BucketAggregationInternal,
-        schema: &Schema,
     ) -> crate::Result<BucketResult> {
         match self {
             IntermediateBucketResult::Range(range_res) => {
@@ -330,9 +296,9 @@ impl IntermediateBucketResult {
                     .map(|bucket| {
                         bucket.into_final_bucket_entry(
                             &req.sub_aggregation,
-                            schema,
                             req.as_range()
                                 .expect("unexpected aggregation, expected histogram aggregation"),
+                            range_res.column_type,
                         )
                     })
                     .collect::<crate::Result<Vec<_>>>()?;
@@ -359,16 +325,21 @@ impl IntermediateBucketResult {
                 };
                 Ok(BucketResult::Range { buckets })
             }
-            IntermediateBucketResult::Histogram { buckets } => {
+            IntermediateBucketResult::Histogram {
+                column_type,
+                buckets,
+            } => {
+                let histogram_req = &req
+                    .as_histogram()?
+                    .expect("unexpected aggregation, expected histogram aggregation");
                 let buckets = intermediate_histogram_buckets_to_final_buckets(
                     buckets,
-                    req.as_histogram()
-                        .expect("unexpected aggregation, expected histogram aggregation"),
+                    column_type,
+                    histogram_req,
                     &req.sub_aggregation,
-                    schema,
                 )?;
 
-                let buckets = if req.as_histogram().unwrap().keyed {
+                let buckets = if histogram_req.keyed {
                     let mut bucket_map =
                         FxHashMap::with_capacity_and_hasher(buckets.len(), Default::default());
                     for bucket in buckets {
@@ -384,7 +355,6 @@ impl IntermediateBucketResult {
                 req.as_term()
                     .expect("unexpected aggregation, expected term aggregation"),
                 &req.sub_aggregation,
-                schema,
             ),
         }
     }
@@ -393,8 +363,11 @@ impl IntermediateBucketResult {
         match req {
             BucketAggregationType::Terms(_) => IntermediateBucketResult::Terms(Default::default()),
             BucketAggregationType::Range(_) => IntermediateBucketResult::Range(Default::default()),
-            BucketAggregationType::Histogram(_) => {
-                IntermediateBucketResult::Histogram { buckets: vec![] }
+            BucketAggregationType::Histogram(_) | BucketAggregationType::DateHistogram(_) => {
+                IntermediateBucketResult::Histogram {
+                    buckets: vec![],
+                    column_type: None,
+                }
             }
         }
     }
@@ -404,7 +377,7 @@ impl IntermediateBucketResult {
                 IntermediateBucketResult::Terms(term_res_left),
                 IntermediateBucketResult::Terms(term_res_right),
             ) => {
-                merge_maps(&mut term_res_left.entries, term_res_right.entries);
+                merge_key_maps(&mut term_res_left.entries, term_res_right.entries);
                 term_res_left.sum_other_doc_count += term_res_right.sum_other_doc_count;
                 term_res_left.doc_count_error_upper_bound +=
                     term_res_right.doc_count_error_upper_bound;
@@ -414,7 +387,7 @@ impl IntermediateBucketResult {
                 IntermediateBucketResult::Range(range_res_left),
                 IntermediateBucketResult::Range(range_res_right),
             ) => {
-                merge_maps(&mut range_res_left.buckets, range_res_right.buckets);
+                merge_serialized_key_maps(&mut range_res_left.buckets, range_res_right.buckets);
             }
             (
                 IntermediateBucketResult::Histogram {
@@ -460,12 +433,13 @@ impl IntermediateBucketResult {
 /// Range aggregation including error counts
 pub struct IntermediateRangeBucketResult {
     pub(crate) buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry>,
+    pub(crate) column_type: Option<ColumnType>,
 }
 
 #[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize)]
 /// Term aggregation including error counts
 pub struct IntermediateTermBucketResult {
-    pub(crate) entries: FxHashMap<String, IntermediateTermBucketEntry>,
+    pub(crate) entries: FxHashMap<Key, IntermediateTermBucketEntry>,
     pub(crate) sum_other_doc_count: u64,
     pub(crate) doc_count_error_upper_bound: u64,
 }
@@ -475,7 +449,6 @@ impl IntermediateTermBucketResult {
         self,
         req: &TermsAggregation,
         sub_aggregation_req: &AggregationsInternal,
-        schema: &Schema,
     ) -> crate::Result<BucketResult> {
         let req = TermsAggregationInternal::from_req(req);
         let mut buckets: Vec<BucketEntry> = self
@@ -485,11 +458,11 @@ impl IntermediateTermBucketResult {
             .map(|(key, entry)| {
                 Ok(BucketEntry {
                     key_as_string: None,
-                    key: Key::Str(key),
+                    key,
                     doc_count: entry.doc_count,
                     sub_aggregation: entry
                         .sub_aggregation
-                        .into_final_bucket_result_internal(sub_aggregation_req, schema)?,
+                        .into_final_bucket_result_internal(sub_aggregation_req)?,
                 })
             })
             .collect::<crate::Result<_>>()?;
@@ -563,7 +536,7 @@ trait MergeFruits {
     fn merge_fruits(&mut self, other: Self);
 }
 
-fn merge_maps<V: MergeFruits + Clone>(
+fn merge_serialized_key_maps<V: MergeFruits + Clone>(
     entries_left: &mut FxHashMap<SerializedKey, V>,
     mut entries_right: FxHashMap<SerializedKey, V>,
 ) {
@@ -578,6 +551,21 @@ fn merge_maps<V: MergeFruits + Clone>(
     }
 }
 
+fn merge_key_maps<V: MergeFruits + Clone>(
+    entries_left: &mut FxHashMap<Key, V>,
+    mut entries_right: FxHashMap<Key, V>,
+) {
+    for (name, entry_left) in entries_left.iter_mut() {
+        if let Some(entry_right) = entries_right.remove(name) {
+            entry_left.merge_fruits(entry_right);
+        }
+    }
+
+    for (key, res) in entries_right.into_iter() {
+        entries_left.entry(key).or_insert(res);
+    }
+}
+
 /// This is the histogram entry for a bucket, which contains a key, count, and optionally
 /// sub_aggregations.
 #[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
@@ -594,7 +582,6 @@ impl IntermediateHistogramBucketEntry {
     pub(crate) fn into_final_bucket_entry(
         self,
         req: &AggregationsInternal,
-        schema: &Schema,
     ) -> crate::Result<BucketEntry> {
         Ok(BucketEntry {
             key_as_string: None,
@@ -602,7 +589,7 @@ impl IntermediateHistogramBucketEntry {
             doc_count: self.doc_count,
             sub_aggregation: self
                 .sub_aggregation
-                .into_final_bucket_result_internal(req, schema)?,
+                .into_final_bucket_result_internal(req)?,
         })
     }
 }
@@ -639,15 +626,15 @@ impl IntermediateRangeBucketEntry {
     pub(crate) fn into_final_bucket_entry(
         self,
         req: &AggregationsInternal,
-        schema: &Schema,
-        range_req: &RangeAggregation,
+        _range_req: &RangeAggregation,
+        column_type: Option<ColumnType>,
     ) -> crate::Result<RangeBucketEntry> {
         let mut range_bucket_entry = RangeBucketEntry {
             key: self.key,
             doc_count: self.doc_count,
             sub_aggregation: self
                 .sub_aggregation
-                .into_final_bucket_result_internal(req, schema)?,
+                .into_final_bucket_result_internal(req)?,
             to: self.to,
             from: self.from,
             to_as_string: None,
@@ -656,8 +643,7 @@ impl IntermediateRangeBucketEntry {
 
         // If we have a date type on the histogram buckets, we add the `key_as_string` field as
         // rfc339
-        let field = schema.get_field(&range_req.field)?;
-        if schema.get_field_entry(field).field_type().is_date() {
+        if column_type == Some(ColumnType::DateTime) {
             if let Some(val) = range_bucket_entry.to {
                 let key_as_string = format_date(val as i64)?;
                 range_bucket_entry.to_as_string = Some(key_as_string);
@@ -728,7 +714,10 @@ mod tests {
         }
         map.insert(
             "my_agg_level2".to_string(),
-            IntermediateBucketResult::Range(IntermediateRangeBucketResult { buckets }),
+            IntermediateBucketResult::Range(IntermediateRangeBucketResult {
+                buckets,
+                column_type: None,
+            }),
         );
         IntermediateAggregationResults {
             buckets: Some(VecWithNames::from_entries(map.into_iter().collect())),
@@ -758,7 +747,10 @@ mod tests {
         }
         map.insert(
             "my_agg_level1".to_string(),
-            IntermediateBucketResult::Range(IntermediateRangeBucketResult { buckets }),
+            IntermediateBucketResult::Range(IntermediateRangeBucketResult {
+                buckets,
+                column_type: None,
+            }),
         );
         IntermediateAggregationResults {
             buckets: Some(VecWithNames::from_entries(map.into_iter().collect())),

src/aggregation/metric/mod.rs

@@ -81,7 +81,7 @@ mod tests {
             "price_sum": { "sum": { "field": "price" } }
         }"#;
         let aggregations: Aggregations = serde_json::from_str(aggregations_json).unwrap();
-        let collector = AggregationCollector::from_aggs(aggregations, None, index.schema());
+        let collector = AggregationCollector::from_aggs(aggregations, None);
         let reader = index.reader().unwrap();
         let searcher = reader.searcher();
         let aggregations_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();

src/aggregation/metric/stats.rs

@@ -1,4 +1,4 @@
-use columnar::Column;
+use columnar::{Cardinality, Column, ColumnType};
 use serde::{Deserialize, Serialize};
 
 use super::*;
@@ -8,7 +8,6 @@ use crate::aggregation::intermediate_agg_result::{
 };
 use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
 use crate::aggregation::{f64_from_fastfield_u64, VecWithNames};
-use crate::schema::Type;
 use crate::{DocId, TantivyError};
 
 /// A multi-value metric aggregation that computes a collection of statistics on numeric values that
@@ -153,26 +152,40 @@ pub(crate) enum SegmentStatsType {
 
 #[derive(Clone, Debug, PartialEq)]
 pub(crate) struct SegmentStatsCollector {
-    field_type: Type,
+    field_type: ColumnType,
     pub(crate) collecting_for: SegmentStatsType,
     pub(crate) stats: IntermediateStats,
+    pub(crate) accessor_idx: usize,
 }
 
 impl SegmentStatsCollector {
-    pub fn from_req(field_type: Type, collecting_for: SegmentStatsType) -> Self {
+    pub fn from_req(
+        field_type: ColumnType,
+        collecting_for: SegmentStatsType,
+        accessor_idx: usize,
+    ) -> Self {
         Self {
             field_type,
             collecting_for,
             stats: IntermediateStats::default(),
+            accessor_idx,
         }
     }
-    pub(crate) fn collect_block(&mut self, docs: &[DocId], field: &Column<u64>) {
-        // TODO special case for Required, Optional column type
-        for doc in docs {
-            for val in field.values(*doc) {
+    #[inline]
+    pub(crate) fn collect_block_with_field(&mut self, docs: &[DocId], field: &Column<u64>) {
+        if field.get_cardinality() == Cardinality::Full {
+            for doc in docs {
+                let val = field.values.get_val(*doc);
                 let val1 = f64_from_fastfield_u64(val, &self.field_type);
                 self.stats.collect(val1);
             }
+        } else {
+            for doc in docs {
+                for val in field.values_for_doc(*doc) {
+                    let val1 = f64_from_fastfield_u64(val, &self.field_type);
+                    self.stats.collect(val1);
+                }
+            }
         }
     }
 }
@@ -182,7 +195,7 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
         self: Box<Self>,
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<IntermediateAggregationResults> {
-        let name = agg_with_accessor.metrics.keys[0].to_string();
+        let name = agg_with_accessor.metrics.keys[self.accessor_idx].to_string();
 
         let intermediate_metric_result = match self.collecting_for {
             SegmentStatsType::Average => {
@@ -219,8 +232,9 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
         doc: crate::DocId,
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<()> {
-        let accessor = &agg_with_accessor.metrics.values[0].accessor;
-        for val in accessor.values(doc) {
+        let field = &agg_with_accessor.metrics.values[self.accessor_idx].accessor;
+
+        for val in field.values_for_doc(doc) {
             let val1 = f64_from_fastfield_u64(val, &self.field_type);
             self.stats.collect(val1);
         }
@@ -228,11 +242,14 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
         Ok(())
     }
 
-    fn flush_staged_docs(
+    #[inline]
+    fn collect_block(
         &mut self,
-        _agg_with_accessor: &AggregationsWithAccessor,
-        _force_flush: bool,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<()> {
+        let field = &agg_with_accessor.metrics.values[self.accessor_idx].accessor;
+        self.collect_block_with_field(docs, field);
         Ok(())
     }
 }
@@ -272,7 +289,7 @@ mod tests {
         .into_iter()
         .collect();
 
-        let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
+        let collector = AggregationCollector::from_aggs(agg_req_1, None);
 
         let reader = index.reader()?;
         let searcher = reader.searcher();
@@ -293,6 +310,43 @@ mod tests {
         Ok(())
     }
 
+    #[test]
+    fn test_aggregation_stats_simple() -> crate::Result<()> {
+        // test index without segments
+        let values = vec![10.0];
+
+        let index = get_test_index_from_values(false, &values)?;
+
+        let agg_req_1: Aggregations = vec![(
+            "stats".to_string(),
+            Aggregation::Metric(MetricAggregation::Stats(StatsAggregation::from_field_name(
+                "score".to_string(),
+            ))),
+        )]
+        .into_iter()
+        .collect();
+
+        let collector = AggregationCollector::from_aggs(agg_req_1, None);
+
+        let reader = index.reader()?;
+        let searcher = reader.searcher();
+        let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
+
+        let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
+        assert_eq!(
+            res["stats"],
+            json!({
+                "avg": 10.0,
+                "count": 1,
+                "max": 10.0,
+                "min": 10.0,
+                "sum": 10.0
+            })
+        );
+
+        Ok(())
+    }
+
     #[test]
     fn test_aggregation_stats() -> crate::Result<()> {
         let index = get_test_index_2_segments(false)?;
@@ -349,7 +403,7 @@ mod tests {
         .into_iter()
         .collect();
 
-        let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
+        let collector = AggregationCollector::from_aggs(agg_req_1, None);
 
         let searcher = reader.searcher();
         let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();

src/aggregation/segment_agg_result.rs

@@ -13,17 +13,14 @@ use super::agg_req_with_accessor::{
 };
 use super::bucket::{SegmentHistogramCollector, SegmentRangeCollector, SegmentTermCollector};
 use super::collector::MAX_BUCKET_COUNT;
-use super::intermediate_agg_result::{IntermediateAggregationResults, IntermediateBucketResult};
+use super::intermediate_agg_result::IntermediateAggregationResults;
 use super::metric::{
     AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, SegmentStatsCollector,
     SegmentStatsType, StatsAggregation, SumAggregation,
 };
 use super::VecWithNames;
 use crate::aggregation::agg_req::BucketAggregationType;
-use crate::{DocId, TantivyError};
-
-pub(crate) const DOC_BLOCK_SIZE: usize = 64;
-pub(crate) type DocBlock = [DocId; DOC_BLOCK_SIZE];
+use crate::TantivyError;
 
 pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
     fn into_intermediate_aggregations_result(
@@ -37,11 +34,17 @@ pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<()>;
 
-    fn flush_staged_docs(
+    fn collect_block(
         &mut self,
+        docs: &[crate::DocId],
         agg_with_accessor: &AggregationsWithAccessor,
-        force_flush: bool,
     ) -> 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: &AggregationsWithAccessor) -> crate::Result<()> {
+        Ok(())
+    }
 }
 
 pub(crate) trait CollectorClone {
@@ -68,54 +71,97 @@ pub(crate) fn build_segment_agg_collector(
     // Single metric special case
     if req.buckets.is_empty() && req.metrics.len() == 1 {
         let req = &req.metrics.values[0];
-        let stats_collector = match &req.metric {
-            MetricAggregation::Average(AverageAggregation { .. }) => {
-                SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Average)
-            }
-            MetricAggregation::Count(CountAggregation { .. }) => {
-                SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Count)
-            }
-            MetricAggregation::Max(MaxAggregation { .. }) => {
-                SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Max)
-            }
-            MetricAggregation::Min(MinAggregation { .. }) => {
-                SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Min)
-            }
-            MetricAggregation::Stats(StatsAggregation { .. }) => {
-                SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Stats)
-            }
-            MetricAggregation::Sum(SumAggregation { .. }) => {
-                SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Sum)
-            }
-        };
+        let accessor_idx = 0;
+        return build_metric_segment_agg_collector(req, accessor_idx);
+    }
 
-        return Ok(Box::new(stats_collector));
+    // Single bucket special case
+    if req.metrics.is_empty() && req.buckets.len() == 1 {
+        let req = &req.buckets.values[0];
+        let accessor_idx = 0;
+        return build_bucket_segment_agg_collector(req, accessor_idx);
     }
 
     let agg = GenericSegmentAggregationResultsCollector::from_req_and_validate(req)?;
     Ok(Box::new(agg))
 }
 
-#[derive(Clone)]
+pub(crate) fn build_metric_segment_agg_collector(
+    req: &MetricAggregationWithAccessor,
+    accessor_idx: usize,
+) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
+    let stats_collector = match &req.metric {
+        MetricAggregation::Average(AverageAggregation { .. }) => {
+            SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Average, accessor_idx)
+        }
+        MetricAggregation::Count(CountAggregation { .. }) => {
+            SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Count, accessor_idx)
+        }
+        MetricAggregation::Max(MaxAggregation { .. }) => {
+            SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Max, accessor_idx)
+        }
+        MetricAggregation::Min(MinAggregation { .. }) => {
+            SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Min, accessor_idx)
+        }
+        MetricAggregation::Stats(StatsAggregation { .. }) => {
+            SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Stats, accessor_idx)
+        }
+        MetricAggregation::Sum(SumAggregation { .. }) => {
+            SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Sum, accessor_idx)
+        }
+    };
+
+    Ok(Box::new(stats_collector))
+}
+
+pub(crate) fn build_bucket_segment_agg_collector(
+    req: &BucketAggregationWithAccessor,
+    accessor_idx: usize,
+) -> crate::Result<Box<dyn SegmentAggregationCollector>> {
+    match &req.bucket_agg {
+        BucketAggregationType::Terms(terms_req) => {
+            Ok(Box::new(SegmentTermCollector::from_req_and_validate(
+                terms_req,
+                &req.sub_aggregation,
+                req.field_type,
+                accessor_idx,
+            )?))
+        }
+        BucketAggregationType::Range(range_req) => {
+            Ok(Box::new(SegmentRangeCollector::from_req_and_validate(
+                range_req,
+                &req.sub_aggregation,
+                &req.bucket_count,
+                req.field_type,
+                accessor_idx,
+            )?))
+        }
+        BucketAggregationType::Histogram(histogram) => {
+            Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
+                histogram,
+                &req.sub_aggregation,
+                req.field_type,
+                accessor_idx,
+            )?))
+        }
+        BucketAggregationType::DateHistogram(histogram) => {
+            Ok(Box::new(SegmentHistogramCollector::from_req_and_validate(
+                &histogram.to_histogram_req()?,
+                &req.sub_aggregation,
+                req.field_type,
+                accessor_idx,
+            )?))
+        }
+    }
+}
+
+#[derive(Clone, 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.
 pub(crate) struct GenericSegmentAggregationResultsCollector {
-    pub(crate) metrics: Option<VecWithNames<SegmentMetricResultCollector>>,
-    pub(crate) buckets: Option<VecWithNames<SegmentBucketResultCollector>>,
-    staged_docs: DocBlock,
-    num_staged_docs: usize,
-}
-
-impl Default for GenericSegmentAggregationResultsCollector {
-    fn default() -> Self {
-        Self {
-            metrics: Default::default(),
-            buckets: Default::default(),
-            staged_docs: [0; DOC_BLOCK_SIZE],
-            num_staged_docs: Default::default(),
-        }
-    }
+    pub(crate) metrics: Option<Vec<Box<dyn SegmentAggregationCollector>>>,
+    pub(crate) buckets: Option<Vec<Box<dyn SegmentAggregationCollector>>>,
 }
 
 impl Debug for GenericSegmentAggregationResultsCollector {
@@ -123,8 +169,6 @@ impl Debug for GenericSegmentAggregationResultsCollector {
         f.debug_struct("SegmentAggregationResultsCollector")
             .field("metrics", &self.metrics)
             .field("buckets", &self.buckets)
-            .field("staged_docs", &&self.staged_docs[..self.num_staged_docs])
-            .field("num_staged_docs", &self.num_staged_docs)
             .finish()
     }
 }
@@ -135,16 +179,29 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<IntermediateAggregationResults> {
         let buckets = if let Some(buckets) = self.buckets {
-            let entries = buckets
-                .into_iter()
-                .zip(agg_with_accessor.buckets.values())
-                .map(|((key, bucket), acc)| Ok((key, bucket.into_intermediate_bucket_result(acc)?)))
-                .collect::<crate::Result<Vec<(String, _)>>>()?;
-            Some(VecWithNames::from_entries(entries))
+            let mut intermeditate_buckets = VecWithNames::default();
+            for bucket in buckets {
+                // TODO too many allocations?
+                let res = bucket.into_intermediate_aggregations_result(agg_with_accessor)?;
+                // unwrap is fine since we only have buckets here
+                intermeditate_buckets.extend(res.buckets.unwrap());
+            }
+            Some(intermeditate_buckets)
+        } else {
+            None
+        };
+        let metrics = if let Some(metrics) = self.metrics {
+            let mut intermeditate_metrics = VecWithNames::default();
+            for metric in metrics {
+                // TODO too many allocations?
+                let res = metric.into_intermediate_aggregations_result(agg_with_accessor)?;
+                // unwrap is fine since we only have metrics here
+                intermeditate_metrics.extend(res.metrics.unwrap());
+            }
+            Some(intermeditate_metrics)
         } else {
             None
         };
-        let metrics = self.metrics.map(VecWithNames::from_other);
 
         Ok(IntermediateAggregationResults { metrics, buckets })
     }
@@ -154,229 +211,77 @@ impl SegmentAggregationCollector for GenericSegmentAggregationResultsCollector {
         doc: crate::DocId,
         agg_with_accessor: &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.flush_staged_docs(agg_with_accessor, false)?;
-        }
+        self.collect_block(&[doc], agg_with_accessor)?;
+
         Ok(())
     }
 
-    fn flush_staged_docs(
+    fn collect_block(
         &mut self,
+        docs: &[crate::DocId],
         agg_with_accessor: &AggregationsWithAccessor,
-        force_flush: bool,
     ) -> crate::Result<()> {
-        if self.num_staged_docs == 0 {
-            return Ok(());
+        if let Some(metrics) = self.metrics.as_mut() {
+            for collector in metrics {
+                collector.collect_block(docs, agg_with_accessor)?;
+            }
         }
+
+        if let Some(buckets) = self.buckets.as_mut() {
+            for collector in buckets {
+                collector.collect_block(docs, agg_with_accessor)?;
+            }
+        }
+
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
         if let Some(metrics) = &mut self.metrics {
-            for (collector, agg_with_accessor) in
-                metrics.values_mut().zip(agg_with_accessor.metrics.values())
-            {
-                collector
-                    .collect_block(&self.staged_docs[..self.num_staged_docs], agg_with_accessor);
+            for collector in metrics {
+                collector.flush(agg_with_accessor)?;
             }
         }
-
         if let Some(buckets) = &mut self.buckets {
-            for (collector, agg_with_accessor) in
-                buckets.values_mut().zip(agg_with_accessor.buckets.values())
-            {
-                collector.collect_block(
-                    &self.staged_docs[..self.num_staged_docs],
-                    agg_with_accessor,
-                    force_flush,
-                )?;
+            for collector in buckets {
+                collector.flush(agg_with_accessor)?;
             }
         }
-
-        self.num_staged_docs = 0;
         Ok(())
     }
 }
 
 impl GenericSegmentAggregationResultsCollector {
-    pub fn into_intermediate_aggregations_result(
-        self,
-        agg_with_accessor: &AggregationsWithAccessor,
-    ) -> crate::Result<IntermediateAggregationResults> {
-        let buckets = if let Some(buckets) = self.buckets {
-            let entries = buckets
-                .into_iter()
-                .zip(agg_with_accessor.buckets.values())
-                .map(|((key, bucket), acc)| Ok((key, bucket.into_intermediate_bucket_result(acc)?)))
-                .collect::<crate::Result<Vec<(String, _)>>>()?;
-            Some(VecWithNames::from_entries(entries))
-        } else {
-            None
-        };
-        let metrics = self.metrics.map(VecWithNames::from_other);
-
-        Ok(IntermediateAggregationResults { metrics, buckets })
-    }
-
     pub(crate) fn from_req_and_validate(req: &AggregationsWithAccessor) -> crate::Result<Self> {
         let buckets = req
             .buckets
             .iter()
-            .map(|(key, req)| {
-                Ok((
-                    key.to_string(),
-                    SegmentBucketResultCollector::from_req_and_validate(req)?,
-                ))
+            .enumerate()
+            .map(|(accessor_idx, (_key, req))| {
+                build_bucket_segment_agg_collector(req, accessor_idx)
             })
-            .collect::<crate::Result<Vec<(String, _)>>>()?;
+            .collect::<crate::Result<Vec<Box<dyn SegmentAggregationCollector>>>>()?;
         let metrics = req
             .metrics
             .iter()
-            .map(|(key, req)| {
-                Ok((
-                    key.to_string(),
-                    SegmentMetricResultCollector::from_req_and_validate(req)?,
-                ))
+            .enumerate()
+            .map(|(accessor_idx, (_key, req))| {
+                build_metric_segment_agg_collector(req, accessor_idx)
             })
-            .collect::<crate::Result<Vec<(String, _)>>>()?;
+            .collect::<crate::Result<Vec<Box<dyn SegmentAggregationCollector>>>>()?;
+
         let metrics = if metrics.is_empty() {
             None
         } else {
-            Some(VecWithNames::from_entries(metrics))
+            Some(metrics)
         };
+
         let buckets = if buckets.is_empty() {
             None
         } else {
-            Some(VecWithNames::from_entries(buckets))
+            Some(buckets)
         };
-        Ok(GenericSegmentAggregationResultsCollector {
-            metrics,
-            buckets,
-            staged_docs: [0; DOC_BLOCK_SIZE],
-            num_staged_docs: 0,
-        })
-    }
-}
-
-#[derive(Clone, Debug, PartialEq)]
-pub(crate) enum SegmentMetricResultCollector {
-    Stats(SegmentStatsCollector),
-}
-
-impl SegmentMetricResultCollector {
-    pub fn from_req_and_validate(req: &MetricAggregationWithAccessor) -> crate::Result<Self> {
-        match &req.metric {
-            MetricAggregation::Average(AverageAggregation { .. }) => {
-                Ok(SegmentMetricResultCollector::Stats(
-                    SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Average),
-                ))
-            }
-            MetricAggregation::Count(CountAggregation { .. }) => {
-                Ok(SegmentMetricResultCollector::Stats(
-                    SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Count),
-                ))
-            }
-            MetricAggregation::Max(MaxAggregation { .. }) => {
-                Ok(SegmentMetricResultCollector::Stats(
-                    SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Max),
-                ))
-            }
-            MetricAggregation::Min(MinAggregation { .. }) => {
-                Ok(SegmentMetricResultCollector::Stats(
-                    SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Min),
-                ))
-            }
-            MetricAggregation::Stats(StatsAggregation { .. }) => {
-                Ok(SegmentMetricResultCollector::Stats(
-                    SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Stats),
-                ))
-            }
-            MetricAggregation::Sum(SumAggregation { .. }) => {
-                Ok(SegmentMetricResultCollector::Stats(
-                    SegmentStatsCollector::from_req(req.field_type, SegmentStatsType::Sum),
-                ))
-            }
-        }
-    }
-    pub(crate) fn collect_block(&mut self, doc: &[DocId], metric: &MetricAggregationWithAccessor) {
-        match self {
-            SegmentMetricResultCollector::Stats(stats_collector) => {
-                stats_collector.collect_block(doc, &metric.accessor);
-            }
-        }
-    }
-}
-
-/// SegmentBucketAggregationResultCollectors will have specialized buckets for collection inside
-/// segments.
-/// The typical structure of Map<Key, Bucket> is not suitable during collection for performance
-/// reasons.
-#[derive(Clone, Debug)]
-pub(crate) enum SegmentBucketResultCollector {
-    Range(SegmentRangeCollector),
-    Histogram(Box<SegmentHistogramCollector>),
-    Terms(Box<SegmentTermCollector>),
-}
-
-impl SegmentBucketResultCollector {
-    pub fn into_intermediate_bucket_result(
-        self,
-        agg_with_accessor: &BucketAggregationWithAccessor,
-    ) -> crate::Result<IntermediateBucketResult> {
-        match self {
-            SegmentBucketResultCollector::Terms(terms) => {
-                terms.into_intermediate_bucket_result(agg_with_accessor)
-            }
-            SegmentBucketResultCollector::Range(range) => {
-                range.into_intermediate_bucket_result(agg_with_accessor)
-            }
-            SegmentBucketResultCollector::Histogram(histogram) => {
-                histogram.into_intermediate_bucket_result(agg_with_accessor)
-            }
-        }
-    }
-
-    pub fn from_req_and_validate(req: &BucketAggregationWithAccessor) -> crate::Result<Self> {
-        match &req.bucket_agg {
-            BucketAggregationType::Terms(terms_req) => Ok(Self::Terms(Box::new(
-                SegmentTermCollector::from_req_and_validate(terms_req, &req.sub_aggregation)?,
-            ))),
-            BucketAggregationType::Range(range_req) => {
-                Ok(Self::Range(SegmentRangeCollector::from_req_and_validate(
-                    range_req,
-                    &req.sub_aggregation,
-                    &req.bucket_count,
-                    req.field_type,
-                )?))
-            }
-            BucketAggregationType::Histogram(histogram) => Ok(Self::Histogram(Box::new(
-                SegmentHistogramCollector::from_req_and_validate(
-                    histogram,
-                    &req.sub_aggregation,
-                    req.field_type,
-                    &req.accessor,
-                )?,
-            ))),
-        }
-    }
-
-    #[inline]
-    pub(crate) fn collect_block(
-        &mut self,
-        doc: &[DocId],
-        bucket_with_accessor: &BucketAggregationWithAccessor,
-        force_flush: bool,
-    ) -> crate::Result<()> {
-        match self {
-            SegmentBucketResultCollector::Range(range) => {
-                range.collect_block(doc, bucket_with_accessor, force_flush)?;
-            }
-            SegmentBucketResultCollector::Histogram(histogram) => {
-                histogram.collect_block(doc, bucket_with_accessor, force_flush)?;
-            }
-            SegmentBucketResultCollector::Terms(terms) => {
-                terms.collect_block(doc, bucket_with_accessor, force_flush)?;
-            }
-        }
-        Ok(())
+        Ok(GenericSegmentAggregationResultsCollector { metrics, buckets })
     }
 }
 

src/collector/facet_collector.rs

@@ -515,8 +515,7 @@ mod tests {
         expected_compressed_collapsed_mapping: &[usize],
         expected_unique_facet_ords: &[(u64, usize)],
     ) {
-        let (compressed_collapsed_mapping, unique_facet_ords) =
-            compress_mapping(&collapsed_mapping);
+        let (compressed_collapsed_mapping, unique_facet_ords) = compress_mapping(collapsed_mapping);
         assert_eq!(
             compressed_collapsed_mapping,
             expected_compressed_collapsed_mapping

src/collector/mod.rs

@@ -106,7 +106,7 @@ mod tweak_score_top_collector;
 pub use self::tweak_score_top_collector::{ScoreSegmentTweaker, ScoreTweaker};
 mod facet_collector;
 pub use self::facet_collector::{FacetCollector, FacetCounts};
-use crate::query::Weight;
+use crate::query::{for_each_docset, for_each_scorer, Weight};
 
 mod docset_collector;
 pub use self::docset_collector::DocSetCollector;
@@ -173,28 +173,32 @@ pub trait Collector: Sync + Send {
 
         match (reader.alive_bitset(), self.requires_scoring()) {
             (Some(alive_bitset), true) => {
-                weight.for_each(reader, &mut |doc, score| {
+                let mut scorer = weight.scorer(reader, 1.0)?;
+                for_each_scorer(scorer.as_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 |doc| {
+                let mut docset = weight.scorer(reader, 1.0)?;
+                for_each_docset(docset.as_mut(), |doc| {
                     if alive_bitset.is_alive(doc) {
                         segment_collector.collect(doc, 0.0);
                     }
-                })?;
+                });
             }
             (None, true) => {
-                weight.for_each(reader, &mut |doc, score| {
+                let mut scorer = weight.scorer(reader, 1.0)?;
+                for_each_scorer(scorer.as_mut(), |doc, score| {
                     segment_collector.collect(doc, score);
-                })?;
+                });
             }
             (None, false) => {
-                weight.for_each_no_score(reader, &mut |doc| {
+                let mut docset = weight.scorer(reader, 1.0)?;
+                for_each_docset(docset.as_mut(), |doc| {
                     segment_collector.collect(doc, 0.0);
-                })?;
+                });
             }
         }
 

src/collector/tests.rs

@@ -56,9 +56,8 @@ pub fn test_filter_collector() -> crate::Result<()> {
     assert_eq!(filtered_top_docs.len(), 0);
 
     fn date_filter(value: DateTime) -> bool {
-        (crate::DateTime::from(value).into_utc()
-            - OffsetDateTime::parse("2019-04-09T00:00:00+00:00", &Rfc3339).unwrap())
-        .whole_weeks()
+        (value.into_utc() - OffsetDateTime::parse("2019-04-09T00:00:00+00:00", &Rfc3339).unwrap())
+            .whole_weeks()
             > 0
     }
 
@@ -201,7 +200,7 @@ impl SegmentCollector for FastFieldSegmentCollector {
     type Fruit = Vec<u64>;
 
     fn collect(&mut self, doc: DocId, _score: Score) {
-        self.vals.extend(self.reader.values(doc));
+        self.vals.extend(self.reader.values_for_doc(doc));
     }
 
     fn harvest(self) -> Vec<u64> {

src/core/index.rs

@@ -662,304 +662,3 @@ impl fmt::Debug for Index {
         write!(f, "Index({:?})", self.directory)
     }
 }
-
-#[cfg(test)]
-mod tests {
-    use crate::collector::Count;
-    use crate::directory::{RamDirectory, WatchCallback};
-    use crate::query::TermQuery;
-    use crate::schema::{Field, IndexRecordOption, Schema, INDEXED, TEXT};
-    use crate::tokenizer::TokenizerManager;
-    use crate::{Directory, Index, IndexBuilder, IndexReader, IndexSettings, ReloadPolicy, Term};
-
-    #[test]
-    fn test_indexer_for_field() {
-        let mut schema_builder = Schema::builder();
-        let num_likes_field = schema_builder.add_u64_field("num_likes", INDEXED);
-        let body_field = schema_builder.add_text_field("body", TEXT);
-        let schema = schema_builder.build();
-        let index = Index::create_in_ram(schema);
-        assert!(index.tokenizer_for_field(body_field).is_ok());
-        assert_eq!(
-            format!("{:?}", index.tokenizer_for_field(num_likes_field).err()),
-            "Some(SchemaError(\"\\\"num_likes\\\" is not a text field.\"))"
-        );
-    }
-
-    #[test]
-    fn test_set_tokenizer_manager() {
-        let mut schema_builder = Schema::builder();
-        schema_builder.add_u64_field("num_likes", INDEXED);
-        schema_builder.add_text_field("body", TEXT);
-        let schema = schema_builder.build();
-        let index = IndexBuilder::new()
-            // set empty tokenizer manager
-            .tokenizers(TokenizerManager::new())
-            .schema(schema)
-            .create_in_ram()
-            .unwrap();
-        assert!(index.tokenizers().get("raw").is_none());
-    }
-
-    #[test]
-    fn test_index_exists() {
-        let directory: Box<dyn Directory> = Box::new(RamDirectory::create());
-        assert!(!Index::exists(directory.as_ref()).unwrap());
-        assert!(Index::create(
-            directory.clone(),
-            throw_away_schema(),
-            IndexSettings::default()
-        )
-        .is_ok());
-        assert!(Index::exists(directory.as_ref()).unwrap());
-    }
-
-    #[test]
-    fn open_or_create_should_create() {
-        let directory = RamDirectory::create();
-        assert!(!Index::exists(&directory).unwrap());
-        assert!(Index::open_or_create(directory.clone(), throw_away_schema()).is_ok());
-        assert!(Index::exists(&directory).unwrap());
-    }
-
-    #[test]
-    fn open_or_create_should_open() {
-        let directory: Box<dyn Directory> = Box::new(RamDirectory::create());
-        assert!(Index::create(
-            directory.clone(),
-            throw_away_schema(),
-            IndexSettings::default()
-        )
-        .is_ok());
-        assert!(Index::exists(directory.as_ref()).unwrap());
-        assert!(Index::open_or_create(directory, throw_away_schema()).is_ok());
-    }
-
-    #[test]
-    fn create_should_wipeoff_existing() {
-        let directory: Box<dyn Directory> = Box::new(RamDirectory::create());
-        assert!(Index::create(
-            directory.clone(),
-            throw_away_schema(),
-            IndexSettings::default()
-        )
-        .is_ok());
-        assert!(Index::exists(directory.as_ref()).unwrap());
-        assert!(Index::create(
-            directory,
-            Schema::builder().build(),
-            IndexSettings::default()
-        )
-        .is_ok());
-    }
-
-    #[test]
-    fn open_or_create_exists_but_schema_does_not_match() {
-        let directory = RamDirectory::create();
-        assert!(Index::create(
-            directory.clone(),
-            throw_away_schema(),
-            IndexSettings::default()
-        )
-        .is_ok());
-        assert!(Index::exists(&directory).unwrap());
-        assert!(Index::open_or_create(directory.clone(), throw_away_schema()).is_ok());
-        let err = Index::open_or_create(directory, Schema::builder().build());
-        assert_eq!(
-            format!("{:?}", err.unwrap_err()),
-            "SchemaError(\"An index exists but the schema does not match.\")"
-        );
-    }
-
-    fn throw_away_schema() -> Schema {
-        let mut schema_builder = Schema::builder();
-        let _ = schema_builder.add_u64_field("num_likes", INDEXED);
-        schema_builder.build()
-    }
-
-    #[test]
-    fn test_index_on_commit_reload_policy() -> crate::Result<()> {
-        let schema = throw_away_schema();
-        let field = schema.get_field("num_likes").unwrap();
-        let index = Index::create_in_ram(schema);
-        let reader = index
-            .reader_builder()
-            .reload_policy(ReloadPolicy::OnCommit)
-            .try_into()
-            .unwrap();
-        assert_eq!(reader.searcher().num_docs(), 0);
-        test_index_on_commit_reload_policy_aux(field, &index, &reader)
-    }
-
-    #[cfg(feature = "mmap")]
-    mod mmap_specific {
-
-        use std::path::PathBuf;
-
-        use tempfile::TempDir;
-
-        use super::*;
-        use crate::Directory;
-
-        #[test]
-        fn test_index_on_commit_reload_policy_mmap() -> crate::Result<()> {
-            let schema = throw_away_schema();
-            let field = schema.get_field("num_likes").unwrap();
-            let tempdir = TempDir::new().unwrap();
-            let tempdir_path = PathBuf::from(tempdir.path());
-            let index = Index::create_in_dir(tempdir_path, schema).unwrap();
-            let reader = index
-                .reader_builder()
-                .reload_policy(ReloadPolicy::OnCommit)
-                .try_into()
-                .unwrap();
-            assert_eq!(reader.searcher().num_docs(), 0);
-            test_index_on_commit_reload_policy_aux(field, &index, &reader)
-        }
-
-        #[test]
-        fn test_index_manual_policy_mmap() -> crate::Result<()> {
-            let schema = throw_away_schema();
-            let field = schema.get_field("num_likes").unwrap();
-            let mut index = Index::create_from_tempdir(schema)?;
-            let mut writer = index.writer_for_tests()?;
-            writer.commit()?;
-            let reader = index
-                .reader_builder()
-                .reload_policy(ReloadPolicy::Manual)
-                .try_into()?;
-            assert_eq!(reader.searcher().num_docs(), 0);
-            writer.add_document(doc!(field=>1u64))?;
-            let (sender, receiver) = crossbeam_channel::unbounded();
-            let _handle = index.directory_mut().watch(WatchCallback::new(move || {
-                let _ = sender.send(());
-            }));
-            writer.commit()?;
-            assert!(receiver.recv().is_ok());
-            assert_eq!(reader.searcher().num_docs(), 0);
-            reader.reload()?;
-            assert_eq!(reader.searcher().num_docs(), 1);
-            Ok(())
-        }
-
-        #[test]
-        fn test_index_on_commit_reload_policy_different_directories() -> crate::Result<()> {
-            let schema = throw_away_schema();
-            let field = schema.get_field("num_likes").unwrap();
-            let tempdir = TempDir::new().unwrap();
-            let tempdir_path = PathBuf::from(tempdir.path());
-            let write_index = Index::create_in_dir(&tempdir_path, schema).unwrap();
-            let read_index = Index::open_in_dir(&tempdir_path).unwrap();
-            let reader = read_index
-                .reader_builder()
-                .reload_policy(ReloadPolicy::OnCommit)
-                .try_into()
-                .unwrap();
-            assert_eq!(reader.searcher().num_docs(), 0);
-            test_index_on_commit_reload_policy_aux(field, &write_index, &reader)
-        }
-    }
-    fn test_index_on_commit_reload_policy_aux(
-        field: Field,
-        index: &Index,
-        reader: &IndexReader,
-    ) -> crate::Result<()> {
-        let mut reader_index = reader.index();
-        let (sender, receiver) = crossbeam_channel::unbounded();
-        let _watch_handle = reader_index
-            .directory_mut()
-            .watch(WatchCallback::new(move || {
-                let _ = sender.send(());
-            }));
-        let mut writer = index.writer_for_tests()?;
-        assert_eq!(reader.searcher().num_docs(), 0);
-        writer.add_document(doc!(field=>1u64))?;
-        writer.commit().unwrap();
-        // We need a loop here because it is possible for notify to send more than
-        // one modify event. It was observed on CI on MacOS.
-        loop {
-            assert!(receiver.recv().is_ok());
-            if reader.searcher().num_docs() == 1 {
-                break;
-            }
-        }
-        writer.add_document(doc!(field=>2u64))?;
-        writer.commit().unwrap();
-        // ... Same as above
-        loop {
-            assert!(receiver.recv().is_ok());
-            if reader.searcher().num_docs() == 2 {
-                break;
-            }
-        }
-        Ok(())
-    }
-
-    // This test will not pass on windows, because windows
-    // prevent deleting files that are MMapped.
-    #[cfg(not(target_os = "windows"))]
-    #[test]
-    fn garbage_collect_works_as_intended() -> crate::Result<()> {
-        let directory = RamDirectory::create();
-        let schema = throw_away_schema();
-        let field = schema.get_field("num_likes").unwrap();
-        let index = Index::create(directory.clone(), schema, IndexSettings::default())?;
-
-        let mut writer = index.writer_with_num_threads(1, 32_000_000).unwrap();
-        for _seg in 0..8 {
-            for i in 0u64..1_000u64 {
-                writer.add_document(doc!(field => i))?;
-            }
-            writer.commit()?;
-        }
-
-        let mem_right_after_commit = directory.total_mem_usage();
-
-        let reader = index
-            .reader_builder()
-            .reload_policy(ReloadPolicy::Manual)
-            .try_into()?;
-        assert_eq!(reader.searcher().num_docs(), 8_000);
-        assert_eq!(reader.searcher().segment_readers().len(), 8);
-
-        writer.wait_merging_threads()?;
-
-        let mem_right_after_merge_finished = directory.total_mem_usage();
-
-        reader.reload().unwrap();
-        let searcher = reader.searcher();
-        assert_eq!(searcher.segment_readers().len(), 1);
-        assert_eq!(searcher.num_docs(), 8_000);
-        assert!(
-            mem_right_after_merge_finished < mem_right_after_commit,
-            "(mem after merge){} is expected < (mem before merge){}",
-            mem_right_after_merge_finished,
-            mem_right_after_commit
-        );
-        Ok(())
-    }
-
-    #[test]
-    fn test_single_segment_index_writer() -> crate::Result<()> {
-        let mut schema_builder = Schema::builder();
-        let text_field = schema_builder.add_text_field("text", TEXT);
-        let schema = schema_builder.build();
-        let directory = RamDirectory::default();
-        let mut single_segment_index_writer = Index::builder()
-            .schema(schema)
-            .single_segment_index_writer(directory, 10_000_000)?;
-        for _ in 0..10 {
-            let doc = doc!(text_field=>"hello");
-            single_segment_index_writer.add_document(doc)?;
-        }
-        let index = single_segment_index_writer.finalize()?;
-        let searcher = index.reader()?.searcher();
-        let term_query = TermQuery::new(
-            Term::from_field_text(text_field, "hello"),
-            IndexRecordOption::Basic,
-        );
-        let count = searcher.search(&term_query, &Count)?;
-        assert_eq!(count, 10);
-        Ok(())
-    }
-}

src/core/json_utils.rs

@@ -1,10 +1,11 @@
 use columnar::MonotonicallyMappableToU64;
+use common::replace_in_place;
 use murmurhash32::murmurhash2;
 use rustc_hash::FxHashMap;
 
 use crate::fastfield::FastValue;
 use crate::postings::{IndexingContext, IndexingPosition, PostingsWriter};
-use crate::schema::term::{JSON_END_OF_PATH, JSON_PATH_SEGMENT_SEP};
+use crate::schema::term::{JSON_END_OF_PATH, JSON_PATH_SEGMENT_SEP, JSON_PATH_SEGMENT_SEP_STR};
 use crate::schema::{Field, Type};
 use crate::time::format_description::well_known::Rfc3339;
 use crate::time::{OffsetDateTime, UtcOffset};
@@ -199,7 +200,7 @@ fn infer_type_from_str(text: &str) -> TextOrDateTime {
     }
 }
 
-// Tries to infer a JSON type from a string
+// Tries to infer a JSON type from a string.
 pub(crate) fn convert_to_fast_value_and_get_term(
     json_term_writer: &mut JsonTermWriter,
     phrase: &str,
@@ -295,6 +296,32 @@ fn split_json_path(json_path: &str) -> Vec<String> {
     json_path_segments
 }
 
+/// Takes a field name, a json path as supplied by a user, and whether we should expand dots, and
+/// return a column key, as expected by the columnar crate.
+///
+/// This function will detect unescaped dots in the path, and split over them.
+/// If expand_dots is enabled, then even escaped dots will be split over.
+///
+/// The resulting list of segment then gets stitched together, joined by \1 separator,
+/// as defined in the columnar crate.
+pub(crate) fn encode_column_name(
+    field_name: &str,
+    json_path: &str,
+    expand_dots_enabled: bool,
+) -> String {
+    let mut column_key: String = String::with_capacity(field_name.len() + json_path.len() + 1);
+    column_key.push_str(field_name);
+    for mut segment in split_json_path(json_path) {
+        column_key.push_str(JSON_PATH_SEGMENT_SEP_STR);
+        if expand_dots_enabled {
+            // We need to replace `.` by JSON_PATH_SEGMENT_SEP.
+            unsafe { replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, segment.as_bytes_mut()) };
+        }
+        column_key.push_str(&segment);
+    }
+    column_key
+}
+
 impl<'a> JsonTermWriter<'a> {
     pub fn from_field_and_json_path(
         field: Field,
@@ -343,18 +370,10 @@ impl<'a> JsonTermWriter<'a> {
         if self.path_stack.len() > 1 {
             buffer[buffer_len - 1] = JSON_PATH_SEGMENT_SEP;
         }
-        if self.expand_dots_enabled && segment.as_bytes().contains(&b'.') {
+        let appended_segment = self.term_buffer.append_bytes(segment.as_bytes());
+        if self.expand_dots_enabled {
             // We need to replace `.` by JSON_PATH_SEGMENT_SEP.
-            self.term_buffer
-                .append_bytes(segment.as_bytes())
-                .iter_mut()
-                .for_each(|byte| {
-                    if *byte == b'.' {
-                        *byte = JSON_PATH_SEGMENT_SEP;
-                    }
-                });
-        } else {
-            self.term_buffer.append_bytes(segment.as_bytes());
+            replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, appended_segment);
         }
         self.term_buffer.push_byte(JSON_PATH_SEGMENT_SEP);
         self.path_stack.push(self.term_buffer.len_bytes());
@@ -373,7 +392,7 @@ impl<'a> JsonTermWriter<'a> {
         &self.term().value_bytes()[..end_of_path - 1]
     }
 
-    pub fn set_fast_value<T: FastValue>(&mut self, val: T) {
+    pub(crate) fn set_fast_value<T: FastValue>(&mut self, val: T) {
         self.close_path_and_set_type(T::to_type());
         let value = if T::to_type() == Type::Date {
             DateTime::from_u64(val.to_u64())

src/core/mod.rs

@@ -2,6 +2,7 @@ mod executor;
 pub mod index;
 mod index_meta;
 mod inverted_index_reader;
+pub mod json_utils;
 pub mod searcher;
 mod segment;
 mod segment_component;
@@ -36,3 +37,6 @@ pub static META_FILEPATH: Lazy<&'static Path> = Lazy::new(|| Path::new("meta.jso
 /// Removing this file is safe, but will prevent the garbage collection of all of the file that
 /// are currently in the directory
 pub static MANAGED_FILEPATH: Lazy<&'static Path> = Lazy::new(|| Path::new(".managed.json"));
+
+#[cfg(test)]
+mod tests;

src/core/searcher.rs

@@ -4,7 +4,7 @@ use std::{fmt, io};
 
 use crate::collector::Collector;
 use crate::core::{Executor, SegmentReader};
-use crate::query::{EnableScoring, Query};
+use crate::query::{Bm25StatisticsProvider, EnableScoring, Query};
 use crate::schema::{Document, Schema, Term};
 use crate::space_usage::SearcherSpaceUsage;
 use crate::store::{CacheStats, StoreReader};
@@ -176,8 +176,27 @@ impl Searcher {
         query: &dyn Query,
         collector: &C,
     ) -> crate::Result<C::Fruit> {
+        self.search_with_statistics_provider(query, collector, self)
+    }
+
+    /// Same as [`search(...)`](Searcher::search) but allows specifying
+    /// a [Bm25StatisticsProvider].
+    ///
+    /// This can be used to adjust the statistics used in computing BM25
+    /// scores.
+    pub fn search_with_statistics_provider<C: Collector>(
+        &self,
+        query: &dyn Query,
+        collector: &C,
+        statistics_provider: &dyn Bm25StatisticsProvider,
+    ) -> crate::Result<C::Fruit> {
+        let enabled_scoring = if collector.requires_scoring() {
+            EnableScoring::enabled_from_statistics_provider(statistics_provider, self)
+        } else {
+            EnableScoring::disabled_from_searcher(self)
+        };
         let executor = self.inner.index.search_executor();
-        self.search_with_executor(query, collector, executor)
+        self.search_with_executor(query, collector, executor, enabled_scoring)
     }
 
     /// Same as [`search(...)`](Searcher::search) but multithreaded.
@@ -197,12 +216,8 @@ impl Searcher {
         query: &dyn Query,
         collector: &C,
         executor: &Executor,
+        enabled_scoring: EnableScoring,
     ) -> crate::Result<C::Fruit> {
-        let enabled_scoring = if collector.requires_scoring() {
-            EnableScoring::enabled_from_searcher(self)
-        } else {
-            EnableScoring::disabled_from_searcher(self)
-        };
         let weight = query.weight(enabled_scoring)?;
         let segment_readers = self.segment_readers();
         let fruits = executor.map(

src/core/segment_reader.rs

@@ -38,7 +38,7 @@ pub struct SegmentReader {
     termdict_composite: CompositeFile,
     postings_composite: CompositeFile,
     positions_composite: CompositeFile,
-    fast_fields_readers: Arc<FastFieldReaders>,
+    fast_fields_readers: FastFieldReaders,
     fieldnorm_readers: FieldNormReaders,
 
     store_file: FileSlice,
@@ -167,7 +167,7 @@ impl SegmentReader {
         let schema = segment.schema();
 
         let fast_fields_data = segment.open_read(SegmentComponent::FastFields)?;
-        let fast_fields_readers = Arc::new(FastFieldReaders::open(fast_fields_data)?);
+        let fast_fields_readers = FastFieldReaders::open(fast_fields_data, schema.clone())?;
         let fieldnorm_data = segment.open_read(SegmentComponent::FieldNorms)?;
         let fieldnorm_readers = FieldNormReaders::open(fieldnorm_data)?;
 

src/core/tests.rs

@@ -0,0 +1,347 @@
+use crate::collector::Count;
+use crate::directory::{RamDirectory, WatchCallback};
+use crate::indexer::NoMergePolicy;
+use crate::query::TermQuery;
+use crate::schema::{Field, IndexRecordOption, Schema, INDEXED, STRING, TEXT};
+use crate::tokenizer::TokenizerManager;
+use crate::{
+    Directory, Document, Index, IndexBuilder, IndexReader, IndexSettings, ReloadPolicy, SegmentId,
+    Term,
+};
+
+#[test]
+fn test_indexer_for_field() {
+    let mut schema_builder = Schema::builder();
+    let num_likes_field = schema_builder.add_u64_field("num_likes", INDEXED);
+    let body_field = schema_builder.add_text_field("body", TEXT);
+    let schema = schema_builder.build();
+    let index = Index::create_in_ram(schema);
+    assert!(index.tokenizer_for_field(body_field).is_ok());
+    assert_eq!(
+        format!("{:?}", index.tokenizer_for_field(num_likes_field).err()),
+        "Some(SchemaError(\"\\\"num_likes\\\" is not a text field.\"))"
+    );
+}
+
+#[test]
+fn test_set_tokenizer_manager() {
+    let mut schema_builder = Schema::builder();
+    schema_builder.add_u64_field("num_likes", INDEXED);
+    schema_builder.add_text_field("body", TEXT);
+    let schema = schema_builder.build();
+    let index = IndexBuilder::new()
+        // set empty tokenizer manager
+        .tokenizers(TokenizerManager::new())
+        .schema(schema)
+        .create_in_ram()
+        .unwrap();
+    assert!(index.tokenizers().get("raw").is_none());
+}
+
+#[test]
+fn test_index_exists() {
+    let directory: Box<dyn Directory> = Box::new(RamDirectory::create());
+    assert!(!Index::exists(directory.as_ref()).unwrap());
+    assert!(Index::create(
+        directory.clone(),
+        throw_away_schema(),
+        IndexSettings::default()
+    )
+    .is_ok());
+    assert!(Index::exists(directory.as_ref()).unwrap());
+}
+
+#[test]
+fn open_or_create_should_create() {
+    let directory = RamDirectory::create();
+    assert!(!Index::exists(&directory).unwrap());
+    assert!(Index::open_or_create(directory.clone(), throw_away_schema()).is_ok());
+    assert!(Index::exists(&directory).unwrap());
+}
+
+#[test]
+fn open_or_create_should_open() {
+    let directory: Box<dyn Directory> = Box::new(RamDirectory::create());
+    assert!(Index::create(
+        directory.clone(),
+        throw_away_schema(),
+        IndexSettings::default()
+    )
+    .is_ok());
+    assert!(Index::exists(directory.as_ref()).unwrap());
+    assert!(Index::open_or_create(directory, throw_away_schema()).is_ok());
+}
+
+#[test]
+fn create_should_wipeoff_existing() {
+    let directory: Box<dyn Directory> = Box::new(RamDirectory::create());
+    assert!(Index::create(
+        directory.clone(),
+        throw_away_schema(),
+        IndexSettings::default()
+    )
+    .is_ok());
+    assert!(Index::exists(directory.as_ref()).unwrap());
+    assert!(Index::create(
+        directory,
+        Schema::builder().build(),
+        IndexSettings::default()
+    )
+    .is_ok());
+}
+
+#[test]
+fn open_or_create_exists_but_schema_does_not_match() {
+    let directory = RamDirectory::create();
+    assert!(Index::create(
+        directory.clone(),
+        throw_away_schema(),
+        IndexSettings::default()
+    )
+    .is_ok());
+    assert!(Index::exists(&directory).unwrap());
+    assert!(Index::open_or_create(directory.clone(), throw_away_schema()).is_ok());
+    let err = Index::open_or_create(directory, Schema::builder().build());
+    assert_eq!(
+        format!("{:?}", err.unwrap_err()),
+        "SchemaError(\"An index exists but the schema does not match.\")"
+    );
+}
+
+fn throw_away_schema() -> Schema {
+    let mut schema_builder = Schema::builder();
+    let _ = schema_builder.add_u64_field("num_likes", INDEXED);
+    schema_builder.build()
+}
+
+#[test]
+fn test_index_on_commit_reload_policy() -> crate::Result<()> {
+    let schema = throw_away_schema();
+    let field = schema.get_field("num_likes").unwrap();
+    let index = Index::create_in_ram(schema);
+    let reader = index
+        .reader_builder()
+        .reload_policy(ReloadPolicy::OnCommit)
+        .try_into()
+        .unwrap();
+    assert_eq!(reader.searcher().num_docs(), 0);
+    test_index_on_commit_reload_policy_aux(field, &index, &reader)
+}
+
+#[cfg(feature = "mmap")]
+mod mmap_specific {
+
+    use std::path::PathBuf;
+
+    use tempfile::TempDir;
+
+    use super::*;
+    use crate::Directory;
+
+    #[test]
+    fn test_index_on_commit_reload_policy_mmap() -> crate::Result<()> {
+        let schema = throw_away_schema();
+        let field = schema.get_field("num_likes").unwrap();
+        let tempdir = TempDir::new().unwrap();
+        let tempdir_path = PathBuf::from(tempdir.path());
+        let index = Index::create_in_dir(tempdir_path, schema).unwrap();
+        let reader = index
+            .reader_builder()
+            .reload_policy(ReloadPolicy::OnCommit)
+            .try_into()
+            .unwrap();
+        assert_eq!(reader.searcher().num_docs(), 0);
+        test_index_on_commit_reload_policy_aux(field, &index, &reader)
+    }
+
+    #[test]
+    fn test_index_manual_policy_mmap() -> crate::Result<()> {
+        let schema = throw_away_schema();
+        let field = schema.get_field("num_likes").unwrap();
+        let mut index = Index::create_from_tempdir(schema)?;
+        let mut writer = index.writer_for_tests()?;
+        writer.commit()?;
+        let reader = index
+            .reader_builder()
+            .reload_policy(ReloadPolicy::Manual)
+            .try_into()?;
+        assert_eq!(reader.searcher().num_docs(), 0);
+        writer.add_document(doc!(field=>1u64))?;
+        let (sender, receiver) = crossbeam_channel::unbounded();
+        let _handle = index.directory_mut().watch(WatchCallback::new(move || {
+            let _ = sender.send(());
+        }));
+        writer.commit()?;
+        assert!(receiver.recv().is_ok());
+        assert_eq!(reader.searcher().num_docs(), 0);
+        reader.reload()?;
+        assert_eq!(reader.searcher().num_docs(), 1);
+        Ok(())
+    }
+
+    #[test]
+    fn test_index_on_commit_reload_policy_different_directories() -> crate::Result<()> {
+        let schema = throw_away_schema();
+        let field = schema.get_field("num_likes").unwrap();
+        let tempdir = TempDir::new().unwrap();
+        let tempdir_path = PathBuf::from(tempdir.path());
+        let write_index = Index::create_in_dir(&tempdir_path, schema).unwrap();
+        let read_index = Index::open_in_dir(&tempdir_path).unwrap();
+        let reader = read_index
+            .reader_builder()
+            .reload_policy(ReloadPolicy::OnCommit)
+            .try_into()
+            .unwrap();
+        assert_eq!(reader.searcher().num_docs(), 0);
+        test_index_on_commit_reload_policy_aux(field, &write_index, &reader)
+    }
+}
+fn test_index_on_commit_reload_policy_aux(
+    field: Field,
+    index: &Index,
+    reader: &IndexReader,
+) -> crate::Result<()> {
+    let mut reader_index = reader.index();
+    let (sender, receiver) = crossbeam_channel::unbounded();
+    let _watch_handle = reader_index
+        .directory_mut()
+        .watch(WatchCallback::new(move || {
+            let _ = sender.send(());
+        }));
+    let mut writer = index.writer_for_tests()?;
+    assert_eq!(reader.searcher().num_docs(), 0);
+    writer.add_document(doc!(field=>1u64))?;
+    writer.commit().unwrap();
+    // We need a loop here because it is possible for notify to send more than
+    // one modify event. It was observed on CI on MacOS.
+    loop {
+        assert!(receiver.recv().is_ok());
+        if reader.searcher().num_docs() == 1 {
+            break;
+        }
+    }
+    writer.add_document(doc!(field=>2u64))?;
+    writer.commit().unwrap();
+    // ... Same as above
+    loop {
+        assert!(receiver.recv().is_ok());
+        if reader.searcher().num_docs() == 2 {
+            break;
+        }
+    }
+    Ok(())
+}
+
+// This test will not pass on windows, because windows
+// prevent deleting files that are MMapped.
+#[cfg(not(target_os = "windows"))]
+#[test]
+fn garbage_collect_works_as_intended() -> crate::Result<()> {
+    let directory = RamDirectory::create();
+    let schema = throw_away_schema();
+    let field = schema.get_field("num_likes").unwrap();
+    let index = Index::create(directory.clone(), schema, IndexSettings::default())?;
+
+    let mut writer = index.writer_with_num_threads(1, 32_000_000).unwrap();
+    for _seg in 0..8 {
+        for i in 0u64..1_000u64 {
+            writer.add_document(doc!(field => i))?;
+        }
+        writer.commit()?;
+    }
+
+    let mem_right_after_commit = directory.total_mem_usage();
+
+    let reader = index
+        .reader_builder()
+        .reload_policy(ReloadPolicy::Manual)
+        .try_into()?;
+    assert_eq!(reader.searcher().num_docs(), 8_000);
+    assert_eq!(reader.searcher().segment_readers().len(), 8);
+
+    writer.wait_merging_threads()?;
+
+    let mem_right_after_merge_finished = directory.total_mem_usage();
+
+    reader.reload().unwrap();
+    let searcher = reader.searcher();
+    assert_eq!(searcher.segment_readers().len(), 1);
+    assert_eq!(searcher.num_docs(), 8_000);
+    assert!(
+        mem_right_after_merge_finished < mem_right_after_commit,
+        "(mem after merge){} is expected < (mem before merge){}",
+        mem_right_after_merge_finished,
+        mem_right_after_commit
+    );
+    Ok(())
+}
+
+#[test]
+fn test_single_segment_index_writer() -> crate::Result<()> {
+    let mut schema_builder = Schema::builder();
+    let text_field = schema_builder.add_text_field("text", TEXT);
+    let schema = schema_builder.build();
+    let directory = RamDirectory::default();
+    let mut single_segment_index_writer = Index::builder()
+        .schema(schema)
+        .single_segment_index_writer(directory, 10_000_000)?;
+    for _ in 0..10 {
+        let doc = doc!(text_field=>"hello");
+        single_segment_index_writer.add_document(doc)?;
+    }
+    let index = single_segment_index_writer.finalize()?;
+    let searcher = index.reader()?.searcher();
+    let term_query = TermQuery::new(
+        Term::from_field_text(text_field, "hello"),
+        IndexRecordOption::Basic,
+    );
+    let count = searcher.search(&term_query, &Count)?;
+    assert_eq!(count, 10);
+    Ok(())
+}
+
+#[test]
+fn test_merging_segment_update_docfreq() {
+    let mut schema_builder = Schema::builder();
+    let text_field = schema_builder.add_text_field("text", TEXT);
+    let id_field = schema_builder.add_text_field("id", STRING);
+    let schema = schema_builder.build();
+    let index = Index::create_in_ram(schema);
+    let mut writer = index.writer_for_tests().unwrap();
+    writer.set_merge_policy(Box::new(NoMergePolicy));
+    for _ in 0..5 {
+        writer.add_document(doc!(text_field=>"hello")).unwrap();
+    }
+    writer
+        .add_document(doc!(text_field=>"hello", id_field=>"TO_BE_DELETED"))
+        .unwrap();
+    writer
+        .add_document(doc!(text_field=>"hello", id_field=>"TO_BE_DELETED"))
+        .unwrap();
+    writer.add_document(Document::default()).unwrap();
+    writer.commit().unwrap();
+    for _ in 0..7 {
+        writer.add_document(doc!(text_field=>"hello")).unwrap();
+    }
+    writer.add_document(Document::default()).unwrap();
+    writer.add_document(Document::default()).unwrap();
+    writer.delete_term(Term::from_field_text(id_field, "TO_BE_DELETED"));
+    writer.commit().unwrap();
+
+    let segment_ids: Vec<SegmentId> = index
+        .list_all_segment_metas()
+        .into_iter()
+        .map(|reader| reader.id())
+        .collect();
+    writer.merge(&segment_ids[..]).wait().unwrap();
+    let index_reader = index.reader().unwrap();
+    let searcher = index_reader.searcher();
+    assert_eq!(searcher.segment_readers().len(), 1);
+    assert_eq!(searcher.num_docs(), 15);
+    let segment_reader = searcher.segment_reader(0);
+    assert_eq!(segment_reader.max_doc(), 15);
+    let inv_index = segment_reader.inverted_index(text_field).unwrap();
+    let term = Term::from_field_text(text_field, "hello");
+    let term_info = inv_index.get_term_info(&term).unwrap().unwrap();
+    assert_eq!(term_info.doc_freq, 12);
+}

src/error.rs

@@ -6,6 +6,7 @@ use std::{fmt, io};
 
 use thiserror::Error;
 
+use crate::aggregation::AggregationError;
 use crate::directory::error::{
     Incompatibility, LockError, OpenDirectoryError, OpenReadError, OpenWriteError,
 };
@@ -53,6 +54,9 @@ impl fmt::Debug for DataCorruption {
 /// The library's error enum
 #[derive(Debug, Clone, Error)]
 pub enum TantivyError {
+    /// Error when handling aggregations.
+    #[error("AggregationError {0:?}")]
+    AggregationError(#[from] AggregationError),
     /// Failed to open the directory.
     #[error("Failed to open the directory: '{0:?}'")]
     OpenDirectoryError(#[from] OpenDirectoryError),

src/fastfield/facet_reader.rs

@@ -51,7 +51,7 @@ impl FacetReader {
 
     /// Return the list of facet ordinals associated with a document.
     pub fn facet_ords(&self, doc: DocId) -> impl Iterator<Item = u64> + '_ {
-        self.facet_column.ords().values(doc)
+        self.facet_column.ords().values_for_doc(doc)
     }
 
     /// Accessor to the facet dictionary.

src/fastfield/mod.rs

@@ -19,9 +19,8 @@
 //!
 //! Read access performance is comparable to that of an array lookup.
 
-use std::net::Ipv6Addr;
-
 pub use columnar::Column;
+use columnar::MonotonicallyMappableToU64;
 
 pub use self::alive_bitset::{intersect_alive_bitsets, write_alive_bitset, AliveBitSet};
 pub use self::error::{FastFieldNotAvailableError, Result};
@@ -37,38 +36,9 @@ mod facet_reader;
 mod readers;
 mod writer;
 
-/// Trait for types that provide a zero value.
-///
-/// The resulting value is never used, just as placeholder, e.g. for `vec.resize()`.
-pub trait MakeZero {
-    /// Build a default value. This default value is never used, so the value does not
-    /// really matter.
-    fn make_zero() -> Self;
-}
-
-impl<T: FastValue> MakeZero for T {
-    fn make_zero() -> Self {
-        T::from_u64(0)
-    }
-}
-
-impl MakeZero for u128 {
-    fn make_zero() -> Self {
-        0
-    }
-}
-
-impl MakeZero for Ipv6Addr {
-    fn make_zero() -> Self {
-        Ipv6Addr::from(0u128.to_be_bytes())
-    }
-}
-
 /// Trait for types that are allowed for fast fields:
 /// (u64, i64 and f64, bool, DateTime).
-pub trait FastValue:
-    Copy + Send + Sync + columnar::MonotonicallyMappableToU64 + PartialOrd + 'static
-{
+pub trait FastValue: MonotonicallyMappableToU64 {
     /// Returns the `schema::Type` for this FastValue.
     fn to_type() -> Type;
 }
@@ -105,10 +75,11 @@ impl FastValue for DateTime {
 #[cfg(test)]
 mod tests {
 
+    use std::net::Ipv6Addr;
     use std::ops::{Range, RangeInclusive};
     use std::path::Path;
 
-    use columnar::{Column, MonotonicallyMappableToU64};
+    use columnar::{Column, MonotonicallyMappableToU64, StrColumn};
     use common::{HasLen, TerminatingWrite};
     use once_cell::sync::Lazy;
     use rand::prelude::SliceRandom;
@@ -119,7 +90,8 @@ mod tests {
     use crate::directory::{Directory, RamDirectory, WritePtr};
     use crate::merge_policy::NoMergePolicy;
     use crate::schema::{
-        Document, Facet, FacetOptions, Field, Schema, SchemaBuilder, FAST, INDEXED, STRING, TEXT,
+        Document, Facet, FacetOptions, Field, JsonObjectOptions, Schema, SchemaBuilder, FAST,
+        INDEXED, STORED, STRING, TEXT,
     };
     use crate::time::OffsetDateTime;
     use crate::{DateOptions, DatePrecision, Index, SegmentId, SegmentReader};
@@ -159,7 +131,7 @@ mod tests {
         let file = directory.open_read(path).unwrap();
 
         assert_eq!(file.len(), 161);
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
         let column = fast_field_readers
             .u64("field")
             .unwrap()
@@ -209,7 +181,7 @@ mod tests {
         }
         let file = directory.open_read(path).unwrap();
         assert_eq!(file.len(), 189);
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
         let col = fast_field_readers
             .u64("field")
             .unwrap()
@@ -242,7 +214,7 @@ mod tests {
         }
         let file = directory.open_read(path).unwrap();
         assert_eq!(file.len(), 162);
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
         let fast_field_reader = fast_field_readers
             .u64("field")
             .unwrap()
@@ -266,7 +238,7 @@ mod tests {
                 .unwrap();
             for doc_id in 1u64..10_000u64 {
                 fast_field_writers
-                    .add_document(&doc!(*FIELD=>5_000_000_000_000_000_000u64 + doc_id as u64))
+                    .add_document(&doc!(*FIELD=>5_000_000_000_000_000_000u64 + doc_id))
                     .unwrap();
             }
             fast_field_writers.serialize(&mut write, None).unwrap();
@@ -275,7 +247,7 @@ mod tests {
         let file = directory.open_read(path).unwrap();
         assert_eq!(file.len(), 4557);
         {
-            let fast_field_readers = FastFieldReaders::open(file).unwrap();
+            let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
             let col = fast_field_readers
                 .u64("field")
                 .unwrap()
@@ -309,7 +281,7 @@ mod tests {
         assert_eq!(file.len(), 333_usize);
 
         {
-            let fast_field_readers = FastFieldReaders::open(file).unwrap();
+            let fast_field_readers = FastFieldReaders::open(file, schema).unwrap();
             let col = fast_field_readers
                 .i64("field")
                 .unwrap()
@@ -346,7 +318,7 @@ mod tests {
         }
 
         let file = directory.open_read(path).unwrap();
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, schema).unwrap();
         let col = fast_field_readers.i64("field").unwrap();
         assert_eq!(col.first(0), None);
 
@@ -379,7 +351,7 @@ mod tests {
         }
 
         let file = directory.open_read(path).unwrap();
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, schema).unwrap();
         let col = fast_field_readers
             .date("date")
             .unwrap()
@@ -415,7 +387,7 @@ mod tests {
             write.terminate().unwrap();
         }
         let file = directory.open_read(path).unwrap();
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
         let col = fast_field_readers
             .u64("field")
             .unwrap()
@@ -466,7 +438,7 @@ mod tests {
 
     fn get_vals_for_docs(column: &Column<u64>, docs: Range<u32>) -> Vec<u64> {
         docs.into_iter()
-            .flat_map(|doc| column.values(doc))
+            .flat_map(|doc| column.values_for_doc(doc))
             .collect()
     }
 
@@ -514,11 +486,11 @@ mod tests {
             let segment_reader = searcher.segment_reader(0);
             let fast_fields = segment_reader.fast_fields();
             let str_column = fast_fields.str("text").unwrap().unwrap();
-            assert!(str_column.ords().values(0u32).eq([1, 0]),);
-            assert!(str_column.ords().values(1u32).next().is_none());
-            assert!(str_column.ords().values(2u32).eq([0]),);
-            assert!(str_column.ords().values(3u32).eq([0, 1]),);
-            assert!(str_column.ords().values(4u32).eq([2]),);
+            assert!(str_column.ords().values_for_doc(0u32).eq([1, 0]),);
+            assert!(str_column.ords().values_for_doc(1u32).next().is_none());
+            assert!(str_column.ords().values_for_doc(2u32).eq([0]),);
+            assert!(str_column.ords().values_for_doc(3u32).eq([0, 1]),);
+            assert!(str_column.ords().values_for_doc(4u32).eq([2]),);
 
             let mut str_term = String::default();
             assert!(str_column.ord_to_str(0, &mut str_term).unwrap());
@@ -557,7 +529,7 @@ mod tests {
             let fast_fields = segment_reader.fast_fields();
             let text_fast_field = fast_fields.str("text").unwrap().unwrap();
 
-            assert_eq!(&get_vals_for_docs(&text_fast_field.ords(), 0..2), &[0, 1]);
+            assert_eq!(&get_vals_for_docs(text_fast_field.ords(), 0..2), &[0, 1]);
         }
 
         // TODO uncomment once merging is available
@@ -653,7 +625,7 @@ mod tests {
             let fast_fields = segment_reader.fast_fields();
             let text_col = fast_fields.str("text").unwrap().unwrap();
 
-            assert_eq!(get_vals_for_docs(&text_col.ords(), 0..6), vec![1, 0, 0, 2]);
+            assert_eq!(get_vals_for_docs(text_col.ords(), 0..6), vec![1, 0, 0, 2]);
 
             let inverted_index = segment_reader.inverted_index(text_field)?;
             assert_eq!(inverted_index.terms().num_terms(), 3);
@@ -701,7 +673,7 @@ mod tests {
         let text_fast_field = fast_fields.str("text").unwrap().unwrap();
 
         assert_eq!(
-            get_vals_for_docs(&text_fast_field.ords(), 0..9),
+            get_vals_for_docs(text_fast_field.ords(), 0..9),
             vec![1, 0, 0, 3 /* next segment */, 0, 2]
         );
 
@@ -801,7 +773,7 @@ mod tests {
         }
         let file = directory.open_read(path).unwrap();
         assert_eq!(file.len(), 175);
-        let fast_field_readers = FastFieldReaders::open(file).unwrap();
+        let fast_field_readers = FastFieldReaders::open(file, schema).unwrap();
         let bool_col = fast_field_readers.bool("field_bool").unwrap();
         assert_eq!(bool_col.first(0), Some(true));
         assert_eq!(bool_col.first(1), Some(false));
@@ -833,7 +805,7 @@ mod tests {
         }
         let file = directory.open_read(path).unwrap();
         assert_eq!(file.len(), 187);
-        let readers = FastFieldReaders::open(file).unwrap();
+        let readers = FastFieldReaders::open(file, schema).unwrap();
         let bool_col = readers.bool("field_bool").unwrap();
         for i in 0..25 {
             assert_eq!(bool_col.first(i * 2), Some(true));
@@ -858,7 +830,7 @@ mod tests {
         }
         let file = directory.open_read(path).unwrap();
         assert_eq!(file.len(), 177);
-        let fastfield_readers = FastFieldReaders::open(file).unwrap();
+        let fastfield_readers = FastFieldReaders::open(file, schema).unwrap();
         let col = fastfield_readers.bool("field_bool").unwrap();
         assert_eq!(col.first(0), None);
         let col = fastfield_readers
@@ -920,11 +892,11 @@ mod tests {
         let directory = get_index(&docs[..], &schema).unwrap();
         let path = Path::new("test");
         let file = directory.open_read(path).unwrap();
-        let readers = FastFieldReaders::open(file).unwrap();
+        let readers = FastFieldReaders::open(file, schema).unwrap();
         let col = readers.date("field").unwrap();
 
         for (i, time) in times.iter().enumerate() {
-            let dt: DateTime = col.first(i as u32).unwrap().into();
+            let dt: DateTime = col.first(i as u32).unwrap();
             assert_eq!(dt, time.truncate(precision));
         }
         readers.column_num_bytes("field").unwrap()
@@ -1071,4 +1043,158 @@ mod tests {
         test_range_variant(1000, 1000);
         test_range_variant(1000, 1002);
     }
+
+    #[test]
+    fn test_json_object_fast_field() {
+        let mut schema_builder = Schema::builder();
+        let without_fast_field = schema_builder.add_json_field("without", STORED);
+        let with_fast_field = schema_builder.add_json_field("with", STORED | FAST);
+        let schema = schema_builder.build();
+        let index = Index::create_in_ram(schema);
+        let mut writer = index.writer_for_tests().unwrap();
+        writer
+            .add_document(doc!(without_fast_field=>json!({"hello": "without"})))
+            .unwrap();
+        writer
+            .add_document(doc!(with_fast_field=>json!({"hello": "with"})))
+            .unwrap();
+        writer
+            .add_document(doc!(with_fast_field=>json!({"hello": "with2"})))
+            .unwrap();
+        writer
+            .add_document(doc!(with_fast_field=>json!({"hello": "with1"})))
+            .unwrap();
+        writer.commit().unwrap();
+        let searcher = index.reader().unwrap().searcher();
+        let segment_reader = searcher.segment_reader(0u32);
+        let fast_fields = segment_reader.fast_fields();
+        let column_without_opt: Option<StrColumn> = fast_fields.str("without.hello").unwrap();
+        assert!(column_without_opt.is_none());
+        let column_with_opt: Option<StrColumn> = fast_fields.str("with.hello").unwrap();
+        let column_with: StrColumn = column_with_opt.unwrap();
+        assert!(column_with.term_ords(0).next().is_none());
+        assert!(column_with.term_ords(1).eq([0]));
+        assert!(column_with.term_ords(2).eq([2]));
+        assert!(column_with.term_ords(3).eq([1]));
+    }
+
+    #[test]
+    fn test_fast_field_in_json_field_expand_dots_disabled() {
+        let mut schema_builder = Schema::builder();
+        let json_option = JsonObjectOptions::default().set_fast();
+        let json = schema_builder.add_json_field("json", json_option);
+        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(doc!(json => json!({"attr.age": 32})))
+            .unwrap();
+        index_writer.commit().unwrap();
+        let searcher = index.reader().unwrap().searcher();
+        let fast_field_reader = searcher.segment_reader(0u32).fast_fields();
+        assert!(fast_field_reader
+            .column_opt::<i64>("json.attr.age")
+            .unwrap()
+            .is_none());
+        let column = fast_field_reader
+            .column_opt::<i64>(r#"json.attr\.age"#)
+            .unwrap()
+            .unwrap();
+        let vals: Vec<i64> = column.values_for_doc(0u32).collect();
+        assert_eq!(&vals, &[32])
+    }
+
+    #[test]
+    fn test_fast_field_in_json_field_expand_dots_enabled() {
+        let mut schema_builder = Schema::builder();
+        let json_option = JsonObjectOptions::default()
+            .set_fast()
+            .set_expand_dots_enabled();
+        let json = schema_builder.add_json_field("json", json_option);
+        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(doc!(json => json!({"attr.age": 32})))
+            .unwrap();
+        index_writer.commit().unwrap();
+        let searcher = index.reader().unwrap().searcher();
+        let fast_field_reader = searcher.segment_reader(0u32).fast_fields();
+        for test_column_name in &["json.attr.age", "json.attr\\.age"] {
+            let column = fast_field_reader
+                .column_opt::<i64>(test_column_name)
+                .unwrap()
+                .unwrap();
+            let vals: Vec<i64> = column.values_for_doc(0u32).collect();
+            assert_eq!(&vals, &[32]);
+        }
+    }
+
+    #[test]
+    fn test_fast_field_dot_in_schema_field_name() {
+        let mut schema_builder = Schema::builder();
+        let field_with_dot = schema_builder.add_i64_field("field.with.dot", FAST);
+        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(doc!(field_with_dot => 32i64))
+            .unwrap();
+        index_writer.commit().unwrap();
+        let searcher = index.reader().unwrap().searcher();
+        let fast_field_reader = searcher.segment_reader(0u32).fast_fields();
+        let column = fast_field_reader
+            .column_opt::<i64>("field.with.dot")
+            .unwrap()
+            .unwrap();
+        let vals: Vec<i64> = column.values_for_doc(0u32).collect();
+        assert_eq!(&vals, &[32]);
+    }
+
+    #[test]
+    fn test_shadowing_fast_field() {
+        let mut schema_builder = Schema::builder();
+        let json_field = schema_builder.add_json_field("jsonfield", FAST);
+        let shadowing_json_field = schema_builder.add_json_field("jsonfield.attr", FAST);
+        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(doc!(json_field=> json!({"attr": {"age": 32}}), shadowing_json_field=>json!({"age": 33})))
+            .unwrap();
+        index_writer.commit().unwrap();
+        let searcher = index.reader().unwrap().searcher();
+        let fast_field_reader = searcher.segment_reader(0u32).fast_fields();
+        let column = fast_field_reader
+            .column_opt::<i64>(&"jsonfield.attr.age")
+            .unwrap()
+            .unwrap();
+        let vals: Vec<i64> = column.values_for_doc(0u32).collect();
+        assert_eq!(&vals, &[33]);
+    }
+
+    #[test]
+    fn test_shadowing_fast_field_with_expand_dots() {
+        let mut schema_builder = Schema::builder();
+        let json_option = JsonObjectOptions::default()
+            .set_fast()
+            .set_expand_dots_enabled();
+        let json_field = schema_builder.add_json_field("jsonfield", json_option.clone());
+        let shadowing_json_field = schema_builder.add_json_field("jsonfield.attr", json_option);
+        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(doc!(json_field=> json!({"attr.age": 32}), shadowing_json_field=>json!({"age": 33})))
+            .unwrap();
+        index_writer.commit().unwrap();
+        let searcher = index.reader().unwrap().searcher();
+        let fast_field_reader = searcher.segment_reader(0u32).fast_fields();
+        let column = fast_field_reader
+            .column_opt::<i64>(&"jsonfield.attr.age")
+            .unwrap()
+            .unwrap();
+        let vals: Vec<i64> = column.values_for_doc(0u32).collect();
+        assert_eq!(&vals, &[33]);
+    }
 }

src/fastfield/readers.rs

@@ -7,8 +7,9 @@ use columnar::{
     DynamicColumnHandle, HasAssociatedColumnType, StrColumn,
 };
 
+use crate::core::json_utils::encode_column_name;
 use crate::directory::FileSlice;
-use crate::schema::Schema;
+use crate::schema::{Field, FieldEntry, FieldType, Schema};
 use crate::space_usage::{FieldUsage, PerFieldSpaceUsage};
 
 /// Provides access to all of the BitpackedFastFieldReader.
@@ -18,16 +19,22 @@ use crate::space_usage::{FieldUsage, PerFieldSpaceUsage};
 #[derive(Clone)]
 pub struct FastFieldReaders {
     columnar: Arc<ColumnarReader>,
+    schema: Schema,
 }
 
 impl FastFieldReaders {
-    pub(crate) fn open(fast_field_file: FileSlice) -> io::Result<FastFieldReaders> {
+    pub(crate) fn open(fast_field_file: FileSlice, schema: Schema) -> io::Result<FastFieldReaders> {
         let columnar = Arc::new(ColumnarReader::open(fast_field_file)?);
-        Ok(FastFieldReaders { columnar })
+        Ok(FastFieldReaders { columnar, schema })
     }
 
-    pub(crate) fn columnar(&self) -> &ColumnarReader {
-        self.columnar.as_ref()
+    fn resolve_field(&self, column_name: &str) -> Option<String> {
+        let default_field_opt: Option<Field> = if cfg!(feature = "quickwit") {
+            self.schema.get_field("_dynamic").ok()
+        } else {
+            None
+        };
+        self.resolve_column_name_given_default_field(column_name, default_field_opt)
     }
 
     pub(crate) fn space_usage(&self, schema: &Schema) -> io::Result<PerFieldSpaceUsage> {
@@ -46,6 +53,59 @@ impl FastFieldReaders {
         Ok(PerFieldSpaceUsage::new(per_field_usages))
     }
 
+    pub(crate) fn columnar(&self) -> &ColumnarReader {
+        self.columnar.as_ref()
+    }
+
+    /// Transforms a user-supplied fast field name into a column name.
+    ///
+    /// A user-supplied fast field name is not necessarily a schema field name
+    /// because we handle fast fields.
+    ///
+    /// For instance, if the documents look like `{.., "attributes": {"color": "red"}}` and
+    /// `attributes` is a json fast field,  a user could want to run a term aggregation over
+    /// colors, by referring to the field as `attributes.color`.
+    ///
+    /// This function transforms `attributes.color` into a column key to be used in the `columnar`.
+    ///
+    /// The logic works as follows, first we identify which field is targetted by calling
+    /// `schema.find_field(..)`. This method will attempt to split the user splied fast field
+    /// name by non-escaped dots, and find the longest matching schema field name.
+    /// In our case, it would return the (attribute_field, "color").
+    ///
+    /// If no field is found, but a dynamic field is supplied, then we
+    /// will simply assuem the user is targetting the dynamic field. (This feature is used in
+    /// Quickwit.)
+    ///
+    /// We then encode the `(field, path)` into the right `columnar_key`.
+    fn resolve_column_name_given_default_field<'a>(
+        &'a self,
+        field_name: &'a str,
+        default_field_opt: Option<Field>,
+    ) -> Option<String> {
+        let (field, path): (Field, &str) = self
+            .schema
+            .find_field(field_name)
+            .or_else(|| default_field_opt.map(|default_field| (default_field, field_name)))?;
+        let field_name = self.schema.get_field_name(field);
+        if path.is_empty() {
+            return Some(field_name.to_string());
+        }
+        let field_entry: &FieldEntry = self.schema.get_field_entry(field);
+        let field_type = field_entry.field_type();
+        match (field_type, path) {
+            (FieldType::JsonObject(json_options), path) if !path.is_empty() => {
+                Some(encode_column_name(
+                    field_entry.name(),
+                    path,
+                    json_options.is_expand_dots_enabled(),
+                ))
+            }
+            (_, "") => Some(field_entry.name().to_string()),
+            _ => None,
+        }
+    }
+
     /// Returns a typed column associated to a given field name.
     ///
     /// If no column associated with that field_name exists,
@@ -53,11 +113,10 @@ impl FastFieldReaders {
     /// returns `None`.
     pub fn column_opt<T>(&self, field_name: &str) -> crate::Result<Option<Column<T>>>
     where
-        T: PartialOrd + Copy + HasAssociatedColumnType + Send + Sync + 'static,
+        T: HasAssociatedColumnType,
         DynamicColumn: Into<Option<Column<T>>>,
     {
-        let column_type = T::column_type();
-        let Some(dynamic_column_handle) = self.dynamic_column_handle(field_name, column_type)?
+        let Some(dynamic_column_handle) = self.dynamic_column_handle(field_name, T::column_type())?
         else {
             return Ok(None);
         };
@@ -66,10 +125,15 @@ impl FastFieldReaders {
     }
 
     /// Returns the number of `bytes` associated with a column.
+    ///
+    /// Returns 0 if the column does not exist.
     pub fn column_num_bytes(&self, field: &str) -> crate::Result<usize> {
+        let Some(resolved_field_name) = self.resolve_field(field) else {
+            return Ok(0);
+        };
         Ok(self
             .columnar
-            .read_columns(field)?
+            .read_columns(&resolved_field_name)?
             .into_iter()
             .map(|column_handle| column_handle.num_bytes())
             .sum())
@@ -92,7 +156,7 @@ impl FastFieldReaders {
     /// Returns a typed column associated to a given field name.
     ///
     /// Returns an error if no column associated with that field_name exists.
-    pub fn column<T>(&self, field: &str) -> crate::Result<Column<T>>
+    fn column<T>(&self, field: &str) -> crate::Result<Column<T>>
     where
         T: PartialOrd + Copy + HasAssociatedColumnType + Send + Sync + 'static,
         DynamicColumn: Into<Option<Column<T>>>,
@@ -152,20 +216,52 @@ impl FastFieldReaders {
         field_name: &str,
         column_type: ColumnType,
     ) -> crate::Result<Option<DynamicColumnHandle>> {
+        let Some(resolved_field_name) = self.resolve_field(field_name) else {
+            return Ok(None);
+        };
         let dynamic_column_handle_opt = self
             .columnar
-            .read_columns(field_name)?
+            .read_columns(&resolved_field_name)?
             .into_iter()
             .find(|column| column.column_type() == column_type);
         Ok(dynamic_column_handle_opt)
     }
 
+    #[doc(hidden)]
+    pub async fn list_dynamic_column_handles(
+        &self,
+        field_name: &str,
+    ) -> crate::Result<Vec<DynamicColumnHandle>> {
+        let Some(resolved_field_name) = self.resolve_field(field_name) else {
+            return Ok(Vec::new());
+        };
+        let columns = self
+            .columnar
+            .read_columns_async(&resolved_field_name)
+            .await?;
+        Ok(columns)
+    }
+
     /// Returns the `u64` column used to represent any `u64`-mapped typed (i64, u64, f64, DateTime).
     #[doc(hidden)]
     pub fn u64_lenient(&self, field_name: &str) -> crate::Result<Option<Column<u64>>> {
-        for col in self.columnar.read_columns(field_name)? {
+        Ok(self
+            .u64_lenient_with_type(field_name)?
+            .map(|(u64_column, _)| u64_column))
+    }
+
+    /// Returns the `u64` column used to represent any `u64`-mapped typed (i64, u64, f64, DateTime).
+    #[doc(hidden)]
+    pub fn u64_lenient_with_type(
+        &self,
+        field_name: &str,
+    ) -> crate::Result<Option<(Column<u64>, ColumnType)>> {
+        let Some(resolved_field_name) = self.resolve_field(field_name) else {
+            return Ok(None);
+        };
+        for col in self.columnar.read_columns(&resolved_field_name)? {
             if let Some(col_u64) = col.open_u64_lenient()? {
-                return Ok(Some(col_u64));
+                return Ok(Some((col_u64, col.column_type())));
             }
         }
         Ok(None)
@@ -192,3 +288,73 @@ impl FastFieldReaders {
         self.column(field_name)
     }
 }
+
+#[cfg(test)]
+mod tests {
+    use crate::schema::{JsonObjectOptions, Schema, FAST};
+    use crate::{Document, Index};
+
+    #[test]
+    fn test_fast_field_reader_resolve_with_dynamic_internal() {
+        let mut schema_builder = Schema::builder();
+        schema_builder.add_i64_field("age", FAST);
+        schema_builder.add_json_field("json_expand_dots_disabled", FAST);
+        schema_builder.add_json_field(
+            "json_expand_dots_enabled",
+            JsonObjectOptions::default()
+                .set_fast()
+                .set_expand_dots_enabled(),
+        );
+        let dynamic_field = schema_builder.add_json_field("_dyna", FAST);
+        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(Document::default()).unwrap();
+        index_writer.commit().unwrap();
+        let reader = index.reader().unwrap();
+        let searcher = reader.searcher();
+        let reader = searcher.segment_reader(0u32);
+        let fast_field_readers = reader.fast_fields();
+        assert_eq!(
+            fast_field_readers.resolve_column_name_given_default_field("age", None),
+            Some("age".to_string())
+        );
+        assert_eq!(
+            fast_field_readers.resolve_column_name_given_default_field("age", Some(dynamic_field)),
+            Some("age".to_string())
+        );
+        assert_eq!(
+            fast_field_readers.resolve_column_name_given_default_field(
+                "json_expand_dots_disabled.attr.color",
+                None
+            ),
+            Some("json_expand_dots_disabled\u{1}attr\u{1}color".to_string())
+        );
+        assert_eq!(
+            fast_field_readers.resolve_column_name_given_default_field(
+                "json_expand_dots_disabled.attr\\.color",
+                Some(dynamic_field)
+            ),
+            Some("json_expand_dots_disabled\u{1}attr.color".to_string())
+        );
+        assert_eq!(
+            fast_field_readers.resolve_column_name_given_default_field(
+                "json_expand_dots_enabled.attr\\.color",
+                Some(dynamic_field)
+            ),
+            Some("json_expand_dots_enabled\u{1}attr\u{1}color".to_string())
+        );
+        assert_eq!(
+            fast_field_readers
+                .resolve_column_name_given_default_field("notinschema.attr.color", None),
+            None
+        );
+        assert_eq!(
+            fast_field_readers.resolve_column_name_given_default_field(
+                "notinschema.attr.color",
+                Some(dynamic_field)
+            ),
+            Some("_dyna\u{1}notinschema\u{1}attr\u{1}color".to_string())
+        );
+    }
+}

src/fastfield/writer.rs

@@ -1,64 +1,68 @@
 use std::io;
 
-use columnar::{ColumnType, ColumnarWriter, NumericalValue};
+use columnar::{ColumnarWriter, NumericalValue};
+use common::replace_in_place;
 
 use crate::indexer::doc_id_mapping::DocIdMapping;
-use crate::schema::{Document, FieldType, Schema, Type, Value};
+use crate::schema::term::{JSON_PATH_SEGMENT_SEP, JSON_PATH_SEGMENT_SEP_STR};
+use crate::schema::{value_type_to_column_type, Document, FieldType, Schema, Type, Value};
 use crate::{DatePrecision, DocId};
 
+/// Only index JSON down to a depth of 20.
+/// This is mostly to guard us from a stack overflow triggered by malicious input.
+const JSON_DEPTH_LIMIT: usize = 20;
+
 /// The `FastFieldsWriter` groups all of the fast field writers.
 pub struct FastFieldsWriter {
     columnar_writer: ColumnarWriter,
     fast_field_names: Vec<Option<String>>, //< TODO see if we can cash the field name hash too.
     date_precisions: Vec<DatePrecision>,
+    expand_dots: Vec<bool>,
     num_docs: DocId,
+    // Buffer that we recycle to avoid allocation.
+    json_path_buffer: String,
 }
 
 impl FastFieldsWriter {
     /// Create all `FastFieldWriter` required by the schema.
     pub fn from_schema(schema: &Schema) -> FastFieldsWriter {
         let mut columnar_writer = ColumnarWriter::default();
-        let mut fast_fields: Vec<Option<String>> = vec![None; schema.num_fields()];
+        let mut fast_field_names: Vec<Option<String>> = vec![None; schema.num_fields()];
         let mut date_precisions: Vec<DatePrecision> =
             std::iter::repeat_with(DatePrecision::default)
                 .take(schema.num_fields())
                 .collect();
+        let mut expand_dots = vec![false; schema.num_fields()];
         // TODO see other types
         for (field_id, field_entry) in schema.fields() {
             if !field_entry.field_type().is_fast() {
                 continue;
             }
-            fast_fields[field_id.field_id() as usize] = Some(field_entry.name().to_string());
+            fast_field_names[field_id.field_id() as usize] = Some(field_entry.name().to_string());
             let value_type = field_entry.field_type().value_type();
-            let column_type = match value_type {
-                Type::Str => ColumnType::Str,
-                Type::U64 => ColumnType::U64,
-                Type::I64 => ColumnType::I64,
-                Type::F64 => ColumnType::F64,
-                Type::Bool => ColumnType::Bool,
-                Type::Date => ColumnType::DateTime,
-                Type::Facet => ColumnType::Str,
-                Type::Bytes => ColumnType::Bytes,
-                Type::Json => {
-                    continue;
-                }
-                Type::IpAddr => ColumnType::IpAddr,
-            };
             if let FieldType::Date(date_options) = field_entry.field_type() {
                 date_precisions[field_id.field_id() as usize] = date_options.get_precision();
             }
+            if let FieldType::JsonObject(json_object_options) = field_entry.field_type() {
+                expand_dots[field_id.field_id() as usize] =
+                    json_object_options.is_expand_dots_enabled();
+            }
             let sort_values_within_row = value_type == Type::Facet;
-            columnar_writer.record_column_type(
-                field_entry.name(),
-                column_type,
-                sort_values_within_row,
-            );
+            if let Some(column_type) = value_type_to_column_type(value_type) {
+                columnar_writer.record_column_type(
+                    field_entry.name(),
+                    column_type,
+                    sort_values_within_row,
+                );
+            }
         }
         FastFieldsWriter {
             columnar_writer,
-            fast_field_names: fast_fields,
+            fast_field_names,
             num_docs: 0u32,
             date_precisions,
+            expand_dots,
+            json_path_buffer: String::new(),
         }
     }
 
@@ -82,7 +86,7 @@ impl FastFieldsWriter {
         let doc_id = self.num_docs;
         for field_value in doc.field_values() {
             if let Some(field_name) =
-                self.fast_field_names[field_value.field().field_id() as usize].as_ref()
+                &self.fast_field_names[field_value.field().field_id() as usize]
             {
                 match &field_value.value {
                     Value::U64(u64_val) => {
@@ -136,7 +140,19 @@ impl FastFieldsWriter {
                             facet.encoded_str(),
                         );
                     }
-                    Value::JsonObject(_) => todo!(),
+                    Value::JsonObject(json_obj) => {
+                        let expand_dots = self.expand_dots[field_value.field().field_id() as usize];
+                        self.json_path_buffer.clear();
+                        self.json_path_buffer.push_str(field_name);
+                        record_json_obj_to_columnar_writer(
+                            doc_id,
+                            json_obj,
+                            expand_dots,
+                            JSON_DEPTH_LIMIT,
+                            &mut self.json_path_buffer,
+                            &mut self.columnar_writer,
+                        );
+                    }
                     Value::IpAddr(ip_addr) => {
                         self.columnar_writer
                             .record_ip_addr(doc_id, field_name.as_str(), *ip_addr);
@@ -163,3 +179,242 @@ impl FastFieldsWriter {
         Ok(())
     }
 }
+
+#[inline]
+fn columnar_numerical_value(json_number: &serde_json::Number) -> Option<NumericalValue> {
+    if let Some(num_i64) = json_number.as_i64() {
+        return Some(num_i64.into());
+    }
+    if let Some(num_u64) = json_number.as_u64() {
+        return Some(num_u64.into());
+    }
+    if let Some(num_f64) = json_number.as_f64() {
+        return Some(num_f64.into());
+    }
+    // This can happen with arbitrary precision.... but we do not handle it.
+    None
+}
+
+fn record_json_obj_to_columnar_writer(
+    doc: DocId,
+    json_obj: &serde_json::Map<String, serde_json::Value>,
+    expand_dots: bool,
+    remaining_depth_limit: usize,
+    json_path_buffer: &mut String,
+    columnar_writer: &mut columnar::ColumnarWriter,
+) {
+    for (key, child) in json_obj {
+        let len_path = json_path_buffer.len();
+        if !json_path_buffer.is_empty() {
+            json_path_buffer.push_str(JSON_PATH_SEGMENT_SEP_STR);
+        }
+        json_path_buffer.push_str(key);
+        if expand_dots {
+            // This might include the separation byte, which is ok because it is not a dot.
+            let appended_segment = &mut json_path_buffer[len_path..];
+            // The unsafe below is safe as long as b'.' and JSON_PATH_SEGMENT_SEP are
+            // valid single byte ut8 strings.
+            // By utf-8 design, they cannot be part of another codepoint.
+            replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, unsafe {
+                appended_segment.as_bytes_mut()
+            });
+        }
+        record_json_value_to_columnar_writer(
+            doc,
+            child,
+            expand_dots,
+            remaining_depth_limit,
+            json_path_buffer,
+            columnar_writer,
+        );
+        // popping our sub path.
+        json_path_buffer.truncate(len_path);
+    }
+}
+
+fn record_json_value_to_columnar_writer(
+    doc: DocId,
+    json_val: &serde_json::Value,
+    expand_dots: bool,
+    mut remaining_depth_limit: usize,
+    json_path_writer: &mut String,
+    columnar_writer: &mut columnar::ColumnarWriter,
+) {
+    if remaining_depth_limit == 0 {
+        return;
+    }
+    remaining_depth_limit -= 1;
+    match json_val {
+        serde_json::Value::Null => {
+            // TODO handle null
+        }
+        serde_json::Value::Bool(bool_val) => {
+            columnar_writer.record_bool(doc, json_path_writer, *bool_val);
+        }
+        serde_json::Value::Number(json_number) => {
+            if let Some(numerical_value) = columnar_numerical_value(json_number) {
+                columnar_writer.record_numerical(doc, json_path_writer.as_str(), numerical_value);
+            }
+        }
+        serde_json::Value::String(text) => {
+            columnar_writer.record_str(doc, json_path_writer.as_str(), text);
+        }
+        serde_json::Value::Array(arr) => {
+            for el in arr {
+                record_json_value_to_columnar_writer(
+                    doc,
+                    el,
+                    expand_dots,
+                    remaining_depth_limit,
+                    json_path_writer,
+                    columnar_writer,
+                );
+            }
+        }
+        serde_json::Value::Object(json_obj) => {
+            record_json_obj_to_columnar_writer(
+                doc,
+                json_obj,
+                expand_dots,
+                remaining_depth_limit,
+                json_path_writer,
+                columnar_writer,
+            );
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use columnar::{Column, ColumnarReader, ColumnarWriter, StrColumn};
+
+    use super::record_json_value_to_columnar_writer;
+    use crate::fastfield::writer::JSON_DEPTH_LIMIT;
+    use crate::DocId;
+
+    fn test_columnar_from_jsons_aux(
+        json_docs: &[serde_json::Value],
+        expand_dots: bool,
+    ) -> ColumnarReader {
+        let mut columnar_writer = ColumnarWriter::default();
+        let mut json_path = String::new();
+        for (doc, json_doc) in json_docs.iter().enumerate() {
+            record_json_value_to_columnar_writer(
+                doc as u32,
+                json_doc,
+                expand_dots,
+                JSON_DEPTH_LIMIT,
+                &mut json_path,
+                &mut columnar_writer,
+            );
+        }
+        let mut buffer = Vec::new();
+        columnar_writer
+            .serialize(json_docs.len() as DocId, None, &mut buffer)
+            .unwrap();
+        ColumnarReader::open(buffer).unwrap()
+    }
+
+    #[test]
+    fn test_json_fastfield_record_simple() {
+        let json_doc = serde_json::json!({
+            "float": 1.02,
+            "text": "hello happy tax payer",
+            "nested": {"child": 3, "child2": 5},
+            "arr": ["hello", "happy", "tax", "payer"]
+        });
+        let columnar_reader = test_columnar_from_jsons_aux(&[json_doc], false);
+        let columns = columnar_reader.list_columns().unwrap();
+        {
+            assert_eq!(columns[0].0, "arr");
+            let column_arr_opt: Option<StrColumn> = columns[0].1.open().unwrap().into();
+            assert!(column_arr_opt
+                .unwrap()
+                .term_ords(0)
+                .eq([1, 0, 3, 2].into_iter()));
+        }
+        {
+            assert_eq!(columns[1].0, "float");
+            let column_float_opt: Option<Column<f64>> = columns[1].1.open().unwrap().into();
+            assert!(column_float_opt
+                .unwrap()
+                .values_for_doc(0)
+                .eq([1.02f64].into_iter()));
+        }
+        {
+            assert_eq!(columns[2].0, "nested\u{1}child");
+            let column_nest_child_opt: Option<Column<i64>> = columns[2].1.open().unwrap().into();
+            assert!(column_nest_child_opt
+                .unwrap()
+                .values_for_doc(0)
+                .eq([3].into_iter()));
+        }
+        {
+            assert_eq!(columns[3].0, "nested\u{1}child2");
+            let column_nest_child2_opt: Option<Column<i64>> = columns[3].1.open().unwrap().into();
+            assert!(column_nest_child2_opt
+                .unwrap()
+                .values_for_doc(0)
+                .eq([5].into_iter()));
+        }
+        {
+            assert_eq!(columns[4].0, "text");
+            let column_text_opt: Option<StrColumn> = columns[4].1.open().unwrap().into();
+            assert!(column_text_opt.unwrap().term_ords(0).eq([0].into_iter()));
+        }
+    }
+
+    #[test]
+    fn test_json_fastfield_deep_obj() {
+        let json_doc = serde_json::json!(
+            {"a": {"a": {"a": {"a": {"a":
+            {"a": {"a": {"a": {"a": {"a":
+            {"a": {"a": {"a": {"a": {"a":
+            {"a": {"a": {"a": {"depth_accepted": 19, "a": {  "depth_truncated": 20}
+        }}}}}}}}}}}}}}}}}}});
+        let columnar_reader = test_columnar_from_jsons_aux(&[json_doc], false);
+        let columns = columnar_reader.list_columns().unwrap();
+        assert_eq!(columns.len(), 1);
+        assert!(columns[0].0.ends_with("a\u{1}a\u{1}a\u{1}depth_accepted"));
+    }
+
+    #[test]
+    fn test_json_fastfield_deep_arr() {
+        let json_doc = json!(
+        {"obj":
+        [[[[[,
+        [[[[[,
+        [[[[[,
+        [[18, [19, //< within limits
+        [20]]]]]]]]]]]]]]]]]]]});
+        let columnar_reader = test_columnar_from_jsons_aux(&[json_doc], false);
+        let columns = columnar_reader.list_columns().unwrap();
+        assert_eq!(columns.len(), 1);
+        assert_eq!(columns[0].0, "obj");
+        let dynamic_column = columns[0].1.open().unwrap();
+        let col: Option<Column<i64>> = dynamic_column.into();
+        let vals: Vec<i64> = col.unwrap().values_for_doc(0).collect();
+        assert_eq!(&vals, &[18, 19])
+    }
+
+    #[test]
+    fn test_json_fast_field_do_not_expand_dots() {
+        let json_doc = json!({"field.with.dots": {"child.with.dot": "hello"}});
+        let columnar_reader = test_columnar_from_jsons_aux(&[json_doc], false);
+        let columns = columnar_reader.list_columns().unwrap();
+        assert_eq!(columns.len(), 1);
+        assert_eq!(columns[0].0, "field.with.dots\u{1}child.with.dot");
+    }
+
+    #[test]
+    fn test_json_fast_field_expand_dots() {
+        let json_doc = json!({"field.with.dots": {"child.with.dot": "hello"}});
+        let columnar_reader = test_columnar_from_jsons_aux(&[json_doc], true);
+        let columns = columnar_reader.list_columns().unwrap();
+        assert_eq!(columns.len(), 1);
+        assert_eq!(
+            columns[0].0,
+            "field\u{1}with\u{1}dots\u{1}child\u{1}with\u{1}dot"
+        );
+    }
+}

src/fieldnorm/mod.rs

@@ -112,7 +112,7 @@ mod tests {
             Term::from_field_text(text, "hello"),
             IndexRecordOption::WithFreqs,
         );
-        let weight = query.weight(EnableScoring::Enabled(&searcher))?;
+        let weight = query.weight(EnableScoring::enabled_from_searcher(&searcher))?;
         let mut scorer = weight.scorer(searcher.segment_reader(0), 1.0f32)?;
         assert_eq!(scorer.doc(), 0);
         assert!((scorer.score() - 0.22920431).abs() < 0.001f32);
@@ -141,7 +141,7 @@ mod tests {
             Term::from_field_text(text, "hello"),
             IndexRecordOption::WithFreqs,
         );
-        let weight = query.weight(EnableScoring::Enabled(&searcher))?;
+        let weight = query.weight(EnableScoring::enabled_from_searcher(&searcher))?;
         let mut scorer = weight.scorer(searcher.segment_reader(0), 1.0f32)?;
         assert_eq!(scorer.doc(), 0);
         assert!((scorer.score() - 0.22920431).abs() < 0.001f32);

src/indexer/index_writer.rs

@@ -1490,7 +1490,7 @@ mod tests {
 
         let in_order_alive_ids: Vec<u64> = segment_reader
             .doc_ids_alive()
-            .flat_map(|doc| fast_field_reader.values(doc))
+            .flat_map(|doc| fast_field_reader.values_for_doc(doc))
             .collect();
         assert_eq!(&in_order_alive_ids[..], &[9, 8, 7, 6, 5, 4, 1, 0]);
         Ok(())
@@ -1550,7 +1550,7 @@ mod tests {
         let fast_field_reader = segment_reader.fast_fields().u64("id")?;
         let in_order_alive_ids: Vec<u64> = segment_reader
             .doc_ids_alive()
-            .flat_map(|doc| fast_field_reader.values(doc))
+            .flat_map(|doc| fast_field_reader.values_for_doc(doc))
             .collect();
         assert_eq!(&in_order_alive_ids[..], &[9, 8, 7, 6, 5, 4, 2, 0]);
         Ok(())
@@ -1795,7 +1795,7 @@ mod tests {
                 let ff_reader = segment_reader.fast_fields().u64("id").unwrap();
                 segment_reader
                     .doc_ids_alive()
-                    .flat_map(move |doc| ff_reader.values(doc).collect_vec().into_iter())
+                    .flat_map(move |doc| ff_reader.values_for_doc(doc).collect_vec().into_iter())
             })
             .collect();
 
@@ -1806,7 +1806,7 @@ mod tests {
                 let ff_reader = segment_reader.fast_fields().u64("id").unwrap();
                 segment_reader
                     .doc_ids_alive()
-                    .flat_map(move |doc| ff_reader.values(doc).collect_vec().into_iter())
+                    .flat_map(move |doc| ff_reader.values_for_doc(doc).collect_vec().into_iter())
             })
             .collect();
 
@@ -1824,7 +1824,7 @@ mod tests {
                 .unwrap()
                 .unwrap();
             for doc in segment_reader.doc_ids_alive() {
-                all_ips.extend(ip_reader.values(doc));
+                all_ips.extend(ip_reader.values_for_doc(doc));
             }
             num_ips += ip_reader.values.num_vals();
         }
@@ -1883,7 +1883,7 @@ mod tests {
         for reader in searcher.segment_readers() {
             if let Some(ff_reader) = reader.fast_fields().column_opt::<Ipv6Addr>("ips").unwrap() {
                 for doc in reader.doc_ids_alive() {
-                    ips.extend(ff_reader.values(doc));
+                    ips.extend(ff_reader.values_for_doc(doc));
                 }
             }
         }
@@ -1915,7 +1915,7 @@ mod tests {
         for reader in searcher.segment_readers() {
             if let Some(ff_reader) = reader.fast_fields().column_opt::<Ipv6Addr>("ips").unwrap() {
                 for doc in reader.doc_ids_alive() {
-                    ips.extend(ff_reader.values(doc));
+                    ips.extend(ff_reader.values_for_doc(doc));
                 }
             }
         }
@@ -1935,12 +1935,12 @@ mod tests {
                 .unwrap()
                 .unwrap();
             for doc in segment_reader.doc_ids_alive() {
-                let vals: Vec<u64> = ff_reader.values(doc).collect();
+                let vals: Vec<u64> = ff_reader.values_for_doc(doc).collect();
                 assert_eq!(vals.len(), 2);
                 assert_eq!(vals[0], vals[1]);
                 assert_eq!(id_reader.first(doc), Some(vals[0]));
 
-                let bool_vals: Vec<bool> = bool_ff_reader.values(doc).collect();
+                let bool_vals: Vec<bool> = bool_ff_reader.values_for_doc(doc).collect();
                 assert_eq!(bool_vals.len(), 2);
                 assert_ne!(bool_vals[0], bool_vals[1]);
 
@@ -2236,8 +2236,8 @@ mod tests {
         assert_eq!(val_col.get_cardinality(), Cardinality::Multivalued);
         assert_eq!(id_col.first(0u32), Some(1u64));
         assert_eq!(id_col.first(1u32), Some(2u64));
-        assert!(val_col.values(0u32).eq([1u64, 1u64].into_iter()));
-        assert!(val_col.values(1u32).eq([2u64, 2u64].into_iter()));
+        assert!(val_col.values_for_doc(0u32).eq([1u64, 1u64].into_iter()));
+        assert!(val_col.values_for_doc(1u32).eq([2u64, 2u64].into_iter()));
     }
 
     #[test]

src/indexer/merger.rs

@@ -1,7 +1,8 @@
 use std::sync::Arc;
 
 use columnar::{
-    ColumnValues, ColumnarReader, MergeRowOrder, RowAddr, ShuffleMergeOrder, StackMergeOrder,
+    ColumnType, ColumnValues, ColumnarReader, MergeRowOrder, RowAddr, ShuffleMergeOrder,
+    StackMergeOrder,
 };
 use common::ReadOnlyBitSet;
 use itertools::Itertools;
@@ -16,7 +17,7 @@ use crate::fieldnorm::{FieldNormReader, FieldNormReaders, FieldNormsSerializer,
 use crate::indexer::doc_id_mapping::{MappingType, SegmentDocIdMapping};
 use crate::indexer::SegmentSerializer;
 use crate::postings::{InvertedIndexSerializer, Postings, SegmentPostings};
-use crate::schema::{Field, FieldType, Schema};
+use crate::schema::{value_type_to_column_type, Field, FieldType, Schema};
 use crate::store::StoreWriter;
 use crate::termdict::{TermMerger, TermOrdinal};
 use crate::{
@@ -135,6 +136,19 @@ fn convert_to_merge_order(
     }
 }
 
+fn extract_fast_field_required_columns(schema: &Schema) -> Vec<(String, ColumnType)> {
+    schema
+        .fields()
+        .map(|(_, field_entry)| field_entry)
+        .filter(|field_entry| field_entry.is_fast())
+        .filter_map(|field_entry| {
+            let column_name = field_entry.name().to_string();
+            let column_type = value_type_to_column_type(field_entry.field_type().value_type())?;
+            Some((column_name, column_type))
+        })
+        .collect()
+}
+
 impl IndexMerger {
     pub fn open(
         schema: Schema,
@@ -248,13 +262,19 @@ impl IndexMerger {
         doc_id_mapping: SegmentDocIdMapping,
     ) -> crate::Result<()> {
         debug_time!("write-fast-fields");
+        let required_columns = extract_fast_field_required_columns(&self.schema);
         let columnars: Vec<&ColumnarReader> = self
             .readers
             .iter()
             .map(|reader| reader.fast_fields().columnar())
             .collect();
         let merge_row_order = convert_to_merge_order(&columnars[..], doc_id_mapping);
-        columnar::merge_columnar(&columnars[..], merge_row_order, fast_field_wrt)?;
+        columnar::merge_columnar(
+            &columnars[..],
+            &required_columns,
+            merge_row_order,
+            fast_field_wrt,
+        )?;
         Ok(())
     }
 
@@ -1477,7 +1497,7 @@ mod tests {
         let mut vals: Vec<u64> = Vec::new();
         let mut test_vals = move |col: &Column<u64>, doc: DocId, expected: &[u64]| {
             vals.clear();
-            vals.extend(col.values(doc));
+            vals.extend(col.values_for_doc(doc));
             assert_eq!(&vals[..], expected);
         };
 
@@ -1628,7 +1648,7 @@ mod tests {
         let reader = index.reader()?;
         let searcher = reader.searcher();
         let mut term_scorer = term_query
-            .specialized_weight(EnableScoring::Enabled(&searcher))?
+            .specialized_weight(EnableScoring::enabled_from_searcher(&searcher))?
             .specialized_scorer(searcher.segment_reader(0u32), 1.0)?;
         assert_eq!(term_scorer.doc(), 0);
         assert_nearly_equals!(term_scorer.block_max_score(), 0.0079681855);
@@ -1643,7 +1663,7 @@ mod tests {
         assert_eq!(searcher.segment_readers().len(), 2);
         for segment_reader in searcher.segment_readers() {
             let mut term_scorer = term_query
-                .specialized_weight(EnableScoring::Enabled(&searcher))?
+                .specialized_weight(EnableScoring::enabled_from_searcher(&searcher))?
                 .specialized_scorer(segment_reader, 1.0)?;
             // the difference compared to before is intrinsic to the bm25 formula. no worries
             // there.
@@ -1668,7 +1688,7 @@ mod tests {
 
         let segment_reader = searcher.segment_reader(0u32);
         let mut term_scorer = term_query
-            .specialized_weight(EnableScoring::Enabled(&searcher))?
+            .specialized_weight(EnableScoring::enabled_from_searcher(&searcher))?
             .specialized_scorer(segment_reader, 1.0)?;
         // the difference compared to before is intrinsic to the bm25 formula. no worries there.
         for doc in segment_reader.doc_ids_alive() {

src/indexer/merger_sorted_index_test.rs

@@ -475,8 +475,6 @@ mod tests {
 #[cfg(all(test, feature = "unstable"))]
 mod bench_sorted_index_merge {
 
-    use std::sync::Arc;
-
     use test::{self, Bencher};
 
     use crate::core::Index;

src/indexer/mod.rs

@@ -5,7 +5,6 @@ mod doc_opstamp_mapping;
 mod flat_map_with_buffer;
 pub mod index_writer;
 mod index_writer_status;
-mod json_term_writer;
 mod log_merge_policy;
 mod merge_operation;
 pub mod merge_policy;
@@ -25,9 +24,6 @@ use crossbeam_channel as channel;
 use smallvec::SmallVec;
 
 pub use self::index_writer::IndexWriter;
-pub(crate) use self::json_term_writer::{
-    convert_to_fast_value_and_get_term, set_string_and_get_terms, JsonTermWriter,
-};
 pub use self::log_merge_policy::LogMergePolicy;
 pub use self::merge_operation::MergeOperation;
 pub use self::merge_policy::{MergeCandidate, MergePolicy, NoMergePolicy};
@@ -56,8 +52,9 @@ type AddBatchReceiver = channel::Receiver<AddBatch>;
 #[cfg(test)]
 mod tests_mmap {
 
-    // use crate::query::QueryParser;
-    use crate::schema::{Schema, TEXT};
+    use crate::collector::Count;
+    use crate::query::QueryParser;
+    use crate::schema::{JsonObjectOptions, Schema, TEXT};
     use crate::{Index, Term};
 
     #[test]
@@ -77,45 +74,63 @@ mod tests_mmap {
         Ok(())
     }
 
-    // #[test]
-    // fn test_json_field_expand_dots_disabled_dot_escaped_required() {
-    //     let mut schema_builder = Schema::builder();
-    //     let json_field = schema_builder.add_json_field("json", TEXT);
-    //     let index = Index::create_in_ram(schema_builder.build());
-    //     let mut index_writer = index.writer_for_tests().unwrap();
-    //     let json = serde_json::json!({"k8s.container.name": "prometheus", "val": "hello"});
-    //     index_writer.add_document(doc!(json_field=>json)).unwrap();
-    //     index_writer.commit().unwrap();
-    //     let reader = index.reader().unwrap();
-    //     let searcher = reader.searcher();
-    //     assert_eq!(searcher.num_docs(), 1);
-    //     let parse_query = QueryParser::for_index(&index, Vec::new());
-    //     let query = parse_query
-    //         .parse_query(r#"json.k8s\.container\.name:prometheus"#)
-    //         .unwrap();
-    //     let num_docs = searcher.search(&query, &Count).unwrap();
-    //     assert_eq!(num_docs, 1);
-    // }
+    #[test]
+    fn test_json_field_expand_dots_disabled_dot_escaped_required() {
+        let mut schema_builder = Schema::builder();
+        let json_field = schema_builder.add_json_field("json", TEXT);
+        let index = Index::create_in_ram(schema_builder.build());
+        let mut index_writer = index.writer_for_tests().unwrap();
+        let json = serde_json::json!({"k8s.container.name": "prometheus", "val": "hello"});
+        index_writer.add_document(doc!(json_field=>json)).unwrap();
+        index_writer.commit().unwrap();
+        let reader = index.reader().unwrap();
+        let searcher = reader.searcher();
+        assert_eq!(searcher.num_docs(), 1);
+        let parse_query = QueryParser::for_index(&index, Vec::new());
+        {
+            let query = parse_query
+                .parse_query(r#"json.k8s\.container\.name:prometheus"#)
+                .unwrap();
+            let num_docs = searcher.search(&query, &Count).unwrap();
+            assert_eq!(num_docs, 1);
+        }
+        {
+            let query = parse_query
+                .parse_query(r#"json.k8s.container.name:prometheus"#)
+                .unwrap();
+            let num_docs = searcher.search(&query, &Count).unwrap();
+            assert_eq!(num_docs, 0);
+        }
+    }
 
-    // #[test]
-    // fn test_json_field_expand_dots_enabled_dot_escape_not_required() {
-    //     let mut schema_builder = Schema::builder();
-    //     let json_options: JsonObjectOptions =
-    //         JsonObjectOptions::from(TEXT).set_expand_dots_enabled();
-    //     let json_field = schema_builder.add_json_field("json", json_options);
-    //     let index = Index::create_in_ram(schema_builder.build());
-    //     let mut index_writer = index.writer_for_tests().unwrap();
-    //     let json = serde_json::json!({"k8s.container.name": "prometheus", "val": "hello"});
-    //     index_writer.add_document(doc!(json_field=>json)).unwrap();
-    //     index_writer.commit().unwrap();
-    //     let reader = index.reader().unwrap();
-    //     let searcher = reader.searcher();
-    //     assert_eq!(searcher.num_docs(), 1);
-    //     let parse_query = QueryParser::for_index(&index, Vec::new());
-    //     let query = parse_query
-    //         .parse_query(r#"json.k8s.container.name:prometheus"#)
-    //         .unwrap();
-    //     let num_docs = searcher.search(&query, &Count).unwrap();
-    //     assert_eq!(num_docs, 1);
-    // }
+    #[test]
+    fn test_json_field_expand_dots_enabled_dot_escape_not_required() {
+        let mut schema_builder = Schema::builder();
+        let json_options: JsonObjectOptions =
+            JsonObjectOptions::from(TEXT).set_expand_dots_enabled();
+        let json_field = schema_builder.add_json_field("json", json_options);
+        let index = Index::create_in_ram(schema_builder.build());
+        let mut index_writer = index.writer_for_tests().unwrap();
+        let json = serde_json::json!({"k8s.container.name": "prometheus", "val": "hello"});
+        index_writer.add_document(doc!(json_field=>json)).unwrap();
+        index_writer.commit().unwrap();
+        let reader = index.reader().unwrap();
+        let searcher = reader.searcher();
+        assert_eq!(searcher.num_docs(), 1);
+        let parse_query = QueryParser::for_index(&index, Vec::new());
+        {
+            let query = parse_query
+                .parse_query(r#"json.k8s.container.name:prometheus"#)
+                .unwrap();
+            let num_docs = searcher.search(&query, &Count).unwrap();
+            assert_eq!(num_docs, 1);
+        }
+        {
+            let query = parse_query
+                .parse_query(r#"json.k8s\.container\.name:prometheus"#)
+                .unwrap();
+            let num_docs = searcher.search(&query, &Count).unwrap();
+            assert_eq!(num_docs, 1);
+        }
+    }
 }

src/indexer/segment_writer.rs

@@ -3,10 +3,10 @@ use itertools::Itertools;
 
 use super::doc_id_mapping::{get_doc_id_mapping_from_field, DocIdMapping};
 use super::operation::AddOperation;
+use crate::core::json_utils::index_json_values;
 use crate::core::Segment;
 use crate::fastfield::FastFieldsWriter;
 use crate::fieldnorm::{FieldNormReaders, FieldNormsWriter};
-use crate::indexer::json_term_writer::index_json_values;
 use crate::indexer::segment_serializer::SegmentSerializer;
 use crate::postings::{
     compute_table_size, serialize_postings, IndexingContext, IndexingPosition,
@@ -435,8 +435,8 @@ mod tests {
 
     use super::compute_initial_table_size;
     use crate::collector::Count;
+    use crate::core::json_utils::JsonTermWriter;
     use crate::directory::RamDirectory;
-    use crate::indexer::json_term_writer::JsonTermWriter;
     use crate::postings::TermInfo;
     use crate::query::PhraseQuery;
     use crate::schema::{IndexRecordOption, Schema, Type, STORED, STRING, TEXT};

src/lib.rs

@@ -123,11 +123,9 @@ mod functional_test;
 mod macros;
 mod future_result;
 
+// Re-exports
 pub use common::DateTime;
-/// Re-export of the `time` crate
-///
-/// Tantivy uses [`time`](https://crates.io/crates/time) for dates.
-pub use time;
+pub use {columnar, query_grammar, time};
 
 pub use crate::error::TantivyError;
 pub use crate::future_result::FutureResult;

src/query/bm25.rs

@@ -2,11 +2,53 @@ use serde::{Deserialize, Serialize};
 
 use crate::fieldnorm::FieldNormReader;
 use crate::query::Explanation;
+use crate::schema::Field;
 use crate::{Score, Searcher, Term};
 
 const K1: Score = 1.2;
 const B: Score = 0.75;
 
+/// An interface to compute the statistics needed in BM25 scoring.
+///
+/// The standard implementation is a [Searcher] but you can also
+/// create your own to adjust the statistics.
+pub trait Bm25StatisticsProvider {
+    /// The total number of tokens in a given field across all documents in
+    /// the index.
+    fn total_num_tokens(&self, field: Field) -> crate::Result<u64>;
+
+    /// The total number of documents in the index.
+    fn total_num_docs(&self) -> crate::Result<u64>;
+
+    /// The number of documents containing the given term.
+    fn doc_freq(&self, term: &Term) -> crate::Result<u64>;
+}
+
+impl Bm25StatisticsProvider for Searcher {
+    fn total_num_tokens(&self, field: Field) -> crate::Result<u64> {
+        let mut total_num_tokens = 0u64;
+
+        for segment_reader in self.segment_readers() {
+            let inverted_index = segment_reader.inverted_index(field)?;
+            total_num_tokens += inverted_index.total_num_tokens();
+        }
+        Ok(total_num_tokens)
+    }
+
+    fn total_num_docs(&self) -> crate::Result<u64> {
+        let mut total_num_docs = 0u64;
+
+        for segment_reader in self.segment_readers() {
+            total_num_docs += u64::from(segment_reader.max_doc());
+        }
+        Ok(total_num_docs)
+    }
+
+    fn doc_freq(&self, term: &Term) -> crate::Result<u64> {
+        self.doc_freq(term)
+    }
+}
+
 pub(crate) fn idf(doc_freq: u64, doc_count: u64) -> Score {
     assert!(doc_count >= doc_freq, "{} >= {}", doc_count, doc_freq);
     let x = ((doc_count - doc_freq) as Score + 0.5) / (doc_freq as Score + 0.5);
@@ -32,6 +74,7 @@ pub struct Bm25Params {
     pub avg_fieldnorm: Score,
 }
 
+/// A struct used for computing BM25 scores.
 #[derive(Clone)]
 pub struct Bm25Weight {
     idf_explain: Explanation,
@@ -41,6 +84,7 @@ pub struct Bm25Weight {
 }
 
 impl Bm25Weight {
+    /// Increase the weight by a multiplicative factor.
     pub fn boost_by(&self, boost: Score) -> Bm25Weight {
         Bm25Weight {
             idf_explain: self.idf_explain.clone(),
@@ -50,7 +94,11 @@ impl Bm25Weight {
         }
     }
 
-    pub fn for_terms(searcher: &Searcher, terms: &[Term]) -> crate::Result<Bm25Weight> {
+    /// Construct a [Bm25Weight] for a phrase of terms.
+    pub fn for_terms(
+        statistics: &dyn Bm25StatisticsProvider,
+        terms: &[Term],
+    ) -> crate::Result<Bm25Weight> {
         assert!(!terms.is_empty(), "Bm25 requires at least one term");
         let field = terms[0].field();
         for term in &terms[1..] {
@@ -61,17 +109,12 @@ impl Bm25Weight {
             );
         }
 
-        let mut total_num_tokens = 0u64;
-        let mut total_num_docs = 0u64;
-        for segment_reader in searcher.segment_readers() {
-            let inverted_index = segment_reader.inverted_index(field)?;
-            total_num_tokens += inverted_index.total_num_tokens();
-            total_num_docs += u64::from(segment_reader.max_doc());
-        }
+        let total_num_tokens = statistics.total_num_tokens(field)?;
+        let total_num_docs = statistics.total_num_docs()?;
         let average_fieldnorm = total_num_tokens as Score / total_num_docs as Score;
 
         if terms.len() == 1 {
-            let term_doc_freq = searcher.doc_freq(&terms[0])?;
+            let term_doc_freq = statistics.doc_freq(&terms[0])?;
             Ok(Bm25Weight::for_one_term(
                 term_doc_freq,
                 total_num_docs,
@@ -80,7 +123,7 @@ impl Bm25Weight {
         } else {
             let mut idf_sum: Score = 0.0;
             for term in terms {
-                let term_doc_freq = searcher.doc_freq(term)?;
+                let term_doc_freq = statistics.doc_freq(term)?;
                 idf_sum += idf(term_doc_freq, total_num_docs);
             }
             let idf_explain = Explanation::new("idf", idf_sum);
@@ -88,6 +131,7 @@ impl Bm25Weight {
         }
     }
 
+    /// Construct a [Bm25Weight] for a single term.
     pub fn for_one_term(
         term_doc_freq: u64,
         total_num_docs: u64,
@@ -114,11 +158,13 @@ impl Bm25Weight {
         }
     }
 
+    /// Compute the BM25 score of a single document.
     #[inline]
     pub fn score(&self, fieldnorm_id: u8, term_freq: u32) -> Score {
         self.weight * self.tf_factor(fieldnorm_id, term_freq)
     }
 
+    /// Compute the maximum possible BM25 score given this weight.
     pub fn max_score(&self) -> Score {
         self.score(255u8, 2_013_265_944)
     }
@@ -130,6 +176,7 @@ impl Bm25Weight {
         term_freq / (term_freq + norm)
     }
 
+    /// Produce an [Explanation] of a BM25 score.
     pub fn explain(&self, fieldnorm_id: u8, term_freq: u32) -> Explanation {
         // The explain format is directly copied from Lucene's.
         // (So, Kudos to Lucene)

src/query/boolean_query/mod.rs

@@ -55,7 +55,7 @@ mod tests {
         let query_parser = QueryParser::for_index(&index, vec![text_field]);
         let query = query_parser.parse_query("+a")?;
         let searcher = index.reader()?.searcher();
-        let weight = query.weight(EnableScoring::Enabled(&searcher))?;
+        let weight = query.weight(EnableScoring::enabled_from_searcher(&searcher))?;
         let scorer = weight.scorer(searcher.segment_reader(0u32), 1.0)?;
         assert!(scorer.is::<TermScorer>());
         Ok(())
@@ -68,13 +68,13 @@ mod tests {
         let searcher = index.reader()?.searcher();
         {
             let query = query_parser.parse_query("+a +b +c")?;
-            let weight = query.weight(EnableScoring::Enabled(&searcher))?;
+            let weight = query.weight(EnableScoring::enabled_from_searcher(&searcher))?;
             let scorer = weight.scorer(searcher.segment_reader(0u32), 1.0)?;
             assert!(scorer.is::<Intersection<TermScorer>>());
         }
         {
             let query = query_parser.parse_query("+a +(b c)")?;
-            let weight = query.weight(EnableScoring::Enabled(&searcher))?;
+            let weight = query.weight(EnableScoring::enabled_from_searcher(&searcher))?;
             let scorer = weight.scorer(searcher.segment_reader(0u32), 1.0)?;
             assert!(scorer.is::<Intersection<Box<dyn Scorer>>>());
         }
@@ -88,7 +88,7 @@ mod tests {
         let searcher = index.reader()?.searcher();
         {
             let query = query_parser.parse_query("+a b")?;
-            let weight = query.weight(EnableScoring::Enabled(&searcher))?;
+            let weight = query.weight(EnableScoring::enabled_from_searcher(&searcher))?;
             let scorer = weight.scorer(searcher.segment_reader(0u32), 1.0)?;
             assert!(scorer.is::<RequiredOptionalScorer<
                 Box<dyn Scorer>,
@@ -243,7 +243,7 @@ mod tests {
         let boolean_query =
             BooleanQuery::new(vec![(Occur::Should, term_a), (Occur::Should, term_b)]);
         let boolean_weight = boolean_query
-            .weight(EnableScoring::Enabled(&searcher))
+            .weight(EnableScoring::enabled_from_searcher(&searcher))
             .unwrap();
         {
             let mut boolean_scorer = boolean_weight.scorer(searcher.segment_reader(0u32), 1.0)?;

src/query/disjunction_max_query.rs

@@ -1,6 +1,4 @@
-use tantivy_query_grammar::Occur;
-
-use crate::query::{BooleanWeight, DisjunctionMaxCombiner, EnableScoring, Query, Weight};
+use crate::query::{BooleanWeight, DisjunctionMaxCombiner, EnableScoring, Occur, Query, Weight};
 use crate::{Score, Term};
 
 /// The disjunction max query returns documents matching one or more wrapped queries,

src/query/mod.rs

@@ -12,6 +12,7 @@ mod explanation;
 mod fuzzy_query;
 mod intersection;
 mod more_like_this;
+mod phrase_prefix_query;
 mod phrase_query;
 mod query;
 mod query_parser;
@@ -28,12 +29,12 @@ mod weight;
 mod vec_docset;
 
 pub(crate) mod score_combiner;
-pub use tantivy_query_grammar::Occur;
+pub use query_grammar::Occur;
 
 pub use self::all_query::{AllQuery, AllScorer, AllWeight};
 pub use self::automaton_weight::AutomatonWeight;
 pub use self::bitset::BitSetDocSet;
-pub(crate) use self::bm25::Bm25Weight;
+pub use self::bm25::{Bm25StatisticsProvider, Bm25Weight};
 pub use self::boolean_query::BooleanQuery;
 pub(crate) use self::boolean_query::BooleanWeight;
 pub use self::boost_query::BoostQuery;
@@ -47,6 +48,7 @@ pub(crate) use self::fuzzy_query::DfaWrapper;
 pub use self::fuzzy_query::FuzzyTermQuery;
 pub use self::intersection::{intersect_scorers, Intersection};
 pub use self::more_like_this::{MoreLikeThisQuery, MoreLikeThisQueryBuilder};
+pub use self::phrase_prefix_query::PhrasePrefixQuery;
 pub use self::phrase_query::PhraseQuery;
 pub use self::query::{EnableScoring, Query, QueryClone};
 pub use self::query_parser::{QueryParser, QueryParserError};
@@ -63,6 +65,7 @@ pub use self::union::Union;
 #[cfg(test)]
 pub use self::vec_docset::VecDocSet;
 pub use self::weight::Weight;
+pub(crate) use self::weight::{for_each_docset, for_each_pruning_scorer, for_each_scorer};
 
 #[cfg(test)]
 mod tests {

src/query/more_like_this/query.rs

@@ -44,7 +44,7 @@ impl MoreLikeThisQuery {
 impl Query for MoreLikeThisQuery {
     fn weight(&self, enable_scoring: EnableScoring<'_>) -> crate::Result<Box<dyn Weight>> {
         let searcher = match enable_scoring {
-            EnableScoring::Enabled(searcher) => searcher,
+            EnableScoring::Enabled { searcher, .. } => searcher,
             EnableScoring::Disabled { .. } => {
                 let err = "MoreLikeThisQuery requires to enable scoring.".to_string();
                 return Err(crate::TantivyError::InvalidArgument(err));

src/query/phrase_prefix_query/mod.rs

@@ -0,0 +1,34 @@
+mod phrase_prefix_query;
+mod phrase_prefix_scorer;
+mod phrase_prefix_weight;
+
+pub use phrase_prefix_query::PhrasePrefixQuery;
+pub use phrase_prefix_scorer::PhrasePrefixScorer;
+pub use phrase_prefix_weight::PhrasePrefixWeight;
+
+fn prefix_end(prefix_start: &[u8]) -> Option<Vec<u8>> {
+    let mut res = prefix_start.to_owned();
+    while !res.is_empty() {
+        let end = res.len() - 1;
+        if res[end] == u8::MAX {
+            res.pop();
+        } else {
+            res[end] += 1;
+            return Some(res);
+        }
+    }
+    None
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_prefix_end() {
+        assert_eq!(prefix_end(b"aaa"), Some(b"aab".to_vec()));
+        assert_eq!(prefix_end(b"aa\xff"), Some(b"ab".to_vec()));
+        assert_eq!(prefix_end(b"a\xff\xff"), Some(b"b".to_vec()));
+        assert_eq!(prefix_end(b"\xff\xff\xff"), None);
+    }
+}

src/query/phrase_prefix_query/phrase_prefix_query.rs

@@ -0,0 +1,169 @@
+use std::ops::Bound;
+
+use super::{prefix_end, PhrasePrefixWeight};
+use crate::query::bm25::Bm25Weight;
+use crate::query::{EnableScoring, Query, RangeQuery, Weight};
+use crate::schema::{Field, IndexRecordOption, Term};
+
+const DEFAULT_MAX_EXPANSIONS: u32 = 50;
+
+/// `PhrasePrefixQuery` matches a specific sequence of words followed by term of which only a
+/// prefix is known.
+///
+/// For instance the phrase prefix query for `"part t"` will match
+/// the sentence
+///
+/// **Alan just got a part time job.**
+///
+/// On the other hand it will not match the sentence.
+///
+/// **This is my favorite part of the job.**
+///
+/// Using a `PhrasePrefixQuery` on a field requires positions
+/// to be indexed for this field.
+#[derive(Clone, Debug)]
+pub struct PhrasePrefixQuery {
+    field: Field,
+    phrase_terms: Vec<(usize, Term)>,
+    prefix: (usize, Term),
+    max_expansions: u32,
+}
+
+impl PhrasePrefixQuery {
+    /// Creates a new `PhrasePrefixQuery` given a list of terms.
+    ///
+    /// There must be at least two terms, and all terms
+    /// must belong to the same field.
+    /// Offset for each term will be same as index in the Vector
+    /// The last Term is a prefix and not a full value
+    pub fn new(terms: Vec<Term>) -> PhrasePrefixQuery {
+        let terms_with_offset = terms.into_iter().enumerate().collect();
+        PhrasePrefixQuery::new_with_offset(terms_with_offset)
+    }
+
+    /// Creates a new `PhrasePrefixQuery` given a list of terms and their offsets.
+    ///
+    /// Can be used to provide custom offset for each term.
+    pub fn new_with_offset(mut terms: Vec<(usize, Term)>) -> PhrasePrefixQuery {
+        assert!(
+            !terms.is_empty(),
+            "A phrase prefix query is required to have at least one term."
+        );
+        terms.sort_by_key(|&(offset, _)| offset);
+        let field = terms[0].1.field();
+        assert!(
+            terms[1..].iter().all(|term| term.1.field() == field),
+            "All terms from a phrase query must belong to the same field"
+        );
+        PhrasePrefixQuery {
+            field,
+            prefix: terms.pop().unwrap(),
+            phrase_terms: terms,
+            max_expansions: DEFAULT_MAX_EXPANSIONS,
+        }
+    }
+
+    /// Maximum number of terms to which the last provided term will expand.
+    pub fn set_max_expansions(&mut self, value: u32) {
+        self.max_expansions = value;
+    }
+
+    /// The [`Field`] this `PhrasePrefixQuery` is targeting.
+    pub fn field(&self) -> Field {
+        self.field
+    }
+
+    /// `Term`s in the phrase without the associated offsets.
+    pub fn phrase_terms(&self) -> Vec<Term> {
+        // TODO should we include the last term too?
+        self.phrase_terms
+            .iter()
+            .map(|(_, term)| term.clone())
+            .collect::<Vec<Term>>()
+    }
+
+    /// Returns the [`PhrasePrefixWeight`] for the given phrase query given a specific `searcher`.
+    ///
+    /// This function is the same as [`Query::weight()`] except it returns
+    /// a specialized type [`PhraseQueryWeight`] instead of a Boxed trait.
+    /// If the query was only one term long, this returns `None` wherease [`Query::weight`]
+    /// returns a boxed [`RangeWeight`]
+    ///
+    /// Returns `None`, if phrase_terms is empty, which happens if the phrase prefix query was
+    /// built with a single term.
+    pub(crate) fn phrase_prefix_query_weight(
+        &self,
+        enable_scoring: EnableScoring<'_>,
+    ) -> crate::Result<Option<PhrasePrefixWeight>> {
+        if self.phrase_terms.is_empty() {
+            return Ok(None);
+        }
+        let schema = enable_scoring.schema();
+        let field_entry = schema.get_field_entry(self.field);
+        let has_positions = field_entry
+            .field_type()
+            .get_index_record_option()
+            .map(IndexRecordOption::has_positions)
+            .unwrap_or(false);
+        if !has_positions {
+            let field_name = field_entry.name();
+            return Err(crate::TantivyError::SchemaError(format!(
+                "Applied phrase query on field {:?}, which does not have positions indexed",
+                field_name
+            )));
+        }
+        let terms = self.phrase_terms();
+        let bm25_weight_opt = match enable_scoring {
+            EnableScoring::Enabled { searcher, .. } => {
+                Some(Bm25Weight::for_terms(searcher, &terms)?)
+            }
+            EnableScoring::Disabled { .. } => None,
+        };
+        let weight = PhrasePrefixWeight::new(
+            self.phrase_terms.clone(),
+            self.prefix.clone(),
+            bm25_weight_opt,
+            self.max_expansions,
+        );
+        Ok(Some(weight))
+    }
+}
+
+impl Query for PhrasePrefixQuery {
+    /// Create the weight associated with a query.
+    ///
+    /// See [`Weight`].
+    fn weight(&self, enable_scoring: EnableScoring<'_>) -> crate::Result<Box<dyn Weight>> {
+        if let Some(phrase_weight) = self.phrase_prefix_query_weight(enable_scoring)? {
+            Ok(Box::new(phrase_weight))
+        } else {
+            // There are no prefix. Let's just match the suffix.
+            let end_term = if let Some(end_value) = prefix_end(self.prefix.1.value_bytes()) {
+                let mut end_term = Term::with_capacity(end_value.len());
+                end_term.set_field_and_type(self.field, self.prefix.1.typ());
+                end_term.append_bytes(&end_value);
+                Bound::Excluded(end_term)
+            } else {
+                Bound::Unbounded
+            };
+
+            let mut range_query = RangeQuery::new_term_bounds(
+                enable_scoring
+                    .schema()
+                    .get_field_name(self.field)
+                    .to_owned(),
+                self.prefix.1.typ(),
+                &Bound::Included(self.prefix.1.clone()),
+                &end_term,
+            );
+            range_query.limit(self.max_expansions as u64);
+            range_query.weight(enable_scoring)
+        }
+    }
+
+    fn query_terms<'a>(&'a self, visitor: &mut dyn FnMut(&'a Term, bool)) {
+        for (_, term) in &self.phrase_terms {
+            visitor(term, true);
+        }
+    }
+}

src/query/phrase_prefix_query/phrase_prefix_scorer.rs

@@ -0,0 +1,207 @@
+use crate::docset::{DocSet, TERMINATED};
+use crate::fieldnorm::FieldNormReader;
+use crate::postings::Postings;
+use crate::query::bm25::Bm25Weight;
+use crate::query::phrase_query::{intersection_count, PhraseScorer};
+use crate::query::Scorer;
+use crate::{DocId, Score};
+
+enum PhraseKind<TPostings: Postings> {
+    SinglePrefix {
+        position_offset: u32,
+        postings: TPostings,
+        positions: Vec<u32>,
+    },
+    MultiPrefix(PhraseScorer<TPostings>),
+}
+
+impl<TPostings: Postings> PhraseKind<TPostings> {
+    fn get_intersection(&mut self) -> &[u32] {
+        match self {
+            PhraseKind::SinglePrefix {
+                position_offset,
+                postings,
+                positions,
+            } => {
+                if positions.is_empty() {
+                    postings.positions_with_offset(*position_offset, positions);
+                }
+                positions
+            }
+            PhraseKind::MultiPrefix(postings) => postings.get_intersection(),
+        }
+    }
+}
+
+impl<TPostings: Postings> DocSet for PhraseKind<TPostings> {
+    fn advance(&mut self) -> DocId {
+        match self {
+            PhraseKind::SinglePrefix {
+                postings,
+                positions,
+                ..
+            } => {
+                positions.clear();
+                postings.advance()
+            }
+            PhraseKind::MultiPrefix(postings) => postings.advance(),
+        }
+    }
+
+    fn doc(&self) -> DocId {
+        match self {
+            PhraseKind::SinglePrefix { postings, .. } => postings.doc(),
+            PhraseKind::MultiPrefix(postings) => postings.doc(),
+        }
+    }
+
+    fn size_hint(&self) -> u32 {
+        match self {
+            PhraseKind::SinglePrefix { postings, .. } => postings.size_hint(),
+            PhraseKind::MultiPrefix(postings) => postings.size_hint(),
+        }
+    }
+
+    fn seek(&mut self, target: DocId) -> DocId {
+        match self {
+            PhraseKind::SinglePrefix {
+                postings,
+                positions,
+                ..
+            } => {
+                positions.clear();
+                postings.seek(target)
+            }
+            PhraseKind::MultiPrefix(postings) => postings.seek(target),
+        }
+    }
+}
+
+impl<TPostings: Postings> Scorer for PhraseKind<TPostings> {
+    fn score(&mut self) -> Score {
+        match self {
+            PhraseKind::SinglePrefix { positions, .. } => {
+                if positions.is_empty() {
+                    0.0
+                } else {
+                    1.0
+                }
+            }
+            PhraseKind::MultiPrefix(postings) => postings.score(),
+        }
+    }
+}
+
+pub struct PhrasePrefixScorer<TPostings: Postings> {
+    phrase_scorer: PhraseKind<TPostings>,
+    suffixes: Vec<TPostings>,
+    suffix_offset: u32,
+    phrase_count: u32,
+}
+
+impl<TPostings: Postings> PhrasePrefixScorer<TPostings> {
+    // If similarity_weight is None, then scoring is disabled.
+    pub fn new(
+        mut term_postings: Vec<(usize, TPostings)>,
+        similarity_weight_opt: Option<Bm25Weight>,
+        fieldnorm_reader: FieldNormReader,
+        suffixes: Vec<TPostings>,
+        suffix_pos: usize,
+    ) -> PhrasePrefixScorer<TPostings> {
+        // correct indices so we can merge with our suffix term the PhraseScorer doesn't know about
+        let max_offset = term_postings
+            .iter()
+            .map(|(pos, _)| *pos)
+            .chain(std::iter::once(suffix_pos))
+            .max()
+            .unwrap();
+
+        let phrase_scorer = if term_postings.len() > 1 {
+            PhraseKind::MultiPrefix(PhraseScorer::new_with_offset(
+                term_postings,
+                similarity_weight_opt,
+                fieldnorm_reader,
+                0,
+                1,
+            ))
+        } else {
+            let (pos, postings) = term_postings
+                .pop()
+                .expect("PhrasePrefixScorer must have at least two terms");
+            let offset = suffix_pos - pos;
+            PhraseKind::SinglePrefix {
+                position_offset: offset as u32,
+                postings,
+                positions: Vec::with_capacity(100),
+            }
+        };
+        let mut phrase_prefix_scorer = PhrasePrefixScorer {
+            phrase_scorer,
+            suffixes,
+            suffix_offset: (max_offset - suffix_pos) as u32,
+            phrase_count: 0,
+        };
+        if !phrase_prefix_scorer.matches_prefix() {
+            phrase_prefix_scorer.advance();
+        }
+        phrase_prefix_scorer
+    }
+
+    pub fn phrase_count(&self) -> u32 {
+        self.phrase_count
+    }
+
+    fn matches_prefix(&mut self) -> bool {
+        let mut count = 0;
+        let mut positions = Vec::new();
+        let current_doc = self.doc();
+        let pos_matching = self.phrase_scorer.get_intersection();
+        for suffix in &mut self.suffixes {
+            if suffix.doc() > current_doc {
+                continue;
+            }
+            let doc = suffix.seek(current_doc);
+            if doc == current_doc {
+                suffix.positions_with_offset(self.suffix_offset, &mut positions);
+                count += intersection_count(pos_matching, &positions);
+            }
+        }
+        self.phrase_count = count as u32;
+        count != 0
+    }
+}
+
+impl<TPostings: Postings> DocSet for PhrasePrefixScorer<TPostings> {
+    fn advance(&mut self) -> DocId {
+        loop {
+            let doc = self.phrase_scorer.advance();
+            if doc == TERMINATED || self.matches_prefix() {
+                return doc;
+            }
+        }
+    }
+
+    fn seek(&mut self, target: DocId) -> DocId {
+        self.phrase_scorer.seek(target);
+        let doc = self.phrase_scorer.seek(target);
+        if doc == TERMINATED || self.matches_prefix() {
+            return doc;
+        }
+        self.advance()
+    }
+
+    fn doc(&self) -> DocId {
+        self.phrase_scorer.doc()
+    }
+
+    fn size_hint(&self) -> u32 {
+        self.phrase_scorer.size_hint()
+    }
+}
+
+impl<TPostings: Postings> Scorer for PhrasePrefixScorer<TPostings> {
+    fn score(&mut self) -> Score {
+        // TODO modify score??
+        self.phrase_scorer.score()
+    }
+}

src/query/phrase_prefix_query/phrase_prefix_weight.rs

@@ -0,0 +1,258 @@
+use super::{prefix_end, PhrasePrefixScorer};
+use crate::core::SegmentReader;
+use crate::fieldnorm::FieldNormReader;
+use crate::postings::SegmentPostings;
+use crate::query::bm25::Bm25Weight;
+use crate::query::explanation::does_not_match;
+use crate::query::{EmptyScorer, Explanation, Scorer, Weight};
+use crate::schema::{IndexRecordOption, Term};
+use crate::{DocId, DocSet, Score};
+
+pub struct PhrasePrefixWeight {
+    phrase_terms: Vec<(usize, Term)>,
+    prefix: (usize, Term),
+    similarity_weight_opt: Option<Bm25Weight>,
+    max_expansions: u32,
+}
+
+impl PhrasePrefixWeight {
+    /// Creates a new phrase weight.
+    /// If `similarity_weight_opt` is None, then scoring is disabled
+    pub fn new(
+        phrase_terms: Vec<(usize, Term)>,
+        prefix: (usize, Term),
+        similarity_weight_opt: Option<Bm25Weight>,
+        max_expansions: u32,
+    ) -> PhrasePrefixWeight {
+        PhrasePrefixWeight {
+            phrase_terms,
+            prefix,
+            similarity_weight_opt,
+            max_expansions,
+        }
+    }
+
+    fn fieldnorm_reader(&self, reader: &SegmentReader) -> crate::Result<FieldNormReader> {
+        let field = self.phrase_terms[0].1.field();
+        if self.similarity_weight_opt.is_some() {
+            if let Some(fieldnorm_reader) = reader.fieldnorms_readers().get_field(field)? {
+                return Ok(fieldnorm_reader);
+            }
+        }
+        Ok(FieldNormReader::constant(reader.max_doc(), 1))
+    }
+
+    pub(crate) fn phrase_scorer(
+        &self,
+        reader: &SegmentReader,
+        boost: Score,
+    ) -> crate::Result<Option<PhrasePrefixScorer<SegmentPostings>>> {
+        let similarity_weight_opt = self
+            .similarity_weight_opt
+            .as_ref()
+            .map(|similarity_weight| similarity_weight.boost_by(boost));
+        let fieldnorm_reader = self.fieldnorm_reader(reader)?;
+        let mut term_postings_list = Vec::new();
+        if reader.has_deletes() {
+            for &(offset, ref term) in &self.phrase_terms {
+                if let Some(postings) = reader
+                    .inverted_index(term.field())?
+                    .read_postings(term, IndexRecordOption::WithFreqsAndPositions)?
+                {
+                    term_postings_list.push((offset, postings));
+                } else {
+                    return Ok(None);
+                }
+            }
+        } else {
+            for &(offset, ref term) in &self.phrase_terms {
+                if let Some(postings) = reader
+                    .inverted_index(term.field())?
+                    .read_postings_no_deletes(term, IndexRecordOption::WithFreqsAndPositions)?
+                {
+                    term_postings_list.push((offset, postings));
+                } else {
+                    return Ok(None);
+                }
+            }
+        }
+
+        let inv_index = reader.inverted_index(self.prefix.1.field())?;
+        let mut stream = inv_index.terms().range().ge(self.prefix.1.value_bytes());
+        if let Some(end) = prefix_end(self.prefix.1.value_bytes()) {
+            stream = stream.lt(&end);
+        }
+
+        #[cfg(feature = "quickwit")]
+        {
+            // We don't have this on the fst, hence  we end up needing a feature flag.
+            //
+            // This is not a problem however as we enforce the limit below too.
+            // The point of `stream.limit` is to limit the number of term dictionary
+            // blocks being downloaded.
+            stream = stream.limit(self.max_expansions as u64);
+        }
+
+        let mut stream = stream.into_stream()?;
+
+        let mut suffixes = Vec::with_capacity(self.max_expansions as usize);
+        let mut new_term = self.prefix.1.clone();
+        while stream.advance() && (suffixes.len() as u32) < self.max_expansions {
+            new_term.clear_with_type(new_term.typ());
+            new_term.append_bytes(stream.key());
+            if reader.has_deletes() {
+                if let Some(postings) =
+                    inv_index.read_postings(&new_term, IndexRecordOption::WithFreqsAndPositions)?
+                {
+                    suffixes.push(postings);
+                }
+            } else if let Some(postings) = inv_index
+                .read_postings_no_deletes(&new_term, IndexRecordOption::WithFreqsAndPositions)?
+            {
+                suffixes.push(postings);
+            }
+        }
+
+        Ok(Some(PhrasePrefixScorer::new(
+            term_postings_list,
+            similarity_weight_opt,
+            fieldnorm_reader,
+            suffixes,
+            self.prefix.0,
+        )))
+    }
+}
+
+impl Weight for PhrasePrefixWeight {
+    fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>> {
+        if let Some(scorer) = self.phrase_scorer(reader, boost)? {
+            Ok(Box::new(scorer))
+        } else {
+            Ok(Box::new(EmptyScorer))
+        }
+    }
+
+    fn explain(&self, reader: &SegmentReader, doc: DocId) -> crate::Result<Explanation> {
+        let scorer_opt = self.phrase_scorer(reader, 1.0)?;
+        if scorer_opt.is_none() {
+            return Err(does_not_match(doc));
+        }
+        let mut scorer = scorer_opt.unwrap();
+        if scorer.seek(doc) != doc {
+            return Err(does_not_match(doc));
+        }
+        let fieldnorm_reader = self.fieldnorm_reader(reader)?;
+        let fieldnorm_id = fieldnorm_reader.fieldnorm_id(doc);
+        let phrase_count = scorer.phrase_count();
+        let mut explanation = Explanation::new("Phrase Prefix Scorer", scorer.score());
+        if let Some(similarity_weight) = self.similarity_weight_opt.as_ref() {
+            explanation.add_detail(similarity_weight.explain(fieldnorm_id, phrase_count));
+        }
+        Ok(explanation)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use crate::core::Index;
+    use crate::docset::TERMINATED;
+    use crate::query::{EnableScoring, PhrasePrefixQuery, Query};
+    use crate::schema::{Schema, TEXT};
+    use crate::{DocSet, Term};
+
+    pub fn create_index(texts: &[&'static str]) -> crate::Result<Index> {
+        let mut schema_builder = Schema::builder();
+        let text_field = schema_builder.add_text_field("text", TEXT);
+        let schema = schema_builder.build();
+        let index = Index::create_in_ram(schema);
+        {
+            let mut index_writer = index.writer_for_tests()?;
+            for &text in texts {
+                let doc = doc!(text_field=>text);
+                index_writer.add_document(doc)?;
+            }
+            index_writer.commit()?;
+        }
+        Ok(index)
+    }
+
+    #[test]
+    pub fn test_phrase_count_long() -> crate::Result<()> {
+        let index = create_index(&[
+            "aa bb dd cc",
+            "aa aa bb c dd aa bb cc aa bb dc",
+            " aa bb cd",
+        ])?;
+        let schema = index.schema();
+        let text_field = schema.get_field("text").unwrap();
+        let searcher = index.reader()?.searcher();
+        let phrase_query = PhrasePrefixQuery::new(vec![
+            Term::from_field_text(text_field, "aa"),
+            Term::from_field_text(text_field, "bb"),
+            Term::from_field_text(text_field, "c"),
+        ]);
+        let enable_scoring = EnableScoring::enabled_from_searcher(&searcher);
+        let phrase_weight = phrase_query
+            .phrase_prefix_query_weight(enable_scoring)
+            .unwrap()
+            .unwrap();
+        let mut phrase_scorer = phrase_weight
+            .phrase_scorer(searcher.segment_reader(0u32), 1.0)?
+            .unwrap();
+        assert_eq!(phrase_scorer.doc(), 1);
+        assert_eq!(phrase_scorer.phrase_count(), 2);
+        assert_eq!(phrase_scorer.advance(), 2);
+        assert_eq!(phrase_scorer.doc(), 2);
+        assert_eq!(phrase_scorer.phrase_count(), 1);
+        assert_eq!(phrase_scorer.advance(), TERMINATED);
+        Ok(())
+    }
+
+    #[test]
+    pub fn test_phrase_count_mid() -> crate::Result<()> {
+        let index = create_index(&["aa dd cc", "aa aa bb c dd aa bb cc aa dc", " aa bb cd"])?;
+        let schema = index.schema();
+        let text_field = schema.get_field("text").unwrap();
+        let searcher = index.reader()?.searcher();
+        let phrase_query = PhrasePrefixQuery::new(vec![
+            Term::from_field_text(text_field, "aa"),
+            Term::from_field_text(text_field, "b"),
+        ]);
+        let enable_scoring = EnableScoring::enabled_from_searcher(&searcher);
+        let phrase_weight = phrase_query
+            .phrase_prefix_query_weight(enable_scoring)
+            .unwrap()
+            .unwrap();
+        let mut phrase_scorer = phrase_weight
+            .phrase_scorer(searcher.segment_reader(0u32), 1.0)?
+            .unwrap();
+        assert_eq!(phrase_scorer.doc(), 1);
+        assert_eq!(phrase_scorer.phrase_count(), 2);
+        assert_eq!(phrase_scorer.advance(), 2);
+        assert_eq!(phrase_scorer.doc(), 2);
+        assert_eq!(phrase_scorer.phrase_count(), 1);
+        assert_eq!(phrase_scorer.advance(), TERMINATED);
+        Ok(())
+    }
+
+    #[test]
+    pub fn test_phrase_count_short() -> crate::Result<()> {
+        let index = create_index(&["aa dd", "aa aa bb c dd aa bb cc aa dc", " aa bb cd"])?;
+        let schema = index.schema();
+        let text_field = schema.get_field("text").unwrap();
+        let searcher = index.reader()?.searcher();
+        let phrase_query = PhrasePrefixQuery::new(vec![Term::from_field_text(text_field, "c")]);
+        let enable_scoring = EnableScoring::enabled_from_searcher(&searcher);
+        assert!(phrase_query
+            .phrase_prefix_query_weight(enable_scoring)
+            .unwrap()
+            .is_none());
+        let weight = phrase_query.weight(enable_scoring).unwrap();
+        let mut phrase_scorer = weight.scorer(searcher.segment_reader(0u32), 1.0)?;
+        assert_eq!(phrase_scorer.doc(), 1);
+        assert_eq!(phrase_scorer.advance(), 2);
+        assert_eq!(phrase_scorer.doc(), 2);
+        assert_eq!(phrase_scorer.advance(), TERMINATED);
+        Ok(())
+    }
+}

src/query/phrase_query/mod.rs

@@ -3,6 +3,7 @@ mod phrase_scorer;
 mod phrase_weight;
 
 pub use self::phrase_query::PhraseQuery;
+pub(crate) use self::phrase_scorer::intersection_count;
 pub use self::phrase_scorer::PhraseScorer;
 pub use self::phrase_weight::PhraseWeight;
 

src/query/phrase_query/phrase_query.rs

@@ -108,7 +108,10 @@ impl PhraseQuery {
         }
         let terms = self.phrase_terms();
         let bm25_weight_opt = match enable_scoring {
-            EnableScoring::Enabled(searcher) => Some(Bm25Weight::for_terms(searcher, &terms)?),
+            EnableScoring::Enabled {
+                statistics_provider,
+                ..
+            } => Some(Bm25Weight::for_terms(statistics_provider, &terms)?),
             EnableScoring::Disabled { .. } => None,
         };
         let mut weight = PhraseWeight::new(self.phrase_terms.clone(), bm25_weight_opt);