Added a columnar cli

.github/workflows/coverage.yml

@@ -2,9 +2,9 @@ name: Coverage
 
 on:
   push:
-    branches: [main]
+    branches: [ main ]
   pull_request:
-    branches: [main]
+    branches: [ main ]
 
 jobs:
   coverage:
@@ -16,7 +16,7 @@ jobs:
       - uses: Swatinem/rust-cache@v2
       - uses: taiki-e/install-action@cargo-llvm-cov
       - name: Generate code coverage
-        run: cargo +nightly llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
+        run: cargo +nightly llvm-cov --all-features --workspace --lcov --output-path lcov.info
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         continue-on-error: true

.gitignore

@@ -13,5 +13,3 @@ benchmark
 .idea
 trace.dat
 cargo-timing*
-control
-variable

Cargo.toml

@@ -23,7 +23,7 @@ regex = { version = "1.5.5", default-features = false, features = ["std", "unico
 aho-corasick = "0.7"
 tantivy-fst = "0.4.0"
 memmap2 = { version = "0.5.3", optional = true }
-lz4_flex = { version = "0.10", default-features = false, features = ["checked-decode"], optional = true }
+lz4_flex = { version = "0.9.2", default-features = false, features = ["checked-decode"], optional = true }
 brotli = { version = "3.3.4", optional = true }
 zstd = { version = "0.12", optional = true, default-features = false }
 snap = { version = "1.0.5", optional = true }
@@ -44,11 +44,11 @@ rustc-hash = "1.1.0"
 thiserror = "1.0.30"
 htmlescape = "0.3.1"
 fail = "0.5.0"
-murmurhash32 = "0.3.0"
+murmurhash32 = "0.2.0"
 time = { version = "0.3.10", features = ["serde-well-known"] }
 smallvec = "1.8.0"
 rayon = "1.5.2"
-lru = "0.10.0"
+lru = "0.9.0"
 fastdivide = "0.4.0"
 itertools = "0.10.3"
 measure_time = "0.8.2"
@@ -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" }
-query-grammar = { version= "0.19.0", path="./query-grammar", package = "tantivy-query-grammar" }
+tantivy-query-grammar = { version= "0.19.0", path="./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" }
@@ -77,7 +77,6 @@ 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"

ci/before_deploy.ps1

@@ -0,0 +1,23 @@
+# This script takes care of packaging the build artifacts that will go in the
+# release zipfile
+
+$SRC_DIR = $PWD.Path
+$STAGE = [System.Guid]::NewGuid().ToString()
+
+Set-Location $ENV:Temp
+New-Item -Type Directory -Name $STAGE
+Set-Location $STAGE
+
+$ZIP = "$SRC_DIR\$($Env:CRATE_NAME)-$($Env:APPVEYOR_REPO_TAG_NAME)-$($Env:TARGET).zip"
+
+# TODO Update this to package the right artifacts
+Copy-Item "$SRC_DIR\target\$($Env:TARGET)\release\hello.exe" '.\'
+
+7z a "$ZIP" *
+
+Push-AppveyorArtifact "$ZIP"
+
+Remove-Item *.* -Force
+Set-Location ..
+Remove-Item $STAGE
+Set-Location $SRC_DIR

ci/before_deploy.sh

@@ -0,0 +1,33 @@
+# This script takes care of building your crate and packaging it for release
+
+set -ex
+
+main() {
+    local src=$(pwd) \
+          stage=
+
+    case $TRAVIS_OS_NAME in
+        linux)
+            stage=$(mktemp -d)
+            ;;
+        osx)
+            stage=$(mktemp -d -t tmp)
+            ;;
+    esac
+
+    test -f Cargo.lock || cargo generate-lockfile
+
+    # TODO Update this to build the artifacts that matter to you
+    cross rustc --bin hello --target $TARGET --release -- -C lto
+
+    # TODO Update this to package the right artifacts
+    cp target/$TARGET/release/hello $stage/
+
+    cd $stage
+    tar czf $src/$CRATE_NAME-$TRAVIS_TAG-$TARGET.tar.gz *
+    cd $src
+
+    rm -rf $stage
+}
+
+main

ci/install.sh

@@ -0,0 +1,47 @@
+set -ex
+
+main() {
+    local target=
+    if [ $TRAVIS_OS_NAME = linux ]; then
+        target=x86_64-unknown-linux-musl
+        sort=sort
+    else
+        target=x86_64-apple-darwin
+        sort=gsort  # for `sort --sort-version`, from brew's coreutils.
+    fi
+
+    # Builds for iOS are done on OSX, but require the specific target to be
+    # installed.
+    case $TARGET in
+        aarch64-apple-ios)
+            rustup target install aarch64-apple-ios
+            ;;
+        armv7-apple-ios)
+            rustup target install armv7-apple-ios
+            ;;
+        armv7s-apple-ios)
+            rustup target install armv7s-apple-ios
+            ;;
+        i386-apple-ios)
+            rustup target install i386-apple-ios
+            ;;
+        x86_64-apple-ios)
+            rustup target install x86_64-apple-ios
+            ;;
+    esac
+
+    # This fetches latest stable release
+    local tag=$(git ls-remote --tags --refs --exit-code https://github.com/japaric/cross \
+                       | cut -d/ -f3 \
+                       | grep -E '^v[0.1.0-9.]+$' \
+                       | $sort --version-sort \
+                       | tail -n1)
+    curl -LSfs https://japaric.github.io/trust/install.sh | \
+        sh -s -- \
+           --force \
+           --git japaric/cross \
+           --tag $tag \
+           --target $target
+}
+
+main

ci/script.sh

@@ -0,0 +1,30 @@
+#!/usr/bin/env bash
+
+# This script takes care of testing your crate
+
+set -ex
+
+main() {
+    if [ ! -z $CODECOV ]; then
+        echo "Codecov"
+        cargo build --verbose && cargo coverage --verbose --all && bash <(curl -s https://codecov.io/bash) -s target/kcov
+    else
+        echo "Build"
+        cross build --target $TARGET
+        if [ ! -z $DISABLE_TESTS ]; then
+            return
+        fi
+        echo "Test"
+        cross test --target $TARGET --no-default-features --features mmap
+        cross test --target $TARGET --no-default-features --features mmap query-grammar
+    fi
+    for example in $(ls examples/*.rs)
+    do
+        cargo run --example  $(basename $example .rs)
+    done
+}
+
+# we don't run the "test phase" when doing deploys
+if [ -z $TRAVIS_TAG ]; then
+    main
+fi

columnar/Cargo.toml

@@ -17,7 +17,6 @@ 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/benches/bench_u128.rs

@@ -58,7 +58,7 @@ fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(
+        column.get_docids_for_value_range(
             *FIFTY_PERCENT_RANGE.start() as u128..=*FIFTY_PERCENT_RANGE.end() as u128,
             0..data.len() as u32,
             &mut positions,
@@ -74,7 +74,7 @@ fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(
+        column.get_docids_for_value_range(
             *SINGLE_ITEM_RANGE.start() as u128..=*SINGLE_ITEM_RANGE.end() as u128,
             0..data.len() as u32,
             &mut positions,
@@ -90,7 +90,7 @@ fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
+        column.get_docids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
         positions
     });
 }

columnar/benches/bench_u64.rs

@@ -89,7 +89,7 @@ fn bench_intfastfield_getrange_u64_50percent_hit(b: &mut Bencher) {
     let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(
+        column.get_docids_for_value_range(
             FIFTY_PERCENT_RANGE,
             0..data.len() as u32,
             &mut positions,
@@ -106,7 +106,7 @@ fn bench_intfastfield_getrange_u64_1percent_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(
+        column.get_docids_for_value_range(
             ONE_PERCENT_ITEM_RANGE,
             0..data.len() as u32,
             &mut positions,
@@ -123,7 +123,7 @@ fn bench_intfastfield_getrange_u64_single_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(SINGLE_ITEM_RANGE, 0..data.len() as u32, &mut positions);
+        column.get_docids_for_value_range(SINGLE_ITEM_RANGE, 0..data.len() as u32, &mut positions);
         positions
     });
 }
@@ -136,7 +136,7 @@ fn bench_intfastfield_getrange_u64_hit_all(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
+        column.get_docids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
         positions
     });
 }

columnar/src/TODO.md

@@ -1,22 +1,29 @@
 # 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
+* move datetime to quickwit common
 * switch to nanos
 * reintroduce the gcd map.
 
 # Perf and Size
+* remove alloc in `ord_to_term`
 + multivaued range queries restrat frm the beginning all of the time.
 * re-add ZSTD compression for dictionaries
-* no systematic monotonic mapping
-* consider removing multilinear
-* f32?
-* adhoc solution for bool?
-* add metrics helper for aggregate. sum(row_id)
-* review inline absence/presence
-* improv perf of select using PDEP
-* compare with roaring bitmap/elias fano etc etc.
-* SIMD range? (see blog post)
-* Add alignment?
-* Consider another codec to bridge the gap between few and 5k elements
+no systematic monotonic mapping
+consider removing multilinear
+f32?
+adhoc solution for bool?
+add metrics helper for aggregate. sum(row_id)
+review inline absence/presence
+improv perf of select using PDEP
+compare with roaring bitmap/elias fano etc etc.
+SIMD range? (see blog post)
+Add alignment?
+Consider another codec to bridge the gap between few and 5k elements
 
 # Cleanup and rationalization
 in benchmark, unify percent vs ratio, f32 vs f64.
@@ -24,10 +31,15 @@ investigate if should have better errors? io::Error is overused at the moment.
 rename rank/select in unit tests
 Review the public API via cargo doc
 go through TODOs
+remove all  doc_id occurences -> row_id
+use the rank & select naming in unit tests branch.
 multi-linear -> blockwise
 linear codec -> simply a multiplication for the index column
+rename columnar to something more explicit, like column_dictionary or columnar_table
+rename fastfield -> column
 document changes
 rationalization FastFieldValue, HasColumnType
+isolate u128_based and uniform naming
 
 # Other
 fix enhance column-cli

columnar/src/column/dictionary_encoded.rs

@@ -32,11 +32,11 @@ impl BytesColumn {
 
     /// Returns the number of rows in the column.
     pub fn num_rows(&self) -> RowId {
-        self.term_ord_column.num_docs()
+        self.term_ord_column.num_rows()
     }
 
     pub fn term_ords(&self, row_id: RowId) -> impl Iterator<Item = u64> + '_ {
-        self.term_ord_column.values_for_doc(row_id)
+        self.term_ord_column.values(row_id)
     }
 
     /// Returns the column of ordinals

columnar/src/column/mod.rs

@@ -3,7 +3,7 @@ mod serialize;
 
 use std::fmt::Debug;
 use std::io::Write;
-use std::ops::{Deref, Range, RangeInclusive};
+use std::ops::Deref;
 use std::sync::Arc;
 
 use common::BinarySerializable;
@@ -38,20 +38,18 @@ 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 {
+    pub fn num_rows(&self) -> RowId {
         match &self.idx {
-            ColumnIndex::Empty { num_docs } => *num_docs,
-            ColumnIndex::Full => self.values.num_vals(),
-            ColumnIndex::Optional(optional_index) => optional_index.num_docs(),
+            ColumnIndex::Full => self.values.num_vals() as u32,
+            ColumnIndex::Optional(optional_index) => optional_index.num_rows(),
             ColumnIndex::Multivalued(col_index) => {
                 // The multivalued index contains all value start row_id,
                 // and one extra value at the end with the overall number of rows.
-                col_index.num_docs()
+                col_index.num_rows()
             }
         }
     }
@@ -65,40 +63,21 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
     }
 
     pub fn first(&self, row_id: RowId) -> Option<T> {
-        self.values_for_doc(row_id).next()
+        self.values(row_id).next()
     }
 
-    pub fn values_for_doc(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
+    pub fn values(&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))
     }
 
-    /// Get the docids of values which are in the provided value range.
-    #[inline]
-    pub fn get_docids_for_value_range(
-        &self,
-        value_range: RangeInclusive<T>,
-        selected_docid_range: Range<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, doc_ids);
-        // Convert rows to docids
-        self.idx
-            .select_batch_in_place(selected_docid_range.start, doc_ids);
-    }
-
     /// Fils the output vector with the (possibly multiple values that are associated_with
     /// `row_id`.
     ///
     /// This method clears the `output` vector.
     pub fn fill_vals(&self, row_id: RowId, output: &mut Vec<T>) {
         output.clear();
-        output.extend(self.values_for_doc(row_id));
+        output.extend(self.values(row_id));
     }
 
     pub fn first_or_default_col(self, default_value: T) -> Arc<dyn ColumnValues<T>> {
@@ -152,10 +131,9 @@ 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(),
+            ColumnIndex::Optional(optional_idx) => optional_idx.num_rows(),
+            ColumnIndex::Multivalued(multivalue_idx) => multivalue_idx.num_rows(),
         }
     }
 }

columnar/src/column/serialize.rs

@@ -7,10 +7,9 @@ use sstable::Dictionary;
 
 use crate::column::{BytesColumn, Column};
 use crate::column_index::{serialize_column_index, SerializableColumnIndex};
-use crate::column_values::{
-    load_u64_based_column_values, serialize_column_values_u128, serialize_u64_based_column_values,
-    CodecType, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
-};
+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::iterable::Iterable;
 use crate::StrColumn;
 
@@ -50,7 +49,8 @@ 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 = load_u64_based_column_values(column_values_data)?;
+    let column_values =
+        crate::column_values::u64_based::load_u64_based_column_values(column_values_data)?;
     Ok(Column {
         idx: column_index,
         values: column_values,

columnar/src/column_index/merge/shuffled.rs

@@ -91,10 +91,13 @@ 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))
+                if optional_index.contains(row_addr.row_id) {
+                    1u32
+                } else {
+                    0u32
+                }
             }
             ColumnIndex::Multivalued(multivalued_index) => {
                 multivalued_index.range(row_addr.row_id).len() as u32

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 | Some(ColumnIndex::Empty { .. }) => Box::new(std::iter::empty()),
+                        None => Box::new(std::iter::empty()),
                     };
                     rows_it
                 }),
@@ -74,9 +74,7 @@ fn convert_column_opt_to_multivalued_index<'a>(
     num_rows: RowId,
 ) -> Box<dyn Iterator<Item = RowId> + 'a> {
     match column_index_opt {
-        None | Some(ColumnIndex::Empty { .. }) => {
-            Box::new(iter::repeat(0u32).take(num_rows as usize + 1))
-        }
+        None => 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

@@ -10,13 +10,10 @@ pub use optional_index::{OptionalIndex, Set};
 pub use serialize::{open_column_index, serialize_column_index, SerializableColumnIndex};
 
 use crate::column_index::multivalued_index::MultiValueIndex;
-use crate::{Cardinality, DocId, RowId};
+use crate::{Cardinality, RowId};
 
 #[derive(Clone)]
 pub enum ColumnIndex {
-    Empty {
-        num_docs: u32,
-    },
     Full,
     Optional(OptionalIndex),
     /// In addition, at index num_rows, an extra value is added
@@ -37,10 +34,8 @@ 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,
@@ -48,58 +43,32 @@ 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 {
+    pub fn has_value(&self, row_id: RowId) -> bool {
         match self {
-            ColumnIndex::Empty { .. } => false,
             ColumnIndex::Full => true,
-            ColumnIndex::Optional(optional_index) => optional_index.contains(doc_id),
+            ColumnIndex::Optional(optional_index) => optional_index.contains(row_id),
             ColumnIndex::Multivalued(multivalued_index) => {
-                !multivalued_index.range(doc_id).is_empty()
+                multivalued_index.range(row_id).len() > 0
             }
         }
     }
 
-    pub fn value_row_ids(&self, doc_id: DocId) -> Range<RowId> {
+    pub fn value_row_ids(&self, row_id: RowId) -> Range<RowId> {
         match self {
-            ColumnIndex::Empty { .. } => 0..0,
-            ColumnIndex::Full => doc_id..doc_id + 1,
+            ColumnIndex::Full => row_id..row_id + 1,
             ColumnIndex::Optional(optional_index) => {
-                if let Some(val) = optional_index.rank_if_exists(doc_id) {
+                if let Some(val) = optional_index.rank_if_exists(row_id) {
                     val..val + 1
                 } else {
                     0..0
                 }
             }
-            ColumnIndex::Multivalued(multivalued_index) => multivalued_index.range(doc_id),
+            ColumnIndex::Multivalued(multivalued_index) => multivalued_index.range(row_id),
         }
     }
 
-    pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
+    pub fn select_batch_in_place(&self, rank_ids: &mut Vec<RowId>) {
         match self {
-            ColumnIndex::Empty { .. } => 0..0,
-            ColumnIndex::Full => doc_id,
-            ColumnIndex::Optional(optional_index) => {
-                let row_start = optional_index.rank(doc_id.start);
-                let row_end = optional_index.rank(doc_id.end);
-                row_start..row_end
-            }
-            ColumnIndex::Multivalued(multivalued_index) => {
-                let end_docid = doc_id.end.min(multivalued_index.num_docs() - 1) + 1;
-                let start_docid = doc_id.start.min(end_docid);
-
-                let row_start = multivalued_index.start_index_column.get_val(start_docid);
-                let row_end = multivalued_index.start_index_column.get_val(end_docid);
-
-                row_start..row_end
-            }
-        }
-    }
-
-    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.
@@ -108,7 +77,8 @@ impl ColumnIndex {
                 optional_index.select_batch(&mut rank_ids[..]);
             }
             ColumnIndex::Multivalued(multivalued_index) => {
-                multivalued_index.select_batch_in_place(doc_id_start, rank_ids)
+                // TODO important: avoid using 0u32, and restart from the beginning all of the time.
+                multivalued_index.select_batch_in_place(0u32, rank_ids)
             }
         }
     }

columnar/src/column_index/multivalued_index.rs

@@ -5,17 +5,16 @@ use std::sync::Arc;
 
 use common::OwnedBytes;
 
-use crate::column_values::{
-    load_u64_based_column_values, serialize_u64_based_column_values, CodecType, ColumnValues,
-};
+use crate::column_values::u64_based::CodecType;
+use crate::column_values::ColumnValues;
 use crate::iterable::Iterable;
-use crate::{DocId, RowId};
+use crate::RowId;
 
 pub fn serialize_multivalued_index(
     multivalued_index: &dyn Iterable<RowId>,
     output: &mut impl Write,
 ) -> io::Result<()> {
-    serialize_u64_based_column_values(
+    crate::column_values::u64_based::serialize_u64_based_column_values(
         multivalued_index,
         &[CodecType::Bitpacked, CodecType::Linear],
         output,
@@ -24,7 +23,8 @@ pub fn serialize_multivalued_index(
 }
 
 pub fn open_multivalued_index(bytes: OwnedBytes) -> io::Result<MultiValueIndex> {
-    let start_index_column: Arc<dyn ColumnValues<RowId>> = load_u64_based_column_values(bytes)?;
+    let start_index_column: Arc<dyn ColumnValues<RowId>> =
+        crate::column_values::u64_based::load_u64_based_column_values(bytes)?;
     Ok(MultiValueIndex { start_index_column })
 }
 
@@ -52,20 +52,20 @@ impl MultiValueIndex {
     /// Returns `[start, end)`, such that the values associated with
     /// the given document are `start..end`.
     #[inline]
-    pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
-        let start = self.start_index_column.get_val(doc_id);
-        let end = self.start_index_column.get_val(doc_id + 1);
+    pub(crate) fn range(&self, row_id: RowId) -> Range<RowId> {
+        let start = self.start_index_column.get_val(row_id);
+        let end = self.start_index_column.get_val(row_id + 1);
         start..end
     }
 
     /// Returns the number of documents in the index.
     #[inline]
-    pub fn num_docs(&self) -> u32 {
+    pub fn num_rows(&self) -> u32 {
         self.start_index_column.num_vals() - 1
     }
 
     /// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
-    /// docids. Positions are converted inplace to docids.
+    /// row_ids. Positions are converted inplace to docids.
     ///
     /// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
     /// index.
@@ -76,20 +76,20 @@ impl MultiValueIndex {
     /// TODO: Instead of a linear scan we can employ a exponential search into binary search to
     /// match a docid to its value position.
     #[allow(clippy::bool_to_int_with_if)]
-    pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
+    pub(crate) fn select_batch_in_place(&self, row_start: RowId, ranks: &mut Vec<u32>) {
         if ranks.is_empty() {
             return;
         }
-        let mut cur_doc = docid_start;
+        let mut cur_doc = row_start;
         let mut last_doc = None;
 
-        assert!(self.start_index_column.get_val(docid_start) <= ranks[0]);
+        assert!(self.start_index_column.get_val(row_start) as u32 <= 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);
+                let end = self.start_index_column.get_val(cur_doc + 1) as u32;
                 if end > pos {
                     ranks[write_doc_pos] = cur_doc;
                     write_doc_pos += if last_doc == Some(cur_doc) { 0 } else { 1 };
@@ -127,7 +127,7 @@ mod tests {
         let offsets: Vec<RowId> = vec![0, 10, 12, 15, 22, 23]; // docid values are [0..10, 10..12, 12..15, etc.]
         let column: Arc<dyn ColumnValues<RowId>> = Arc::new(IterColumn::from(offsets.into_iter()));
         let index = MultiValueIndex::from(column);
-        assert_eq!(index.num_docs(), 5);
+        assert_eq!(index.num_rows(), 5);
         let positions = &[10u32, 11, 15, 20, 21, 22];
         assert_eq!(index_to_pos_helper(&index, 0..5, positions), vec![1, 3, 4]);
         assert_eq!(index_to_pos_helper(&index, 1..5, positions), vec![1, 3, 4]);

columnar/src/column_index/optional_index/mod.rs

@@ -11,7 +11,7 @@ use set_block::{
 };
 
 use crate::iterable::Iterable;
-use crate::{DocId, InvalidData, RowId};
+use crate::{InvalidData, RowId};
 
 /// The threshold for for number of elements after which we switch to dense block encoding.
 ///
@@ -177,11 +177,11 @@ impl Set<RowId> for OptionalIndex {
     }
 
     #[inline]
-    fn rank(&self, doc_id: DocId) -> RowId {
+    fn rank(&self, row_id: RowId) -> RowId {
         let RowAddr {
             block_id,
             in_block_row_id,
-        } = row_addr_from_row_id(doc_id);
+        } = row_addr_from_row_id(row_id);
         let block_meta = self.block_metas[block_id as usize];
         let block = self.block(block_meta);
         let block_offset_row_id = match block {
@@ -192,11 +192,11 @@ impl Set<RowId> for OptionalIndex {
     }
 
     #[inline]
-    fn rank_if_exists(&self, doc_id: DocId) -> Option<RowId> {
+    fn rank_if_exists(&self, row_id: RowId) -> Option<RowId> {
         let RowAddr {
             block_id,
             in_block_row_id,
-        } = row_addr_from_row_id(doc_id);
+        } = row_addr_from_row_id(row_id);
         let block_meta = self.block_metas[block_id as usize];
         let block = self.block(block_meta);
         let block_offset_row_id = match block {
@@ -220,7 +220,7 @@ impl Set<RowId> for OptionalIndex {
         block_doc_idx_start + in_block_rank as u32
     }
 
-    fn select_cursor(&self) -> OptionalIndexSelectCursor<'_> {
+    fn select_cursor<'b>(&'b self) -> OptionalIndexSelectCursor<'b> {
         OptionalIndexSelectCursor {
             current_block_cursor: BlockSelectCursor::Sparse(
                 SparseBlockCodec::open(b"").select_cursor(),
@@ -247,7 +247,7 @@ impl OptionalIndex {
         open_optional_index(bytes).unwrap()
     }
 
-    pub fn num_docs(&self) -> RowId {
+    pub fn num_rows(&self) -> RowId {
         self.num_rows
     }
 
@@ -255,7 +255,7 @@ impl OptionalIndex {
         self.num_non_null_rows
     }
 
-    pub fn iter_rows(&self) -> impl Iterator<Item = RowId> + '_ {
+    pub fn iter_rows<'a>(&'a self) -> impl Iterator<Item = RowId> + 'a {
         // TODO optimize
         let mut select_batch = self.select_cursor();
         (0..self.num_non_null_rows).map(move |rank| select_batch.select(rank))
@@ -268,7 +268,7 @@ impl OptionalIndex {
     }
 
     #[inline]
-    fn block(&self, block_meta: BlockMeta) -> Block<'_> {
+    fn block<'a>(&'a self, block_meta: BlockMeta) -> Block<'a> {
         let BlockMeta {
             start_byte_offset,
             block_variant,
@@ -351,7 +351,7 @@ fn serialize_optional_index_block(block_els: &[u16], out: &mut impl io::Write) -
     Ok(())
 }
 
-pub fn serialize_optional_index<W: io::Write>(
+pub fn serialize_optional_index<'a, W: io::Write>(
     non_null_rows: &dyn Iterable<RowId>,
     num_rows: RowId,
     output: &mut W,
@@ -427,7 +427,7 @@ impl SerializedBlockMeta {
     }
 
     #[inline]
-    fn to_bytes(self) -> [u8; SERIALIZED_BLOCK_META_NUM_BYTES] {
+    fn to_bytes(&self) -> [u8; SERIALIZED_BLOCK_META_NUM_BYTES] {
         assert!(self.num_non_null_rows > 0);
         let mut bytes = [0u8; SERIALIZED_BLOCK_META_NUM_BYTES];
         bytes[0..2].copy_from_slice(&self.block_id.to_le_bytes());
@@ -440,7 +440,7 @@ impl SerializedBlockMeta {
 
 #[inline]
 fn is_sparse(num_rows_in_block: u32) -> bool {
-    num_rows_in_block < DENSE_BLOCK_THRESHOLD
+    num_rows_in_block < DENSE_BLOCK_THRESHOLD as u32
 }
 
 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 + 1);
+    let mut block_metas = Vec::with_capacity(num_blocks as usize + 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;
+        non_null_rows_before_block += num_non_null_rows as u32;
     }
     block_metas.resize(
         ((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,
@@ -501,7 +501,7 @@ pub fn open_optional_index(bytes: OwnedBytes) -> io::Result<OptionalIndex> {
         num_non_empty_block_bytes as usize * SERIALIZED_BLOCK_META_NUM_BYTES;
     let (block_data, block_metas) = bytes.rsplit(block_metas_num_bytes);
     let (block_metas, num_non_null_rows) =
-        deserialize_optional_index_block_metadatas(block_metas.as_slice(), num_rows);
+        deserialize_optional_index_block_metadatas(block_metas.as_slice(), num_rows).into();
     let optional_index = OptionalIndex {
         num_rows,
         num_non_null_rows,

columnar/src/column_index/optional_index/set.rs

@@ -10,7 +10,7 @@ pub trait SetCodec {
     ///
     /// May panic if the elements are not sorted.
     fn serialize(els: impl Iterator<Item = Self::Item>, wrt: impl io::Write) -> io::Result<()>;
-    fn open(data: &[u8]) -> Self::Reader<'_>;
+    fn open<'a>(data: &'a [u8]) -> Self::Reader<'a>;
 }
 
 /// Stateful object that makes it possible to compute several select in a row,
@@ -43,5 +43,5 @@ pub trait Set<T> {
     fn select(&self, rank: T) -> T;
 
     /// Creates a brand new select cursor.
-    fn select_cursor(&self) -> Self::SelectCursor<'_>;
+    fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b>;
 }

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 / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
+    (ELEMENTS_PER_BLOCK as u32 / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
 
 pub struct DenseBlockCodec;
 
@@ -45,7 +45,7 @@ impl SetCodec for DenseBlockCodec {
     }
 
     #[inline]
-    fn open(data: &[u8]) -> Self::Reader<'_> {
+    fn open<'a>(data: &'a [u8]) -> Self::Reader<'a> {
         assert_eq!(data.len(), DENSE_BLOCK_NUM_BYTES as usize);
         DenseBlock(data)
     }
@@ -94,7 +94,7 @@ impl DenseMiniBlock {
         Self { bitvec, rank }
     }
 
-    fn to_bytes(self) -> [u8; MINI_BLOCK_NUM_BYTES] {
+    fn to_bytes(&self) -> [u8; MINI_BLOCK_NUM_BYTES] {
         let mut bytes = [0u8; MINI_BLOCK_NUM_BYTES];
         bytes[..MINI_BLOCK_BITVEC_NUM_BYTES].copy_from_slice(&self.bitvec.to_le_bytes());
         bytes[MINI_BLOCK_BITVEC_NUM_BYTES..].copy_from_slice(&self.rank.to_le_bytes());
@@ -166,7 +166,7 @@ impl<'a> Set<u16> for DenseBlock<'a> {
     }
 
     #[inline(always)]
-    fn select_cursor(&self) -> Self::SelectCursor<'_> {
+    fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b> {
         DenseBlockSelectCursor {
             block_id: 0,
             dense_block: *self,
@@ -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,
+                rank: non_null_rows_before as u16,
             };
             output.write_all(&dense_mini_block.to_bytes())?;
             non_null_rows_before += block.count_ones() as u16;

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

@@ -16,7 +16,7 @@ impl SetCodec for SparseBlockCodec {
         Ok(())
     }
 
-    fn open(data: &[u8]) -> Self::Reader<'_> {
+    fn open<'a>(data: &'a [u8]) -> Self::Reader<'a> {
         SparseBlock(data)
     }
 }
@@ -56,7 +56,7 @@ impl<'a> Set<u16> for SparseBlock<'a> {
     }
 
     #[inline(always)]
-    fn select_cursor(&self) -> Self::SelectCursor<'_> {
+    fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b> {
         *self
     }
 }

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, 100, &mut out).unwrap();
+    serialize_optional_index(&vals.clone(), 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();
@@ -142,7 +142,7 @@ fn test_optional_index_large() {
 
 fn test_optional_index_iter_aux(row_ids: &[RowId], num_rows: RowId) {
     let optional_index = OptionalIndex::for_test(num_rows, row_ids);
-    assert_eq!(optional_index.num_docs(), num_rows);
+    assert_eq!(optional_index.num_rows(), num_rows);
     assert!(optional_index.iter_rows().eq(row_ids.iter().copied()));
 }
 
@@ -154,7 +154,7 @@ fn test_optional_index_iter_empty() {
 fn test_optional_index_rank_aux(row_ids: &[RowId]) {
     let num_rows = row_ids.last().copied().unwrap_or(0u32) + 1;
     let null_index = OptionalIndex::for_test(num_rows, row_ids);
-    assert_eq!(null_index.num_docs(), num_rows);
+    assert_eq!(null_index.num_rows(), num_rows);
     for (row_id, row_val) in row_ids.iter().copied().enumerate() {
         assert_eq!(null_index.rank(row_val), row_id as u32);
         assert_eq!(null_index.rank_if_exists(row_val), Some(row_id as u32));
@@ -196,7 +196,7 @@ fn test_optional_index_for_tests() {
     assert!(optional_index.contains(1));
     assert!(optional_index.contains(2));
     assert!(!optional_index.contains(3));
-    assert_eq!(optional_index.num_docs(), 4);
+    assert_eq!(optional_index.num_rows(), 4);
 }
 
 #[cfg(all(test, feature = "unstable"))]
@@ -212,13 +212,10 @@ mod bench {
     fn gen_bools(fill_ratio: f64) -> OptionalIndex {
         let mut out = Vec::new();
         let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
-        let vals: Vec<RowId> = (0..TOTAL_NUM_VALUES)
+        let vals: Vec<bool> = (0..TOTAL_NUM_VALUES)
             .map(|_| rng.gen_bool(fill_ratio))
-            .enumerate()
-            .filter(|(pos, val)| *val)
-            .map(|(pos, _)| pos as RowId)
             .collect();
-        serialize_optional_index(&&vals[..], TOTAL_NUM_VALUES, &mut out).unwrap();
+        serialize_optional_index(&&vals[..], &mut out).unwrap();
         let codec = open_optional_index(OwnedBytes::new(out)).unwrap();
         codec
     }

columnar/src/column_values/bench.rs

@@ -1,135 +0,0 @@
-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

@@ -0,0 +1,383 @@
+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;
+
+/// `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 positions of values which are in the provided value range.
+    ///
+    /// Note that position == docid for single value fast fields
+    #[inline(always)]
+    fn get_docids_for_value_range(
+        &self,
+        value_range: RangeInclusive<T>,
+        doc_id_range: Range<u32>,
+        positions: &mut Vec<u32>,
+    ) {
+        let doc_id_range = doc_id_range.start..doc_id_range.end.min(self.num_vals());
+        for idx in doc_id_range.start..doc_id_range.end {
+            let val = self.get_val(idx);
+            if value_range.contains(&val) {
+                positions.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)
+    }
+}
+
+impl<'a, C: ColumnValues<T> + ?Sized, T: Copy + PartialOrd + Debug> ColumnValues<T> for &'a C {
+    fn get_val(&self, idx: u32) -> T {
+        (*self).get_val(idx)
+    }
+
+    fn min_value(&self) -> T {
+        (*self).min_value()
+    }
+
+    fn max_value(&self) -> T {
+        (*self).max_value()
+    }
+
+    fn num_vals(&self) -> u32 {
+        (*self).num_vals()
+    }
+
+    fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
+        (*self).iter()
+    }
+
+    fn get_range(&self, start: u64, output: &mut [T]) {
+        (*self).get_range(start, output)
+    }
+}
+
+/// 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_docids_for_value_range(
+        &self,
+        range: RangeInclusive<Output>,
+        doc_id_range: Range<u32>,
+        positions: &mut Vec<u32>,
+    ) {
+        self.from_column.get_docids_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/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.
 ///
@@ -313,7 +313,7 @@ impl ColumnValues<u128> for CompactSpaceDecompressor {
     }
 
     #[inline]
-    fn get_row_ids_for_value_range(
+    fn get_docids_for_value_range(
         &self,
         value_range: RangeInclusive<u128>,
         positions_range: Range<u32>,
@@ -464,7 +464,7 @@ mod tests {
     use itertools::Itertools;
 
     use super::*;
-    use crate::column_values::u128_based::U128Header;
+    use crate::column_values::serialize::U128Header;
     use crate::column_values::{open_u128_mapped, serialize_column_values_u128};
 
     #[test]
@@ -709,7 +709,7 @@ mod tests {
         doc_id_range: Range<u32>,
     ) -> Vec<u32> {
         let mut positions = Vec::new();
-        column.get_row_ids_for_value_range(value_range, doc_id_range, &mut positions);
+        column.get_docids_for_value_range(value_range, doc_id_range, &mut positions);
         positions
     }
 

columnar/src/column_values/merge.rs

@@ -1,41 +0,0 @@
-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

@@ -1,4 +1,5 @@
 #![warn(missing_docs)]
+#![cfg_attr(all(feature = "unstable", test), feature(test))]
 
 //! # `fastfield_codecs`
 //!
@@ -7,225 +8,248 @@
 //! - Monotonically map values to u64/u128
 
 use std::fmt::Debug;
-use std::ops::{Range, RangeInclusive};
+use std::io;
+use std::io::Write;
 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 merge;
+mod compact_space;
 pub(crate) mod monotonic_mapping;
 pub(crate) mod monotonic_mapping_u128;
 mod stats;
-mod u128_based;
-mod u64_based;
-mod vec_column;
+pub(crate) mod u64_based;
 
-mod monotonic_column;
+mod column;
+pub mod serialize;
 
-pub(crate) use merge::MergedColumnValues;
-pub use stats::ColumnStats;
-pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
+pub use serialize::serialize_column_values_u128;
+pub use stats::Stats;
 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::monotonic_column::monotonic_map_column;
-use crate::RowId;
+pub use self::column::{monotonic_map_column, ColumnValues, IterColumn, VecColumn};
+use crate::iterable::Iterable;
+use crate::{ColumnIndex, 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;
+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,
+}
 
-    /// 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, indexes: &[u32], output: &mut [T]) {
-        assert!(indexes.len() == output.len());
-        let out_and_idx_chunks = output.chunks_exact_mut(4).zip(indexes.chunks_exact(4));
-        for (out_x4, idx_x4) in out_and_idx_chunks {
-            out_x4[0] = self.get_val(idx_x4[0]);
-            out_x4[1] = self.get_val(idx_x4[1]);
-            out_x4[2] = self.get_val(idx_x4[2]);
-            out_x4[3] = self.get_val(idx_x4[3]);
+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))
+                    })
+                )
+            },
         }
-
-        let step_size = 4;
-        let cutoff = indexes.len() - indexes.len() % step_size;
-
-        for idx in cutoff..indexes.len() {
-            output[idx] = self.get_val(indexes[idx]);
-        }
-    }
-
-    /// 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)
+#[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)
     }
 
-    #[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)
+    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)
     }
 }
 
-/// Wraps an cloneable iterator into a `Column`.
-pub struct IterColumn<T>(T);
+impl U128FastFieldCodecType {
+    pub(crate) fn to_code(self) -> u8 {
+        self as u8
+    }
 
-impl<T> From<T> for IterColumn<T>
-where T: Iterator + Clone + ExactSizeIterator
-{
-    fn from(iter: T) -> Self {
-        IterColumn(iter)
+    pub(crate) fn from_code(code: u8) -> Option<Self> {
+        match code {
+            1 => Some(Self::CompactSpace),
+            _ => None,
+        }
     }
 }
 
-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()
-    }
+/// 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)?;
 
-    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())
-    }
+    let inverted: StrictlyMonotonicMappingInverter<StrictlyMonotonicMappingToInternal<T>> =
+        StrictlyMonotonicMappingToInternal::<T>::new().into();
+    Ok(Arc::new(monotonic_map_column(reader, inverted)))
 }
 
 #[cfg(all(test, feature = "unstable"))]
-mod bench;
+mod bench {
+    use std::sync::Arc;
+
+    use common::OwnedBytes;
+    use rand::rngs::StdRng;
+    use rand::{Rng, SeedableRng};
+    use test::{self, Bencher};
 
-#[cfg(test)]
-mod tests {
     use super::*;
 
-    #[test]
-    fn test_range_as_col() {
-        let col = IterColumn::from(10..100);
-        assert_eq!(col.num_vals(), 90);
-        assert_eq!(col.max_value(), 99);
+    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
+    }
+
+    #[inline(never)]
+    fn value_iter() -> impl Iterator<Item = u64> {
+        0..20_000
+    }
+    fn get_reader_for_bench<Codec: FastFieldCodec>(data: &[u64]) -> Codec::Reader {
+        let mut bytes = Vec::new();
+        let min_value = *data.iter().min().unwrap();
+        let data = data.iter().map(|el| *el - min_value).collect::<Vec<_>>();
+        let col = VecColumn::from(&data);
+        let normalized_header = NormalizedHeader {
+            num_vals: col.num_vals(),
+            max_value: col.max_value(),
+        };
+        Codec::serialize(&VecColumn::from(&data), &mut bytes).unwrap();
+        Codec::open_from_bytes(OwnedBytes::new(bytes), normalized_header).unwrap()
+    }
+    fn bench_get<Codec: FastFieldCodec>(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: FastFieldCodec>(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: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
+        let min_value = *data.iter().min().unwrap();
+        let data = data.iter().map(|el| *el - min_value).collect::<Vec<_>>();
+
+        let mut bytes = Vec::new();
+        b.iter(|| {
+            bytes.clear();
+            Codec::serialize(&VecColumn::from(&data), &mut bytes).unwrap();
+        });
+    }
+
+    #[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/monotonic_column.rs

@@ -1,120 +0,0 @@
-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(always)]
-    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

@@ -1,7 +1,7 @@
 use std::fmt::Debug;
 use std::marker::PhantomData;
 
-use common::DateTime;
+use fastdivide::DividerU64;
 
 use super::MonotonicallyMappableToU128;
 use crate::RowId;
@@ -112,6 +112,65 @@ 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 {
+    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 {
+    #[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 {
@@ -136,15 +195,17 @@ impl MonotonicallyMappableToU64 for i64 {
     }
 }
 
-impl MonotonicallyMappableToU64 for DateTime {
+impl MonotonicallyMappableToU64 for crate::DateTime {
     #[inline(always)]
     fn to_u64(self) -> u64 {
-        common::i64_to_u64(self.into_timestamp_micros())
+        common::i64_to_u64(self.timestamp_micros)
     }
 
     #[inline(always)]
     fn from_u64(val: u64) -> Self {
-        DateTime::from_timestamp_micros(common::u64_to_i64(val))
+        crate::DateTime {
+            timestamp_micros: common::u64_to_i64(val),
+        }
     }
 }
 
@@ -200,6 +261,13 @@ 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/serialize.rs

@@ -1,19 +1,25 @@
 use std::fmt::Debug;
 use std::io;
-use std::io::Write;
-use std::sync::Arc;
 
-mod compact_space;
+use common::{BinarySerializable, VInt};
 
-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::column_values::compact_space::CompactSpaceCompressor;
+use crate::column_values::U128FastFieldCodecType;
 use crate::iterable::Iterable;
-use crate::{ColumnValues, MonotonicallyMappableToU128};
+use crate::MonotonicallyMappableToU128;
+
+/// The normalized header gives some parameters after applying the following
+/// normalization of the vector:
+/// `val -> (val - min_value) / gcd`
+///
+/// By design, after normalization, `min_value = 0` and `gcd = 1`.
+#[derive(Debug, Copy, Clone)]
+pub struct NormalizedHeader {
+    /// The number of values in the underlying column.
+    pub num_vals: u32,
+    /// The max value of the underlying column.
+    pub max_value: u64,
+}
 
 #[derive(Debug, Copy, Clone, PartialEq, Eq)]
 pub(crate) struct U128Header {
@@ -62,52 +68,6 @@ 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/stats.rs

@@ -6,28 +6,21 @@ use common::{BinarySerializable, VInt};
 
 use crate::RowId;
 
-/// Column statistics.
 #[derive(Debug, Clone, Eq, PartialEq)]
-pub struct ColumnStats {
-    /// GCD of the elements `el - min(column)`.
+pub struct Stats {
     pub gcd: NonZeroU64,
-    /// Minimum value of the column.
     pub min_value: u64,
-    /// Maximum value of the column.
     pub max_value: u64,
-    /// Number of rows in the column.
     pub num_rows: RowId,
 }
 
-impl ColumnStats {
-    /// Amplitude of value.
-    /// Difference between the maximum and the minimum value.
+impl Stats {
     pub fn amplitude(&self) -> u64 {
         self.max_value - self.min_value
     }
 }
 
-impl BinarySerializable for ColumnStats {
+impl BinarySerializable for Stats {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
         VInt(self.min_value).serialize(writer)?;
         VInt(self.gcd.get()).serialize(writer)?;
@@ -44,7 +37,7 @@ impl BinarySerializable for ColumnStats {
         let amplitude = VInt::deserialize(reader)?.0 * gcd.get();
         let max_value = min_value + amplitude;
         let num_rows = VInt::deserialize(reader)?.0 as RowId;
-        Ok(ColumnStats {
+        Ok(Stats {
             min_value,
             max_value,
             num_rows,
@@ -59,21 +52,21 @@ mod tests {
 
     use common::BinarySerializable;
 
-    use crate::column_values::ColumnStats;
+    use crate::column_values::Stats;
 
     #[track_caller]
-    fn test_stats_ser_deser_aux(stats: &ColumnStats, num_bytes: usize) {
+    fn test_stats_ser_deser_aux(stats: &Stats, num_bytes: usize) {
         let mut buffer: Vec<u8> = Vec::new();
         stats.serialize(&mut buffer).unwrap();
         assert_eq!(buffer.len(), num_bytes);
-        let deser_stats = ColumnStats::deserialize(&mut &buffer[..]).unwrap();
+        let deser_stats = Stats::deserialize(&mut &buffer[..]).unwrap();
         assert_eq!(stats, &deser_stats);
     }
 
     #[test]
     fn test_stats_serialization() {
         test_stats_ser_deser_aux(
-            &(ColumnStats {
+            &(Stats {
                 gcd: NonZeroU64::new(3).unwrap(),
                 min_value: 1,
                 max_value: 3001,
@@ -82,7 +75,7 @@ mod tests {
             5,
         );
         test_stats_ser_deser_aux(
-            &(ColumnStats {
+            &(Stats {
                 gcd: NonZeroU64::new(1_000).unwrap(),
                 min_value: 1,
                 max_value: 3001,
@@ -91,7 +84,7 @@ mod tests {
             5,
         );
         test_stats_ser_deser_aux(
-            &(ColumnStats {
+            &(Stats {
                 gcd: NonZeroU64::new(1).unwrap(),
                 min_value: 0,
                 max_value: 0,

columnar/src/column_values/u64_based/bitpacked.rs

@@ -4,7 +4,7 @@ use common::{BinarySerializable, OwnedBytes};
 use fastdivide::DividerU64;
 use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
 
-use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, ColumnStats};
+use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
 use crate::{ColumnValues, RowId};
 
 /// Depending on the field type, a different
@@ -13,7 +13,7 @@ use crate::{ColumnValues, RowId};
 pub struct BitpackedReader {
     data: OwnedBytes,
     bit_unpacker: BitUnpacker,
-    stats: ColumnStats,
+    stats: Stats,
 }
 
 impl ColumnValues for BitpackedReader {
@@ -36,7 +36,7 @@ impl ColumnValues for BitpackedReader {
     }
 }
 
-fn num_bits(stats: &ColumnStats) -> u8 {
+fn num_bits(stats: &Stats) -> u8 {
     compute_num_bits(stats.amplitude() / stats.gcd)
 }
 
@@ -46,14 +46,14 @@ pub struct BitpackedCodecEstimator;
 impl ColumnCodecEstimator for BitpackedCodecEstimator {
     fn collect(&mut self, _value: u64) {}
 
-    fn estimate(&self, stats: &ColumnStats) -> Option<u64> {
+    fn estimate(&self, stats: &Stats) -> Option<u64> {
         let num_bits_per_value = num_bits(stats);
         Some(stats.num_bytes() + (stats.num_rows as u64 * (num_bits_per_value as u64) + 7) / 8)
     }
 
     fn serialize(
         &self,
-        stats: &ColumnStats,
+        stats: &Stats,
         vals: &mut dyn Iterator<Item = u64>,
         wrt: &mut dyn Write,
     ) -> io::Result<()> {
@@ -72,12 +72,12 @@ impl ColumnCodecEstimator for BitpackedCodecEstimator {
 pub struct BitpackedCodec;
 
 impl ColumnCodec for BitpackedCodec {
-    type ColumnValues = BitpackedReader;
+    type Reader = BitpackedReader;
     type Estimator = BitpackedCodecEstimator;
 
     /// Opens a fast field given a file.
-    fn load(mut data: OwnedBytes) -> io::Result<Self::ColumnValues> {
-        let stats = ColumnStats::deserialize(&mut data)?;
+    fn load(mut data: OwnedBytes) -> io::Result<Self::Reader> {
+        let stats = Stats::deserialize(&mut data)?;
         let num_bits = num_bits(&stats);
         let bit_unpacker = BitUnpacker::new(num_bits);
         Ok(BitpackedReader {

columnar/src/column_values/u64_based/blockwise_linear.rs

@@ -7,7 +7,7 @@ use fastdivide::DividerU64;
 use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
 
 use crate::column_values::u64_based::line::Line;
-use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, ColumnStats};
+use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
 use crate::column_values::{ColumnValues, VecColumn};
 use crate::MonotonicallyMappableToU64;
 
@@ -84,7 +84,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
             self.block.clear();
         }
     }
-    fn estimate(&self, stats: &ColumnStats) -> Option<u64> {
+    fn estimate(&self, stats: &Stats) -> Option<u64> {
         let mut estimate = 4 + stats.num_bytes() + self.meta_num_bytes + self.values_num_bytes;
         if stats.gcd.get() > 1 {
             let estimate_gain_from_gcd =
@@ -100,7 +100,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
 
     fn serialize(
         &self,
-        stats: &ColumnStats,
+        stats: &Stats,
         mut vals: &mut dyn Iterator<Item = u64>,
         wrt: &mut dyn Write,
     ) -> io::Result<()> {
@@ -165,12 +165,12 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
 pub struct BlockwiseLinearCodec;
 
 impl ColumnCodec<u64> for BlockwiseLinearCodec {
-    type ColumnValues = BlockwiseLinearReader;
+    type Reader = BlockwiseLinearReader;
 
     type Estimator = BlockwiseLinearEstimator;
 
-    fn load(mut bytes: OwnedBytes) -> io::Result<Self::ColumnValues> {
-        let stats = ColumnStats::deserialize(&mut bytes)?;
+    fn load(mut bytes: OwnedBytes) -> io::Result<Self::Reader> {
+        let stats = Stats::deserialize(&mut bytes)?;
         let footer_len: u32 = (&bytes[bytes.len() - 4..]).deserialize()?;
         let footer_offset = bytes.len() - 4 - footer_len as usize;
         let (data, mut footer) = bytes.split(footer_offset);
@@ -195,14 +195,14 @@ impl ColumnCodec<u64> for BlockwiseLinearCodec {
 pub struct BlockwiseLinearReader {
     blocks: Arc<[Block]>,
     data: OwnedBytes,
-    stats: ColumnStats,
+    stats: Stats,
 }
 
 impl ColumnValues for BlockwiseLinearReader {
     #[inline(always)]
     fn get_val(&self, idx: u32) -> u64 {
-        let block_id = (idx / BLOCK_SIZE) as usize;
-        let idx_within_block = idx % BLOCK_SIZE;
+        let block_id = (idx / BLOCK_SIZE as u32) as usize;
+        let idx_within_block = idx % (BLOCK_SIZE as u32);
         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/linear.rs

@@ -5,7 +5,7 @@ use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
 
 use super::line::Line;
 use super::ColumnValues;
-use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, ColumnStats};
+use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
 use crate::column_values::VecColumn;
 use crate::RowId;
 
@@ -18,7 +18,7 @@ const LINE_ESTIMATION_BLOCK_LEN: usize = 512;
 pub struct LinearReader {
     data: OwnedBytes,
     linear_params: LinearParams,
-    stats: ColumnStats,
+    stats: Stats,
 }
 
 impl ColumnValues for LinearReader {
@@ -106,7 +106,7 @@ impl ColumnCodecEstimator for LinearCodecEstimator {
         }
     }
 
-    fn estimate(&self, stats: &ColumnStats) -> Option<u64> {
+    fn estimate(&self, stats: &Stats) -> Option<u64> {
         let line = self.line?;
         let amplitude = self.max_deviation - self.min_deviation;
         let num_bits = compute_num_bits(amplitude);
@@ -123,7 +123,7 @@ impl ColumnCodecEstimator for LinearCodecEstimator {
 
     fn serialize(
         &self,
-        stats: &ColumnStats,
+        stats: &Stats,
         vals: &mut dyn Iterator<Item = u64>,
         wrt: &mut dyn io::Write,
     ) -> io::Result<()> {
@@ -184,12 +184,12 @@ impl LinearCodecEstimator {
 }
 
 impl ColumnCodec for LinearCodec {
-    type ColumnValues = LinearReader;
+    type Reader = LinearReader;
 
     type Estimator = LinearCodecEstimator;
 
-    fn load(mut data: OwnedBytes) -> io::Result<Self::ColumnValues> {
-        let stats = ColumnStats::deserialize(&mut data)?;
+    fn load(mut data: OwnedBytes) -> io::Result<Self::Reader> {
+        let stats = Stats::deserialize(&mut data)?;
         let linear_params = LinearParams::deserialize(&mut data)?;
         Ok(LinearReader {
             stats,

columnar/src/column_values/u64_based/mod.rs

@@ -13,61 +13,35 @@ use common::{BinarySerializable, OwnedBytes};
 use crate::column_values::monotonic_mapping::{
     StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
 };
-pub use crate::column_values::u64_based::bitpacked::BitpackedCodec;
-pub use crate::column_values::u64_based::blockwise_linear::BlockwiseLinearCodec;
-pub use crate::column_values::u64_based::linear::LinearCodec;
-pub use crate::column_values::u64_based::stats_collector::StatsCollector;
-use crate::column_values::{monotonic_map_column, ColumnStats};
+use crate::column_values::u64_based::bitpacked::BitpackedCodec;
+use crate::column_values::u64_based::blockwise_linear::BlockwiseLinearCodec;
+use crate::column_values::u64_based::linear::LinearCodec;
+use crate::column_values::u64_based::stats_collector::StatsCollector;
+use crate::column_values::{monotonic_map_column, Stats};
 use crate::iterable::Iterable;
 use crate::{ColumnValues, MonotonicallyMappableToU64};
 
-/// A `ColumnCodecEstimator` is in charge of gathering all
-/// data required to serialize a column.
-///
-/// This happens during a first pass on data of the column elements.
-/// During that pass, all column estimators receive a call to their
-/// `.collect(el)`.
-///
-/// After this first pass, finalize is called.
-/// `.estimate(..)` then should return an accurate estimation of the
-/// size of the serialized column (were we to pick this codec.).
-/// `.serialize(..)` then serializes the column using this codec.
 pub trait ColumnCodecEstimator<T = u64>: 'static {
-    /// Records a new value for estimation.
-    /// This method will be called for each element of the column during
-    /// `estimation`.
     fn collect(&mut self, value: u64);
-    /// Finalizes the first pass phase.
+    fn estimate(&self, stats: &Stats) -> Option<u64>;
     fn finalize(&mut self) {}
-    /// Returns an accurate estimation of the number of bytes that will
-    /// be used to represent this column.
-    fn estimate(&self, stats: &ColumnStats) -> Option<u64>;
-    /// Serializes the column using the given codec.
-    /// This constitutes a second pass over the columns values.
     fn serialize(
         &self,
-        stats: &ColumnStats,
+        stats: &Stats,
         vals: &mut dyn Iterator<Item = T>,
         wrt: &mut dyn io::Write,
     ) -> io::Result<()>;
 }
 
-/// A column codec describes a colunm serialization format.
 pub trait ColumnCodec<T: PartialOrd = u64> {
-    /// Specialized `ColumnValues` type.
-    type ColumnValues: ColumnValues<T> + 'static;
-    /// `Estimator` for the given codec.
+    type Reader: ColumnValues<T> + 'static;
     type Estimator: ColumnCodecEstimator + Default;
 
-    /// Loads a column that has been serialized using this codec.
-    fn load(bytes: OwnedBytes) -> io::Result<Self::ColumnValues>;
+    fn load(bytes: OwnedBytes) -> io::Result<Self::Reader>;
 
-    /// Returns an estimator.
     fn estimator() -> Self::Estimator {
         Self::Estimator::default()
     }
-
-    /// Returns a boxed estimator.
     fn boxed_estimator() -> Box<dyn ColumnCodecEstimator> {
         Box::new(Self::estimator())
     }
@@ -88,7 +62,6 @@ pub enum CodecType {
     BlockwiseLinear = 2u8,
 }
 
-/// List of all available u64-base codecs.
 pub const ALL_U64_CODEC_TYPES: [CodecType; 3] = [
     CodecType::Bitpacked,
     CodecType::Linear,
@@ -133,7 +106,6 @@ fn load_specific_codec<C: ColumnCodec, T: MonotonicallyMappableToU64>(
 }
 
 impl CodecType {
-    /// Returns a boxed codec estimator associated to a given `CodecType`.
     pub fn estimator(&self) -> Box<dyn ColumnCodecEstimator> {
         match self {
             CodecType::Bitpacked => BitpackedCodec::boxed_estimator(),
@@ -143,8 +115,7 @@ impl CodecType {
     }
 }
 
-/// Serializes a given column of u64-mapped values.
-pub fn serialize_u64_based_column_values<T: MonotonicallyMappableToU64>(
+pub fn serialize_u64_based_column_values<'a, T: MonotonicallyMappableToU64>(
     vals: &dyn Iterable<T>,
     codec_types: &[CodecType],
     wrt: &mut dyn Write,
@@ -185,14 +156,11 @@ pub fn serialize_u64_based_column_values<T: MonotonicallyMappableToU64>(
     Ok(())
 }
 
-/// Load u64-based column values.
-///
-/// This method first identifies the codec off the first byte.
 pub fn load_u64_based_column_values<T: MonotonicallyMappableToU64>(
     mut bytes: OwnedBytes,
 ) -> io::Result<Arc<dyn ColumnValues<T>>> {
     let codec_type: CodecType = bytes
-        .first()
+        .get(0)
         .copied()
         .and_then(CodecType::try_from_code)
         .ok_or_else(|| io::Error::new(io::ErrorKind::InvalidData, "Failed to read codec type"))?;

columnar/src/column_values/u64_based/stats_collector.rs

@@ -2,7 +2,7 @@ use std::num::NonZeroU64;
 
 use fastdivide::DividerU64;
 
-use crate::column_values::ColumnStats;
+use crate::column_values::Stats;
 use crate::RowId;
 
 /// Compute the gcd of two non null numbers.
@@ -33,14 +33,14 @@ pub struct StatsCollector {
 }
 
 impl StatsCollector {
-    pub fn stats(&self) -> ColumnStats {
+    pub fn stats(&self) -> Stats {
         let (min_value, max_value) = self.min_max_opt.unwrap_or((0u64, 0u64));
         let increment_gcd = if let Some((increment_gcd, _)) = self.increment_gcd_opt {
             increment_gcd
         } else {
             NonZeroU64::new(1u64).unwrap()
         };
-        ColumnStats {
+        Stats {
             min_value,
             max_value,
             num_rows: self.num_rows,
@@ -97,9 +97,9 @@ mod tests {
     use std::num::NonZeroU64;
 
     use crate::column_values::u64_based::stats_collector::{compute_gcd, StatsCollector};
-    use crate::column_values::u64_based::ColumnStats;
+    use crate::column_values::u64_based::Stats;
 
-    fn compute_stats(vals: impl Iterator<Item = u64>) -> ColumnStats {
+    fn compute_stats(vals: impl Iterator<Item = u64>) -> Stats {
         let mut stats_collector = StatsCollector::default();
         for val in vals {
             stats_collector.collect(val);
@@ -144,7 +144,7 @@ mod tests {
     fn test_stats() {
         assert_eq!(
             compute_stats([].into_iter()),
-            ColumnStats {
+            Stats {
                 gcd: NonZeroU64::new(1).unwrap(),
                 min_value: 0,
                 max_value: 0,
@@ -153,7 +153,7 @@ mod tests {
         );
         assert_eq!(
             compute_stats([0, 1].into_iter()),
-            ColumnStats {
+            Stats {
                 gcd: NonZeroU64::new(1).unwrap(),
                 min_value: 0,
                 max_value: 1,
@@ -162,7 +162,7 @@ mod tests {
         );
         assert_eq!(
             compute_stats([0, 1].into_iter()),
-            ColumnStats {
+            Stats {
                 gcd: NonZeroU64::new(1).unwrap(),
                 min_value: 0,
                 max_value: 1,
@@ -171,7 +171,7 @@ mod tests {
         );
         assert_eq!(
             compute_stats([10, 20, 30].into_iter()),
-            ColumnStats {
+            Stats {
                 gcd: NonZeroU64::new(10).unwrap(),
                 min_value: 10,
                 max_value: 30,
@@ -180,7 +180,7 @@ mod tests {
         );
         assert_eq!(
             compute_stats([10, 50, 10, 30].into_iter()),
-            ColumnStats {
+            Stats {
                 gcd: NonZeroU64::new(20).unwrap(),
                 min_value: 10,
                 max_value: 50,
@@ -189,7 +189,7 @@ mod tests {
         );
         assert_eq!(
             compute_stats([10, 0, 30].into_iter()),
-            ColumnStats {
+            Stats {
                 gcd: NonZeroU64::new(10).unwrap(),
                 min_value: 0,
                 max_value: 30,

columnar/src/column_values/u64_based/tests.rs

@@ -19,62 +19,6 @@ 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,
@@ -99,28 +43,14 @@ pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
 
     let reader = TColumnCodec::load(OwnedBytes::new(buffer)).unwrap();
     assert_eq!(reader.num_vals(), vals.len() as u32);
-    let mut buffer = Vec::new();
     for (doc, orig_val) in vals.iter().copied().enumerate() {
         let val = reader.get_val(doc as u32);
         assert_eq!(
             val, orig_val,
             "val `{val}` does not match orig_val {orig_val:?}, in data set {name}, data `{vals:?}`",
         );
-
-        buffer.resize(1, 0);
-        reader.get_vals(&[doc as u32], &mut buffer);
-        let val = buffer[0];
-        assert_eq!(
-            val, orig_val,
-            "val `{val}` does not match orig_val {orig_val:?}, in data set {name}, data `{vals:?}`",
-        );
     }
 
-    let all_docs: Vec<u32> = (0..vals.len() as u32).collect();
-    buffer.resize(all_docs.len(), 0);
-    reader.get_vals(&all_docs, &mut buffer);
-    assert_eq!(vals, buffer);
-
     if !vals.is_empty() {
         let test_rand_idx = rand::thread_rng().gen_range(0..=vals.len() - 1);
         let expected_positions: Vec<u32> = vals
@@ -130,7 +60,7 @@ pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
             .map(|(pos, _)| pos as u32)
             .collect();
         let mut positions = Vec::new();
-        reader.get_row_ids_for_value_range(
+        reader.get_docids_for_value_range(
             vals[test_rand_idx]..=vals[test_rand_idx],
             0..vals.len() as u32,
             &mut positions,

columnar/src/column_values/vec_column.rs

@@ -1,52 +0,0 @@
-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

@@ -1,14 +1,12 @@
 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, Serialize, Deserialize)]
+#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy, Ord, PartialOrd)]
 #[repr(u8)]
 pub enum ColumnType {
     I64 = 0u8,
@@ -113,7 +111,7 @@ impl HasAssociatedColumnType for bool {
     }
 }
 
-impl HasAssociatedColumnType for common::DateTime {
+impl HasAssociatedColumnType for crate::DateTime {
     fn column_type() -> ColumnType {
         ColumnType::DateTime
     }
@@ -145,7 +143,7 @@ mod tests {
             }
         }
         for code in COLUMN_TYPES.len() as u8..=u8::MAX {
-            assert!(ColumnType::try_from_code(code).is_err());
+            assert!(ColumnType::try_from_code(code as u8).is_err());
         }
     }
 

columnar/src/columnar/format_version.rs

@@ -4,7 +4,7 @@ pub const VERSION_FOOTER_NUM_BYTES: usize = MAGIC_BYTES.len() + std::mem::size_o
 
 /// We end the file by these 4 bytes just to somewhat identify that
 /// this is indeed a columnar file.
-const MAGIC_BYTES: [u8; 4] = [2, 113, 119, 66];
+const MAGIC_BYTES: [u8; 4] = [2, 113, 119, 066];
 
 pub fn footer() -> [u8; VERSION_FOOTER_NUM_BYTES] {
     let mut footer_bytes = [0u8; VERSION_FOOTER_NUM_BYTES];
@@ -27,8 +27,8 @@ pub enum Version {
 }
 
 impl Version {
-    fn to_bytes(self) -> [u8; 4] {
-        (self as u32).to_le_bytes()
+    fn to_bytes(&self) -> [u8; 4] {
+        (*self as u32).to_le_bytes()
     }
 
     fn try_from_bytes(bytes: [u8; 4]) -> Result<Version, InvalidData> {

columnar/src/columnar/merge/merge_dict_column.rs

@@ -52,18 +52,21 @@ impl<'a> Iterable for RemappedTermOrdinalsValues<'a> {
 
 impl<'a> RemappedTermOrdinalsValues<'a> {
     fn boxed_iter_stacked(&self) -> Box<dyn Iterator<Item = u64> + '_> {
-        let iter = self.bytes_columns.iter().flatten().enumerate().flat_map(
-            move |(seg_ord_with_column, bytes_column)| {
-                let term_ord_after_merge_mapping = self
-                    .term_ord_mapping
-                    .get_segment(seg_ord_with_column as u32);
-                bytes_column
-                    .ords()
-                    .values
-                    .iter()
-                    .map(move |term_ord| term_ord_after_merge_mapping[term_ord as usize])
-            },
-        );
+        let iter = self
+            .bytes_columns
+            .iter()
+            .enumerate()
+            .flat_map(|(segment_ord, byte_column)| {
+                let segment_ord = self.term_ord_mapping.get_segment(segment_ord as u32);
+                byte_column.into_iter().flat_map(move |bytes_column| {
+                    bytes_column
+                        .ords()
+                        .values
+                        .iter()
+                        .map(move |term_ord| segment_ord[term_ord as usize])
+                })
+            });
+        // TODO see if we can better decompose the mapping / and the stacking
         Box::new(iter)
     }
 
@@ -93,7 +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_for_doc(row_id) {
+        for term_ord in column.term_ord_column.values(row_id) {
             term_bitset.insert(term_ord as u32);
         }
     }
@@ -130,6 +133,7 @@ fn serialize_merged_dict(
     let mut merged_terms = TermMerger::new(field_term_streams);
     let mut sstable_builder = sstable::VoidSSTable::writer(output);
 
+    // TODO support complex `merge_row_order`.
     match merge_row_order {
         MergeRowOrder::Stack(_) => {
             let mut current_term_ord = 0;
@@ -187,7 +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]);
+            .push(vec![TermOrdinal::default(); max_term_ord as usize]);
     }
 
     fn register_from_to(&mut self, segment_ord: usize, from_ord: TermOrdinal, to_ord: TermOrdinal) {

columnar/src/columnar/merge/mod.rs

@@ -2,6 +2,8 @@ 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;
@@ -52,34 +54,14 @@ 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, required_columns)?;
+    let columns_to_merge = group_columns_for_merge(columnar_readers)?;
     for ((column_name, column_type), columns) in columns_to_merge {
         let mut column_serializer =
             serializer.serialize_column(column_name.as_bytes(), column_type);
@@ -192,183 +174,97 @@ 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), GroupedColumns> = HashMap::new();
+    let mut columns_grouped: HashMap<(String, ColumnTypeCategory), Vec<Option<DynamicColumn>>> =
+        HashMap::new();
 
-    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)?;
-    }
+    let num_columnars = columnar_readers.len();
 
     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_category: ColumnTypeCategory = handle.column_type().into();
+            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 = handle.open()?;
-            columns_grouped
-                .entry((column_name, column_category))
-                .or_insert_with(|| {
-                    GroupedColumns::for_category(column_category, columnar_readers.len())
-                })
-                .set_column(columnar_id, column);
+            columns[columnar_id] = Some(column);
         }
     }
 
     let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        Default::default();
+        BTreeMap::default();
 
-    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);
+    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);
     }
 
     Ok(merge_columns)
 }
 
-fn coerce_columns(
-    column_type: ColumnType,
-    columns: &mut [Option<DynamicColumn>],
-) -> io::Result<()> {
+/// 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();
     for column_opt in columns.iter_mut() {
         if let Some(column) = column_opt.take() {
-            *column_opt = Some(coerce_column(column_type, column)?);
+            *column_opt = column.coerce_numerical(coerce_type);
         }
     }
-    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

@@ -0,0 +1,107 @@
+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)));
 }
@@ -44,74 +44,17 @@ 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)));
     {
@@ -153,24 +96,20 @@ fn make_numerical_columnar_multiple_columns(
     ColumnarReader::open(buffer).unwrap()
 }
 
-#[track_caller]
-fn make_byte_columnar_multiple_columns(
-    columns: &[(&str, &[&[&[u8]]])],
-    num_rows: u32,
-) -> ColumnarReader {
+fn make_byte_columnar_multiple_columns(columns: &[(&str, &[&[&[u8]]])]) -> ColumnarReader {
     let mut dataframe_writer = ColumnarWriter::default();
     for (column_name, column_values) in columns {
-        assert_eq!(
-            column_values.len(),
-            num_rows as usize,
-            "All columns must have `{num_rows}` rows"
-        );
         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);
             }
         }
     }
+    let num_rows = columns
+        .iter()
+        .map(|(_, val_rows)| val_rows.len() as RowId)
+        .max()
+        .unwrap_or(0u32);
     let mut buffer: Vec<u8> = Vec::new();
     dataframe_writer
         .serialize(num_rows, None, &mut buffer)
@@ -183,7 +122,7 @@ 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);
             }
         }
     }
@@ -212,7 +151,6 @@ fn test_merge_columnar_numbers() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
-        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -238,7 +176,6 @@ fn test_merge_columnar_texts() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
-        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -276,14 +213,13 @@ fn test_merge_columnar_texts() {
 
 #[test]
 fn test_merge_columnar_byte() {
-    let columnar1 = make_byte_columnar_multiple_columns(&[("bytes", &[&[b"bbbb"], &[b"baaa"]])], 2);
-    let columnar2 = make_byte_columnar_multiple_columns(&[("bytes", &[&[], &[b"a"]])], 2);
+    let columnar1 = make_byte_columnar_multiple_columns(&[("bytes", &[&[b"bbbb"], &[b"baaa"]])]);
+    let columnar2 = make_byte_columnar_multiple_columns(&[("bytes", &[&[], &[b"a"]])]);
     let mut buffer = Vec::new();
     let columnars = &[&columnar1, &columnar2];
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
-        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -320,59 +256,3 @@ fn test_merge_columnar_byte() {
     assert_eq!(get_bytes_for_row(2), b"");
     assert_eq!(get_bytes_for_row(3), b"a");
 }
-
-#[test]
-fn test_merge_columnar_byte_with_missing() {
-    let columnar1 = make_byte_columnar_multiple_columns(&[], 3);
-    let columnar2 = make_byte_columnar_multiple_columns(&[("col", &[&[b"b"], &[]])], 2);
-    let columnar3 = make_byte_columnar_multiple_columns(
-        &[
-            ("col", &[&[], &[b"b"], &[b"a", b"b"]]),
-            ("col2", &[&[b"hello"], &[], &[b"a", b"b"]]),
-        ],
-        3,
-    );
-    let mut buffer = Vec::new();
-    let columnars = &[&columnar1, &columnar2, &columnar3];
-    let stack_merge_order = StackMergeOrder::stack(columnars);
-    crate::columnar::merge_columnar(
-        columnars,
-        &[],
-        MergeRowOrder::Stack(stack_merge_order),
-        &mut buffer,
-    )
-    .unwrap();
-    let columnar_reader = ColumnarReader::open(buffer).unwrap();
-    assert_eq!(columnar_reader.num_rows(), 3 + 2 + 3);
-    assert_eq!(columnar_reader.num_columns(), 2);
-    let cols = columnar_reader.read_columns("col").unwrap();
-    let dynamic_column = cols[0].open().unwrap();
-    let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
-    let get_bytes_for_ord = |ord| {
-        let mut out = Vec::new();
-        vals.ord_to_bytes(ord, &mut out).unwrap();
-        out
-    };
-    assert_eq!(vals.dictionary.num_terms(), 2);
-    assert_eq!(get_bytes_for_ord(0), b"a");
-    assert_eq!(get_bytes_for_ord(1), b"b");
-    let get_bytes_for_row = |row_id| {
-        let terms: Vec<Vec<u8>> = vals
-            .term_ords(row_id)
-            .map(|term_ord| {
-                let mut out = Vec::new();
-                vals.ord_to_bytes(term_ord, &mut out).unwrap();
-                out
-            })
-            .collect();
-        terms
-    };
-    assert!(get_bytes_for_row(0).is_empty());
-    assert!(get_bytes_for_row(1).is_empty());
-    assert!(get_bytes_for_row(2).is_empty());
-    assert_eq!(get_bytes_for_row(3), vec![b"b".to_vec()]);
-    assert!(get_bytes_for_row(4).is_empty());
-    assert!(get_bytes_for_row(5).is_empty());
-    assert_eq!(get_bytes_for_row(6), vec![b"b".to_vec()]);
-    assert_eq!(get_bytes_for_row(7), vec![b"a".to_vec(), b"b".to_vec()]);
-}

columnar/src/columnar/merge_index.rs

@@ -0,0 +1 @@
+

columnar/src/columnar/mod.rs

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

columnar/src/columnar/reader/mod.rs

@@ -21,32 +21,6 @@ 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>
@@ -102,7 +76,11 @@ impl ColumnarReader {
         Ok(results)
     }
 
-    fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {
+    /// 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>> {
         // Each column is a associated to a given `column_key`,
         // that starts by `column_name\0column_header`.
         //
@@ -111,35 +89,36 @@ 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 dictionary.
+
+        // TODO can we get some more generic `prefix(..)` logic in the dictioanry.
         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);
-        self.column_dictionary
+        let mut stream = self
+            .column_dictionary
             .range()
             .ge(start_key.as_bytes())
             .lt(end_key.as_bytes())
-    }
-
-    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)
+            .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)
     }
 
     /// Return the number of columns in the columnar.
@@ -183,7 +162,7 @@ mod tests {
     }
 
     #[test]
-    #[should_panic(expected = "Input type forbidden")]
+    #[should_panic(expect = "Input type forbidden")]
     fn test_list_columns_strict_typing_panics_on_wrong_types() {
         let mut columnar_writer = ColumnarWriter::default();
         columnar_writer.record_column_type("count", ColumnType::U64, false);

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(), buffer.len());
+        assert_eq!(bytes.len() + buf.as_ref().len() as usize, 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() }, expected_len);
+        assert_eq!(minibuf.as_ref().len() as usize, 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

@@ -47,7 +47,6 @@ struct SpareBuffers {
 /// let mut wrt: Vec<u8> =  Vec::new();
 /// columnar_writer.serialize(2u32, None, &mut wrt).unwrap();
 /// ```
-#[derive(Default)]
 pub struct ColumnarWriter {
     numerical_field_hash_map: ArenaHashMap,
     datetime_field_hash_map: ArenaHashMap,
@@ -61,6 +60,22 @@ pub struct ColumnarWriter {
     buffers: SpareBuffers,
 }
 
+impl Default for ColumnarWriter {
+    fn default() -> Self {
+        ColumnarWriter {
+            numerical_field_hash_map: ArenaHashMap::new(10_000),
+            bool_field_hash_map: ArenaHashMap::new(10_000),
+            ip_addr_field_hash_map: ArenaHashMap::new(10_000),
+            bytes_field_hash_map: ArenaHashMap::new(10_000),
+            str_field_hash_map: ArenaHashMap::new(10_000),
+            datetime_field_hash_map: ArenaHashMap::new(10_000),
+            dictionaries: Vec::new(),
+            arena: MemoryArena::default(),
+            buffers: SpareBuffers::default(),
+        }
+    }
+}
+
 #[inline]
 fn mutate_or_create_column<V, TMutator>(
     arena_hash_map: &mut ArenaHashMap,
@@ -251,15 +266,11 @@ impl ColumnarWriter {
         });
     }
 
-    pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: common::DateTime) {
+    pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: crate::DateTime) {
         let (hash_map, arena) = (&mut self.datetime_field_hash_map, &mut self.arena);
         mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
             let mut column: ColumnWriter = column_opt.unwrap_or_default();
-            column.record(
-                doc,
-                NumericalValue::I64(datetime.into_timestamp_micros()),
-                arena,
-            );
+            column.record(doc, NumericalValue::I64(datetime.timestamp_micros), arena);
             column
         });
     }
@@ -656,7 +667,7 @@ where
     Ok(())
 }
 
-fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut [u64]) {
+fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut Vec<u64>) {
     let mut start_index: usize = 0;
     for end_index in multivalued_index.iter().copied() {
         let end_index = end_index as usize;
@@ -761,7 +772,7 @@ 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(&arena, None, &mut buffer)
+            .operation_iterator(&mut arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 6);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -790,7 +801,7 @@ 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(&arena, None, &mut buffer)
+            .operation_iterator(&mut arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 4);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
@@ -813,7 +824,7 @@ 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(&arena, None, &mut buffer)
+            .operation_iterator(&mut arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 2);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -832,7 +843,7 @@ 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(&arena, None, &mut buffer)
+            .operation_iterator(&mut arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 3);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));

columnar/src/columnar/writer/value_index.rs

@@ -29,7 +29,7 @@ pub struct OptionalIndexBuilder {
 }
 
 impl OptionalIndexBuilder {
-    pub fn finish(&mut self, num_rows: RowId) -> impl Iterable<RowId> + '_ {
+    pub fn finish<'a>(&'a mut self, num_rows: RowId) -> impl Iterable<RowId> + 'a {
         debug_assert!(self
             .docs
             .last()
@@ -150,7 +150,11 @@ mod tests {
         multivalued_value_index_builder.record_row(2u32);
         multivalued_value_index_builder.record_value();
         assert_eq!(
-            multivalued_value_index_builder.finish(4u32).to_vec(),
+            multivalued_value_index_builder
+                .finish(4u32)
+                .iter()
+                .copied()
+                .collect::<Vec<u32>>(),
             vec![0, 0, 2, 3, 3]
         );
         multivalued_value_index_builder.reset();
@@ -158,7 +162,11 @@ mod tests {
         multivalued_value_index_builder.record_value();
         multivalued_value_index_builder.record_value();
         assert_eq!(
-            multivalued_value_index_builder.finish(4u32).to_vec(),
+            multivalued_value_index_builder
+                .finish(4u32)
+                .iter()
+                .copied()
+                .collect::<Vec<u32>>(),
             vec![0, 0, 0, 2, 2]
         );
     }

columnar/src/dynamic_column.rs

@@ -3,12 +3,12 @@ use std::net::Ipv6Addr;
 use std::sync::Arc;
 
 use common::file_slice::FileSlice;
-use common::{ByteCount, DateTime, HasLen, OwnedBytes};
+use common::{HasLen, OwnedBytes};
 
 use crate::column::{BytesColumn, Column, StrColumn};
 use crate::column_values::{monotonic_map_column, StrictlyMonotonicFn};
 use crate::columnar::ColumnType;
-use crate::{Cardinality, NumericalType};
+use crate::{Cardinality, DateTime, NumericalType};
 
 #[derive(Clone)]
 pub enum DynamicColumn {
@@ -166,9 +166,9 @@ impl StrictlyMonotonicFn<i64, u64> for MapI64ToU64 {
 
 macro_rules! static_dynamic_conversions {
     ($typ:ty, $enum_name:ident) => {
-        impl From<DynamicColumn> for Option<$typ> {
-            fn from(dynamic_column: DynamicColumn) -> Option<$typ> {
-                if let DynamicColumn::$enum_name(col) = dynamic_column {
+        impl Into<Option<$typ>> for DynamicColumn {
+            fn into(self) -> Option<$typ> {
+                if let DynamicColumn::$enum_name(col) = self {
                     Some(col)
                 } else {
                     None
@@ -188,7 +188,7 @@ static_dynamic_conversions!(Column<bool>, Bool);
 static_dynamic_conversions!(Column<u64>, U64);
 static_dynamic_conversions!(Column<i64>, I64);
 static_dynamic_conversions!(Column<f64>, F64);
-static_dynamic_conversions!(Column<DateTime>, DateTime);
+static_dynamic_conversions!(Column<crate::DateTime>, DateTime);
 static_dynamic_conversions!(StrColumn, Str);
 static_dynamic_conversions!(BytesColumn, Bytes);
 static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
@@ -206,9 +206,10 @@ impl DynamicColumnHandle {
         self.open_internal(column_bytes)
     }
 
-    #[doc(hidden)]
-    pub fn file_slice(&self) -> &FileSlice {
-        &self.file_slice
+    // 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)
     }
 
     /// Returns the `u64` fast field reader reader associated with `fields` of types
@@ -242,14 +243,14 @@ impl DynamicColumnHandle {
             ColumnType::Bool => crate::column::open_column_u64::<bool>(column_bytes)?.into(),
             ColumnType::IpAddr => crate::column::open_column_u128::<Ipv6Addr>(column_bytes)?.into(),
             ColumnType::DateTime => {
-                crate::column::open_column_u64::<DateTime>(column_bytes)?.into()
+                crate::column::open_column_u64::<crate::DateTime>(column_bytes)?.into()
             }
         };
         Ok(dynamic_column)
     }
 
-    pub fn num_bytes(&self) -> ByteCount {
-        self.file_slice.len().into()
+    pub fn num_bytes(&self) -> usize {
+        self.file_slice.len()
     }
 
     pub fn column_type(&self) -> ColumnType {

columnar/src/lib.rs

@@ -32,7 +32,6 @@ pub use value::{NumericalType, NumericalValue};
 pub use self::dynamic_column::{DynamicColumn, DynamicColumnHandle};
 
 pub type RowId = u32;
-pub type DocId = u32;
 
 #[derive(Clone, Copy)]
 pub struct RowAddr {
@@ -43,7 +42,16 @@ pub struct RowAddr {
 pub use sstable::Dictionary;
 pub type Streamer<'a> = sstable::Streamer<'a, VoidSSTable>;
 
-pub use common::DateTime;
+#[derive(Clone, Copy, PartialOrd, PartialEq, Default, Debug)]
+pub struct DateTime {
+    pub timestamp_micros: i64,
+}
+
+impl DateTime {
+    pub fn into_timestamp_micros(self) -> i64 {
+        self.timestamp_micros
+    }
+}
 
 #[derive(Copy, Clone, Debug)]
 pub struct InvalidData;

columnar/src/tests.rs

@@ -75,7 +75,7 @@ fn test_dataframe_writer_u64_multivalued() {
         divisor_col.get_cardinality(),
         crate::Cardinality::Multivalued
     );
-    assert_eq!(divisor_col.num_docs(), 7);
+    assert_eq!(divisor_col.num_rows(), 7);
 }
 
 #[test]

columnar/src/value.rs

@@ -1,5 +1,3 @@
-use common::DateTime;
-
 use crate::InvalidData;
 
 #[derive(Copy, Clone, PartialEq, Debug)]
@@ -106,10 +104,10 @@ impl Coerce for f64 {
     }
 }
 
-impl Coerce for DateTime {
+impl Coerce for crate::DateTime {
     fn coerce(value: NumericalValue) -> Self {
         let timestamp_micros = i64::coerce(value);
-        DateTime::from_timestamp_micros(timestamp_micros)
+        crate::DateTime { timestamp_micros }
     }
 }
 

common/Cargo.toml

@@ -16,8 +16,6 @@ repository = "https://github.com/quickwit-oss/tantivy"
 byteorder = "1.4.3"
 ownedbytes = { version= "0.5", path="../ownedbytes" }
 async-trait = "0.1"
-time = { version = "0.3.10", features = ["serde-well-known"] }
-serde = { version = "1.0.136", features = ["derive"] }
 
 [dev-dependencies]
 proptest = "1.0.0"

common/src/bitset.rs

@@ -4,8 +4,6 @@ use std::{fmt, io, u64};
 
 use ownedbytes::OwnedBytes;
 
-use crate::ByteCount;
-
 #[derive(Clone, Copy, Eq, PartialEq)]
 pub struct TinySet(u64);
 
@@ -388,8 +386,8 @@ impl ReadOnlyBitSet {
     }
 
     /// Number of bytes used in the bitset representation.
-    pub fn num_bytes(&self) -> ByteCount {
-        self.data.len().into()
+    pub fn num_bytes(&self) -> usize {
+        self.data.len()
     }
 }
 

common/src/byte_count.rs

@@ -1,114 +0,0 @@
-use std::iter::Sum;
-use std::ops::{Add, AddAssign};
-
-use serde::{Deserialize, Serialize};
-
-/// Indicates space usage in bytes
-#[derive(Copy, Clone, Default, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize)]
-pub struct ByteCount(u64);
-
-impl std::fmt::Debug for ByteCount {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        f.write_str(&self.human_readable())
-    }
-}
-
-impl std::fmt::Display for ByteCount {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        f.write_str(&self.human_readable())
-    }
-}
-
-const SUFFIX_AND_THRESHOLD: [(&str, u64); 5] = [
-    ("KB", 1_000),
-    ("MB", 1_000_000),
-    ("GB", 1_000_000_000),
-    ("TB", 1_000_000_000_000),
-    ("PB", 1_000_000_000_000_000),
-];
-
-impl ByteCount {
-    #[inline]
-    pub fn get_bytes(&self) -> u64 {
-        self.0
-    }
-
-    pub fn human_readable(&self) -> String {
-        for (suffix, threshold) in SUFFIX_AND_THRESHOLD.iter().rev() {
-            if self.get_bytes() >= *threshold {
-                let unit_num = self.get_bytes() as f64 / *threshold as f64;
-                return format!("{:.2} {}", unit_num, suffix);
-            }
-        }
-        format!("{:.2} B", self.get_bytes())
-    }
-}
-
-impl From<u64> for ByteCount {
-    fn from(value: u64) -> Self {
-        ByteCount(value)
-    }
-}
-impl From<usize> for ByteCount {
-    fn from(value: usize) -> Self {
-        ByteCount(value as u64)
-    }
-}
-
-impl Sum for ByteCount {
-    #[inline]
-    fn sum<I: Iterator<Item = Self>>(iter: I) -> Self {
-        iter.fold(ByteCount::default(), |acc, x| acc + x)
-    }
-}
-
-impl PartialEq<u64> for ByteCount {
-    #[inline]
-    fn eq(&self, other: &u64) -> bool {
-        self.get_bytes() == *other
-    }
-}
-
-impl PartialOrd<u64> for ByteCount {
-    #[inline]
-    fn partial_cmp(&self, other: &u64) -> Option<std::cmp::Ordering> {
-        self.get_bytes().partial_cmp(other)
-    }
-}
-
-impl Add for ByteCount {
-    type Output = Self;
-
-    #[inline]
-    fn add(self, other: Self) -> Self {
-        Self(self.get_bytes() + other.get_bytes())
-    }
-}
-
-impl AddAssign for ByteCount {
-    #[inline]
-    fn add_assign(&mut self, other: Self) {
-        *self = Self(self.get_bytes() + other.get_bytes());
-    }
-}
-
-#[cfg(test)]
-mod test {
-    use crate::ByteCount;
-
-    #[test]
-    fn test_bytes() {
-        assert_eq!(ByteCount::from(0u64).human_readable(), "0 B");
-        assert_eq!(ByteCount::from(300u64).human_readable(), "300 B");
-        assert_eq!(ByteCount::from(1_000_000u64).human_readable(), "1.00 MB");
-        assert_eq!(ByteCount::from(1_500_000u64).human_readable(), "1.50 MB");
-        assert_eq!(
-            ByteCount::from(1_500_000_000u64).human_readable(),
-            "1.50 GB"
-        );
-        assert_eq!(
-            ByteCount::from(3_213_000_000_000u64).human_readable(),
-            "3.21 TB"
-        );
-    }
-}

common/src/datetime.rs

@@ -1,136 +0,0 @@
-use std::fmt;
-
-use serde::{Deserialize, Serialize};
-use time::format_description::well_known::Rfc3339;
-use time::{OffsetDateTime, PrimitiveDateTime, UtcOffset};
-
-/// DateTime Precision
-#[derive(
-    Clone, Copy, Debug, Hash, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize, Default,
-)]
-#[serde(rename_all = "lowercase")]
-pub enum DatePrecision {
-    /// Seconds precision
-    #[default]
-    Seconds,
-    /// Milli-seconds precision.
-    Milliseconds,
-    /// Micro-seconds precision.
-    Microseconds,
-}
-
-/// A date/time value with microsecond precision.
-///
-/// This timestamp does not carry any explicit time zone information.
-/// Users are responsible for applying the provided conversion
-/// functions consistently. Internally the time zone is assumed
-/// to be UTC, which is also used implicitly for JSON serialization.
-///
-/// 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, Hash)]
-pub struct DateTime {
-    // Timestamp in microseconds.
-    pub(crate) timestamp_micros: i64,
-}
-
-impl DateTime {
-    /// Create new from UNIX timestamp in seconds
-    pub const fn from_timestamp_secs(seconds: i64) -> Self {
-        Self {
-            timestamp_micros: seconds * 1_000_000,
-        }
-    }
-
-    /// Create new from UNIX timestamp in milliseconds
-    pub const fn from_timestamp_millis(milliseconds: i64) -> Self {
-        Self {
-            timestamp_micros: milliseconds * 1_000,
-        }
-    }
-
-    /// Create new from UNIX timestamp in microseconds.
-    pub const fn from_timestamp_micros(microseconds: i64) -> Self {
-        Self {
-            timestamp_micros: microseconds,
-        }
-    }
-
-    /// Create new from `OffsetDateTime`
-    ///
-    /// The given date/time is converted to UTC and the actual
-    /// time zone is discarded.
-    pub const fn from_utc(dt: OffsetDateTime) -> Self {
-        let timestamp_micros = dt.unix_timestamp() * 1_000_000 + dt.microsecond() as i64;
-        Self { timestamp_micros }
-    }
-
-    /// Create new from `PrimitiveDateTime`
-    ///
-    /// Implicitly assumes that the given date/time is in UTC!
-    /// Otherwise the original value must only be reobtained with
-    /// [`Self::into_primitive()`].
-    pub fn from_primitive(dt: PrimitiveDateTime) -> Self {
-        Self::from_utc(dt.assume_utc())
-    }
-
-    /// Convert to UNIX timestamp in seconds.
-    pub const fn into_timestamp_secs(self) -> i64 {
-        self.timestamp_micros / 1_000_000
-    }
-
-    /// Convert to UNIX timestamp in milliseconds.
-    pub const fn into_timestamp_millis(self) -> i64 {
-        self.timestamp_micros / 1_000
-    }
-
-    /// Convert to UNIX timestamp in microseconds.
-    pub const fn into_timestamp_micros(self) -> i64 {
-        self.timestamp_micros
-    }
-
-    /// Convert to UTC `OffsetDateTime`
-    pub fn into_utc(self) -> OffsetDateTime {
-        let timestamp_nanos = self.timestamp_micros as i128 * 1000;
-        let utc_datetime = OffsetDateTime::from_unix_timestamp_nanos(timestamp_nanos)
-            .expect("valid UNIX timestamp");
-        debug_assert_eq!(UtcOffset::UTC, utc_datetime.offset());
-        utc_datetime
-    }
-
-    /// Convert to `OffsetDateTime` with the given time zone
-    pub fn into_offset(self, offset: UtcOffset) -> OffsetDateTime {
-        self.into_utc().to_offset(offset)
-    }
-
-    /// Convert to `PrimitiveDateTime` without any time zone
-    ///
-    /// The value should have been constructed with [`Self::from_primitive()`].
-    /// Otherwise the time zone is implicitly assumed to be UTC.
-    pub fn into_primitive(self) -> PrimitiveDateTime {
-        let utc_datetime = self.into_utc();
-        // Discard the UTC time zone offset
-        debug_assert_eq!(UtcOffset::UTC, utc_datetime.offset());
-        PrimitiveDateTime::new(utc_datetime.date(), utc_datetime.time())
-    }
-
-    /// Truncates the microseconds value to the corresponding precision.
-    pub fn truncate(self, precision: DatePrecision) -> Self {
-        let truncated_timestamp_micros = match precision {
-            DatePrecision::Seconds => (self.timestamp_micros / 1_000_000) * 1_000_000,
-            DatePrecision::Milliseconds => (self.timestamp_micros / 1_000) * 1_000,
-            DatePrecision::Microseconds => self.timestamp_micros,
-        };
-        Self {
-            timestamp_micros: truncated_timestamp_micros,
-        }
-    }
-}
-
-impl fmt::Debug for DateTime {
-    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
-        let utc_rfc3339 = self.into_utc().format(&Rfc3339).map_err(|_| fmt::Error)?;
-        f.write_str(&utc_rfc3339)
-    }
-}

common/src/file_slice.rs

@@ -5,7 +5,7 @@ use std::{fmt, io};
 use async_trait::async_trait;
 use ownedbytes::{OwnedBytes, StableDeref};
 
-use crate::{ByteCount, HasLen};
+use crate::HasLen;
 
 /// Objects that represents files sections in tantivy.
 ///
@@ -216,11 +216,6 @@ impl FileSlice {
     pub fn slice_to(&self, to_offset: usize) -> FileSlice {
         self.slice(0..to_offset)
     }
-
-    /// Returns the byte count of the FileSlice.
-    pub fn num_bytes(&self) -> ByteCount {
-        self.range.len().into()
-    }
 }
 
 #[async_trait]

common/src/lib.rs

@@ -5,16 +5,12 @@ use std::ops::Deref;
 pub use byteorder::LittleEndian as Endianness;
 
 mod bitset;
-mod byte_count;
-mod datetime;
 pub mod file_slice;
 mod group_by;
 mod serialize;
 mod vint;
 mod writer;
 pub use bitset::*;
-pub use byte_count::ByteCount;
-pub use datetime::{DatePrecision, DateTime};
 pub use group_by::GroupByIteratorExtended;
 pub use ownedbytes::{OwnedBytes, StableDeref};
 pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
@@ -111,21 +107,6 @@ 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 {
 
@@ -190,20 +171,4 @@ 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-disabled/aggregation.rs

@@ -0,0 +1,130 @@
+// # Aggregation example
+//
+// This example shows how you can use built-in aggregations.
+// We will use range buckets and compute the average in each bucket.
+//
+
+use serde_json::Value;
+use tantivy::aggregation::agg_req::{
+    Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
+    RangeAggregation,
+};
+use tantivy::aggregation::agg_result::AggregationResults;
+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};
+
+fn main() -> tantivy::Result<()> {
+    let mut schema_builder = Schema::builder();
+    let text_fieldtype = schema::TextOptions::default()
+        .set_indexing_options(
+            TextFieldIndexing::default().set_index_option(IndexRecordOption::WithFreqs),
+        )
+        .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);
+
+    let schema = schema_builder.build();
+
+    // # Indexing documents
+    //
+    // Lets index a bunch of documents for this example.
+    let index = Index::create_in_ram(schema);
+
+    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,
+    ))?;
+
+    index_writer.commit()?;
+
+    let reader = index.reader()?;
+    let text_field = reader.searcher().schema().get_field("text").unwrap();
+
+    let term_query = TermQuery::new(
+        Term::from_field_text(text_field, "cool"),
+        IndexRecordOption::Basic,
+    );
+
+    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();
+
+    let agg_req_1: Aggregations = vec![(
+        "score_ranges".to_string(),
+        Aggregation::Bucket(BucketAggregation {
+            bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                field: "highscore".to_string(),
+                ranges: vec![
+                    (-1f64..9f64).into(),
+                    (9f64..14f64).into(),
+                    (14f64..20f64).into(),
+                ],
+                ..Default::default()
+            }),
+            sub_aggregation: sub_agg_req_1,
+        }),
+    )]
+    .into_iter()
+    .collect();
+
+    let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
+
+    let searcher = reader.searcher();
+    let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();
+
+    let res: Value = serde_json::to_value(agg_res)?;
+    println!("{}", serde_json::to_string_pretty(&res)?);
+
+    Ok(())
+}

examples-disabled/custom_collector.rs

@@ -7,7 +7,9 @@
 // Of course, you can have a look at the tantivy's built-in collectors
 // such as the `CountCollector` for more examples.
 
-use columnar::Column;
+use std::sync::Arc;
+
+use fastfield_codecs::Column;
 // ---
 // Importing tantivy...
 use tantivy::collector::{Collector, SegmentCollector};
@@ -95,7 +97,7 @@ impl Collector for StatsCollector {
 }
 
 struct StatsSegmentCollector {
-    fast_field_reader: Column,
+    fast_field_reader: Arc<dyn Column<u64>>,
     stats: Stats,
 }
 
@@ -103,14 +105,10 @@ impl SegmentCollector for StatsSegmentCollector {
     type Fruit = Option<Stats>;
 
     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_for_doc(doc) {
-            let value = value as f64;
-            self.stats.count += 1;
-            self.stats.sum += value;
-            self.stats.squared_sum += value * value;
-        }
+        let value = self.fast_field_reader.get_val(doc) as f64;
+        self.stats.count += 1;
+        self.stats.sum += value;
+        self.stats.squared_sum += value * value;
     }
 
     fn harvest(self) -> <Self as SegmentCollector>::Fruit {
@@ -171,7 +169,7 @@ fn main() -> tantivy::Result<()> {
     let searcher = reader.searcher();
     let query_parser = QueryParser::for_index(&index, vec![product_name, product_description]);
 
-    // here we want to search for `broom` and use `StatsCollector` on the hits.
+    // here we want to get a hit on the 'ken' in Frankenstein
     let query = query_parser.parse_query("broom")?;
     if let Some(stats) =
         searcher.search(&query, &StatsCollector::with_field("price".to_string()))?

examples-disabled/custom_tokenizer.rs

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

examples-disabled/date_time_field.rs

@@ -14,7 +14,6 @@ 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();
@@ -23,7 +22,6 @@ 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",
@@ -43,16 +41,14 @@ fn main() -> tantivy::Result<()> {
     let reader = index.reader()?;
     let searcher = reader.searcher();
 
-    // # Search
+    // # Default fields: event_type
     let query_parser = QueryParser::for_index(&index, vec![event_type]);
     {
-        // Simple exact search on the date
-        let query = query_parser.parse_query("occurred_at:\"2022-06-22T12:53:50.53Z\"")?;
+        let query = query_parser.parse_query("event:comment")?;
         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-disabled/faceted_search.rs

@@ -71,7 +71,7 @@ fn main() -> tantivy::Result<()> {
     let reader = index.reader()?;
     let searcher = reader.searcher();
     {
-        let mut facet_collector = FacetCollector::for_field("classification");
+        let mut facet_collector = FacetCollector::for_field(classification);
         facet_collector.add_facet("/Felidae");
         let facet_counts = searcher.search(&AllQuery, &facet_collector)?;
         // This lists all of the facet counts, right below "/Felidae".
@@ -97,7 +97,7 @@ fn main() -> tantivy::Result<()> {
         let facet = Facet::from("/Felidae/Pantherinae");
         let facet_term = Term::from_facet(classification, &facet);
         let facet_term_query = TermQuery::new(facet_term, IndexRecordOption::Basic);
-        let mut facet_collector = FacetCollector::for_field("classification");
+        let mut facet_collector = FacetCollector::for_field(classification);
         facet_collector.add_facet("/Felidae/Pantherinae");
         let facet_counts = searcher.search(&facet_term_query, &facet_collector)?;
         let facets: Vec<(&Facet, u64)> = facet_counts.get("/Felidae/Pantherinae").collect();

examples-disabled/faceted_search_with_tweaked_score.rs

@@ -1,12 +1,3 @@
-// # 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;
@@ -64,9 +55,8 @@ 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 ingredient_reader = segment_reader.facet_reader(ingredient).unwrap();
                 let facet_dict = ingredient_reader.facet_dict();
 
                 let query_ords: HashSet<u64> = facets
@@ -74,10 +64,12 @@ fn main() -> tantivy::Result<()> {
                     .filter_map(|key| facet_dict.term_ord(key.encoded_str()).unwrap())
                     .collect();
 
+                let mut facet_ords_buffer: Vec<u64> = Vec::with_capacity(20);
+
                 move |doc: DocId, original_score: Score| {
-                    // Update the original score with a tweaked score
-                    let missing_ingredients = ingredient_reader
-                        .facet_ords(doc)
+                    ingredient_reader.facet_ords(doc, &mut facet_ords_buffer);
+                    let missing_ingredients = facet_ords_buffer
+                        .iter()
                         .filter(|ord| !query_ords.contains(ord))
                         .count();
                     let tweak = 1.0 / 4_f32.powi(missing_ingredients as i32);

examples-disabled/ip_field.rs

@@ -0,0 +1,73 @@
+// # IP Address example
+//
+// This example shows how the ip field can be used
+// with IpV6 and IpV4.
+
+use tantivy::collector::{Count, TopDocs};
+use tantivy::query::QueryParser;
+use tantivy::schema::{Schema, FAST, INDEXED, STORED, STRING};
+use tantivy::Index;
+
+fn main() -> tantivy::Result<()> {
+    // # Defining the schema
+    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);
+    let schema = schema_builder.build();
+
+    // # Indexing documents
+    let index = Index::create_in_ram(schema.clone());
+
+    let mut index_writer = index.writer(50_000_000)?;
+    let doc = schema.parse_document(
+        r#"{
+        "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"
+    }"#,
+    )?;
+    index_writer.add_document(doc)?;
+    let doc = schema.parse_document(
+        r#"{
+        "ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334",
+        "event_type": "checkout"
+    }"#,
+    )?;
+
+    index_writer.add_document(doc)?;
+    index_writer.commit()?;
+
+    let reader = index.reader()?;
+    let searcher = reader.searcher();
+
+    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]")?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(5))?;
+        assert_eq!(count_docs.len(), 2);
+    }
+    {
+        let query = query_parser.parse_query("ip:[192.168.1.0 TO 192.168.1.100]")?;
+        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
+        assert_eq!(count_docs.len(), 0);
+    }
+    {
+        let query = query_parser.parse_query("ip:192.168.0.80")?;
+        let count_docs = searcher.search(&*query, &Count)?;
+        assert_eq!(count_docs, 1);
+    }
+    {
+        // 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);
+    }
+
+    Ok(())
+}

examples-disabled/pre_tokenized_text.rs

@@ -12,7 +12,7 @@
 use tantivy::collector::{Count, TopDocs};
 use tantivy::query::TermQuery;
 use tantivy::schema::*;
-use tantivy::tokenizer::{PreTokenizedString, SimpleTokenizer, Token, TokenStream, Tokenizer};
+use tantivy::tokenizer::{PreTokenizedString, SimpleTokenizer, Token, Tokenizer};
 use tantivy::{doc, Index, ReloadPolicy};
 use tempfile::TempDir;
 

examples-disabled/stop_words.rs

@@ -50,13 +50,12 @@ fn main() -> tantivy::Result<()> {
 
     // This tokenizer lowers all of the text (to help with stop word matching)
     // then removes all instances of `the` and `and` from the corpus
-    let tokenizer = TextAnalyzer::builder(SimpleTokenizer)
+    let tokenizer = TextAnalyzer::from(SimpleTokenizer)
         .filter(LowerCaser)
         .filter(StopWordFilter::remove(vec![
             "the".to_string(),
             "and".to_string(),
-        ]))
-        .build();
+        ]));
 
     index.tokenizers().register("stoppy", tokenizer);
 

examples-disabled/warmer.rs

@@ -17,6 +17,7 @@ use tantivy::{
 
 type ProductId = u64;
 
+/// Price
 type Price = u32;
 
 pub trait PriceFetcher: Send + Sync + 'static {
@@ -47,10 +48,7 @@ impl Warmer for DynamicPriceColumn {
     fn warm(&self, searcher: &Searcher) -> tantivy::Result<()> {
         for segment in searcher.segment_readers() {
             let key = (segment.segment_id(), segment.delete_opstamp());
-            let product_id_reader = segment
-                .fast_fields()
-                .u64(&self.field)?
-                .first_or_default_col(0);
+            let product_id_reader = segment.fast_fields().u64(&self.field)?;
             let product_ids: Vec<ProductId> = segment
                 .doc_ids_alive()
                 .map(|doc| product_id_reader.get_val(doc))
@@ -89,10 +87,10 @@ 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>>>,

examples/aggregation.rs

@@ -1,319 +0,0 @@
-// # Aggregation example
-//
-// This example shows how you can use built-in aggregations.
-// 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::{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::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)
-                .set_tokenizer("raw"),
-        )
-        .set_fast()
-        .set_stored();
-    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.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)?;
-    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 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 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 }
-          ]
-        }
-      }
-    } "#;
-
-    // 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: Aggregations = serde_json::from_str(agg_req_str)?;
-    let collector = AggregationCollector::from_aggs(agg_req, Default::default());
-
-    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(Box::new(BucketAggregation {
-            bucket_agg: BucketAggregationType::Range(RangeAggregation {
-                field: "stock".to_string(),
-                ranges: vec![
-                    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: 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, Default::default());
-    // We use the `AllQuery` which will pass all documents to the AggregationCollector.
-    let agg_res: AggregationResults = searcher.search(&AllQuery, &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, Default::default());
-
-    let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
-    let res: Value = serde_json::to_value(agg_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/fuzzy_search.rs

@@ -1,167 +0,0 @@
-// # 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

@@ -1,107 +0,0 @@
-// # IP Address example
-//
-// This example shows how the ip field can be used
-// with IpV6 and IpV4.
-
-use tantivy::collector::{Count, TopDocs};
-use tantivy::query::QueryParser;
-use tantivy::schema::{Schema, FAST, INDEXED, STORED, STRING};
-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);
-    let schema = schema_builder.build();
-
-    // # Indexing documents
-    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"
-        }"#,
-    )?;
-    index_writer.add_document(doc)?;
-    let doc = schema.parse_document(
-        r#"{
-            "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"
-        }"#,
-    )?;
-
-    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]);
-    {
-        // 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(), 1);
-    }
-    {
-        // Exclusive range queries
-        let query = query_parser.parse_query("ip:{192.168.0.80 TO 192.168.1.100]")?;
-        let count_docs = searcher.search(&*query, &TopDocs::with_limit(2))?;
-        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 `:`
-    {
-        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);
-    }
-
-    Ok(())
-}

src/aggregation/agg_limits.rs

@@ -1,94 +0,0 @@
-use std::collections::HashMap;
-use std::sync::atomic::AtomicU64;
-use std::sync::Arc;
-
-use common::ByteCount;
-
-use super::collector::DEFAULT_MEMORY_LIMIT;
-use super::{AggregationError, DEFAULT_BUCKET_LIMIT};
-use crate::TantivyError;
-
-/// An estimate for memory consumption
-pub trait MemoryConsumption {
-    fn memory_consumption(&self) -> usize;
-}
-
-impl<K, V, S> MemoryConsumption for HashMap<K, V, S> {
-    fn memory_consumption(&self) -> usize {
-        let num_items = self.capacity();
-        (std::mem::size_of::<K>() + std::mem::size_of::<V>()) * num_items
-    }
-}
-
-/// Aggregation memory limit after which the request fails. Defaults to DEFAULT_MEMORY_LIMIT
-/// (500MB). The limit is shared by all SegmentCollectors
-pub struct AggregationLimits {
-    /// The counter which is shared between the aggregations for one request.
-    memory_consumption: Arc<AtomicU64>,
-    /// The memory_limit in bytes
-    memory_limit: ByteCount,
-    /// The maximum number of buckets _returned_
-    /// This is not counting intermediate buckets.
-    bucket_limit: u32,
-}
-impl Clone for AggregationLimits {
-    fn clone(&self) -> Self {
-        Self {
-            memory_consumption: Arc::clone(&self.memory_consumption),
-            memory_limit: self.memory_limit,
-            bucket_limit: self.bucket_limit,
-        }
-    }
-}
-
-impl Default for AggregationLimits {
-    fn default() -> Self {
-        Self {
-            memory_consumption: Default::default(),
-            memory_limit: DEFAULT_MEMORY_LIMIT.into(),
-            bucket_limit: DEFAULT_BUCKET_LIMIT,
-        }
-    }
-}
-
-impl AggregationLimits {
-    /// *memory_limit*
-    /// memory_limit is defined in bytes.
-    /// Aggregation fails when the estimated memory consumption of the aggregation is higher than
-    /// memory_limit.     
-    /// memory_limit will default to `DEFAULT_MEMORY_LIMIT` (500MB)
-    ///
-    /// *bucket_limit*
-    /// Limits the maximum number of buckets returned from an aggregation request.
-    /// bucket_limit will default to `DEFAULT_BUCKET_LIMIT` (65000)
-    pub fn new(memory_limit: Option<u64>, bucket_limit: Option<u32>) -> Self {
-        Self {
-            memory_consumption: Default::default(),
-            memory_limit: memory_limit.unwrap_or(DEFAULT_MEMORY_LIMIT).into(),
-            bucket_limit: bucket_limit.unwrap_or(DEFAULT_BUCKET_LIMIT),
-        }
-    }
-    pub(crate) fn validate_memory_consumption(&self) -> crate::Result<()> {
-        if self.get_memory_consumed() > self.memory_limit {
-            return Err(TantivyError::AggregationError(
-                AggregationError::MemoryExceeded {
-                    limit: self.memory_limit,
-                    current: self.get_memory_consumed(),
-                },
-            ));
-        }
-        Ok(())
-    }
-    pub(crate) fn add_memory_consumed(&self, num_bytes: u64) {
-        self.memory_consumption
-            .fetch_add(num_bytes, std::sync::atomic::Ordering::Relaxed);
-    }
-    pub fn get_memory_consumed(&self) -> ByteCount {
-        self.memory_consumption
-            .load(std::sync::atomic::Ordering::Relaxed)
-            .into()
-    }
-    pub fn get_bucket_limit(&self) -> u32 {
-        self.bucket_limit
-    }
-}

src/aggregation/agg_req.rs

@@ -16,14 +16,14 @@
 //! let agg_req1: Aggregations = vec![
 //!     (
 //!         "range".to_string(),
-//!         Aggregation::Bucket(Box::new(BucketAggregation {
+//!         Aggregation::Bucket(BucketAggregation {
 //!             bucket_agg: BucketAggregationType::Range(RangeAggregation{
 //!                 field: "score".to_string(),
 //!                 ranges: vec![(3f64..7f64).into(), (7f64..20f64).into()],
 //!                 keyed: false,
 //!             }),
 //!             sub_aggregation: Default::default(),
-//!         })),
+//!         }),
 //!     ),
 //! ]
 //! .into_iter()
@@ -50,7 +50,7 @@ use std::collections::{HashMap, HashSet};
 use serde::{Deserialize, Serialize};
 
 pub use super::bucket::RangeAggregation;
-use super::bucket::{DateHistogramAggregationReq, HistogramAggregation, TermsAggregation};
+use super::bucket::{HistogramAggregation, TermsAggregation};
 use super::metric::{
     AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
     SumAggregation,
@@ -110,13 +110,10 @@ impl BucketAggregationInternal {
             _ => None,
         }
     }
-    pub(crate) fn as_histogram(&self) -> crate::Result<Option<HistogramAggregation>> {
+    pub(crate) fn as_histogram(&self) -> Option<&HistogramAggregation> {
         match &self.bucket_agg {
-            BucketAggregationType::Histogram(histogram) => Ok(Some(histogram.clone())),
-            BucketAggregationType::DateHistogram(histogram) => {
-                Ok(Some(histogram.to_histogram_req()?))
-            }
-            _ => Ok(None),
+            BucketAggregationType::Histogram(histogram) => Some(histogram),
+            _ => None,
         }
     }
     pub(crate) fn as_term(&self) -> Option<&TermsAggregation> {
@@ -127,6 +124,15 @@ 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();
@@ -143,18 +149,22 @@ pub fn get_fast_field_names(aggs: &Aggregations) -> HashSet<String> {
 #[serde(untagged)]
 pub enum Aggregation {
     /// Bucket aggregation, see [`BucketAggregation`] for details.
-    Bucket(Box<BucketAggregation>),
+    Bucket(BucketAggregation),
     /// Metric aggregation, see [`MetricAggregation`] for details.
     Metric(MetricAggregation),
 }
 
 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) => {
-                fast_field_names.insert(metric.get_fast_field_name().to_string());
-            }
+            Aggregation::Metric(metric) => metric.get_fast_field_names(fast_field_names),
         }
     }
 }
@@ -183,9 +193,14 @@ 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>) {
-        let fast_field_name = self.bucket_agg.get_fast_field_name();
-        fast_field_names.insert(fast_field_name.to_string());
+        self.bucket_agg.get_fast_field_names(fast_field_names);
         fast_field_names.extend(get_fast_field_names(&self.sub_aggregation));
     }
 }
@@ -199,22 +214,20 @@ 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_name(&self) -> &str {
+    fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
         match self {
-            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(),
-        }
+            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())
+            }
+        };
     }
 }
 
@@ -249,15 +262,16 @@ pub enum MetricAggregation {
 }
 
 impl MetricAggregation {
-    fn get_fast_field_name(&self) -> &str {
-        match self {
+    fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
+        let fast_field_name = 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());
     }
 }
 
@@ -301,7 +315,7 @@ mod tests {
     fn serialize_to_json_test() {
         let agg_req1: Aggregations = vec![(
             "range".to_string(),
-            Aggregation::Bucket(Box::new(BucketAggregation {
+            Aggregation::Bucket(BucketAggregation {
                 bucket_agg: BucketAggregationType::Range(RangeAggregation {
                     field: "score".to_string(),
                     ranges: vec![
@@ -313,7 +327,7 @@ mod tests {
                     keyed: true,
                 }),
                 sub_aggregation: Default::default(),
-            })),
+            }),
         )]
         .into_iter()
         .collect();
@@ -351,7 +365,7 @@ mod tests {
         let agg_req2: Aggregations = vec![
             (
                 "range".to_string(),
-                Aggregation::Bucket(Box::new(BucketAggregation {
+                Aggregation::Bucket(BucketAggregation {
                     bucket_agg: BucketAggregationType::Range(RangeAggregation {
                         field: "score2".to_string(),
                         ranges: vec![
@@ -363,7 +377,7 @@ mod tests {
                         ..Default::default()
                     }),
                     sub_aggregation: Default::default(),
-                })),
+                }),
             ),
             (
                 "metric".to_string(),
@@ -377,7 +391,7 @@ mod tests {
 
         let agg_req1: Aggregations = vec![(
             "range".to_string(),
-            Aggregation::Bucket(Box::new(BucketAggregation {
+            Aggregation::Bucket(BucketAggregation {
                 bucket_agg: BucketAggregationType::Range(RangeAggregation {
                     field: "score".to_string(),
                     ranges: vec![
@@ -389,7 +403,7 @@ mod tests {
                     ..Default::default()
                 }),
                 sub_aggregation: agg_req2,
-            })),
+            }),
         )]
         .into_iter()
         .collect();

src/aggregation/agg_req_with_accessor.rs

@@ -1,20 +1,20 @@
 //! This will enhance the request tree with access to the fastfield and metadata.
 
-use std::sync::Arc;
+use std::rc::Rc;
+use std::sync::atomic::AtomicU32;
 
-use columnar::{Column, ColumnType, ColumnValues, StrColumn};
+use columnar::{Column, StrColumn};
 
 use super::agg_req::{Aggregation, Aggregations, BucketAggregationType, MetricAggregation};
-use super::bucket::{
-    DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
-};
+use super::bucket::{HistogramAggregation, RangeAggregation, TermsAggregation};
 use super::metric::{
     AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
     SumAggregation,
 };
-use super::segment_agg_result::AggregationLimits;
+use super::segment_agg_result::BucketCount;
 use super::VecWithNames;
-use crate::SegmentReader;
+use crate::schema::Type;
+use crate::{SegmentReader, TantivyError};
 
 #[derive(Clone, Default)]
 pub(crate) struct AggregationsWithAccessor {
@@ -41,10 +41,10 @@ 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: ColumnType,
+    pub(crate) field_type: Type,
     pub(crate) bucket_agg: BucketAggregationType,
     pub(crate) sub_aggregation: AggregationsWithAccessor,
-    pub(crate) limits: AggregationLimits,
+    pub(crate) bucket_count: BucketCount,
 }
 
 impl BucketAggregationWithAccessor {
@@ -52,7 +52,8 @@ impl BucketAggregationWithAccessor {
         bucket: &BucketAggregationType,
         sub_aggregation: &Aggregations,
         reader: &SegmentReader,
-        limits: AggregationLimits,
+        bucket_count: Rc<AtomicU32>,
+        max_bucket_count: u32,
     ) -> crate::Result<BucketAggregationWithAccessor> {
         let mut str_dict_column = None;
         let (accessor, field_type) = match &bucket {
@@ -62,14 +63,10 @@ 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, ..
             }) => {
-                str_dict_column = reader.fast_fields().str(field_name)?;
+                str_dict_column = reader.fast_fields().str(&field_name)?;
                 get_ff_reader_and_validate(reader, field_name)?
             }
         };
@@ -80,11 +77,15 @@ impl BucketAggregationWithAccessor {
             sub_aggregation: get_aggs_with_accessor_and_validate(
                 &sub_aggregation,
                 reader,
-                &limits.clone(),
+                bucket_count.clone(),
+                max_bucket_count,
             )?,
             bucket_agg: bucket.clone(),
             str_dict_column,
-            limits,
+            bucket_count: BucketCount {
+                bucket_count,
+                max_bucket_count,
+            },
         })
     }
 }
@@ -93,7 +94,7 @@ impl BucketAggregationWithAccessor {
 #[derive(Clone)]
 pub struct MetricAggregationWithAccessor {
     pub metric: MetricAggregation,
-    pub field_type: ColumnType,
+    pub field_type: Type,
     pub accessor: Column<u64>,
 }
 
@@ -124,7 +125,8 @@ impl MetricAggregationWithAccessor {
 pub(crate) fn get_aggs_with_accessor_and_validate(
     aggs: &Aggregations,
     reader: &SegmentReader,
-    limits: &AggregationLimits,
+    bucket_count: Rc<AtomicU32>,
+    max_bucket_count: u32,
 ) -> crate::Result<AggregationsWithAccessor> {
     let mut metrics = vec![];
     let mut buckets = vec![];
@@ -136,7 +138,8 @@ pub(crate) fn get_aggs_with_accessor_and_validate(
                     &bucket.bucket_agg,
                     &bucket.sub_aggregation,
                     reader,
-                    limits.clone(),
+                    Rc::clone(&bucket_count),
+                    max_bucket_count,
                 )?,
             )),
             Aggregation::Metric(metric) => metrics.push((
@@ -155,35 +158,22 @@ 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>, ColumnType)> {
+) -> 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
+
     let ff_fields = reader.fast_fields();
-    let ff_field_with_type = ff_fields
-        .u64_lenient_with_type(field_name)?
-        .unwrap_or_else(|| (build_empty_column(reader.num_docs()), ColumnType::U64));
-
-    Ok(ff_field_with_type)
-}
-
-// Empty Column
-fn build_empty_column(num_docs: u32) -> Column {
-    struct EmptyValues;
-    impl ColumnValues for EmptyValues {
-        fn get_val(&self, _idx: u32) -> u64 {
-            unimplemented!("Internal Error: Called get_val of empty column.")
-        }
-        fn min_value(&self) -> u64 {
-            unimplemented!("Internal Error: Called min_value of empty column.")
-        }
-        fn max_value(&self) -> u64 {
-            unimplemented!("Internal Error: Called max_value of empty column.")
-        }
-        fn num_vals(&self) -> u32 {
-            0
-        }
-    }
-
-    Column {
-        idx: columnar::ColumnIndex::Empty { num_docs },
-        values: Arc::new(EmptyValues),
-    }
+    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))
 }

src/aggregation/agg_result.rs

@@ -11,8 +11,8 @@ use super::agg_req::BucketAggregationInternal;
 use super::bucket::GetDocCount;
 use super::intermediate_agg_result::{IntermediateBucketResult, IntermediateMetricResult};
 use super::metric::{SingleMetricResult, Stats};
-use super::segment_agg_result::AggregationLimits;
 use super::Key;
+use crate::schema::Schema;
 use crate::TantivyError;
 
 #[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
@@ -20,13 +20,6 @@ use crate::TantivyError;
 pub struct AggregationResults(pub FxHashMap<String, AggregationResult>);
 
 impl AggregationResults {
-    pub(crate) fn get_bucket_count(&self) -> u64 {
-        self.0
-            .values()
-            .map(|agg| agg.get_bucket_count())
-            .sum::<u64>()
-    }
-
     pub(crate) fn get_value_from_aggregation(
         &self,
         name: &str,
@@ -55,13 +48,6 @@ pub enum AggregationResult {
 }
 
 impl AggregationResult {
-    pub(crate) fn get_bucket_count(&self) -> u64 {
-        match self {
-            AggregationResult::BucketResult(bucket) => bucket.get_bucket_count(),
-            AggregationResult::MetricResult(_) => 0,
-        }
-    }
-
     pub(crate) fn get_value_from_aggregation(
         &self,
         _name: &str,
@@ -168,28 +154,12 @@ pub enum BucketResult {
 }
 
 impl BucketResult {
-    pub(crate) fn get_bucket_count(&self) -> u64 {
-        match self {
-            BucketResult::Range { buckets } => {
-                buckets.iter().map(|bucket| bucket.get_bucket_count()).sum()
-            }
-            BucketResult::Histogram { buckets } => {
-                buckets.iter().map(|bucket| bucket.get_bucket_count()).sum()
-            }
-            BucketResult::Terms {
-                buckets,
-                sum_other_doc_count: _,
-                doc_count_error_upper_bound: _,
-            } => buckets.iter().map(|bucket| bucket.get_bucket_count()).sum(),
-        }
-    }
-
     pub(crate) fn empty_from_req(
         req: &BucketAggregationInternal,
-        limits: &AggregationLimits,
+        schema: &Schema,
     ) -> crate::Result<Self> {
         let empty_bucket = IntermediateBucketResult::empty_from_req(&req.bucket_agg);
-        empty_bucket.into_final_bucket_result(req, limits)
+        empty_bucket.into_final_bucket_result(req, schema)
     }
 }
 
@@ -204,15 +174,6 @@ pub enum BucketEntries<T> {
     HashMap(FxHashMap<String, T>),
 }
 
-impl<T> BucketEntries<T> {
-    fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = &T> + 'a> {
-        match self {
-            BucketEntries::Vec(vec) => Box::new(vec.iter()),
-            BucketEntries::HashMap(map) => Box::new(map.values()),
-        }
-    }
-}
-
 /// This is the default entry for a bucket, which contains a key, count, and optionally
 /// sub-aggregations.
 ///
@@ -252,11 +213,6 @@ pub struct BucketEntry {
     /// Sub-aggregations in this bucket.
     pub sub_aggregation: AggregationResults,
 }
-impl BucketEntry {
-    pub(crate) fn get_bucket_count(&self) -> u64 {
-        1 + self.sub_aggregation.get_bucket_count()
-    }
-}
 impl GetDocCount for &BucketEntry {
     fn doc_count(&self) -> u64 {
         self.doc_count
@@ -320,8 +276,3 @@ pub struct RangeBucketEntry {
     #[serde(skip_serializing_if = "Option::is_none")]
     pub to_as_string: Option<String>,
 }
-impl RangeBucketEntry {
-    pub(crate) fn get_bucket_count(&self) -> u64 {
-        1 + self.sub_aggregation.get_bucket_count()
-    }
-}

src/aggregation/bucket/histogram/date_histogram.rs

@@ -1,8 +1,5 @@
 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.
 ///
@@ -32,16 +29,8 @@ use crate::aggregation::AggregationError;
 /// 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
     ///
@@ -62,449 +51,76 @@ pub struct DateHistogramAggregationReq {
     ///
     /// Fractional time values are not supported, but you can address this by shifting to another
     /// time unit (e.g., `1.5h` could instead be specified as `90m`).
-    ///
-    /// `Option` for validation, the parameter is not optional
-    pub fixed_interval: Option<String>,
+    pub fixed_interval: String,
     /// 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_ref().unwrap())? 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 let Some(interval) = self.interval.as_ref() {
-            return Err(crate::TantivyError::InvalidArgument(format!(
-                "`interval` parameter {:?} in date histogram is unsupported, only \
-                 `fixed_interval` is supported",
-                interval
-            )));
-        }
-        if let Some(interval) = self.date_interval.as_ref() {
-            return Err(crate::TantivyError::InvalidArgument(format!(
-                "`date_interval` parameter {:?} in date histogram is unsupported, only \
-                 `fixed_interval` is supported",
-                interval
-            )));
-        }
-        if self.format.is_some() {
-            return Err(crate::TantivyError::InvalidArgument(
-                "format parameter on date_histogram is unsupported".to_string(),
-            ));
-        }
-
-        if self.fixed_interval.is_none() {
-            return Err(crate::TantivyError::InvalidArgument(
-                "fixed_interval in date histogram is missing".to_string(),
-            ));
-        }
-
-        parse_into_microseconds(self.fixed_interval.as_ref().unwrap())?;
-
         Ok(())
     }
 }
 
-#[derive(Debug, Clone, PartialEq, Eq, Error)]
+#[derive(Debug, PartialEq, Eq)]
 /// 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_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> {
+fn parse_into_milliseconds(input: &str) -> Result<u64, DateHistogramParseError> {
     let split_boundary = input
-        .as_bytes()
-        .iter()
-        .take_while(|byte| byte.is_ascii_digit())
+        .char_indices()
+        .take_while(|(pos, el)| el.is_numeric())
         .count();
     let (number, unit) = input.split_at(split_boundary);
     if number.is_empty() {
-        return Err(DateHistogramParseError::NumberMissing(input.to_string()).into());
+        return Err(DateHistogramParseError::NumberMissing(input.to_string()));
     }
     if unit.is_empty() {
-        return Err(DateHistogramParseError::UnitMissing(input.to_string()).into());
+        return Err(DateHistogramParseError::UnitMissing(input.to_string()));
     }
-    let number: i64 = number
-        .parse()
-        // Technically this should never happen, but there was a bug
-        // here and being defensive does not hurt.
-        .map_err(|_err| DateHistogramParseError::NumberMissing(input.to_string()))?;
-
+    let number: u64 = number.parse().unwrap();
     let multiplier_from_unit = match unit {
         "ms" => 1,
         "s" => 1000,
         "m" => 60 * 1000,
         "h" => 60 * 60 * 1000,
         "d" => 24 * 60 * 60 * 1000,
-        _ => return Err(DateHistogramParseError::UnitNotRecognized(unit.to_string()).into()),
+        _ => return Err(DateHistogramParseError::UnitNotRecognized(unit.to_string())),
     };
 
-    Ok(number * multiplier_from_unit * 1000)
+    Ok(number * multiplier_from_unit)
 }
 
 #[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_microseconds() {
-        assert_eq!(parse_into_microseconds("1m").unwrap(), 60_000_000);
-        assert_eq!(parse_into_microseconds("2m").unwrap(), 120_000_000);
+    fn parser_test() {
+        assert_eq!(parse_into_milliseconds("1m").unwrap(), 60_000);
+        assert_eq!(parse_into_milliseconds("2m").unwrap(), 120_000);
         assert_eq!(
-            parse_into_microseconds("2y").unwrap_err(),
-            DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
+            parse_into_milliseconds("2y").unwrap_err(),
+            DateHistogramParseError::UnitNotRecognized("y".to_string())
         );
         assert_eq!(
-            parse_into_microseconds("2000").unwrap_err(),
-            DateHistogramParseError::UnitMissing("2000".to_string()).into()
+            parse_into_milliseconds("2000").unwrap_err(),
+            DateHistogramParseError::UnitMissing("2000".to_string())
         );
         assert_eq!(
-            parse_into_microseconds("ms").unwrap_err(),
-            DateHistogramParseError::NumberMissing("ms".to_string()).into()
+            parse_into_milliseconds("ms").unwrap_err(),
+            DateHistogramParseError::NumberMissing("ms".to_string())
         );
     }
-
-    #[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_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(())
-    }
-    #[test]
-    fn histogram_test_invalid_req() -> crate::Result<()> {
-        let docs = vec![];
-
-        let index = get_test_index_from_docs(false, &docs)?;
-        let elasticsearch_compatible_json = json!(
-            {
-              "sales_over_time": {
-                "date_histogram": {
-                  "field": "date",
-                  "interval": "30d",
-                  "offset": "-4d"
-                }
-              }
-            }
-        );
-
-        let agg_req: Aggregations =
-            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
-                .unwrap();
-        let err = exec_request(agg_req, &index).unwrap_err();
-        assert_eq!(
-            err.to_string(),
-            r#"An invalid argument was passed: '`interval` parameter "30d" in date histogram is unsupported, only `fixed_interval` is supported'"#
-        );
-
-        Ok(())
-    }
 }

src/aggregation/bucket/mod.rs

@@ -21,25 +21,28 @@ 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, Default)]
+#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize)]
 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`.
     ///
@@ -47,6 +50,11 @@ 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

@@ -1,22 +1,24 @@
 use std::fmt::Debug;
 use std::ops::Range;
 
-use columnar::{ColumnType, MonotonicallyMappableToU64};
+use columnar::MonotonicallyMappableToU64;
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 
-use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
+use crate::aggregation::agg_req_with_accessor::{
+    AggregationsWithAccessor, BucketAggregationWithAccessor,
+};
 use crate::aggregation::intermediate_agg_result::{
-    IntermediateAggregationResults, IntermediateBucketResult, IntermediateRangeBucketEntry,
-    IntermediateRangeBucketResult,
+    IntermediateBucketResult, IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
 };
 use crate::aggregation::segment_agg_result::{
-    build_segment_agg_collector, AggregationLimits, SegmentAggregationCollector,
+    BucketCount, GenericSegmentAggregationResultsCollector, SegmentAggregationCollector,
 };
 use crate::aggregation::{
-    f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey, VecWithNames,
+    f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
 };
-use crate::TantivyError;
+use crate::schema::Type;
+use crate::{DocId, TantivyError};
 
 /// Provide user-defined buckets to aggregate on.
 /// Two special buckets will automatically be created to cover the whole range of values.
@@ -126,15 +128,14 @@ pub(crate) struct SegmentRangeAndBucketEntry {
 pub struct SegmentRangeCollector {
     /// The buckets containing the aggregation data.
     buckets: Vec<SegmentRangeAndBucketEntry>,
-    column_type: ColumnType,
-    pub(crate) accessor_idx: usize,
+    field_type: Type,
 }
 
 #[derive(Clone)]
 pub(crate) struct SegmentRangeBucketEntry {
     pub key: Key,
     pub doc_count: u64,
-    pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
+    pub sub_aggregation: Option<GenericSegmentAggregationResultsCollector>,
     /// 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
@@ -173,14 +174,12 @@ impl SegmentRangeBucketEntry {
     }
 }
 
-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;
+impl SegmentRangeCollector {
+    pub fn into_intermediate_bucket_result(
+        self,
+        agg_with_accessor: &BucketAggregationWithAccessor,
+    ) -> crate::Result<IntermediateBucketResult> {
+        let field_type = self.field_type;
 
         let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
             .buckets
@@ -190,79 +189,21 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
                     range_to_string(&range_bucket.range, &field_type)?,
                     range_bucket
                         .bucket
-                        .into_intermediate_bucket_entry(sub_agg)?,
+                        .into_intermediate_bucket_entry(&agg_with_accessor.sub_aggregation)?,
                 ))
             })
             .collect::<crate::Result<_>>()?;
 
-        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,
-        })
+        Ok(IntermediateBucketResult::Range(
+            IntermediateRangeBucketResult { buckets },
+        ))
     }
 
-    #[inline]
-    fn collect(
-        &mut self,
-        doc: crate::DocId,
-        agg_with_accessor: &AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collect_block(&[doc], agg_with_accessor)
-    }
-
-    #[inline]
-    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,
-        limits: &AggregationLimits,
-        field_type: ColumnType,
-        accessor_idx: usize,
+        bucket_count: &BucketCount,
+        field_type: Type,
     ) -> 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.
@@ -288,7 +229,11 @@ impl SegmentRangeCollector {
                 let sub_aggregation = if sub_aggregation.is_empty() {
                     None
                 } else {
-                    Some(build_segment_agg_collector(sub_aggregation)?)
+                    Some(
+                        GenericSegmentAggregationResultsCollector::from_req_and_validate(
+                            sub_aggregation,
+                        )?,
+                    )
                 };
 
                 Ok(SegmentRangeAndBucketEntry {
@@ -304,18 +249,57 @@ impl SegmentRangeCollector {
             })
             .collect::<crate::Result<_>>()?;
 
-        limits.add_memory_consumed(
-            buckets.len() as u64 * std::mem::size_of::<SegmentRangeAndBucketEntry>() as u64,
-        );
-        limits.validate_memory_consumption()?;
+        bucket_count.add_count(buckets.len() as u32);
+        bucket_count.validate_bucket_count()?;
 
         Ok(SegmentRangeCollector {
             buckets,
-            column_type: field_type,
-            accessor_idx,
+            field_type,
         })
     }
 
+    #[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
@@ -341,7 +325,7 @@ impl SegmentRangeCollector {
 /// more computational expensive when many documents are hit.
 fn to_u64_range(
     range: &RangeAggregationRange,
-    field_type: &ColumnType,
+    field_type: &Type,
 ) -> crate::Result<InternalRangeAggregationRange> {
     let start = if let Some(from) = range.from {
         f64_to_fastfield_u64(from, field_type)
@@ -367,7 +351,7 @@ fn to_u64_range(
 /// beginning and end and filling gaps.
 fn extend_validate_ranges(
     buckets: &[RangeAggregationRange],
-    field_type: &ColumnType,
+    field_type: &Type,
 ) -> crate::Result<Vec<InternalRangeAggregationRange>> {
     let mut converted_buckets = buckets
         .iter()
@@ -409,16 +393,13 @@ fn extend_validate_ranges(
     Ok(converted_buckets)
 }
 
-pub(crate) fn range_to_string(
-    range: &Range<u64>,
-    field_type: &ColumnType,
-) -> crate::Result<String> {
+pub(crate) fn range_to_string(range: &Range<u64>, field_type: &Type) -> 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 == ColumnType::DateTime {
+        } else if *field_type == Type::Date {
             let val = i64::from_u64(val);
             format_date(val)
         } else {
@@ -433,7 +414,7 @@ pub(crate) fn range_to_string(
     ))
 }
 
-pub(crate) fn range_to_key(range: &Range<u64>, field_type: &ColumnType) -> crate::Result<Key> {
+pub(crate) fn range_to_key(range: &Range<u64>, field_type: &Type) -> crate::Result<Key> {
     Ok(Key::Str(range_to_string(range, field_type)?))
 }
 
@@ -445,9 +426,8 @@ mod tests {
 
     use super::*;
     use crate::aggregation::agg_req::{
-        Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
+        Aggregation, Aggregations, BucketAggregation, BucketAggregationType,
     };
-    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,
@@ -455,7 +435,7 @@ mod tests {
 
     pub fn get_collector_from_ranges(
         ranges: Vec<RangeAggregationRange>,
-        field_type: ColumnType,
+        field_type: Type,
     ) -> SegmentRangeCollector {
         let req = RangeAggregation {
             field: "dummy".to_string(),
@@ -468,7 +448,6 @@ mod tests {
             &Default::default(),
             &Default::default(),
             field_type,
-            0,
         )
         .expect("unexpected error")
     }
@@ -479,61 +458,14 @@ mod tests {
 
         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: Default::default(),
-                }
-                .into(),
-            ),
-        )]
-        .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_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(),
-            ),
+            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: Default::default(),
+            }),
         )]
         .into_iter()
         .collect();
@@ -558,17 +490,14 @@ mod tests {
 
         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()],
-                        keyed: true,
-                    }),
-                    sub_aggregation: Default::default(),
-                }
-                .into(),
-            ),
+            Aggregation::Bucket(BucketAggregation {
+                bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                    field: "fraction_f64".to_string(),
+                    ranges: vec![(0f64..0.1f64).into(), (0.1f64..0.2f64).into()],
+                    keyed: true,
+                }),
+                sub_aggregation: Default::default(),
+            }),
         )]
         .into_iter()
         .collect();
@@ -598,28 +527,25 @@ mod tests {
 
         let agg_req: Aggregations = vec![(
             "range".to_string(),
-            Aggregation::Bucket(
-                BucketAggregation {
-                    bucket_agg: BucketAggregationType::Range(RangeAggregation {
-                        field: "fraction_f64".to_string(),
-                        ranges: vec![
-                            RangeAggregationRange {
-                                key: Some("custom-key-0-to-0.1".to_string()),
-                                from: Some(0f64),
-                                to: Some(0.1f64),
-                            },
-                            RangeAggregationRange {
-                                key: None,
-                                from: Some(0.1f64),
-                                to: Some(0.2f64),
-                            },
-                        ],
-                        keyed: false,
-                    }),
-                    sub_aggregation: Default::default(),
-                }
-                .into(),
-            ),
+            Aggregation::Bucket(BucketAggregation {
+                bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                    field: "fraction_f64".to_string(),
+                    ranges: vec![
+                        RangeAggregationRange {
+                            key: Some("custom-key-0-to-0.1".to_string()),
+                            from: Some(0f64),
+                            to: Some(0.1f64),
+                        },
+                        RangeAggregationRange {
+                            key: None,
+                            from: Some(0.1f64),
+                            to: Some(0.2f64),
+                        },
+                    ],
+                    keyed: false,
+                }),
+                sub_aggregation: Default::default(),
+            }),
         )]
         .into_iter()
         .collect();
@@ -658,28 +584,25 @@ mod tests {
 
         let agg_req: Aggregations = vec![(
             "date_ranges".to_string(),
-            Aggregation::Bucket(
-                BucketAggregation {
-                    bucket_agg: BucketAggregationType::Range(RangeAggregation {
-                        field: "date".to_string(),
-                        ranges: vec![
-                            RangeAggregationRange {
-                                key: None,
-                                from: None,
-                                to: Some(1546300800000000.0f64),
-                            },
-                            RangeAggregationRange {
-                                key: None,
-                                from: Some(1546300800000000.0f64),
-                                to: Some(1546387200000000.0f64),
-                            },
-                        ],
-                        keyed: false,
-                    }),
-                    sub_aggregation: Default::default(),
-                }
-                .into(),
-            ),
+            Aggregation::Bucket(BucketAggregation {
+                bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                    field: "date".to_string(),
+                    ranges: vec![
+                        RangeAggregationRange {
+                            key: None,
+                            from: None,
+                            to: Some(1546300800000000.0f64),
+                        },
+                        RangeAggregationRange {
+                            key: None,
+                            from: Some(1546300800000000.0f64),
+                            to: Some(1546387200000000.0f64),
+                        },
+                    ],
+                    keyed: false,
+                }),
+                sub_aggregation: Default::default(),
+            }),
         )]
         .into_iter()
         .collect();
@@ -723,21 +646,18 @@ mod tests {
 
         let agg_req: Aggregations = vec![(
             "range".to_string(),
-            Aggregation::Bucket(
-                BucketAggregation {
-                    bucket_agg: BucketAggregationType::Range(RangeAggregation {
-                        field: "fraction_f64".to_string(),
-                        ranges: vec![RangeAggregationRange {
-                            key: Some("custom-key-0-to-0.1".to_string()),
-                            from: Some(0f64),
-                            to: Some(0.1f64),
-                        }],
-                        keyed: true,
-                    }),
-                    sub_aggregation: Default::default(),
-                }
-                .into(),
-            ),
+            Aggregation::Bucket(BucketAggregation {
+                bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                    field: "fraction_f64".to_string(),
+                    ranges: vec![RangeAggregationRange {
+                        key: Some("custom-key-0-to-0.1".to_string()),
+                        from: Some(0f64),
+                        to: Some(0.1f64),
+                    }],
+                    keyed: true,
+                }),
+                sub_aggregation: Default::default(),
+            }),
         )]
         .into_iter()
         .collect();
@@ -763,7 +683,7 @@ 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, ColumnType::F64);
+        let collector = get_collector_from_ranges(buckets, Type::F64);
 
         let buckets = collector.buckets;
         assert_eq!(buckets[0].range.start, u64::MIN);
@@ -786,7 +706,7 @@ mod tests {
             (10f64..20f64).into(),
             (20f64..f64::MAX).into(),
         ];
-        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
+        let collector = get_collector_from_ranges(buckets, Type::F64);
 
         let buckets = collector.buckets;
         assert_eq!(buckets[0].range.start, u64::MIN);
@@ -801,7 +721,7 @@ mod tests {
     #[test]
     fn bucket_range_test_negative_vals() {
         let buckets = vec![(-10f64..-1f64).into()];
-        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
+        let collector = get_collector_from_ranges(buckets, Type::F64);
 
         let buckets = collector.buckets;
         assert_eq!(&buckets[0].bucket.key.to_string(), "*--10");
@@ -810,7 +730,7 @@ mod tests {
     #[test]
     fn bucket_range_test_positive_vals() {
         let buckets = vec![(0f64..10f64).into()];
-        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
+        let collector = get_collector_from_ranges(buckets, Type::F64);
 
         let buckets = collector.buckets;
         assert_eq!(&buckets[0].bucket.key.to_string(), "*-0");
@@ -820,7 +740,7 @@ mod tests {
     #[test]
     fn range_binary_search_test_u64() {
         let check_ranges = |ranges: Vec<RangeAggregationRange>| {
-            let collector = get_collector_from_ranges(ranges, ColumnType::U64);
+            let collector = get_collector_from_ranges(ranges, Type::U64);
             let search = |val: u64| collector.get_bucket_pos(val);
 
             assert_eq!(search(u64::MIN), 0);
@@ -866,7 +786,7 @@ mod tests {
     fn range_binary_search_test_f64() {
         let ranges = vec![(10.0..100.0).into()];
 
-        let collector = get_collector_from_ranges(ranges, ColumnType::F64);
+        let collector = get_collector_from_ranges(ranges, Type::F64);
         let search = |val: u64| collector.get_bucket_pos(val);
 
         assert_eq!(search(u64::MIN), 0);
@@ -901,7 +821,7 @@ mod bench {
             buckets.push((bucket_start..bucket_start + bucket_size as f64).into())
         }
 
-        get_collector_from_ranges(buckets, ColumnType::U64)
+        get_collector_from_ranges(buckets, Type::U64)
     }
 
     fn get_rand_docs(total_docs: u64, num_docs_returned: u64) -> Vec<u64> {

src/aggregation/buf_collector.rs

@@ -1,82 +0,0 @@
-use super::agg_req_with_accessor::AggregationsWithAccessor;
-use super::intermediate_agg_result::IntermediateAggregationResults;
-use super::segment_agg_result::SegmentAggregationCollector;
-use crate::DocId;
-
-pub(crate) const DOC_BLOCK_SIZE: usize = 64;
-pub(crate) type DocBlock = [DocId; DOC_BLOCK_SIZE];
-
-/// BufAggregationCollector buffers documents before calling collect_block().
-#[derive(Clone)]
-pub(crate) struct BufAggregationCollector {
-    pub(crate) collector: Box<dyn SegmentAggregationCollector>,
-    staged_docs: DocBlock,
-    num_staged_docs: usize,
-}
-
-impl std::fmt::Debug for BufAggregationCollector {
-    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
-        f.debug_struct("SegmentAggregationResultsCollector")
-            .field("staged_docs", &&self.staged_docs[..self.num_staged_docs])
-            .field("num_staged_docs", &self.num_staged_docs)
-            .finish()
-    }
-}
-
-impl BufAggregationCollector {
-    pub fn new(collector: Box<dyn SegmentAggregationCollector>) -> Self {
-        Self {
-            collector,
-            num_staged_docs: 0,
-            staged_docs: [0; DOC_BLOCK_SIZE],
-        }
-    }
-}
-
-impl SegmentAggregationCollector for BufAggregationCollector {
-    #[inline]
-    fn 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)
-    }
-
-    #[inline]
-    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(())
-    }
-
-    #[inline]
-    fn collect_block(
-        &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        self.collector.collect_block(docs, agg_with_accessor)?;
-
-        Ok(())
-    }
-
-    #[inline]
-    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

@@ -1,36 +1,41 @@
+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, AggregationLimits, SegmentAggregationCollector,
+    build_segment_agg_collector, GenericSegmentAggregationResultsCollector,
+    SegmentAggregationCollector,
 };
 use crate::aggregation::agg_req_with_accessor::get_aggs_with_accessor_and_validate;
 use crate::collector::{Collector, SegmentCollector};
-use crate::{DocId, SegmentReader, TantivyError};
+use crate::schema::Schema;
+use crate::{SegmentReader, TantivyError};
 
 /// The default max bucket count, before the aggregation fails.
-pub const DEFAULT_BUCKET_LIMIT: u32 = 65000;
-
-/// The default memory limit in bytes before the aggregation fails. 500MB
-pub const DEFAULT_MEMORY_LIMIT: u64 = 500_000_000;
+pub const MAX_BUCKET_COUNT: u32 = 65000;
 
 /// Collector for aggregations.
 ///
 /// The collector collects all aggregations by the underlying aggregation request.
 pub struct AggregationCollector {
+    schema: Schema,
     agg: Aggregations,
-    limits: AggregationLimits,
+    max_bucket_count: u32,
 }
 
 impl AggregationCollector {
     /// Create collector from aggregation request.
     ///
-    /// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
-    /// bucket limit)
-    pub fn from_aggs(agg: Aggregations, limits: AggregationLimits) -> Self {
-        Self { agg, limits }
+    /// 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 {
+        Self {
+            schema,
+            agg,
+            max_bucket_count: max_bucket_count.unwrap_or(MAX_BUCKET_COUNT),
+        }
     }
 }
 
@@ -44,16 +49,18 @@ impl AggregationCollector {
 /// into the final `AggregationResults` via the `into_final_result()` method.
 pub struct DistributedAggregationCollector {
     agg: Aggregations,
-    limits: AggregationLimits,
+    max_bucket_count: u32,
 }
 
 impl DistributedAggregationCollector {
     /// Create collector from aggregation request.
     ///
-    /// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
-    /// bucket limit)
-    pub fn from_aggs(agg: Aggregations, limits: AggregationLimits) -> Self {
-        Self { agg, limits }
+    /// max_bucket_count will default to `MAX_BUCKET_COUNT` (65000) when unset
+    pub fn from_aggs(agg: Aggregations, max_bucket_count: Option<u32>) -> Self {
+        Self {
+            agg,
+            max_bucket_count: max_bucket_count.unwrap_or(MAX_BUCKET_COUNT),
+        }
     }
 }
 
@@ -67,7 +74,11 @@ impl Collector for DistributedAggregationCollector {
         _segment_local_id: crate::SegmentOrdinal,
         reader: &crate::SegmentReader,
     ) -> crate::Result<Self::Child> {
-        AggregationSegmentCollector::from_agg_req_and_reader(&self.agg, reader, &self.limits)
+        AggregationSegmentCollector::from_agg_req_and_reader(
+            &self.agg,
+            reader,
+            self.max_bucket_count,
+        )
     }
 
     fn requires_scoring(&self) -> bool {
@@ -92,7 +103,11 @@ impl Collector for AggregationCollector {
         _segment_local_id: crate::SegmentOrdinal,
         reader: &crate::SegmentReader,
     ) -> crate::Result<Self::Child> {
-        AggregationSegmentCollector::from_agg_req_and_reader(&self.agg, reader, &self.limits)
+        AggregationSegmentCollector::from_agg_req_and_reader(
+            &self.agg,
+            reader,
+            self.max_bucket_count,
+        )
     }
 
     fn requires_scoring(&self) -> bool {
@@ -104,7 +119,7 @@ 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.limits)
+        res.into_final_bucket_result(self.agg.clone(), &self.schema)
     }
 }
 
@@ -125,7 +140,7 @@ fn merge_fruits(
 /// `AggregationSegmentCollector` does the aggregation collection on a segment.
 pub struct AggregationSegmentCollector {
     aggs_with_accessor: AggregationsWithAccessor,
-    agg_collector: BufAggregationCollector,
+    result: Box<dyn SegmentAggregationCollector>,
     error: Option<TantivyError>,
 }
 
@@ -135,14 +150,14 @@ impl AggregationSegmentCollector {
     pub fn from_agg_req_and_reader(
         agg: &Aggregations,
         reader: &SegmentReader,
-        limits: &AggregationLimits,
+        max_bucket_count: u32,
     ) -> crate::Result<Self> {
-        let aggs_with_accessor = get_aggs_with_accessor_and_validate(agg, reader, limits)?;
-        let result =
-            BufAggregationCollector::new(build_segment_agg_collector(&aggs_with_accessor)?);
+        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)?;
         Ok(AggregationSegmentCollector {
             aggs_with_accessor,
-            agg_collector: result,
+            result,
             error: None,
         })
     }
@@ -152,26 +167,11 @@ impl SegmentCollector for AggregationSegmentCollector {
     type Fruit = crate::Result<IntermediateAggregationResults>;
 
     #[inline]
-    fn collect(&mut self, doc: DocId, _score: crate::Score) {
+    fn collect(&mut self, doc: crate::DocId, _score: crate::Score) {
         if self.error.is_some() {
             return;
         }
-        if let Err(err) = self.agg_collector.collect(doc, &self.aggs_with_accessor) {
-            self.error = Some(err);
-        }
-    }
-
-    /// The query pushes the documents to the collector via this method.
-    ///
-    /// Only valid for Collectors that ignore docs
-    fn collect_block(&mut self, docs: &[DocId]) {
-        if self.error.is_some() {
-            return;
-        }
-        if let Err(err) = self
-            .agg_collector
-            .collect_block(docs, &self.aggs_with_accessor)
-        {
+        if let Err(err) = self.result.collect(doc, &self.aggs_with_accessor) {
             self.error = Some(err);
         }
     }
@@ -180,7 +180,9 @@ impl SegmentCollector for AggregationSegmentCollector {
         if let Some(err) = self.error {
             return Err(err);
         }
-        self.agg_collector.flush(&self.aggs_with_accessor)?;
-        Box::new(self.agg_collector).into_intermediate_aggregations_result(&self.aggs_with_accessor)
+        self.result
+            .flush_staged_docs(&self.aggs_with_accessor, true)?;
+        self.result
+            .into_intermediate_aggregations_result(&self.aggs_with_accessor)
     }
 }

src/aggregation/error.rs

@@ -1,33 +0,0 @@
-use common::ByteCount;
-
-use super::bucket::DateHistogramParseError;
-
-/// Error that may occur when opening a directory
-#[derive(Debug, Clone, PartialEq, Eq, Error)]
-pub enum AggregationError {
-    /// Date histogram parse error
-    #[error("Date histogram parse error: {0:?}")]
-    DateHistogramParseError(#[from] DateHistogramParseError),
-    /// Memory limit exceeded
-    #[error(
-        "Aborting aggregation because memory limit was exceeded. Limit: {limit:?}, Current: \
-         {current:?}"
-    )]
-    MemoryExceeded {
-        /// Memory consumption limit
-        limit: ByteCount,
-        /// Current memory consumption
-        current: ByteCount,
-    },
-    /// Bucket limit exceeded
-    #[error(
-        "Aborting aggregation because bucket limit was exceeded. Limit: {limit:?}, Current: \
-         {current:?}"
-    )]
-    BucketLimitExceeded {
-        /// Bucket limit
-        limit: u32,
-        /// Current num buckets
-        current: u32,
-    },
-}

src/aggregation/intermediate_agg_result.rs

@@ -4,7 +4,6 @@
 
 use std::cmp::Ordering;
 
-use columnar::ColumnType;
 use itertools::Itertools;
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
@@ -22,11 +21,11 @@ use super::metric::{
     IntermediateAverage, IntermediateCount, IntermediateMax, IntermediateMin, IntermediateStats,
     IntermediateSum,
 };
-use super::segment_agg_result::AggregationLimits;
-use super::{format_date, AggregationError, Key, SerializedKey, VecWithNames};
+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::TantivyError;
+use crate::schema::Schema;
 
 /// Contains the intermediate aggregation result, which is optimized to be merged with other
 /// intermediate results.
@@ -43,20 +42,9 @@ impl IntermediateAggregationResults {
     pub fn into_final_bucket_result(
         self,
         req: Aggregations,
-        limits: &AggregationLimits,
+        schema: &Schema,
     ) -> crate::Result<AggregationResults> {
-        // TODO count and validate buckets
-        let res = self.into_final_bucket_result_internal(&(req.into()), limits)?;
-        let bucket_count = res.get_bucket_count() as u32;
-        if bucket_count > limits.get_bucket_limit() {
-            return Err(TantivyError::AggregationError(
-                AggregationError::BucketLimitExceeded {
-                    limit: limits.get_bucket_limit(),
-                    current: bucket_count,
-                },
-            ));
-        }
-        Ok(res)
+        self.into_final_bucket_result_internal(&(req.into()), schema)
     }
 
     /// Convert intermediate result and its aggregation request to the final result.
@@ -66,7 +54,7 @@ impl IntermediateAggregationResults {
     pub(crate) fn into_final_bucket_result_internal(
         self,
         req: &AggregationsInternal,
-        limits: &AggregationLimits,
+        schema: &Schema,
     ) -> crate::Result<AggregationResults> {
         // Important assumption:
         // When the tree contains buckets/metric, we expect it to have all buckets/metrics from the
@@ -74,11 +62,11 @@ 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, limits)?
+            convert_and_add_final_buckets_to_result(&mut results, buckets, &req.buckets, schema)?
         } 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, limits)?
+            add_empty_final_buckets_to_result(&mut results, &req.buckets, schema)?
         };
 
         if let Some(metrics) = self.metrics {
@@ -179,12 +167,12 @@ fn add_empty_final_metrics_to_result(
 fn add_empty_final_buckets_to_result(
     results: &mut FxHashMap<String, AggregationResult>,
     req_buckets: &VecWithNames<BucketAggregationInternal>,
-    limits: &AggregationLimits,
+    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, limits)?);
+            AggregationResult::BucketResult(BucketResult::empty_from_req(req, schema)?);
         results.insert(key.to_string(), empty_bucket);
     }
     Ok(())
@@ -194,13 +182,13 @@ fn convert_and_add_final_buckets_to_result(
     results: &mut FxHashMap<String, AggregationResult>,
     buckets: VecWithNames<IntermediateBucketResult>,
     req_buckets: &VecWithNames<BucketAggregationInternal>,
-    limits: &AggregationLimits,
+    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, limits)?);
+        let result = AggregationResult::BucketResult(bucket.into_final_bucket_result(req, schema)?);
         results.insert(key, result);
     }
     Ok(())
@@ -232,6 +220,32 @@ 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 {
@@ -295,8 +309,6 @@ 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>,
     },
@@ -308,7 +320,7 @@ impl IntermediateBucketResult {
     pub(crate) fn into_final_bucket_result(
         self,
         req: &BucketAggregationInternal,
-        limits: &AggregationLimits,
+        schema: &Schema,
     ) -> crate::Result<BucketResult> {
         match self {
             IntermediateBucketResult::Range(range_res) => {
@@ -318,10 +330,9 @@ 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,
-                            limits,
                         )
                     })
                     .collect::<crate::Result<Vec<_>>>()?;
@@ -348,22 +359,16 @@ impl IntermediateBucketResult {
                 };
                 Ok(BucketResult::Range { buckets })
             }
-            IntermediateBucketResult::Histogram {
-                column_type,
-                buckets,
-            } => {
-                let histogram_req = &req
-                    .as_histogram()?
-                    .expect("unexpected aggregation, expected histogram aggregation");
+            IntermediateBucketResult::Histogram { buckets } => {
                 let buckets = intermediate_histogram_buckets_to_final_buckets(
                     buckets,
-                    column_type,
-                    histogram_req,
+                    req.as_histogram()
+                        .expect("unexpected aggregation, expected histogram aggregation"),
                     &req.sub_aggregation,
-                    limits,
+                    schema,
                 )?;
 
-                let buckets = if histogram_req.keyed {
+                let buckets = if req.as_histogram().unwrap().keyed {
                     let mut bucket_map =
                         FxHashMap::with_capacity_and_hasher(buckets.len(), Default::default());
                     for bucket in buckets {
@@ -379,7 +384,7 @@ impl IntermediateBucketResult {
                 req.as_term()
                     .expect("unexpected aggregation, expected term aggregation"),
                 &req.sub_aggregation,
-                limits,
+                schema,
             ),
         }
     }
@@ -388,11 +393,8 @@ impl IntermediateBucketResult {
         match req {
             BucketAggregationType::Terms(_) => IntermediateBucketResult::Terms(Default::default()),
             BucketAggregationType::Range(_) => IntermediateBucketResult::Range(Default::default()),
-            BucketAggregationType::Histogram(_) | BucketAggregationType::DateHistogram(_) => {
-                IntermediateBucketResult::Histogram {
-                    buckets: vec![],
-                    column_type: None,
-                }
+            BucketAggregationType::Histogram(_) => {
+                IntermediateBucketResult::Histogram { buckets: vec![] }
             }
         }
     }
@@ -402,7 +404,7 @@ impl IntermediateBucketResult {
                 IntermediateBucketResult::Terms(term_res_left),
                 IntermediateBucketResult::Terms(term_res_right),
             ) => {
-                merge_key_maps(&mut term_res_left.entries, term_res_right.entries);
+                merge_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;
@@ -412,7 +414,7 @@ impl IntermediateBucketResult {
                 IntermediateBucketResult::Range(range_res_left),
                 IntermediateBucketResult::Range(range_res_right),
             ) => {
-                merge_serialized_key_maps(&mut range_res_left.buckets, range_res_right.buckets);
+                merge_maps(&mut range_res_left.buckets, range_res_right.buckets);
             }
             (
                 IntermediateBucketResult::Histogram {
@@ -458,13 +460,12 @@ 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<Key, IntermediateTermBucketEntry>,
+    pub(crate) entries: FxHashMap<String, IntermediateTermBucketEntry>,
     pub(crate) sum_other_doc_count: u64,
     pub(crate) doc_count_error_upper_bound: u64,
 }
@@ -474,7 +475,7 @@ impl IntermediateTermBucketResult {
         self,
         req: &TermsAggregation,
         sub_aggregation_req: &AggregationsInternal,
-        limits: &AggregationLimits,
+        schema: &Schema,
     ) -> crate::Result<BucketResult> {
         let req = TermsAggregationInternal::from_req(req);
         let mut buckets: Vec<BucketEntry> = self
@@ -484,11 +485,11 @@ impl IntermediateTermBucketResult {
             .map(|(key, entry)| {
                 Ok(BucketEntry {
                     key_as_string: None,
-                    key,
+                    key: Key::Str(key),
                     doc_count: entry.doc_count,
                     sub_aggregation: entry
                         .sub_aggregation
-                        .into_final_bucket_result_internal(sub_aggregation_req, limits)?,
+                        .into_final_bucket_result_internal(sub_aggregation_req, schema)?,
                 })
             })
             .collect::<crate::Result<_>>()?;
@@ -497,7 +498,7 @@ impl IntermediateTermBucketResult {
         match req.order.target {
             OrderTarget::Key => {
                 buckets.sort_by(|left, right| {
-                    if req.order.order == Order::Asc {
+                    if req.order.order == Order::Desc {
                         left.key.partial_cmp(&right.key)
                     } else {
                         right.key.partial_cmp(&left.key)
@@ -520,7 +521,7 @@ impl IntermediateTermBucketResult {
                         let val = bucket
                             .sub_aggregation
                             .get_value_from_aggregation(agg_name, agg_property)?
-                            .unwrap_or(f64::MIN);
+                            .unwrap_or(f64::NAN);
                         Ok((bucket, val))
                     })
                     .collect::<crate::Result<Vec<_>>>()?;
@@ -562,7 +563,7 @@ trait MergeFruits {
     fn merge_fruits(&mut self, other: Self);
 }
 
-fn merge_serialized_key_maps<V: MergeFruits + Clone>(
+fn merge_maps<V: MergeFruits + Clone>(
     entries_left: &mut FxHashMap<SerializedKey, V>,
     mut entries_right: FxHashMap<SerializedKey, V>,
 ) {
@@ -577,21 +578,6 @@ fn merge_serialized_key_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)]
@@ -608,7 +594,7 @@ impl IntermediateHistogramBucketEntry {
     pub(crate) fn into_final_bucket_entry(
         self,
         req: &AggregationsInternal,
-        limits: &AggregationLimits,
+        schema: &Schema,
     ) -> crate::Result<BucketEntry> {
         Ok(BucketEntry {
             key_as_string: None,
@@ -616,7 +602,7 @@ impl IntermediateHistogramBucketEntry {
             doc_count: self.doc_count,
             sub_aggregation: self
                 .sub_aggregation
-                .into_final_bucket_result_internal(req, limits)?,
+                .into_final_bucket_result_internal(req, schema)?,
         })
     }
 }
@@ -653,16 +639,15 @@ impl IntermediateRangeBucketEntry {
     pub(crate) fn into_final_bucket_entry(
         self,
         req: &AggregationsInternal,
-        _range_req: &RangeAggregation,
-        column_type: Option<ColumnType>,
-        limits: &AggregationLimits,
+        schema: &Schema,
+        range_req: &RangeAggregation,
     ) -> 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, limits)?,
+                .into_final_bucket_result_internal(req, schema)?,
             to: self.to,
             from: self.from,
             to_as_string: None,
@@ -671,7 +656,8 @@ impl IntermediateRangeBucketEntry {
 
         // If we have a date type on the histogram buckets, we add the `key_as_string` field as
         // rfc339
-        if column_type == Some(ColumnType::DateTime) {
+        let field = schema.get_field(&range_req.field)?;
+        if schema.get_field_entry(field).field_type().is_date() {
             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);
@@ -742,10 +728,7 @@ mod tests {
         }
         map.insert(
             "my_agg_level2".to_string(),
-            IntermediateBucketResult::Range(IntermediateRangeBucketResult {
-                buckets,
-                column_type: None,
-            }),
+            IntermediateBucketResult::Range(IntermediateRangeBucketResult { buckets }),
         );
         IntermediateAggregationResults {
             buckets: Some(VecWithNames::from_entries(map.into_iter().collect())),
@@ -775,10 +758,7 @@ mod tests {
         }
         map.insert(
             "my_agg_level1".to_string(),
-            IntermediateBucketResult::Range(IntermediateRangeBucketResult {
-                buckets,
-                column_type: None,
-            }),
+            IntermediateBucketResult::Range(IntermediateRangeBucketResult { buckets }),
         );
         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, Default::default());
+        let collector = AggregationCollector::from_aggs(aggregations, None, index.schema());
         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::{Cardinality, Column, ColumnType};
+use columnar::Column;
 use serde::{Deserialize, Serialize};
 
 use super::*;
@@ -8,6 +8,7 @@ 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
@@ -152,54 +153,36 @@ pub(crate) enum SegmentStatsType {
 
 #[derive(Clone, Debug, PartialEq)]
 pub(crate) struct SegmentStatsCollector {
-    field_type: ColumnType,
+    field_type: Type,
     pub(crate) collecting_for: SegmentStatsType,
     pub(crate) stats: IntermediateStats,
-    pub(crate) accessor_idx: usize,
-    val_cache: Vec<u64>,
 }
 
 impl SegmentStatsCollector {
-    pub fn from_req(
-        field_type: ColumnType,
-        collecting_for: SegmentStatsType,
-        accessor_idx: usize,
-    ) -> Self {
+    pub fn from_req(field_type: Type, collecting_for: SegmentStatsType) -> Self {
         Self {
             field_type,
             collecting_for,
             stats: IntermediateStats::default(),
-            accessor_idx,
-            val_cache: Default::default(),
         }
     }
-    #[inline]
-    pub(crate) fn collect_block_with_field(&mut self, docs: &[DocId], field: &Column<u64>) {
-        if field.get_cardinality() == Cardinality::Full {
-            self.val_cache.resize(docs.len(), 0);
-            field.values.get_vals(docs, &mut self.val_cache);
-            for val in self.val_cache.iter() {
-                let val1 = f64_from_fastfield_u64(*val, &self.field_type);
+    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) {
+                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);
-                }
-            }
         }
     }
 }
 
 impl SegmentAggregationCollector for SegmentStatsCollector {
-    #[inline]
     fn into_intermediate_aggregations_result(
         self: Box<Self>,
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<IntermediateAggregationResults> {
-        let name = agg_with_accessor.metrics.keys[self.accessor_idx].to_string();
+        let name = agg_with_accessor.metrics.keys[0].to_string();
 
         let intermediate_metric_result = match self.collecting_for {
             SegmentStatsType::Average => {
@@ -231,15 +214,13 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
         })
     }
 
-    #[inline]
     fn collect(
         &mut self,
         doc: crate::DocId,
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<()> {
-        let field = &agg_with_accessor.metrics.values[self.accessor_idx].accessor;
-
-        for val in field.values_for_doc(doc) {
+        let accessor = &agg_with_accessor.metrics.values[0].accessor;
+        for val in accessor.values(doc) {
             let val1 = f64_from_fastfield_u64(val, &self.field_type);
             self.stats.collect(val1);
         }
@@ -247,14 +228,11 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
         Ok(())
     }
 
-    #[inline]
-    fn collect_block(
+    fn flush_staged_docs(
         &mut self,
-        docs: &[crate::DocId],
-        agg_with_accessor: &AggregationsWithAccessor,
+        _agg_with_accessor: &AggregationsWithAccessor,
+        _force_flush: bool,
     ) -> crate::Result<()> {
-        let field = &agg_with_accessor.metrics.values[self.accessor_idx].accessor;
-        self.collect_block_with_field(docs, field);
         Ok(())
     }
 }
@@ -294,7 +272,7 @@ mod tests {
         .into_iter()
         .collect();
 
-        let collector = AggregationCollector::from_aggs(agg_req_1, Default::default());
+        let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
 
         let reader = index.reader()?;
         let searcher = reader.searcher();
@@ -315,43 +293,6 @@ 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, Default::default());
-
-        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)?;
@@ -385,33 +326,30 @@ mod tests {
             ),
             (
                 "range".to_string(),
-                Aggregation::Bucket(
-                    BucketAggregation {
-                        bucket_agg: BucketAggregationType::Range(RangeAggregation {
-                            field: "score".to_string(),
-                            ranges: vec![
-                                (3f64..7f64).into(),
-                                (7f64..19f64).into(),
-                                (19f64..20f64).into(),
-                            ],
-                            ..Default::default()
-                        }),
-                        sub_aggregation: iter::once((
-                            "stats".to_string(),
-                            Aggregation::Metric(MetricAggregation::Stats(
-                                StatsAggregation::from_field_name("score".to_string()),
-                            )),
-                        ))
-                        .collect(),
-                    }
-                    .into(),
-                ),
+                Aggregation::Bucket(BucketAggregation {
+                    bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                        field: "score".to_string(),
+                        ranges: vec![
+                            (3f64..7f64).into(),
+                            (7f64..19f64).into(),
+                            (19f64..20f64).into(),
+                        ],
+                        ..Default::default()
+                    }),
+                    sub_aggregation: iter::once((
+                        "stats".to_string(),
+                        Aggregation::Metric(MetricAggregation::Stats(
+                            StatsAggregation::from_field_name("score".to_string()),
+                        )),
+                    ))
+                    .collect(),
+                }),
             ),
         ]
         .into_iter()
         .collect();
 
-        let collector = AggregationCollector::from_aggs(agg_req_1, Default::default());
+        let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
 
         let searcher = reader.searcher();
         let agg_res: AggregationResults = searcher.search(&term_query, &collector).unwrap();