Removed azure stuff

* add date_histogram

* add return result

.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 --lcov --output-path lcov.info
+        run: cargo +nightly llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
       - name: Upload coverage to Codecov
         uses: codecov/codecov-action@v3
         continue-on-error: true

Cargo.toml

@@ -16,14 +16,13 @@ rust-version = "1.62"
 [dependencies]
 oneshot = "0.1.5"
 base64 = "0.21.0"
-byteorder = "1.4.3"
 crc32fast = "1.3.2"
 once_cell = "1.10.0"
 regex = { version = "1.5.5", default-features = false, features = ["std", "unicode"] }
 aho-corasick = "0.7"
 tantivy-fst = "0.4.0"
 memmap2 = { version = "0.5.3", optional = true }
-lz4_flex = { version = "0.9.2", default-features = false, features = ["checked-decode"], optional = true }
+lz4_flex = { version = "0.10", 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 }
@@ -44,7 +43,7 @@ rustc-hash = "1.1.0"
 thiserror = "1.0.30"
 htmlescape = "0.3.1"
 fail = "0.5.0"
-murmurhash32 = "0.2.0"
+murmurhash32 = "0.3.0"
 time = { version = "0.3.10", features = ["serde-well-known"] }
 smallvec = "1.8.0"
 rayon = "1.5.2"
@@ -55,12 +54,12 @@ measure_time = "0.8.2"
 async-trait = "0.1.53"
 arc-swap = "1.5.0"
 
+columnar = { version="0.1", path="./columnar", package ="tantivy-columnar" }
 sstable = { version="0.1", path="./sstable", package ="tantivy-sstable", optional = true }
 stacker = { version="0.1", path="./stacker", package ="tantivy-stacker" }
-tantivy-query-grammar = { version= "0.19.0", path="./query-grammar" }
-tantivy-bitpacker = 		{ version= "0.3", path="./bitpacker" }
-columnar = 		{ version= "0.1", path="./columnar", package="tantivy-columnar" }
-common = 								{ version= "0.5", path = "./common/", package = "tantivy-common" }
+query-grammar = { version= "0.19.0", path="./query-grammar", package = "tantivy-query-grammar" }
+tantivy-bitpacker = { version= "0.3", path="./bitpacker" }
+common = { version= "0.5", path = "./common/", package = "tantivy-common" }
 tokenizer-api = { version="0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
 
 [target.'cfg(windows)'.dependencies]
@@ -77,6 +76,7 @@ test-log = "0.2.10"
 env_logger = "0.10.0"
 pprof = { version = "0.11.0", features = ["flamegraph", "criterion"] }
 futures = "0.3.21"
+paste = "1.0.11"
 
 [dev-dependencies.fail]
 version = "0.5.0"

ci/before_deploy.ps1

@@ -1,23 +0,0 @@
-# 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

@@ -1,33 +0,0 @@
-# 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

@@ -1,47 +0,0 @@
-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

@@ -1,30 +0,0 @@
-#!/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

@@ -5,24 +5,24 @@ edition = "2021"
 license = "MIT"
 
 [dependencies]
+itertools = "0.10.5"
+log = "0.4.17"
+fnv = "1.0.7"
+fastdivide = "0.4.0"
+rand = { version = "0.8.5", optional = true }
+measure_time = { version = "0.8.2", optional = true }
+prettytable-rs = { version = "0.10.0", optional = true }
+
 stacker = { path = "../stacker", package="tantivy-stacker"}
-serde_json = "1"
-thiserror = "1"
-fnv = "1"
 sstable = { path = "../sstable", package = "tantivy-sstable" }
 common = { path = "../common", package = "tantivy-common" }
-itertools = "0.10"
-log = "0.4"
 tantivy-bitpacker = { version= "0.3", path = "../bitpacker/" }
-prettytable-rs = {version="0.10.0", optional= true}
-rand = {version="0.8.3", optional= true}
-fastdivide = "0.4"
-measure_time = { version="0.8.2", optional=true}
+serde = "1.0.152"
 
 [dev-dependencies]
 proptest = "1"
-more-asserts = "0.3.0"
-rand = "0.8.3"
+more-asserts = "0.3.1"
+rand = "0.8.5"
 
 [features]
 unstable = []

columnar/Makefile

@@ -1,6 +0,0 @@
-test:
-	echo "Run test only... No examples."
-	cargo test --tests --lib
-
-fmt:
-	cargo +nightly fmt --all

columnar/benches/bench_u128.rs

@@ -28,12 +28,7 @@ fn get_u128_column_random() -> Arc<dyn ColumnValues<u128>> {
 
 fn get_u128_column_from_data(data: &[u128]) -> Arc<dyn ColumnValues<u128>> {
     let mut out = vec![];
-    tantivy_columnar::column_values::serialize_column_values_u128(
-        &(|| data.iter().copied()),
-        data.len() as u32,
-        &mut out,
-    )
-    .unwrap();
+    tantivy_columnar::column_values::serialize_column_values_u128(&data, &mut out).unwrap();
     let out = OwnedBytes::new(out);
     tantivy_columnar::column_values::open_u128_mapped::<u128>(out).unwrap()
 }
@@ -41,7 +36,7 @@ fn get_u128_column_from_data(data: &[u128]) -> Arc<dyn ColumnValues<u128>> {
 const FIFTY_PERCENT_RANGE: RangeInclusive<u64> = 1..=50;
 const SINGLE_ITEM: u64 = 90;
 const SINGLE_ITEM_RANGE: RangeInclusive<u64> = 90..=90;
-const ONE_PERCENT_ITEM_RANGE: RangeInclusive<u64> = 49..=49;
+
 fn get_data_50percent_item() -> Vec<u128> {
     let mut rng = StdRng::from_seed([1u8; 32]);
 
@@ -63,7 +58,7 @@ fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_docids_for_value_range(
+        column.get_row_ids_for_value_range(
             *FIFTY_PERCENT_RANGE.start() as u128..=*FIFTY_PERCENT_RANGE.end() as u128,
             0..data.len() as u32,
             &mut positions,
@@ -79,7 +74,7 @@ fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_docids_for_value_range(
+        column.get_row_ids_for_value_range(
             *SINGLE_ITEM_RANGE.start() as u128..=*SINGLE_ITEM_RANGE.end() as u128,
             0..data.len() as u32,
             &mut positions,
@@ -95,7 +90,7 @@ fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_docids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
+        column.get_row_ids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
         positions
     });
 }

columnar/benches/bench_u64.rs

@@ -5,9 +5,7 @@ use std::ops::RangeInclusive;
 use std::sync::Arc;
 
 use rand::prelude::*;
-use tantivy_columnar::column_values::{
-    serialize_and_load_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
-};
+use tantivy_columnar::column_values::{serialize_and_load_u64_based_column_values, CodecType};
 use tantivy_columnar::*;
 use test::Bencher;
 
@@ -91,7 +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_docids_for_value_range(
+        column.get_row_ids_for_value_range(
             FIFTY_PERCENT_RANGE,
             0..data.len() as u32,
             &mut positions,
@@ -108,7 +106,7 @@ fn bench_intfastfield_getrange_u64_1percent_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_docids_for_value_range(
+        column.get_row_ids_for_value_range(
             ONE_PERCENT_ITEM_RANGE,
             0..data.len() as u32,
             &mut positions,
@@ -125,7 +123,7 @@ fn bench_intfastfield_getrange_u64_single_hit(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_docids_for_value_range(SINGLE_ITEM_RANGE, 0..data.len() as u32, &mut positions);
+        column.get_row_ids_for_value_range(SINGLE_ITEM_RANGE, 0..data.len() as u32, &mut positions);
         positions
     });
 }
@@ -138,7 +136,7 @@ fn bench_intfastfield_getrange_u64_hit_all(b: &mut Bencher) {
 
     b.iter(|| {
         let mut positions = Vec::new();
-        column.get_docids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
+        column.get_row_ids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
         positions
     });
 }
@@ -180,7 +178,7 @@ fn bench_intfastfield_scan_all_fflookup(b: &mut Bencher) {
     b.iter(|| {
         let mut a = 0u64;
         for i in 0u32..n as u32 {
-            a += column.get_val(i);
+            a += column_ref.get_val(i);
         }
         a
     });

columnar/columnar-cli/Cargo.toml

@@ -0,0 +1,17 @@
+[package]
+name = "tantivy-columnar-cli"
+version = "0.1.0"
+edition = "2021"
+license = "MIT"
+
+[dependencies]
+columnar = {path="../", package="tantivy-columnar"}
+serde_json = "1"
+serde_json_borrow = {git="https://github.com/PSeitz/serde_json_borrow/"}
+serde = "1"
+
+[workspace]
+members = []
+
+[profile.release]
+debug = true

columnar/columnar-cli/src/main.rs

@@ -0,0 +1,134 @@
+use columnar::ColumnarWriter;
+use columnar::NumericalValue;
+use serde_json_borrow;
+use std::fs::File;
+use std::io;
+use std::io::BufRead;
+use std::io::BufReader;
+use std::time::Instant;
+
+#[derive(Default)]
+struct JsonStack {
+    path: String,
+    stack: Vec<usize>,
+}
+
+impl JsonStack {
+    fn push(&mut self, seg: &str) {
+        let len = self.path.len();
+        self.stack.push(len);
+        self.path.push('.');
+        self.path.push_str(seg);
+    }
+
+    fn pop(&mut self) {
+        if let Some(len) = self.stack.pop() {
+            self.path.truncate(len);
+        }
+    }
+
+    fn path(&self) -> &str {
+        &self.path[1..]
+    }
+}
+
+fn append_json_to_columnar(
+    doc: u32,
+    json_value: &serde_json_borrow::Value,
+    columnar: &mut ColumnarWriter,
+    stack: &mut JsonStack,
+) -> usize {
+    let mut count = 0;
+    match json_value {
+        serde_json_borrow::Value::Null => {}
+        serde_json_borrow::Value::Bool(val) => {
+            columnar.record_numerical(
+                doc,
+                stack.path(),
+                NumericalValue::from(if *val { 1u64 } else { 0u64 }),
+            );
+            count += 1;
+        }
+        serde_json_borrow::Value::Number(num) => {
+            let numerical_value: NumericalValue = if let Some(num_i64) = num.as_i64() {
+                num_i64.into()
+            } else if let Some(num_u64) = num.as_u64() {
+                num_u64.into()
+            } else if let Some(num_f64) = num.as_f64() {
+                num_f64.into()
+            } else {
+                panic!();
+            };
+            count += 1;
+            columnar.record_numerical(
+                doc,
+                stack.path(),
+                numerical_value,
+            );
+        }
+        serde_json_borrow::Value::Str(msg) => {
+            columnar.record_str(
+                doc,
+                stack.path(),
+                msg,
+            );
+            count += 1;
+        },
+        serde_json_borrow::Value::Array(vals) => {
+            for val in vals {
+                count += append_json_to_columnar(doc, val, columnar, stack);
+            }
+        },
+        serde_json_borrow::Value::Object(json_map) => {
+            for (child_key, child_val) in json_map {
+                stack.push(child_key);
+                count += append_json_to_columnar(doc, child_val, columnar, stack);
+                stack.pop();
+            }
+        },
+    }
+    count
+}
+
+fn main() -> io::Result<()> {
+    let file = File::open("gh_small.json")?;
+    let mut reader = BufReader::new(file);
+    let mut line = String::with_capacity(100);
+    let mut columnar = columnar::ColumnarWriter::default();
+    let mut doc = 0;
+    let start = Instant::now();
+    let mut stack = JsonStack::default();
+    let mut total_count = 0;
+
+    let start_build = Instant::now();
+    loop {
+        line.clear();
+        let len = reader.read_line(&mut line)?;
+        if len == 0 {
+            break;
+        }
+        let Ok(json_value) = serde_json::from_str::<serde_json_borrow::Value>(&line) else { continue; };
+        total_count += append_json_to_columnar(doc, &json_value, &mut columnar, &mut stack);
+        doc += 1;
+    }
+    println!("Build in {:?}", start_build.elapsed());
+
+    println!("value count {total_count}");
+
+    let mut buffer = Vec::new();
+    let start_serialize = Instant::now();
+    columnar.serialize(doc, None, &mut buffer)?;
+    println!("Serialized in {:?}", start_serialize.elapsed());
+    println!("num docs: {doc}, {:?}", start.elapsed());
+    println!("buffer len {} MB", buffer.len() / 1_000_000);
+    let columnar = columnar::ColumnarReader::open(buffer)?;
+    for (column_name, dynamic_column) in columnar.list_columns()? {
+        let num_bytes = dynamic_column.num_bytes();
+        let typ = dynamic_column.column_type();
+        if num_bytes > 1_000_000 {
+            println!("{column_name} {typ:?}  {} KB", num_bytes / 1_000);
+        }
+    }
+    println!("{} columns", columnar.num_columns());
+    Ok(())
+}

columnar/src/TODO.md

@@ -1,14 +1,16 @@
 # zero to one
-* merges with non trivial mapping (deletes / sort)
-* emission of the sort mapping.
-+ muttivaued range queries restrat frm the beginning all of the time.
-* revisit line codec
-* removal of all rows of a column in the schema due to deletes
-* Plugging JSON
-replug examples
 
+* revisit line codec
+* 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

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_rows()
+        self.term_ord_column.num_docs()
     }
 
     pub fn term_ords(&self, row_id: RowId) -> impl Iterator<Item = u64> + '_ {
-        self.term_ord_column.values(row_id)
+        self.term_ord_column.values_for_doc(row_id)
     }
 
     /// Returns the column of ordinals
@@ -56,12 +56,6 @@ impl BytesColumn {
 #[derive(Clone)]
 pub struct StrColumn(BytesColumn);
 
-impl From<BytesColumn> for StrColumn {
-    fn from(bytes_col: BytesColumn) -> Self {
-        StrColumn(bytes_col)
-    }
-}
-
 impl From<StrColumn> for BytesColumn {
     fn from(str_column: StrColumn) -> BytesColumn {
         str_column.0
@@ -69,6 +63,10 @@ impl From<StrColumn> for BytesColumn {
 }
 
 impl StrColumn {
+    pub(crate) fn wrap(bytes_column: BytesColumn) -> StrColumn {
+        StrColumn(bytes_column)
+    }
+
     pub fn dictionary(&self) -> &Dictionary<VoidSSTable> {
         self.0.dictionary.as_ref()
     }

columnar/src/column/mod.rs

@@ -3,14 +3,14 @@ mod serialize;
 
 use std::fmt::Debug;
 use std::io::Write;
-use std::ops::Deref;
+use std::ops::{Deref, Range, RangeInclusive};
 use std::sync::Arc;
 
 use common::BinarySerializable;
 pub use dictionary_encoded::{BytesColumn, StrColumn};
 pub use serialize::{
-    open_column_bytes, open_column_u128, open_column_u64, serialize_column_mappable_to_u128,
-    serialize_column_mappable_to_u64,
+    open_column_bytes, open_column_str, open_column_u128, open_column_u64,
+    serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
 };
 
 use crate::column_index::ColumnIndex;
@@ -38,17 +38,20 @@ 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_rows(&self) -> RowId {
+
+    pub fn num_docs(&self) -> RowId {
         match &self.idx {
-            ColumnIndex::Full => self.values.num_vals() as u32,
-            ColumnIndex::Optional(optional_index) => optional_index.num_rows(),
+            ColumnIndex::Empty { num_docs } => *num_docs,
+            ColumnIndex::Full => self.values.num_vals(),
+            ColumnIndex::Optional(optional_index) => optional_index.num_docs(),
             ColumnIndex::Multivalued(col_index) => {
                 // The multivalued index contains all value start row_id,
                 // and one extra value at the end with the overall number of rows.
-                col_index.num_rows()
+                col_index.num_docs()
             }
         }
     }
@@ -62,14 +65,42 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
     }
 
     pub fn first(&self, row_id: RowId) -> Option<T> {
-        self.values(row_id).next()
+        self.values_for_doc(row_id).next()
     }
 
-    pub fn values(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
+    pub fn values_for_doc(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
         self.value_row_ids(row_id)
             .map(|value_row_id: RowId| self.values.get_val(value_row_id))
     }
 
+    /// 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));
+    }
+
     pub fn first_or_default_col(self, default_value: T) -> Arc<dyn ColumnValues<T>> {
         Arc::new(FirstValueWithDefault {
             column: self,
@@ -121,9 +152,10 @@ 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_rows(),
-            ColumnIndex::Multivalued(_) => todo!(),
+            ColumnIndex::Optional(optional_idx) => optional_idx.num_docs(),
+            ColumnIndex::Multivalued(multivalue_idx) => multivalue_idx.num_docs(),
         }
     }
 }

columnar/src/column/serialize.rs

@@ -1,4 +1,3 @@
-use std::fmt::Debug;
 use std::io;
 use std::io::Write;
 use std::sync::Arc;
@@ -8,24 +7,25 @@ use sstable::Dictionary;
 
 use crate::column::{BytesColumn, Column};
 use crate::column_index::{serialize_column_index, SerializableColumnIndex};
-use crate::column_values::serialize::serialize_column_values_u128;
-use crate::column_values::u64_based::{serialize_u64_based_column_values, CodecType};
-use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
+use crate::column_values::{
+    load_u64_based_column_values, serialize_column_values_u128, serialize_u64_based_column_values,
+    CodecType, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
+};
 use crate::iterable::Iterable;
+use crate::StrColumn;
 
 pub fn serialize_column_mappable_to_u128<T: MonotonicallyMappableToU128>(
     column_index: SerializableColumnIndex<'_>,
     iterable: &dyn Iterable<T>,
-    num_vals: u32,
     output: &mut impl Write,
 ) -> io::Result<()> {
     let column_index_num_bytes = serialize_column_index(column_index, output)?;
-    serialize_column_values_u128(iterable, num_vals, output)?;
+    serialize_column_values_u128(iterable, output)?;
     output.write_all(&column_index_num_bytes.to_le_bytes())?;
     Ok(())
 }
 
-pub fn serialize_column_mappable_to_u64<T: MonotonicallyMappableToU64 + Debug>(
+pub fn serialize_column_mappable_to_u64<T: MonotonicallyMappableToU64>(
     column_index: SerializableColumnIndex<'_>,
     column_values: &impl Iterable<T>,
     output: &mut impl Write,
@@ -50,8 +50,7 @@ pub fn open_column_u64<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::
     );
     let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
     let column_index = crate::column_index::open_column_index(column_index_data)?;
-    let column_values =
-        crate::column_values::u64_based::load_u64_based_column_values(column_values_data)?;
+    let column_values = load_u64_based_column_values(column_values_data)?;
     Ok(Column {
         idx: column_index,
         values: column_values,
@@ -77,15 +76,19 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
     })
 }
 
-pub fn open_column_bytes<T: From<BytesColumn>>(data: OwnedBytes) -> io::Result<T> {
+pub fn open_column_bytes(data: OwnedBytes) -> io::Result<BytesColumn> {
     let (body, dictionary_len_bytes) = data.rsplit(4);
     let dictionary_len = u32::from_le_bytes(dictionary_len_bytes.as_slice().try_into().unwrap());
     let (dictionary_bytes, column_bytes) = body.split(dictionary_len as usize);
     let dictionary = Arc::new(Dictionary::from_bytes(dictionary_bytes)?);
     let term_ord_column = crate::column::open_column_u64::<u64>(column_bytes)?;
-    let bytes_column = BytesColumn {
+    Ok(BytesColumn {
         dictionary,
         term_ord_column,
-    };
-    Ok(bytes_column.into())
+    })
+}
+
+pub fn open_column_str(data: OwnedBytes) -> io::Result<StrColumn> {
+    let bytes_column = open_column_bytes(data)?;
+    Ok(StrColumn::wrap(bytes_column))
 }

columnar/src/column_index/merge/mod.rs

@@ -0,0 +1,136 @@
+mod shuffled;
+mod stacked;
+
+use shuffled::merge_column_index_shuffled;
+use stacked::merge_column_index_stacked;
+
+use crate::column_index::SerializableColumnIndex;
+use crate::{Cardinality, ColumnIndex, MergeRowOrder};
+
+// For simplification, we never have cardinality go down due to deletes.
+fn detect_cardinality(columns: &[Option<ColumnIndex>]) -> Cardinality {
+    columns
+        .iter()
+        .flatten()
+        .map(ColumnIndex::get_cardinality)
+        .max()
+        .unwrap_or(Cardinality::Full)
+}
+
+pub fn merge_column_index<'a>(
+    columns: &'a [Option<ColumnIndex>],
+    merge_row_order: &'a MergeRowOrder,
+) -> SerializableColumnIndex<'a> {
+    // For simplification, we do not try to detect whether the cardinality could be
+    // downgraded thanks to deletes.
+    let cardinality_after_merge = detect_cardinality(columns);
+    match merge_row_order {
+        MergeRowOrder::Stack(stack_merge_order) => {
+            merge_column_index_stacked(columns, cardinality_after_merge, stack_merge_order)
+        }
+        MergeRowOrder::Shuffled(complex_merge_order) => {
+            merge_column_index_shuffled(columns, cardinality_after_merge, complex_merge_order)
+        }
+    }
+}
+
+// TODO actually, the shuffled code path is a bit too general.
+// In practise, we do not really shuffle everything.
+// The merge order restricted to a specific column keeps the original row order.
+//
+// This may offer some optimization that we have not explored yet.
+
+#[cfg(test)]
+mod tests {
+    use crate::column_index::merge::detect_cardinality;
+    use crate::column_index::multivalued_index::MultiValueIndex;
+    use crate::column_index::{merge_column_index, OptionalIndex, SerializableColumnIndex};
+    use crate::{Cardinality, ColumnIndex, MergeRowOrder, RowAddr, RowId, ShuffleMergeOrder};
+
+    #[test]
+    fn test_detect_cardinality() {
+        assert_eq!(detect_cardinality(&[]), Cardinality::Full);
+        let optional_index: ColumnIndex = OptionalIndex::for_test(1, &[]).into();
+        let multivalued_index: ColumnIndex = MultiValueIndex::for_test(&[0, 1]).into();
+        assert_eq!(
+            detect_cardinality(&[Some(optional_index.clone()), None]),
+            Cardinality::Optional
+        );
+        assert_eq!(
+            detect_cardinality(&[Some(optional_index.clone()), Some(ColumnIndex::Full)]),
+            Cardinality::Optional
+        );
+        assert_eq!(
+            detect_cardinality(&[Some(multivalued_index.clone()), None]),
+            Cardinality::Multivalued
+        );
+        assert_eq!(
+            detect_cardinality(&[
+                Some(multivalued_index.clone()),
+                Some(optional_index.clone())
+            ]),
+            Cardinality::Multivalued
+        );
+        assert_eq!(
+            detect_cardinality(&[Some(optional_index), Some(multivalued_index)]),
+            Cardinality::Multivalued
+        );
+    }
+
+    #[test]
+    fn test_merge_index_multivalued_sorted() {
+        let column_indexes: Vec<Option<ColumnIndex>> =
+            vec![Some(MultiValueIndex::for_test(&[0, 2, 5]).into())];
+        let merge_row_order: MergeRowOrder = ShuffleMergeOrder::for_test(
+            &[2],
+            vec![
+                RowAddr {
+                    segment_ord: 0u32,
+                    row_id: 1u32,
+                },
+                RowAddr {
+                    segment_ord: 0u32,
+                    row_id: 0u32,
+                },
+            ],
+        )
+        .into();
+        let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
+        let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
+        else { panic!("Excpected a multivalued index") };
+        let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
+        assert_eq!(&start_indexes, &[0, 3, 5]);
+    }
+
+    #[test]
+    fn test_merge_index_multivalued_sorted_several_segment() {
+        let column_indexes: Vec<Option<ColumnIndex>> = vec![
+            Some(MultiValueIndex::for_test(&[0, 2, 5]).into()),
+            None,
+            Some(MultiValueIndex::for_test(&[0, 1, 4]).into()),
+        ];
+        let merge_row_order: MergeRowOrder = ShuffleMergeOrder::for_test(
+            &[2, 0, 2],
+            vec![
+                RowAddr {
+                    segment_ord: 2u32,
+                    row_id: 1u32,
+                },
+                RowAddr {
+                    segment_ord: 0u32,
+                    row_id: 0u32,
+                },
+                RowAddr {
+                    segment_ord: 2u32,
+                    row_id: 0u32,
+                },
+            ],
+        )
+        .into();
+        let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
+        let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
+        else { panic!("Excpected a multivalued index") };
+        let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
+        assert_eq!(&start_indexes, &[0, 3, 5, 6]);
+    }
+}

columnar/src/column_index/merge/shuffled.rs

@@ -0,0 +1,168 @@
+use std::iter;
+
+use crate::column_index::{SerializableColumnIndex, Set};
+use crate::iterable::Iterable;
+use crate::{Cardinality, ColumnIndex, RowId, ShuffleMergeOrder};
+
+pub fn merge_column_index_shuffled<'a>(
+    column_indexes: &'a [Option<ColumnIndex>],
+    cardinality_after_merge: Cardinality,
+    shuffle_merge_order: &'a ShuffleMergeOrder,
+) -> SerializableColumnIndex<'a> {
+    match cardinality_after_merge {
+        Cardinality::Full => SerializableColumnIndex::Full,
+        Cardinality::Optional => {
+            let non_null_row_ids =
+                merge_column_index_shuffled_optional(column_indexes, shuffle_merge_order);
+            SerializableColumnIndex::Optional {
+                non_null_row_ids,
+                num_rows: shuffle_merge_order.num_rows(),
+            }
+        }
+        Cardinality::Multivalued => {
+            let multivalue_start_index =
+                merge_column_index_shuffled_multivalued(column_indexes, shuffle_merge_order);
+            SerializableColumnIndex::Multivalued(multivalue_start_index)
+        }
+    }
+}
+
+/// Merge several column indexes into one, ordering rows according to the merge_order passed as
+/// argument. While it is true that the `merge_order` may imply deletes and hence could in theory a
+/// multivalued index into an optional one, this is not supported today for simplification.
+///
+/// In other words the column_indexes passed as argument may NOT be multivalued.
+fn merge_column_index_shuffled_optional<'a>(
+    column_indexes: &'a [Option<ColumnIndex>],
+    merge_order: &'a ShuffleMergeOrder,
+) -> Box<dyn Iterable<RowId> + 'a> {
+    Box::new(ShuffledOptionalIndex {
+        column_indexes,
+        merge_order,
+    })
+}
+
+struct ShuffledOptionalIndex<'a> {
+    column_indexes: &'a [Option<ColumnIndex>],
+    merge_order: &'a ShuffleMergeOrder,
+}
+
+impl<'a> Iterable<u32> for ShuffledOptionalIndex<'a> {
+    fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
+        Box::new(self.merge_order
+        .iter_new_to_old_row_addrs()
+        .enumerate()
+        .filter_map(|(new_row_id, old_row_addr)| {
+            let Some(column_index) = &self.column_indexes[old_row_addr.segment_ord as usize] else {
+                return None;
+            };
+            let row_id = new_row_id as u32;
+            if column_index.has_value(old_row_addr.row_id) {
+                Some(row_id)
+            } else {
+                None
+            }
+        }))
+    }
+}
+
+fn merge_column_index_shuffled_multivalued<'a>(
+    column_indexes: &'a [Option<ColumnIndex>],
+    merge_order: &'a ShuffleMergeOrder,
+) -> Box<dyn Iterable<RowId> + 'a> {
+    Box::new(ShuffledMultivaluedIndex {
+        column_indexes,
+        merge_order,
+    })
+}
+
+struct ShuffledMultivaluedIndex<'a> {
+    column_indexes: &'a [Option<ColumnIndex>],
+    merge_order: &'a ShuffleMergeOrder,
+}
+
+fn iter_num_values<'a>(
+    column_indexes: &'a [Option<ColumnIndex>],
+    merge_order: &'a ShuffleMergeOrder,
+) -> impl Iterator<Item = u32> + 'a {
+    merge_order.iter_new_to_old_row_addrs().map(|row_addr| {
+        let Some(column_index) = &column_indexes[row_addr.segment_ord as usize] else {
+                    // No values in the entire column. It surely means there are 0 values associated to this row.
+                    return 0u32;
+                };
+        match column_index {
+            ColumnIndex::Empty { .. } => 0u32,
+            ColumnIndex::Full => 1,
+            ColumnIndex::Optional(optional_index) => {
+                u32::from(optional_index.contains(row_addr.row_id))
+            }
+            ColumnIndex::Multivalued(multivalued_index) => {
+                multivalued_index.range(row_addr.row_id).len() as u32
+            }
+        }
+    })
+}
+
+/// Transforms an iterator containing the number of vals per row (with `num_rows` elements)
+/// into a `start_offset` iterator starting at 0 and (with `num_rows + 1` element)
+fn integrate_num_vals(num_vals: impl Iterator<Item = u32>) -> impl Iterator<Item = RowId> {
+    iter::once(0u32).chain(num_vals.scan(0, |state, num_vals| {
+        *state += num_vals;
+        Some(*state)
+    }))
+}
+
+impl<'a> Iterable<u32> for ShuffledMultivaluedIndex<'a> {
+    fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
+        let num_vals_per_row = iter_num_values(self.column_indexes, self.merge_order);
+        Box::new(integrate_num_vals(num_vals_per_row))
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::column_index::OptionalIndex;
+    use crate::RowAddr;
+
+    #[test]
+    fn test_integrate_num_vals_empty() {
+        assert!(integrate_num_vals(iter::empty()).eq(iter::once(0)));
+    }
+
+    #[test]
+    fn test_integrate_num_vals_one_el() {
+        assert!(integrate_num_vals(iter::once(10)).eq([0, 10].into_iter()));
+    }
+
+    #[test]
+    fn test_integrate_num_vals_several() {
+        assert!(integrate_num_vals([3, 0, 10, 20].into_iter()).eq([0, 3, 3, 13, 33].into_iter()));
+    }
+
+    #[test]
+    fn test_merge_column_index_optional_shuffle() {
+        let optional_index: ColumnIndex = OptionalIndex::for_test(2, &[0]).into();
+        let column_indexes = vec![Some(optional_index), Some(ColumnIndex::Full)];
+        let row_addrs = vec![
+            RowAddr {
+                segment_ord: 0u32,
+                row_id: 1u32,
+            },
+            RowAddr {
+                segment_ord: 1u32,
+                row_id: 0u32,
+            },
+        ];
+        let shuffle_merge_order = ShuffleMergeOrder::for_test(&[2, 1], row_addrs);
+        let serializable_index = merge_column_index_shuffled(
+            &column_indexes[..],
+            Cardinality::Optional,
+            &shuffle_merge_order,
+        );
+        let SerializableColumnIndex::Optional { non_null_row_ids, num_rows } = serializable_index else { panic!() };
+        assert_eq!(num_rows, 2);
+        let non_null_rows: Vec<RowId> = non_null_row_ids.boxed_iter().collect();
+        assert_eq!(&non_null_rows, &[1]);
+    }
+}

columnar/src/column_index/merge/stacked.rs

@@ -1,29 +1,19 @@
 use std::iter;
 
-use crate::column_index::{
-    multivalued_index, serialize_column_index, SerializableColumnIndex, Set,
-};
+use crate::column_index::{SerializableColumnIndex, Set};
 use crate::iterable::Iterable;
-use crate::{Cardinality, ColumnIndex, MergeRowOrder, RowId, StackMergeOrder};
+use crate::{Cardinality, ColumnIndex, RowId, StackMergeOrder};
 
-fn detect_cardinality(columns: &[Option<ColumnIndex>]) -> Cardinality {
-    columns
-        .iter()
-        .flatten()
-        .map(ColumnIndex::get_cardinality)
-        .max()
-        .unwrap_or(Cardinality::Full)
-}
-
-pub fn stack_column_index<'a>(
+/// Simple case:
+/// The new mapping just consists in stacking the different column indexes.
+///
+/// There are no sort nor deletes involved.
+pub fn merge_column_index_stacked<'a>(
     columns: &'a [Option<ColumnIndex>],
-    merge_row_order: &'a MergeRowOrder,
+    cardinality_after_merge: Cardinality,
+    stack_merge_order: &'a StackMergeOrder,
 ) -> SerializableColumnIndex<'a> {
-    let MergeRowOrder::Stack(stack_merge_order) = merge_row_order else {
-        panic!("only supporting stacking at the moment.");
-    };
-    let cardinality = detect_cardinality(columns);
-    match cardinality {
+    match cardinality_after_merge {
         Cardinality::Full => SerializableColumnIndex::Full,
         Cardinality::Optional => SerializableColumnIndex::Optional {
             non_null_row_ids: Box::new(StackedOptionalIndex {
@@ -60,12 +50,12 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
                         Some(ColumnIndex::Optional(optional_index)) => Box::new(
                             optional_index
                                 .iter_rows()
-                                .map(move |row_id: RowId| row_id + columnar_row_range.start),
+                                .map(move |row_id: RowId| columnar_row_range.start + row_id),
                         ),
                         Some(ColumnIndex::Multivalued(_)) => {
                             panic!("No multivalued index is allowed when stacking column index");
                         }
-                        None => Box::new(std::iter::empty()),
+                        None | Some(ColumnIndex::Empty { .. }) => Box::new(std::iter::empty()),
                     };
                     rows_it
                 }),
@@ -84,7 +74,9 @@ fn convert_column_opt_to_multivalued_index<'a>(
     num_rows: RowId,
 ) -> Box<dyn Iterator<Item = RowId> + 'a> {
     match column_index_opt {
-        None => Box::new(iter::repeat(0u32).take(num_rows as usize + 1)),
+        None | Some(ColumnIndex::Empty { .. }) => {
+            Box::new(iter::repeat(0u32).take(num_rows as usize + 1))
+        }
         Some(ColumnIndex::Full) => Box::new(0..num_rows + 1),
         Some(ColumnIndex::Optional(optional_index)) => {
             Box::new(
@@ -141,13 +133,6 @@ fn stack_multivalued_indexes<'a>(
     }))
 }
 
-fn stack_multivalued_index<'a>(
-    columns: &'a [Option<ColumnIndex>],
-    stack_merge_order: &StackMergeOrder,
-) -> Box<dyn Iterable<RowId> + 'a> {
-    todo!()
-}
-
 #[cfg(test)]
 mod tests {
     use crate::RowId;

columnar/src/column_index/mod.rs

@@ -5,15 +5,18 @@ mod serialize;
 
 use std::ops::Range;
 
-pub use merge::stack_column_index;
+pub use merge::merge_column_index;
 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, RowId};
+use crate::{Cardinality, DocId, RowId};
 
 #[derive(Clone)]
 pub enum ColumnIndex {
+    Empty {
+        num_docs: u32,
+    },
     Full,
     Optional(OptionalIndex),
     /// In addition, at index num_rows, an extra value is added
@@ -21,31 +24,82 @@ pub enum ColumnIndex {
     Multivalued(MultiValueIndex),
 }
 
+impl From<OptionalIndex> for ColumnIndex {
+    fn from(optional_index: OptionalIndex) -> ColumnIndex {
+        ColumnIndex::Optional(optional_index)
+    }
+}
+
+impl From<MultiValueIndex> for ColumnIndex {
+    fn from(multi_value_index: MultiValueIndex) -> ColumnIndex {
+        ColumnIndex::Multivalued(multi_value_index)
+    }
+}
+
 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,
         }
     }
 
-    pub fn value_row_ids(&self, row_id: RowId) -> Range<RowId> {
+    /// Returns true if and only if there are at least one value associated to the row.
+    pub fn has_value(&self, doc_id: DocId) -> bool {
         match self {
-            ColumnIndex::Full => row_id..row_id + 1,
+            ColumnIndex::Empty { .. } => false,
+            ColumnIndex::Full => true,
+            ColumnIndex::Optional(optional_index) => optional_index.contains(doc_id),
+            ColumnIndex::Multivalued(multivalued_index) => {
+                !multivalued_index.range(doc_id).is_empty()
+            }
+        }
+    }
+
+    pub fn value_row_ids(&self, doc_id: DocId) -> Range<RowId> {
+        match self {
+            ColumnIndex::Empty { .. } => 0..0,
+            ColumnIndex::Full => doc_id..doc_id + 1,
             ColumnIndex::Optional(optional_index) => {
-                if let Some(val) = optional_index.rank_if_exists(row_id) {
+                if let Some(val) = optional_index.rank_if_exists(doc_id) {
                     val..val + 1
                 } else {
                     0..0
                 }
             }
-            ColumnIndex::Multivalued(multivalued_index) => multivalued_index.range(row_id),
+            ColumnIndex::Multivalued(multivalued_index) => multivalued_index.range(doc_id),
         }
     }
 
-    pub fn select_batch_in_place(&self, rank_ids: &mut Vec<RowId>) {
+    pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
         match self {
+            ColumnIndex::Empty { .. } => 0..0,
+            ColumnIndex::Full => doc_id,
+            ColumnIndex::Optional(optional_index) => {
+                let row_start = optional_index.rank(doc_id.start);
+                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.
@@ -54,8 +108,7 @@ impl ColumnIndex {
                 optional_index.select_batch(&mut rank_ids[..]);
             }
             ColumnIndex::Multivalued(multivalued_index) => {
-                // TODO important: avoid using 0u32, and restart from the beginning all of the time.
-                multivalued_index.select_batch_in_place(0u32, rank_ids)
+                multivalued_index.select_batch_in_place(doc_id_start, rank_ids)
             }
         }
     }

columnar/src/column_index/multivalued_index.rs

@@ -5,16 +5,17 @@ use std::sync::Arc;
 
 use common::OwnedBytes;
 
-use crate::column_values::u64_based::CodecType;
-use crate::column_values::ColumnValues;
+use crate::column_values::{
+    load_u64_based_column_values, serialize_u64_based_column_values, CodecType, ColumnValues,
+};
 use crate::iterable::Iterable;
-use crate::RowId;
+use crate::{DocId, RowId};
 
 pub fn serialize_multivalued_index(
     multivalued_index: &dyn Iterable<RowId>,
     output: &mut impl Write,
 ) -> io::Result<()> {
-    crate::column_values::u64_based::serialize_u64_based_column_values(
+    serialize_u64_based_column_values(
         multivalued_index,
         &[CodecType::Bitpacked, CodecType::Linear],
         output,
@@ -23,8 +24,7 @@ pub fn serialize_multivalued_index(
 }
 
 pub fn open_multivalued_index(bytes: OwnedBytes) -> io::Result<MultiValueIndex> {
-    let start_index_column: Arc<dyn ColumnValues<RowId>> =
-        crate::column_values::u64_based::load_u64_based_column_values(bytes)?;
+    let start_index_column: Arc<dyn ColumnValues<RowId>> = load_u64_based_column_values(bytes)?;
     Ok(MultiValueIndex { start_index_column })
 }
 
@@ -42,23 +42,30 @@ impl From<Arc<dyn ColumnValues<RowId>>> for MultiValueIndex {
 }
 
 impl MultiValueIndex {
+    pub fn for_test(start_offsets: &[RowId]) -> MultiValueIndex {
+        let mut buffer = Vec::new();
+        serialize_multivalued_index(&start_offsets, &mut buffer).unwrap();
+        let bytes = OwnedBytes::new(buffer);
+        open_multivalued_index(bytes).unwrap()
+    }
+
     /// Returns `[start, end)`, such that the values associated with
     /// the given document are `start..end`.
     #[inline]
-    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);
+    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);
         start..end
     }
 
     /// Returns the number of documents in the index.
     #[inline]
-    pub fn num_rows(&self) -> u32 {
+    pub fn num_docs(&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
-    /// row_ids. Positions are converted inplace to docids.
+    /// docids. Positions are converted inplace to docids.
     ///
     /// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
     /// index.
@@ -69,20 +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, row_start: RowId, ranks: &mut Vec<u32>) {
+    pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
         if ranks.is_empty() {
             return;
         }
-        let mut cur_doc = row_start;
+        let mut cur_doc = docid_start;
         let mut last_doc = None;
 
-        assert!(self.start_index_column.get_val(row_start) as u32 <= ranks[0]);
+        assert!(self.start_index_column.get_val(docid_start) <= ranks[0]);
 
         let mut write_doc_pos = 0;
         for i in 0..ranks.len() {
             let pos = ranks[i];
             loop {
-                let end = self.start_index_column.get_val(cur_doc + 1) as u32;
+                let end = self.start_index_column.get_val(cur_doc + 1);
                 if end > pos {
                     ranks[write_doc_pos] = cur_doc;
                     write_doc_pos += if last_doc == Some(cur_doc) { 0 } else { 1 };
@@ -120,7 +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_rows(), 5);
+        assert_eq!(index.num_docs(), 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::{InvalidData, RowId};
+use crate::{DocId, InvalidData, RowId};
 
 /// The threshold for for number of elements after which we switch to dense block encoding.
 ///
@@ -88,22 +88,6 @@ pub struct OptionalIndex {
     block_metas: Arc<[BlockMeta]>,
 }
 
-impl OptionalIndex {
-    pub fn num_rows(&self) -> RowId {
-        self.num_rows
-    }
-
-    pub fn num_non_nulls(&self) -> RowId {
-        self.num_non_null_rows
-    }
-
-    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))
-    }
-}
-
 /// Splits a value address into lower and upper 16bits.
 /// The lower 16 bits are the value in the block
 /// The upper 16 bits are the block index
@@ -193,11 +177,11 @@ impl Set<RowId> for OptionalIndex {
     }
 
     #[inline]
-    fn rank(&self, row_id: RowId) -> RowId {
+    fn rank(&self, doc_id: DocId) -> RowId {
         let RowAddr {
             block_id,
             in_block_row_id,
-        } = row_addr_from_row_id(row_id);
+        } = row_addr_from_row_id(doc_id);
         let block_meta = self.block_metas[block_id as usize];
         let block = self.block(block_meta);
         let block_offset_row_id = match block {
@@ -208,11 +192,11 @@ impl Set<RowId> for OptionalIndex {
     }
 
     #[inline]
-    fn rank_if_exists(&self, row_id: RowId) -> Option<RowId> {
+    fn rank_if_exists(&self, doc_id: DocId) -> Option<RowId> {
         let RowAddr {
             block_id,
             in_block_row_id,
-        } = row_addr_from_row_id(row_id);
+        } = row_addr_from_row_id(doc_id);
         let block_meta = self.block_metas[block_id as usize];
         let block = self.block(block_meta);
         let block_offset_row_id = match block {
@@ -236,7 +220,7 @@ impl Set<RowId> for OptionalIndex {
         block_doc_idx_start + in_block_rank as u32
     }
 
-    fn select_cursor<'b>(&'b self) -> OptionalIndexSelectCursor<'b> {
+    fn select_cursor(&self) -> OptionalIndexSelectCursor<'_> {
         OptionalIndexSelectCursor {
             current_block_cursor: BlockSelectCursor::Sparse(
                 SparseBlockCodec::open(b"").select_cursor(),
@@ -251,6 +235,31 @@ impl Set<RowId> for OptionalIndex {
 }
 
 impl OptionalIndex {
+    pub fn for_test(num_rows: RowId, row_ids: &[RowId]) -> OptionalIndex {
+        assert!(row_ids
+            .last()
+            .copied()
+            .map(|last_row_id| last_row_id < num_rows)
+            .unwrap_or(true));
+        let mut buffer = Vec::new();
+        serialize_optional_index(&row_ids, num_rows, &mut buffer).unwrap();
+        let bytes = OwnedBytes::new(buffer);
+        open_optional_index(bytes).unwrap()
+    }
+
+    pub fn num_docs(&self) -> RowId {
+        self.num_rows
+    }
+
+    pub fn num_non_nulls(&self) -> RowId {
+        self.num_non_null_rows
+    }
+
+    pub fn iter_rows(&self) -> impl Iterator<Item = RowId> + '_ {
+        // TODO optimize
+        let mut select_batch = self.select_cursor();
+        (0..self.num_non_null_rows).map(move |rank| select_batch.select(rank))
+    }
     pub fn select_batch(&self, ranks: &mut [RowId]) {
         let mut select_cursor = self.select_cursor();
         for rank in ranks.iter_mut() {
@@ -259,7 +268,7 @@ impl OptionalIndex {
     }
 
     #[inline]
-    fn block<'a>(&'a self, block_meta: BlockMeta) -> Block<'a> {
+    fn block(&self, block_meta: BlockMeta) -> Block<'_> {
         let BlockMeta {
             start_byte_offset,
             block_variant,
@@ -342,7 +351,7 @@ fn serialize_optional_index_block(block_els: &[u16], out: &mut impl io::Write) -
     Ok(())
 }
 
-pub fn serialize_optional_index<'a, W: io::Write>(
+pub fn serialize_optional_index<W: io::Write>(
     non_null_rows: &dyn Iterable<RowId>,
     num_rows: RowId,
     output: &mut W,
@@ -418,7 +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());
@@ -431,7 +440,7 @@ impl SerializedBlockMeta {
 
 #[inline]
 fn is_sparse(num_rows_in_block: u32) -> bool {
-    num_rows_in_block < DENSE_BLOCK_THRESHOLD as u32
+    num_rows_in_block < DENSE_BLOCK_THRESHOLD
 }
 
 fn deserialize_optional_index_block_metadatas(
@@ -439,7 +448,7 @@ fn deserialize_optional_index_block_metadatas(
     num_rows: u32,
 ) -> (Box<[BlockMeta]>, u32) {
     let num_blocks = data.len() / SERIALIZED_BLOCK_META_NUM_BYTES;
-    let mut block_metas = Vec::with_capacity(num_blocks as usize + 1);
+    let mut block_metas = Vec::with_capacity(num_blocks + 1);
     let mut start_byte_offset = 0;
     let mut non_null_rows_before_block = 0;
     for block_meta_bytes in data.chunks_exact(SERIALIZED_BLOCK_META_NUM_BYTES) {
@@ -470,7 +479,7 @@ fn deserialize_optional_index_block_metadatas(
             block_variant,
         });
         start_byte_offset += block_variant.num_bytes_in_block();
-        non_null_rows_before_block += num_non_null_rows as u32;
+        non_null_rows_before_block += num_non_null_rows;
     }
     block_metas.resize(
         ((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,
@@ -492,7 +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).into();
+        deserialize_optional_index_block_metadatas(block_metas.as_slice(), num_rows);
     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<'a>(data: &'a [u8]) -> Self::Reader<'a>;
+    fn open(data: &[u8]) -> Self::Reader<'_>;
 }
 
 /// 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<'b>(&'b self) -> Self::SelectCursor<'b>;
+    fn select_cursor(&self) -> Self::SelectCursor<'_>;
 }

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

@@ -32,7 +32,7 @@ pub const MINI_BLOCK_NUM_BYTES: usize = MINI_BLOCK_BITVEC_NUM_BYTES + MINI_BLOCK
 
 /// Number of bytes in a dense block.
 pub const DENSE_BLOCK_NUM_BYTES: u32 =
-    (ELEMENTS_PER_BLOCK as u32 / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
+    (ELEMENTS_PER_BLOCK / ELEMENTS_PER_MINI_BLOCK as u32) * MINI_BLOCK_NUM_BYTES as u32;
 
 pub struct DenseBlockCodec;
 
@@ -45,7 +45,7 @@ impl SetCodec for DenseBlockCodec {
     }
 
     #[inline]
-    fn open<'a>(data: &'a [u8]) -> Self::Reader<'a> {
+    fn open(data: &[u8]) -> Self::Reader<'_> {
         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<'b>(&'b self) -> Self::SelectCursor<'b> {
+    fn select_cursor(&self) -> Self::SelectCursor<'_> {
         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 as u16,
+                rank: non_null_rows_before,
             };
             output.write_all(&dense_mini_block.to_bytes())?;
             non_null_rows_before += block.count_ones() as u16;

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

@@ -16,7 +16,7 @@ impl SetCodec for SparseBlockCodec {
         Ok(())
     }
 
-    fn open<'a>(data: &'a [u8]) -> Self::Reader<'a> {
+    fn open(data: &[u8]) -> Self::Reader<'_> {
         SparseBlock(data)
     }
 }
@@ -56,7 +56,7 @@ impl<'a> Set<u16> for SparseBlock<'a> {
     }
 
     #[inline(always)]
-    fn select_cursor<'b>(&'b self) -> Self::SelectCursor<'b> {
+    fn select_cursor(&self) -> Self::SelectCursor<'_> {
         *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.clone(), 100, &mut out).unwrap();
+    serialize_optional_index(&vals, 100, &mut out).unwrap();
     let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
     let ranks: Vec<u32> = (65_472u32..65_473u32).collect();
     let els: Vec<u32> = ranks.iter().copied().map(|rank| rank + 10).collect();
@@ -107,59 +107,43 @@ fn test_null_index(data: &[bool]) {
 
 #[test]
 fn test_optional_index_test_translation() {
-    let mut out = vec![];
-    let iter = &[true, false, true, false];
-    serialize_optional_index(&&iter[..], iter.len() as u32, &mut out).unwrap();
-    let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
-    let mut select_cursor = null_index.select_cursor();
+    let optional_index = OptionalIndex::for_test(4, &[0, 2]);
+    let mut select_cursor = optional_index.select_cursor();
     assert_eq!(select_cursor.select(0), 0);
     assert_eq!(select_cursor.select(1), 2);
 }
 
 #[test]
 fn test_optional_index_translate() {
-    let mut out = vec![];
-    let iter = &[true, false, true, false];
-    serialize_optional_index(&&iter[..], iter.len() as RowId, &mut out).unwrap();
-    let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
-    assert_eq!(null_index.rank_if_exists(0), Some(0));
-    assert_eq!(null_index.rank_if_exists(2), Some(1));
+    let optional_index = OptionalIndex::for_test(4, &[0, 2]);
+    assert_eq!(optional_index.rank_if_exists(0), Some(0));
+    assert_eq!(optional_index.rank_if_exists(2), Some(1));
 }
 
 #[test]
 fn test_optional_index_small() {
-    let mut out = vec![];
-    let iter = &[true, false, true, false];
-    serialize_optional_index(&&iter[..], iter.len() as RowId, &mut out).unwrap();
-    let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
-    assert!(null_index.contains(0));
-    assert!(!null_index.contains(1));
-    assert!(null_index.contains(2));
-    assert!(!null_index.contains(3));
+    let optional_index = OptionalIndex::for_test(4, &[0, 2]);
+    assert!(optional_index.contains(0));
+    assert!(!optional_index.contains(1));
+    assert!(optional_index.contains(2));
+    assert!(!optional_index.contains(3));
 }
 
 #[test]
 fn test_optional_index_large() {
-    let mut docs = vec![];
-    docs.extend((0..ELEMENTS_PER_BLOCK).map(|_idx| false));
-    docs.extend((0..=1).map(|_idx| true));
-
-    let mut out = vec![];
-    serialize_optional_index(&&docs[..], docs.len() as RowId, &mut out).unwrap();
-    let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
-    assert!(!null_index.contains(0));
-    assert!(!null_index.contains(100));
-    assert!(!null_index.contains(ELEMENTS_PER_BLOCK - 1));
-    assert!(null_index.contains(ELEMENTS_PER_BLOCK));
-    assert!(null_index.contains(ELEMENTS_PER_BLOCK + 1));
+    let row_ids = &[ELEMENTS_PER_BLOCK, ELEMENTS_PER_BLOCK + 1];
+    let optional_index = OptionalIndex::for_test(ELEMENTS_PER_BLOCK + 2, row_ids);
+    assert!(!optional_index.contains(0));
+    assert!(!optional_index.contains(100));
+    assert!(!optional_index.contains(ELEMENTS_PER_BLOCK - 1));
+    assert!(optional_index.contains(ELEMENTS_PER_BLOCK));
+    assert!(optional_index.contains(ELEMENTS_PER_BLOCK + 1));
 }
 
 fn test_optional_index_iter_aux(row_ids: &[RowId], num_rows: RowId) {
-    let mut buffer: Vec<u8> = Vec::new();
-    serialize_optional_index(&row_ids, num_rows, &mut buffer).unwrap();
-    let null_index = open_optional_index(OwnedBytes::new(buffer)).unwrap();
-    assert_eq!(null_index.num_rows(), num_rows);
-    assert!(null_index.iter_rows().eq(row_ids.iter().copied()));
+    let optional_index = OptionalIndex::for_test(num_rows, row_ids);
+    assert_eq!(optional_index.num_docs(), num_rows);
+    assert!(optional_index.iter_rows().eq(row_ids.iter().copied()));
 }
 
 #[test]
@@ -168,11 +152,9 @@ fn test_optional_index_iter_empty() {
 }
 
 fn test_optional_index_rank_aux(row_ids: &[RowId]) {
-    let mut buffer: Vec<u8> = Vec::new();
     let num_rows = row_ids.last().copied().unwrap_or(0u32) + 1;
-    serialize_optional_index(&row_ids, num_rows, &mut buffer).unwrap();
-    let null_index = open_optional_index(OwnedBytes::new(buffer)).unwrap();
-    assert_eq!(null_index.num_rows(), num_rows);
+    let null_index = OptionalIndex::for_test(num_rows, row_ids);
+    assert_eq!(null_index.num_docs(), 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));
@@ -207,6 +189,16 @@ fn test_optional_index_iter_dense_block() {
     test_optional_index_iter_aux(&block, 3 * BLOCK_SIZE);
 }
 
+#[test]
+fn test_optional_index_for_tests() {
+    let optional_index = OptionalIndex::for_test(4, &[1, 2]);
+    assert!(!optional_index.contains(0));
+    assert!(optional_index.contains(1));
+    assert!(optional_index.contains(2));
+    assert!(!optional_index.contains(3));
+    assert_eq!(optional_index.num_docs(), 4);
+}
+
 #[cfg(all(test, feature = "unstable"))]
 mod bench {
 
@@ -220,10 +212,13 @@ 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<bool> = (0..TOTAL_NUM_VALUES)
+        let vals: Vec<RowId> = (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[..], &mut out).unwrap();
+        serialize_optional_index(&&vals[..], TOTAL_NUM_VALUES, &mut out).unwrap();
         let codec = open_optional_index(OwnedBytes::new(out)).unwrap();
         codec
     }

columnar/src/column_values/bench.rs

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

columnar/src/column_values/column.rs

@@ -1,390 +0,0 @@
-use std::fmt::Debug;
-use std::marker::PhantomData;
-use std::ops::{Range, RangeInclusive};
-use std::sync::Arc;
-
-use tantivy_bitpacker::minmax;
-
-use crate::column_values::monotonic_mapping::StrictlyMonotonicFn;
-use crate::iterable::Iterable;
-
-/// `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<'a, T: PartialOrd> Iterable<T> for &'a [Arc<dyn ColumnValues<T>>] {
-    fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
-        Box::new(self.iter().flat_map(|column_value| column_value.iter()))
-    }
-}
-
-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/main.rs

@@ -1,222 +0,0 @@
-#[macro_use]
-extern crate prettytable;
-use std::collections::HashSet;
-use std::env;
-use std::io::BufRead;
-use std::net::{IpAddr, Ipv6Addr};
-use std::str::FromStr;
-
-use common::OwnedBytes;
-use fastfield_codecs::{open_u128, serialize_u128, Column, FastFieldCodecType, VecColumn};
-use itertools::Itertools;
-use measure_time::print_time;
-use prettytable::{Cell, Row, Table};
-
-fn print_set_stats(ip_addrs: &[u128]) {
-    println!("NumIps\t{}", ip_addrs.len());
-    let ip_addr_set: HashSet<u128> = ip_addrs.iter().cloned().collect();
-    println!("NumUniqueIps\t{}", ip_addr_set.len());
-    let ratio_unique = ip_addr_set.len() as f64 / ip_addrs.len() as f64;
-    println!("RatioUniqueOverTotal\t{ratio_unique:.4}");
-
-    // histogram
-    let mut ip_addrs = ip_addrs.to_vec();
-    ip_addrs.sort();
-    let mut cnts: Vec<usize> = ip_addrs
-        .into_iter()
-        .dedup_with_count()
-        .map(|(cnt, _)| cnt)
-        .collect();
-    cnts.sort();
-
-    let top_256_cnt: usize = cnts.iter().rev().take(256).sum();
-    let top_128_cnt: usize = cnts.iter().rev().take(128).sum();
-    let top_64_cnt: usize = cnts.iter().rev().take(64).sum();
-    let top_8_cnt: usize = cnts.iter().rev().take(8).sum();
-    let total: usize = cnts.iter().sum();
-
-    println!("{}", total);
-    println!("{}", top_256_cnt);
-    println!("{}", top_128_cnt);
-    println!("Percentage Top8 {:02}", top_8_cnt as f32 / total as f32);
-    println!("Percentage Top64 {:02}", top_64_cnt as f32 / total as f32);
-    println!("Percentage Top128 {:02}", top_128_cnt as f32 / total as f32);
-    println!("Percentage Top256 {:02}", top_256_cnt as f32 / total as f32);
-
-    let mut cnts: Vec<(usize, usize)> = cnts.into_iter().dedup_with_count().collect();
-    cnts.sort_by(|a, b| {
-        if a.1 == b.1 {
-            a.0.cmp(&b.0)
-        } else {
-            b.1.cmp(&a.1)
-        }
-    });
-}
-
-fn ip_dataset() -> Vec<u128> {
-    let mut ip_addr_v4 = 0;
-
-    let stdin = std::io::stdin();
-    let ip_addrs: Vec<u128> = stdin
-        .lock()
-        .lines()
-        .flat_map(|line| {
-            let line = line.unwrap();
-            let line = line.trim();
-            let ip_addr = IpAddr::from_str(line.trim()).ok()?;
-            if ip_addr.is_ipv4() {
-                ip_addr_v4 += 1;
-            }
-            let ip_addr_v6: Ipv6Addr = match ip_addr {
-                IpAddr::V4(v4) => v4.to_ipv6_mapped(),
-                IpAddr::V6(v6) => v6,
-            };
-            Some(ip_addr_v6)
-        })
-        .map(|ip_v6| u128::from_be_bytes(ip_v6.octets()))
-        .collect();
-
-    println!("IpAddrsAny\t{}", ip_addrs.len());
-    println!("IpAddrsV4\t{}", ip_addr_v4);
-
-    ip_addrs
-}
-
-fn bench_ip() {
-    let dataset = ip_dataset();
-    print_set_stats(&dataset);
-
-    // Chunks
-    {
-        let mut data = vec![];
-        for dataset in dataset.chunks(500_000) {
-            serialize_u128(|| dataset.iter().cloned(), dataset.len() as u32, &mut data).unwrap();
-        }
-        let compression = data.len() as f64 / (dataset.len() * 16) as f64;
-        println!("Compression 50_000 chunks {:.4}", compression);
-        println!(
-            "Num Bits per elem {:.2}",
-            (data.len() * 8) as f32 / dataset.len() as f32
-        );
-    }
-
-    let mut data = vec![];
-    {
-        print_time!("creation");
-        serialize_u128(|| dataset.iter().cloned(), dataset.len() as u32, &mut data).unwrap();
-    }
-
-    let compression = data.len() as f64 / (dataset.len() * 16) as f64;
-    println!("Compression {:.2}", compression);
-    println!(
-        "Num Bits per elem {:.2}",
-        (data.len() * 8) as f32 / dataset.len() as f32
-    );
-
-    let decompressor = open_u128::<u128>(OwnedBytes::new(data)).unwrap();
-    // Sample some ranges
-    let mut doc_values = Vec::new();
-    for value in dataset.iter().take(1110).skip(1100).cloned() {
-        doc_values.clear();
-        print_time!("get range");
-        decompressor.get_docids_for_value_range(
-            value..=value,
-            0..decompressor.num_vals(),
-            &mut doc_values,
-        );
-        println!("{:?}", doc_values.len());
-    }
-}
-
-fn main() {
-    if env::args().nth(1).unwrap() == "bench_ip" {
-        bench_ip();
-        return;
-    }
-
-    let mut table = Table::new();
-
-    // Add a row per time
-    table.add_row(row!["", "Compression Ratio", "Compression Estimation"]);
-
-    for (data, data_set_name) in get_codec_test_data_sets() {
-        let results: Vec<(f32, f32, FastFieldCodecType)> = [
-            serialize_with_codec(&data, FastFieldCodecType::Bitpacked),
-            serialize_with_codec(&data, FastFieldCodecType::Linear),
-            serialize_with_codec(&data, FastFieldCodecType::BlockwiseLinear),
-        ]
-        .into_iter()
-        .flatten()
-        .collect();
-        let best_compression_ratio_codec = results
-            .iter()
-            .min_by(|&res1, &res2| res1.partial_cmp(res2).unwrap())
-            .cloned()
-            .unwrap();
-
-        table.add_row(Row::new(vec![Cell::new(data_set_name).style_spec("Bbb")]));
-        for (est, comp, codec_type) in results {
-            let est_cell = est.to_string();
-            let ratio_cell = comp.to_string();
-            let style = if comp == best_compression_ratio_codec.1 {
-                "Fb"
-            } else {
-                ""
-            };
-            table.add_row(Row::new(vec![
-                Cell::new(&format!("{codec_type:?}")).style_spec("bFg"),
-                Cell::new(&ratio_cell).style_spec(style),
-                Cell::new(&est_cell).style_spec(""),
-            ]));
-        }
-    }
-
-    table.printstd();
-}
-
-pub fn get_codec_test_data_sets() -> Vec<(Vec<u64>, &'static str)> {
-    let mut data_and_names = vec![];
-
-    let data = (1000..=200_000_u64).collect::<Vec<_>>();
-    data_and_names.push((data, "Autoincrement"));
-
-    let mut current_cumulative = 0;
-    let data = (1..=200_000_u64)
-        .map(|num| {
-            let num = (num as f32 + num as f32).log10() as u64;
-            current_cumulative += num;
-            current_cumulative
-        })
-        .collect::<Vec<_>>();
-    // let data = (1..=200000_u64).map(|num| num + num).collect::<Vec<_>>();
-    data_and_names.push((data, "Monotonically increasing concave"));
-
-    let mut current_cumulative = 0;
-    let data = (1..=200_000_u64)
-        .map(|num| {
-            let num = (200_000.0 - num as f32).log10() as u64;
-            current_cumulative += num;
-            current_cumulative
-        })
-        .collect::<Vec<_>>();
-    data_and_names.push((data, "Monotonically increasing convex"));
-
-    let data = (1000..=200_000_u64)
-        .map(|num| num + rand::random::<u8>() as u64)
-        .collect::<Vec<_>>();
-    data_and_names.push((data, "Almost monotonically increasing"));
-
-    data_and_names
-}
-
-pub fn serialize_with_codec(
-    data: &[u64],
-    codec_type: FastFieldCodecType,
-) -> Option<(f32, f32, FastFieldCodecType)> {
-    let col = VecColumn::from(data);
-    let estimation = fastfield_codecs::estimate(&col, codec_type)?;
-    let mut out = Vec::new();
-    fastfield_codecs::serialize(&col, &mut out, &[codec_type]).ok()?;
-    let actual_compression = out.len() as f32 / (col.num_vals() * 8) as f32;
-    Some((estimation, actual_compression, codec_type))
-}

columnar/src/column_values/merge.rs

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

columnar/src/column_values/mod.rs

@@ -1,5 +1,4 @@
 #![warn(missing_docs)]
-#![cfg_attr(all(feature = "unstable", test), feature(test))]
 
 //! # `fastfield_codecs`
 //!
@@ -8,206 +7,214 @@
 //! - Monotonically map values to u64/u128
 
 use std::fmt::Debug;
-use std::io;
-use std::io::Write;
+use std::ops::{Range, RangeInclusive};
 use std::sync::Arc;
 
-use common::{BinarySerializable, OwnedBytes};
-use compact_space::CompactSpaceDecompressor;
 pub use monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
-use monotonic_mapping::{StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal};
 pub use monotonic_mapping_u128::MonotonicallyMappableToU128;
-use serialize::U128Header;
 
-mod compact_space;
+mod merge;
 pub(crate) mod monotonic_mapping;
 pub(crate) mod monotonic_mapping_u128;
 mod stats;
-pub(crate) mod u64_based;
+mod u128_based;
+mod u64_based;
+mod vec_column;
 
-mod column;
-pub mod serialize;
+mod monotonic_column;
 
-pub use serialize::serialize_column_values_u128;
-pub use stats::Stats;
+pub(crate) use merge::MergedColumnValues;
+pub use stats::ColumnStats;
+pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
 pub use u64_based::{
     load_u64_based_column_values, serialize_and_load_u64_based_column_values,
     serialize_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
 };
+pub use vec_column::VecColumn;
 
-pub use self::column::{monotonic_map_column, ColumnValues, IterColumn, VecColumn};
+pub use self::monotonic_column::monotonic_map_column;
+use crate::RowId;
 
-#[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,
-}
+/// `ColumnValues` provides access to a dense field column.
+///
+/// `Column` are just a wrapper over `ColumnValues` and a `ColumnIndex`.
+///
+/// Any methods with a default and specialized implementation need to be called in the
+/// wrappers that implement the trait: Arc and MonotonicMappingColumn
+pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
+    /// Return the value associated with the given idx.
+    ///
+    /// This accessor should return as fast as possible.
+    ///
+    /// # Panics
+    ///
+    /// May panic if `idx` is greater than the column length.
+    fn get_val(&self, idx: u32) -> T;
 
-impl 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,
+    /// Allows to push down multiple fetch calls, to avoid dynamic dispatch overhead.
+    ///
+    /// idx and output should have the same length
+    ///
+    /// # Panics
+    ///
+    /// May panic if `idx` is greater than the column length.
+    fn get_vals(&self, idx: &[u32], output: &mut [T]) {
+        assert!(idx.len() == output.len());
+        for (out, idx) in output.iter_mut().zip(idx.iter()) {
+            *out = self.get_val(*idx as u32);
         }
     }
+
+    /// Fills an output buffer with the fast field values
+    /// associated with the `DocId` going from
+    /// `start` to `start + output.len()`.
+    ///
+    /// # Panics
+    ///
+    /// Must panic if `start + output.len()` is greater than
+    /// the segment's `maxdoc`.
+    #[inline(always)]
+    fn get_range(&self, start: u64, output: &mut [T]) {
+        for (out, idx) in output.iter_mut().zip(start..) {
+            *out = self.get_val(idx as u32);
+        }
+    }
+
+    /// Get the row ids of values which are in the provided value range.
+    ///
+    /// Note that position == docid for single value fast fields
+    #[inline(always)]
+    fn get_row_ids_for_value_range(
+        &self,
+        value_range: RangeInclusive<T>,
+        row_id_range: Range<RowId>,
+        row_id_hits: &mut Vec<RowId>,
+    ) {
+        let row_id_range = row_id_range.start..row_id_range.end.min(self.num_vals());
+        for idx in row_id_range.start..row_id_range.end {
+            let val = self.get_val(idx);
+            if value_range.contains(&val) {
+                row_id_hits.push(idx);
+            }
+        }
+    }
+
+    /// Returns the minimum value for this fast field.
+    ///
+    /// This min_value may not be exact.
+    /// For instance, the min value does not take in account of possible
+    /// deleted document. All values are however guaranteed to be higher than
+    /// `.min_value()`.
+    fn min_value(&self) -> T;
+
+    /// Returns the maximum value for this fast field.
+    ///
+    /// This max_value may not be exact.
+    /// For instance, the max value does not take in account of possible
+    /// deleted document. All values are however guaranteed to be higher than
+    /// `.max_value()`.
+    fn max_value(&self) -> T;
+
+    /// The number of values in the column.
+    fn num_vals(&self) -> u32;
+
+    /// Returns a iterator over the data
+    fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = T> + 'a> {
+        Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
+    }
 }
 
-/// Returns the correct codec reader wrapped in the `Arc` for the data.
-pub fn open_u128_mapped<T: MonotonicallyMappableToU128 + Debug>(
-    mut bytes: OwnedBytes,
-) -> io::Result<Arc<dyn ColumnValues<T>>> {
-    let header = U128Header::deserialize(&mut bytes)?;
-    assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
-    let reader = CompactSpaceDecompressor::open(bytes)?;
+impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
+    #[inline(always)]
+    fn get_val(&self, idx: u32) -> T {
+        self.as_ref().get_val(idx)
+    }
 
-    let inverted: StrictlyMonotonicMappingInverter<StrictlyMonotonicMappingToInternal<T>> =
-        StrictlyMonotonicMappingToInternal::<T>::new().into();
-    Ok(Arc::new(monotonic_map_column(reader, inverted)))
+    #[inline(always)]
+    fn min_value(&self) -> T {
+        self.as_ref().min_value()
+    }
+
+    #[inline(always)]
+    fn max_value(&self) -> T {
+        self.as_ref().max_value()
+    }
+
+    #[inline(always)]
+    fn num_vals(&self) -> u32 {
+        self.as_ref().num_vals()
+    }
+
+    #[inline(always)]
+    fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
+        self.as_ref().iter()
+    }
+
+    #[inline(always)]
+    fn get_range(&self, start: u64, output: &mut [T]) {
+        self.as_ref().get_range(start, output)
+    }
+
+    #[inline(always)]
+    fn get_row_ids_for_value_range(
+        &self,
+        range: RangeInclusive<T>,
+        doc_id_range: Range<u32>,
+        positions: &mut Vec<u32>,
+    ) {
+        self.as_ref()
+            .get_row_ids_for_value_range(range, doc_id_range, positions)
+    }
+}
+
+/// Wraps an cloneable iterator into a `Column`.
+pub struct IterColumn<T>(T);
+
+impl<T> From<T> for IterColumn<T>
+where T: Iterator + Clone + ExactSizeIterator
+{
+    fn from(iter: T) -> Self {
+        IterColumn(iter)
+    }
+}
+
+impl<T> ColumnValues<T::Item> for IterColumn<T>
+where
+    T: Iterator + Clone + ExactSizeIterator + Send + Sync,
+    T::Item: PartialOrd + Debug,
+{
+    fn get_val(&self, idx: u32) -> T::Item {
+        self.0.clone().nth(idx as usize).unwrap()
+    }
+
+    fn min_value(&self) -> T::Item {
+        self.0.clone().next().unwrap()
+    }
+
+    fn max_value(&self) -> T::Item {
+        self.0.clone().last().unwrap()
+    }
+
+    fn num_vals(&self) -> u32 {
+        self.0.len() as u32
+    }
+
+    fn iter(&self) -> Box<dyn Iterator<Item = T::Item> + '_> {
+        Box::new(self.0.clone())
+    }
 }
 
 #[cfg(all(test, feature = "unstable"))]
-mod bench {
-    use std::sync::Arc;
-
-    use common::OwnedBytes;
-    use rand::rngs::StdRng;
-    use rand::{Rng, SeedableRng};
-    use test::{self, Bencher};
+mod bench;
 
+#[cfg(test)]
+mod tests {
     use super::*;
 
-    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);
+    #[test]
+    fn test_range_as_col() {
+        let col = IterColumn::from(10..100);
+        assert_eq!(col.num_vals(), 90);
+        assert_eq!(col.max_value(), 99);
     }
 }

columnar/src/column_values/monotonic_column.rs

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

columnar/src/column_values/monotonic_mapping.rs

@@ -1,7 +1,7 @@
 use std::fmt::Debug;
 use std::marker::PhantomData;
 
-use fastdivide::DividerU64;
+use common::DateTime;
 
 use super::MonotonicallyMappableToU128;
 use crate::RowId;
@@ -112,65 +112,6 @@ where T: MonotonicallyMappableToU64
     }
 }
 
-/// Mapping dividing by  gcd and a base value.
-///
-/// The function is assumed to be only called on values divided by passed
-/// gcd value. (It is necessary for the function to be monotonic.)
-pub(crate) struct StrictlyMonotonicMappingToInternalGCDBaseval {
-    gcd_divider: DividerU64,
-    gcd: u64,
-    min_value: u64,
-}
-impl StrictlyMonotonicMappingToInternalGCDBaseval {
-    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 {
@@ -195,17 +136,15 @@ impl MonotonicallyMappableToU64 for i64 {
     }
 }
 
-impl MonotonicallyMappableToU64 for crate::DateTime {
+impl MonotonicallyMappableToU64 for DateTime {
     #[inline(always)]
     fn to_u64(self) -> u64 {
-        common::i64_to_u64(self.timestamp_micros)
+        common::i64_to_u64(self.into_timestamp_micros())
     }
 
     #[inline(always)]
     fn from_u64(val: u64) -> Self {
-        crate::DateTime {
-            timestamp_micros: common::u64_to_i64(val),
-        }
+        DateTime::from_timestamp_micros(common::u64_to_i64(val))
     }
 }
 
@@ -261,13 +200,6 @@ mod tests {
         // TODO
         // identity mapping
         // test_round_trip(&StrictlyMonotonicMappingToInternal::<u128>::new(), 100u128);
-
-        // base value to i64 round trip
-        let mapping = StrictlyMonotonicMappingToInternalBaseval::new(100);
-        test_round_trip::<_, _, u64>(&mapping, 100i64);
-        // base value and gcd to u64 round trip
-        let mapping = StrictlyMonotonicMappingToInternalGCDBaseval::new(10, 100);
-        test_round_trip::<_, _, u64>(&mapping, 100u64);
     }
 
     fn test_round_trip<T: StrictlyMonotonicFn<K, L>, K: std::fmt::Debug + Eq + Copy, L>(

columnar/src/column_values/stats.rs

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

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

@@ -17,14 +17,15 @@ 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;
-
-mod blank_range;
-mod build_compact_space;
+use crate::RowId;
 
 /// The cost per blank is quite hard actually, since blanks are delta encoded, the actual cost of
 /// blanks depends on the number of blanks.
@@ -158,23 +159,30 @@ impl CompactSpace {
 pub struct CompactSpaceCompressor {
     params: IPCodecParams,
 }
+
 #[derive(Debug, Clone)]
 pub struct IPCodecParams {
     compact_space: CompactSpace,
     bit_unpacker: BitUnpacker,
     min_value: u128,
     max_value: u128,
-    num_vals: u32,
+    num_vals: RowId,
     num_bits: u8,
 }
 
 impl CompactSpaceCompressor {
-    /// Taking the vals as Vec may cost a lot of memory. It is used to sort the vals.
-    pub fn train_from(iter: impl Iterator<Item = u128>, num_vals: u32) -> Self {
-        let mut values_sorted = BTreeSet::new();
-        values_sorted.extend(iter);
-        let total_num_values = num_vals;
+    pub fn num_vals(&self) -> RowId {
+        self.params.num_vals
+    }
 
+    /// Taking the vals as Vec may cost a lot of memory. It is used to sort the vals.
+    pub fn train_from(iter: impl Iterator<Item = u128>) -> Self {
+        let mut values_sorted = BTreeSet::new();
+        let mut total_num_values = 0u32;
+        for val in iter {
+            total_num_values += 1u32;
+            values_sorted.insert(val);
+        }
         let compact_space =
             get_compact_space(&values_sorted, total_num_values, COST_PER_BLANK_IN_BITS);
         let amplitude_compact_space = compact_space.amplitude_compact_space();
@@ -305,7 +313,7 @@ impl ColumnValues<u128> for CompactSpaceDecompressor {
     }
 
     #[inline]
-    fn get_docids_for_value_range(
+    fn get_row_ids_for_value_range(
         &self,
         value_range: RangeInclusive<u128>,
         positions_range: Range<u32>,
@@ -450,364 +458,352 @@ impl CompactSpaceDecompressor {
     }
 }
 
-// TODO reenable what can be reenabled.
-// #[cfg(test)]
-// mod tests {
-//
-// use super::*;
-// use crate::column::format_version::read_format_version;
-// use crate::column::column_footer::read_null_index_footer;
-// use crate::column::serialize::U128Header;
-// use crate::column::{open_u128, serialize_u128};
-//
-// #[test]
-// fn compact_space_test() {
-// let ips = &[
-// 2u128, 4u128, 1000, 1001, 1002, 1003, 1004, 1005, 1008, 1010, 1012, 1260,
-// ]
-// .into_iter()
-// .collect();
-// let compact_space = get_compact_space(ips, ips.len() as u32, 11);
-// let amplitude = compact_space.amplitude_compact_space();
-// assert_eq!(amplitude, 17);
-// assert_eq!(1, compact_space.u128_to_compact(2).unwrap());
-// assert_eq!(2, compact_space.u128_to_compact(3).unwrap());
-// assert_eq!(compact_space.u128_to_compact(100).unwrap_err(), 1);
-//
-// for (num1, num2) in (0..3).tuple_windows() {
-// assert_eq!(
-// compact_space.get_range_mapping(num1).compact_end() + 1,
-// compact_space.get_range_mapping(num2).compact_start
-// );
-// }
-//
-// let mut output: Vec<u8> = Vec::new();
-// compact_space.serialize(&mut output).unwrap();
-//
-// assert_eq!(
-// compact_space,
-// CompactSpace::deserialize(&mut &output[..]).unwrap()
-// );
-//
-// for ip in ips {
-// let compact = compact_space.u128_to_compact(*ip).unwrap();
-// assert_eq!(compact_space.compact_to_u128(compact), *ip);
-// }
-// }
-//
-// #[test]
-// fn compact_space_amplitude_test() {
-// let ips = &[100000u128, 1000000].into_iter().collect();
-// let compact_space = get_compact_space(ips, ips.len() as u32, 1);
-// let amplitude = compact_space.amplitude_compact_space();
-// assert_eq!(amplitude, 2);
-// }
-//
-// fn test_all(mut data: OwnedBytes, expected: &[u128]) {
-// let _header = U128Header::deserialize(&mut data);
-// let decompressor = CompactSpaceDecompressor::open(data).unwrap();
-// for (idx, expected_val) in expected.iter().cloned().enumerate() {
-// let val = decompressor.get(idx as u32);
-// assert_eq!(val, expected_val);
-//
-// let test_range = |range: RangeInclusive<u128>| {
-// let expected_positions = expected
-// .iter()
-// .positions(|val| range.contains(val))
-// .map(|pos| pos as u32)
-// .collect::<Vec<_>>();
-// let mut positions = Vec::new();
-// decompressor.get_positions_for_value_range(
-// range,
-// 0..decompressor.num_vals(),
-// &mut positions,
-// );
-// assert_eq!(positions, expected_positions);
-// };
-//
-// test_range(expected_val.saturating_sub(1)..=expected_val);
-// test_range(expected_val..=expected_val);
-// test_range(expected_val..=expected_val.saturating_add(1));
-// test_range(expected_val.saturating_sub(1)..=expected_val.saturating_add(1));
-// }
-// }
-//
-// fn test_aux_vals(u128_vals: &[u128]) -> OwnedBytes {
-// let mut out = Vec::new();
-// serialize_u128(
-// || u128_vals.iter().cloned(),
-// u128_vals.len() as u32,
-// &mut out,
-// )
-// .unwrap();
-//
-// let data = OwnedBytes::new(out);
-// let (data, _format_version) = read_format_version(data).unwrap();
-// let (data, _null_index_footer) = read_null_index_footer(data).unwrap();
-// test_all(data.clone(), u128_vals);
-//
-// data
-// }
-//
-// #[test]
-// fn test_range_1() {
-// let vals = &[
-// 1u128,
-// 100u128,
-// 3u128,
-// 99999u128,
-// 100000u128,
-// 100001u128,
-// 4_000_211_221u128,
-// 4_000_211_222u128,
-// 333u128,
-// ];
-// let mut data = test_aux_vals(vals);
-//
-// let _header = U128Header::deserialize(&mut data);
-// let decomp = CompactSpaceDecompressor::open(data).unwrap();
-// let complete_range = 0..vals.len() as u32;
-// for (pos, val) in vals.iter().enumerate() {
-// let val = *val;
-// let pos = pos as u32;
-// let mut positions = Vec::new();
-// decomp.get_positions_for_value_range(val..=val, pos..pos + 1, &mut positions);
-// assert_eq!(positions, vec![pos]);
-// }
-//
-// handle docid range out of bounds
-// let positions: Vec<u32> = get_positions_for_value_range_helper(&decomp, 0..=1, 1..u32::MAX);
-// assert!(positions.is_empty());
-//
-// let positions =
-// get_positions_for_value_range_helper(&decomp, 0..=1, complete_range.clone());
-// assert_eq!(positions, vec![0]);
-// let positions =
-// get_positions_for_value_range_helper(&decomp, 0..=2, complete_range.clone());
-// assert_eq!(positions, vec![0]);
-// let positions =
-// get_positions_for_value_range_helper(&decomp, 0..=3, complete_range.clone());
-// assert_eq!(positions, vec![0, 2]);
-// assert_eq!(
-// get_positions_for_value_range_helper(
-// &decomp,
-// 99999u128..=99999u128,
-// complete_range.clone()
-// ),
-// vec![3]
-// );
-// assert_eq!(
-// get_positions_for_value_range_helper(
-// &decomp,
-// 99999u128..=100000u128,
-// complete_range.clone()
-// ),
-// vec![3, 4]
-// );
-// assert_eq!(
-// get_positions_for_value_range_helper(
-// &decomp,
-// 99998u128..=100000u128,
-// complete_range.clone()
-// ),
-// vec![3, 4]
-// );
-// assert_eq!(
-// &get_positions_for_value_range_helper(
-// &decomp,
-// 99998u128..=99999u128,
-// complete_range.clone()
-// ),
-// &[3]
-// );
-// assert!(get_positions_for_value_range_helper(
-// &decomp,
-// 99998u128..=99998u128,
-// complete_range.clone()
-// )
-// .is_empty());
-// assert_eq!(
-// &get_positions_for_value_range_helper(
-// &decomp,
-// 333u128..=333u128,
-// complete_range.clone()
-// ),
-// &[8]
-// );
-// assert_eq!(
-// &get_positions_for_value_range_helper(
-// &decomp,
-// 332u128..=333u128,
-// complete_range.clone()
-// ),
-// &[8]
-// );
-// assert_eq!(
-// &get_positions_for_value_range_helper(
-// &decomp,
-// 332u128..=334u128,
-// complete_range.clone()
-// ),
-// &[8]
-// );
-// assert_eq!(
-// &get_positions_for_value_range_helper(
-// &decomp,
-// 333u128..=334u128,
-// complete_range.clone()
-// ),
-// &[8]
-// );
-//
-// assert_eq!(
-// &get_positions_for_value_range_helper(
-// &decomp,
-// 4_000_211_221u128..=5_000_000_000u128,
-// complete_range
-// ),
-// &[6, 7]
-// );
-// }
-//
-// #[test]
-// fn test_empty() {
-// let vals = &[];
-// let data = test_aux_vals(vals);
-// let _decomp = CompactSpaceDecompressor::open(data).unwrap();
-// }
-//
-// #[test]
-// fn test_range_2() {
-// let vals = &[
-// 100u128,
-// 99999u128,
-// 100000u128,
-// 100001u128,
-// 4_000_211_221u128,
-// 4_000_211_222u128,
-// 333u128,
-// ];
-// let mut data = test_aux_vals(vals);
-// let _header = U128Header::deserialize(&mut data);
-// let decomp = CompactSpaceDecompressor::open(data).unwrap();
-// let complete_range = 0..vals.len() as u32;
-// assert!(
-// &get_positions_for_value_range_helper(&decomp, 0..=5, complete_range.clone())
-// .is_empty(),
-// );
-// assert_eq!(
-// &get_positions_for_value_range_helper(&decomp, 0..=100, complete_range.clone()),
-// &[0]
-// );
-// assert_eq!(
-// &get_positions_for_value_range_helper(&decomp, 0..=105, complete_range),
-// &[0]
-// );
-// }
-//
-// fn get_positions_for_value_range_helper<C: Column<T> + ?Sized, T: PartialOrd>(
-// column: &C,
-// value_range: RangeInclusive<T>,
-// doc_id_range: Range<u32>,
-// ) -> Vec<u32> {
-// let mut positions = Vec::new();
-// column.get_docids_for_value_range(value_range, doc_id_range, &mut positions);
-// positions
-// }
-//
-// #[test]
-// fn test_range_3() {
-// let vals = &[
-// 200u128,
-// 201,
-// 202,
-// 203,
-// 204,
-// 204,
-// 206,
-// 207,
-// 208,
-// 209,
-// 210,
-// 1_000_000,
-// 5_000_000_000,
-// ];
-// let mut out = Vec::new();
-// serialize_u128(|| vals.iter().cloned(), vals.len() as u32, &mut out).unwrap();
-// let decomp = open_u128::<u128>(OwnedBytes::new(out)).unwrap();
-// let complete_range = 0..vals.len() as u32;
-//
-// assert_eq!(
-// get_positions_for_value_range_helper(&*decomp, 199..=200, complete_range.clone()),
-// vec![0]
-// );
-//
-// assert_eq!(
-// get_positions_for_value_range_helper(&*decomp, 199..=201, complete_range.clone()),
-// vec![0, 1]
-// );
-//
-// assert_eq!(
-// get_positions_for_value_range_helper(&*decomp, 200..=200, complete_range.clone()),
-// vec![0]
-// );
-//
-// assert_eq!(
-// get_positions_for_value_range_helper(&*decomp, 1_000_000..=1_000_000, complete_range),
-// vec![11]
-// );
-// }
-//
-// #[test]
-// fn test_bug1() {
-// let vals = &[9223372036854775806];
-// let _data = test_aux_vals(vals);
-// }
-//
-// #[test]
-// fn test_bug2() {
-// let vals = &[340282366920938463463374607431768211455u128];
-// let _data = test_aux_vals(vals);
-// }
-//
-// #[test]
-// fn test_bug3() {
-// let vals = &[340282366920938463463374607431768211454];
-// let _data = test_aux_vals(vals);
-// }
-//
-// #[test]
-// fn test_bug4() {
-// let vals = &[340282366920938463463374607431768211455, 0];
-// let _data = test_aux_vals(vals);
-// }
-//
-// #[test]
-// fn test_first_large_gaps() {
-// let vals = &[1_000_000_000u128; 100];
-// let _data = test_aux_vals(vals);
-// }
-// use itertools::Itertools;
-// use proptest::prelude::*;
-//
-// fn num_strategy() -> impl Strategy<Value = u128> {
-// prop_oneof![
-// 1 => prop::num::u128::ANY.prop_map(|num| u128::MAX - (num % 10) ),
-// 1 => prop::num::u128::ANY.prop_map(|num| i64::MAX as u128 + 5 - (num % 10) ),
-// 1 => prop::num::u128::ANY.prop_map(|num| i128::MAX as u128 + 5 - (num % 10) ),
-// 1 => prop::num::u128::ANY.prop_map(|num| num % 10 ),
-// 20 => prop::num::u128::ANY,
-// ]
-// }
-//
-// proptest! {
-// #![proptest_config(ProptestConfig::with_cases(10))]
-//
-// #[test]
-// fn compress_decompress_random(vals in proptest::collection::vec(num_strategy()
-// , 1..1000)) {
-// let _data = test_aux_vals(&vals);
-// }
-// }
-// }
-//
+#[cfg(test)]
+mod tests {
+
+    use itertools::Itertools;
+
+    use super::*;
+    use crate::column_values::u128_based::U128Header;
+    use crate::column_values::{open_u128_mapped, serialize_column_values_u128};
+
+    #[test]
+    fn compact_space_test() {
+        let ips = &[
+            2u128, 4u128, 1000, 1001, 1002, 1003, 1004, 1005, 1008, 1010, 1012, 1260,
+        ]
+        .into_iter()
+        .collect();
+        let compact_space = get_compact_space(ips, ips.len() as u32, 11);
+        let amplitude = compact_space.amplitude_compact_space();
+        assert_eq!(amplitude, 17);
+        assert_eq!(1, compact_space.u128_to_compact(2).unwrap());
+        assert_eq!(2, compact_space.u128_to_compact(3).unwrap());
+        assert_eq!(compact_space.u128_to_compact(100).unwrap_err(), 1);
+
+        for (num1, num2) in (0..3).tuple_windows() {
+            assert_eq!(
+                compact_space.get_range_mapping(num1).compact_end() + 1,
+                compact_space.get_range_mapping(num2).compact_start
+            );
+        }
+
+        let mut output: Vec<u8> = Vec::new();
+        compact_space.serialize(&mut output).unwrap();
+
+        assert_eq!(
+            compact_space,
+            CompactSpace::deserialize(&mut &output[..]).unwrap()
+        );
+
+        for ip in ips {
+            let compact = compact_space.u128_to_compact(*ip).unwrap();
+            assert_eq!(compact_space.compact_to_u128(compact), *ip);
+        }
+    }
+
+    #[test]
+    fn compact_space_amplitude_test() {
+        let ips = &[100000u128, 1000000].into_iter().collect();
+        let compact_space = get_compact_space(ips, ips.len() as u32, 1);
+        let amplitude = compact_space.amplitude_compact_space();
+        assert_eq!(amplitude, 2);
+    }
+
+    fn test_all(mut data: OwnedBytes, expected: &[u128]) {
+        let _header = U128Header::deserialize(&mut data);
+        let decompressor = CompactSpaceDecompressor::open(data).unwrap();
+        for (idx, expected_val) in expected.iter().cloned().enumerate() {
+            let val = decompressor.get(idx as u32);
+            assert_eq!(val, expected_val);
+
+            let test_range = |range: RangeInclusive<u128>| {
+                let expected_positions = expected
+                    .iter()
+                    .positions(|val| range.contains(val))
+                    .map(|pos| pos as u32)
+                    .collect::<Vec<_>>();
+                let mut positions = Vec::new();
+                decompressor.get_positions_for_value_range(
+                    range,
+                    0..decompressor.num_vals(),
+                    &mut positions,
+                );
+                assert_eq!(positions, expected_positions);
+            };
+
+            test_range(expected_val.saturating_sub(1)..=expected_val);
+            test_range(expected_val..=expected_val);
+            test_range(expected_val..=expected_val.saturating_add(1));
+            test_range(expected_val.saturating_sub(1)..=expected_val.saturating_add(1));
+        }
+    }
+
+    fn test_aux_vals(u128_vals: &[u128]) -> OwnedBytes {
+        let mut out = Vec::new();
+        serialize_column_values_u128(&u128_vals, &mut out).unwrap();
+        let data = OwnedBytes::new(out);
+        test_all(data.clone(), u128_vals);
+        data
+    }
+
+    #[test]
+    fn test_range_1() {
+        let vals = &[
+            1u128,
+            100u128,
+            3u128,
+            99999u128,
+            100000u128,
+            100001u128,
+            4_000_211_221u128,
+            4_000_211_222u128,
+            333u128,
+        ];
+        let mut data = test_aux_vals(vals);
+
+        let _header = U128Header::deserialize(&mut data);
+        let decomp = CompactSpaceDecompressor::open(data).unwrap();
+        let complete_range = 0..vals.len() as u32;
+        for (pos, val) in vals.iter().enumerate() {
+            let val = *val;
+            let pos = pos as u32;
+            let mut positions = Vec::new();
+            decomp.get_positions_for_value_range(val..=val, pos..pos + 1, &mut positions);
+            assert_eq!(positions, vec![pos]);
+        }
+
+        // handle docid range out of bounds
+        let positions: Vec<u32> = get_positions_for_value_range_helper(&decomp, 0..=1, 1..u32::MAX);
+        assert!(positions.is_empty());
+
+        let positions =
+            get_positions_for_value_range_helper(&decomp, 0..=1, complete_range.clone());
+        assert_eq!(positions, vec![0]);
+        let positions =
+            get_positions_for_value_range_helper(&decomp, 0..=2, complete_range.clone());
+        assert_eq!(positions, vec![0]);
+        let positions =
+            get_positions_for_value_range_helper(&decomp, 0..=3, complete_range.clone());
+        assert_eq!(positions, vec![0, 2]);
+        assert_eq!(
+            get_positions_for_value_range_helper(
+                &decomp,
+                99999u128..=99999u128,
+                complete_range.clone()
+            ),
+            vec![3]
+        );
+        assert_eq!(
+            get_positions_for_value_range_helper(
+                &decomp,
+                99999u128..=100000u128,
+                complete_range.clone()
+            ),
+            vec![3, 4]
+        );
+        assert_eq!(
+            get_positions_for_value_range_helper(
+                &decomp,
+                99998u128..=100000u128,
+                complete_range.clone()
+            ),
+            vec![3, 4]
+        );
+        assert_eq!(
+            &get_positions_for_value_range_helper(
+                &decomp,
+                99998u128..=99999u128,
+                complete_range.clone()
+            ),
+            &[3]
+        );
+        assert!(get_positions_for_value_range_helper(
+            &decomp,
+            99998u128..=99998u128,
+            complete_range.clone()
+        )
+        .is_empty());
+        assert_eq!(
+            &get_positions_for_value_range_helper(
+                &decomp,
+                333u128..=333u128,
+                complete_range.clone()
+            ),
+            &[8]
+        );
+        assert_eq!(
+            &get_positions_for_value_range_helper(
+                &decomp,
+                332u128..=333u128,
+                complete_range.clone()
+            ),
+            &[8]
+        );
+        assert_eq!(
+            &get_positions_for_value_range_helper(
+                &decomp,
+                332u128..=334u128,
+                complete_range.clone()
+            ),
+            &[8]
+        );
+        assert_eq!(
+            &get_positions_for_value_range_helper(
+                &decomp,
+                333u128..=334u128,
+                complete_range.clone()
+            ),
+            &[8]
+        );
+
+        assert_eq!(
+            &get_positions_for_value_range_helper(
+                &decomp,
+                4_000_211_221u128..=5_000_000_000u128,
+                complete_range
+            ),
+            &[6, 7]
+        );
+    }
+
+    #[test]
+    fn test_empty() {
+        let vals = &[];
+        let data = test_aux_vals(vals);
+        let _decomp = CompactSpaceDecompressor::open(data).unwrap();
+    }
+
+    #[test]
+    fn test_range_2() {
+        let vals = &[
+            100u128,
+            99999u128,
+            100000u128,
+            100001u128,
+            4_000_211_221u128,
+            4_000_211_222u128,
+            333u128,
+        ];
+        let mut data = test_aux_vals(vals);
+        let _header = U128Header::deserialize(&mut data);
+        let decomp = CompactSpaceDecompressor::open(data).unwrap();
+        let complete_range = 0..vals.len() as u32;
+        assert!(
+            &get_positions_for_value_range_helper(&decomp, 0..=5, complete_range.clone())
+                .is_empty(),
+        );
+        assert_eq!(
+            &get_positions_for_value_range_helper(&decomp, 0..=100, complete_range.clone()),
+            &[0]
+        );
+        assert_eq!(
+            &get_positions_for_value_range_helper(&decomp, 0..=105, complete_range),
+            &[0]
+        );
+    }
+
+    fn get_positions_for_value_range_helper<C: ColumnValues<T> + ?Sized, T: PartialOrd>(
+        column: &C,
+        value_range: RangeInclusive<T>,
+        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);
+        positions
+    }
+
+    #[test]
+    fn test_range_3() {
+        let vals = &[
+            200u128,
+            201,
+            202,
+            203,
+            204,
+            204,
+            206,
+            207,
+            208,
+            209,
+            210,
+            1_000_000,
+            5_000_000_000,
+        ];
+        let mut out = Vec::new();
+        serialize_column_values_u128(&&vals[..], &mut out).unwrap();
+        let decomp = open_u128_mapped(OwnedBytes::new(out)).unwrap();
+        let complete_range = 0..vals.len() as u32;
+
+        assert_eq!(
+            get_positions_for_value_range_helper(&*decomp, 199..=200, complete_range.clone()),
+            vec![0]
+        );
+
+        assert_eq!(
+            get_positions_for_value_range_helper(&*decomp, 199..=201, complete_range.clone()),
+            vec![0, 1]
+        );
+
+        assert_eq!(
+            get_positions_for_value_range_helper(&*decomp, 200..=200, complete_range.clone()),
+            vec![0]
+        );
+
+        assert_eq!(
+            get_positions_for_value_range_helper(&*decomp, 1_000_000..=1_000_000, complete_range),
+            vec![11]
+        );
+    }
+
+    #[test]
+    fn test_bug1() {
+        let vals = &[9223372036854775806];
+        let _data = test_aux_vals(vals);
+    }
+
+    #[test]
+    fn test_bug2() {
+        let vals = &[340282366920938463463374607431768211455u128];
+        let _data = test_aux_vals(vals);
+    }
+
+    #[test]
+    fn test_bug3() {
+        let vals = &[340282366920938463463374607431768211454];
+        let _data = test_aux_vals(vals);
+    }
+
+    #[test]
+    fn test_bug4() {
+        let vals = &[340282366920938463463374607431768211455, 0];
+        let _data = test_aux_vals(vals);
+    }
+
+    #[test]
+    fn test_first_large_gaps() {
+        let vals = &[1_000_000_000u128; 100];
+        let _data = test_aux_vals(vals);
+    }
+
+    use proptest::prelude::*;
+
+    fn num_strategy() -> impl Strategy<Value = u128> {
+        prop_oneof![
+            1 => prop::num::u128::ANY.prop_map(|num| u128::MAX - (num % 10) ),
+            1 => prop::num::u128::ANY.prop_map(|num| i64::MAX as u128 + 5 - (num % 10) ),
+            1 => prop::num::u128::ANY.prop_map(|num| i128::MAX as u128 + 5 - (num % 10) ),
+            1 => prop::num::u128::ANY.prop_map(|num| num % 10 ),
+            20 => prop::num::u128::ANY,
+        ]
+    }
+
+    proptest! {
+        #![proptest_config(ProptestConfig::with_cases(10))]
+
+        #[test]
+        fn compress_decompress_random(vals in proptest::collection::vec(num_strategy() , 1..1000)) {
+            let _data = test_aux_vals(&vals);
+        }
+    }
+}

columnar/src/column_values/u128_based/mod.rs

@@ -1,25 +1,19 @@
 use std::fmt::Debug;
 use std::io;
+use std::io::Write;
+use std::sync::Arc;
 
-use common::{BinarySerializable, VInt};
+mod compact_space;
 
-use crate::column_values::compact_space::CompactSpaceCompressor;
-use crate::column_values::U128FastFieldCodecType;
+use common::{BinarySerializable, OwnedBytes, VInt};
+use compact_space::{CompactSpaceCompressor, CompactSpaceDecompressor};
+
+use crate::column_values::monotonic_map_column;
+use crate::column_values::monotonic_mapping::{
+    StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
+};
 use crate::iterable::Iterable;
-use crate::MonotonicallyMappableToU128;
-
-/// 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,
-}
+use crate::{ColumnValues, MonotonicallyMappableToU128};
 
 #[derive(Debug, Copy, Clone, PartialEq, Eq)]
 pub(crate) struct U128Header {
@@ -47,20 +41,18 @@ impl BinarySerializable for U128Header {
 /// Serializes u128 values with the compact space codec.
 pub fn serialize_column_values_u128<T: MonotonicallyMappableToU128>(
     iterable: &dyn Iterable<T>,
-    num_vals: u32,
     output: &mut impl io::Write,
 ) -> io::Result<()> {
-    let header = U128Header {
-        num_vals,
-        codec_type: U128FastFieldCodecType::CompactSpace,
-    };
-    header.serialize(output)?;
     let compressor = CompactSpaceCompressor::train_from(
         iterable
             .boxed_iter()
             .map(MonotonicallyMappableToU128::to_u128),
-        num_vals,
     );
+    let header = U128Header {
+        num_vals: compressor.num_vals(),
+        codec_type: U128FastFieldCodecType::CompactSpace,
+    };
+    header.serialize(output)?;
     compressor.compress_into(
         iterable
             .boxed_iter()
@@ -70,11 +62,57 @@ 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::*;
     use crate::column_values::u64_based::{
-        self, serialize_and_load_u64_based_column_values, serialize_u64_based_column_values,
+        serialize_and_load_u64_based_column_values, serialize_u64_based_column_values,
         ALL_U64_CODEC_TYPES,
     };
     use crate::column_values::CodecType;

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, Stats};
+use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, ColumnStats};
 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: Stats,
+    stats: ColumnStats,
 }
 
 impl ColumnValues for BitpackedReader {
@@ -36,7 +36,7 @@ impl ColumnValues for BitpackedReader {
     }
 }
 
-fn num_bits(stats: &Stats) -> u8 {
+fn num_bits(stats: &ColumnStats) -> 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: &Stats) -> Option<u64> {
+    fn estimate(&self, stats: &ColumnStats) -> Option<u64> {
         let num_bits_per_value = num_bits(stats);
         Some(stats.num_bytes() + (stats.num_rows as u64 * (num_bits_per_value as u64) + 7) / 8)
     }
 
     fn serialize(
         &self,
-        stats: &Stats,
+        stats: &ColumnStats,
         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 Reader = BitpackedReader;
+    type ColumnValues = BitpackedReader;
     type Estimator = BitpackedCodecEstimator;
 
     /// Opens a fast field given a file.
-    fn load(mut data: OwnedBytes) -> io::Result<Self::Reader> {
-        let stats = Stats::deserialize(&mut data)?;
+    fn load(mut data: OwnedBytes) -> io::Result<Self::ColumnValues> {
+        let stats = ColumnStats::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, Stats};
+use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, ColumnStats};
 use crate::column_values::{ColumnValues, VecColumn};
 use crate::MonotonicallyMappableToU64;
 
@@ -84,7 +84,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
             self.block.clear();
         }
     }
-    fn estimate(&self, stats: &Stats) -> Option<u64> {
+    fn estimate(&self, stats: &ColumnStats) -> 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: &Stats,
+        stats: &ColumnStats,
         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 Reader = BlockwiseLinearReader;
+    type ColumnValues = BlockwiseLinearReader;
 
     type Estimator = BlockwiseLinearEstimator;
 
-    fn load(mut bytes: OwnedBytes) -> io::Result<Self::Reader> {
-        let stats = Stats::deserialize(&mut bytes)?;
+    fn load(mut bytes: OwnedBytes) -> io::Result<Self::ColumnValues> {
+        let stats = ColumnStats::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: Stats,
+    stats: ColumnStats,
 }
 
 impl ColumnValues for BlockwiseLinearReader {
     #[inline(always)]
     fn get_val(&self, idx: u32) -> u64 {
-        let block_id = (idx / BLOCK_SIZE as u32) as usize;
-        let idx_within_block = idx % (BLOCK_SIZE as u32);
+        let block_id = (idx / BLOCK_SIZE) as usize;
+        let idx_within_block = idx % BLOCK_SIZE;
         let block = &self.blocks[block_id];
         let interpoled_val: u64 = block.line.eval(idx_within_block);
         let block_bytes = &self.data[block.data_start_offset..];

columnar/src/column_values/u64_based/line.rs

@@ -67,19 +67,6 @@ impl Line {
         self.intercept.wrapping_add(linear_part)
     }
 
-    // Same as train, but the intercept is only estimated from provided sample positions
-    pub fn estimate(sample_positions_and_values: &[(u64, u64)]) -> Self {
-        let first_val = sample_positions_and_values[0].1;
-        let last_val = sample_positions_and_values[sample_positions_and_values.len() - 1].1;
-        let num_vals = sample_positions_and_values[sample_positions_and_values.len() - 1].0 + 1;
-        Self::train_from(
-            first_val,
-            last_val,
-            num_vals as u32,
-            sample_positions_and_values.iter().cloned(),
-        )
-    }
-
     // Intercept is only computed from provided positions
     pub fn train_from(
         first_val: u64,

columnar/src/column_values/u64_based/linear.rs

@@ -5,9 +5,9 @@ use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
 
 use super::line::Line;
 use super::ColumnValues;
-use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, Stats};
+use crate::column_values::u64_based::{ColumnCodec, ColumnCodecEstimator, ColumnStats};
 use crate::column_values::VecColumn;
-use crate::{MonotonicallyMappableToU64, RowId};
+use crate::RowId;
 
 const HALF_SPACE: u64 = u64::MAX / 2;
 const LINE_ESTIMATION_BLOCK_LEN: usize = 512;
@@ -18,7 +18,7 @@ const LINE_ESTIMATION_BLOCK_LEN: usize = 512;
 pub struct LinearReader {
     data: OwnedBytes,
     linear_params: LinearParams,
-    stats: Stats,
+    stats: ColumnStats,
 }
 
 impl ColumnValues for LinearReader {
@@ -106,7 +106,7 @@ impl ColumnCodecEstimator for LinearCodecEstimator {
         }
     }
 
-    fn estimate(&self, stats: &Stats) -> Option<u64> {
+    fn estimate(&self, stats: &ColumnStats) -> 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: &Stats,
+        stats: &ColumnStats,
         vals: &mut dyn Iterator<Item = u64>,
         wrt: &mut dyn io::Write,
     ) -> io::Result<()> {
@@ -184,12 +184,12 @@ impl LinearCodecEstimator {
 }
 
 impl ColumnCodec for LinearCodec {
-    type Reader = LinearReader;
+    type ColumnValues = LinearReader;
 
     type Estimator = LinearCodecEstimator;
 
-    fn load(mut data: OwnedBytes) -> io::Result<Self::Reader> {
-        let stats = Stats::deserialize(&mut data)?;
+    fn load(mut data: OwnedBytes) -> io::Result<Self::ColumnValues> {
+        let stats = ColumnStats::deserialize(&mut data)?;
         let linear_params = LinearParams::deserialize(&mut data)?;
         Ok(LinearReader {
             stats,

columnar/src/column_values/u64_based/mod.rs

@@ -13,35 +13,61 @@ use common::{BinarySerializable, OwnedBytes};
 use crate::column_values::monotonic_mapping::{
     StrictlyMonotonicMappingInverter, StrictlyMonotonicMappingToInternal,
 };
-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};
+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::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);
-    fn estimate(&self, stats: &Stats) -> Option<u64>;
+    /// Finalizes the first pass phase.
     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: &Stats,
+        stats: &ColumnStats,
         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> {
-    type Reader: ColumnValues<T> + 'static;
+    /// Specialized `ColumnValues` type.
+    type ColumnValues: ColumnValues<T> + 'static;
+    /// `Estimator` for the given codec.
     type Estimator: ColumnCodecEstimator + Default;
 
-    fn load(bytes: OwnedBytes) -> io::Result<Self::Reader>;
+    /// Loads a column that has been serialized using this codec.
+    fn load(bytes: OwnedBytes) -> io::Result<Self::ColumnValues>;
 
+    /// Returns an estimator.
     fn estimator() -> Self::Estimator {
         Self::Estimator::default()
     }
+
+    /// Returns a boxed estimator.
     fn boxed_estimator() -> Box<dyn ColumnCodecEstimator> {
         Box::new(Self::estimator())
     }
@@ -62,6 +88,7 @@ pub enum CodecType {
     BlockwiseLinear = 2u8,
 }
 
+/// List of all available u64-base codecs.
 pub const ALL_U64_CODEC_TYPES: [CodecType; 3] = [
     CodecType::Bitpacked,
     CodecType::Linear,
@@ -106,6 +133,7 @@ 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(),
@@ -115,7 +143,8 @@ impl CodecType {
     }
 }
 
-pub fn serialize_u64_based_column_values<'a, T: MonotonicallyMappableToU64>(
+/// Serializes a given column of u64-mapped values.
+pub fn serialize_u64_based_column_values<T: MonotonicallyMappableToU64>(
     vals: &dyn Iterable<T>,
     codec_types: &[CodecType],
     wrt: &mut dyn Write,
@@ -156,11 +185,14 @@ pub fn serialize_u64_based_column_values<'a, 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
-        .get(0)
+        .first()
         .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::Stats;
+use crate::column_values::ColumnStats;
 use crate::RowId;
 
 /// Compute the gcd of two non null numbers.
@@ -33,14 +33,14 @@ pub struct StatsCollector {
 }
 
 impl StatsCollector {
-    pub fn stats(&self) -> Stats {
+    pub fn stats(&self) -> ColumnStats {
         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()
         };
-        Stats {
+        ColumnStats {
             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::Stats;
+    use crate::column_values::u64_based::ColumnStats;
 
-    fn compute_stats(vals: impl Iterator<Item = u64>) -> Stats {
+    fn compute_stats(vals: impl Iterator<Item = u64>) -> ColumnStats {
         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()),
-            Stats {
+            ColumnStats {
                 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()),
-            Stats {
+            ColumnStats {
                 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()),
-            Stats {
+            ColumnStats {
                 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()),
-            Stats {
+            ColumnStats {
                 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()),
-            Stats {
+            ColumnStats {
                 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()),
-            Stats {
+            ColumnStats {
                 gcd: NonZeroU64::new(10).unwrap(),
                 min_value: 0,
                 max_value: 30,

columnar/src/column_values/u64_based/tests.rs

@@ -1,6 +1,6 @@
 use proptest::prelude::*;
 use proptest::strategy::Strategy;
-use proptest::{prop_oneof, proptest};
+use proptest::{num, prop_oneof, proptest};
 
 #[test]
 fn test_serialize_and_load_simple() {
@@ -19,6 +19,62 @@ fn test_serialize_and_load_simple() {
     assert_eq!(col.get_val(1), 2);
     assert_eq!(col.get_val(2), 5);
 }
+
+#[test]
+fn test_empty_column_i64() {
+    let vals: [i64; 0] = [];
+    let mut num_acceptable_codecs = 0;
+    for codec in ALL_U64_CODEC_TYPES {
+        let mut buffer = Vec::new();
+        if serialize_u64_based_column_values(&&vals[..], &[codec], &mut buffer).is_err() {
+            continue;
+        }
+        num_acceptable_codecs += 1;
+        let col = load_u64_based_column_values::<i64>(OwnedBytes::new(buffer)).unwrap();
+        assert_eq!(col.num_vals(), 0);
+        assert_eq!(col.min_value(), i64::MIN);
+        assert_eq!(col.max_value(), i64::MIN);
+    }
+    assert!(num_acceptable_codecs > 0);
+}
+
+#[test]
+fn test_empty_column_u64() {
+    let vals: [u64; 0] = [];
+    let mut num_acceptable_codecs = 0;
+    for codec in ALL_U64_CODEC_TYPES {
+        let mut buffer = Vec::new();
+        if serialize_u64_based_column_values(&&vals[..], &[codec], &mut buffer).is_err() {
+            continue;
+        }
+        num_acceptable_codecs += 1;
+        let col = load_u64_based_column_values::<u64>(OwnedBytes::new(buffer)).unwrap();
+        assert_eq!(col.num_vals(), 0);
+        assert_eq!(col.min_value(), u64::MIN);
+        assert_eq!(col.max_value(), u64::MIN);
+    }
+    assert!(num_acceptable_codecs > 0);
+}
+
+#[test]
+fn test_empty_column_f64() {
+    let vals: [f64; 0] = [];
+    let mut num_acceptable_codecs = 0;
+    for codec in ALL_U64_CODEC_TYPES {
+        let mut buffer = Vec::new();
+        if serialize_u64_based_column_values(&&vals[..], &[codec], &mut buffer).is_err() {
+            continue;
+        }
+        num_acceptable_codecs += 1;
+        let col = load_u64_based_column_values::<f64>(OwnedBytes::new(buffer)).unwrap();
+        assert_eq!(col.num_vals(), 0);
+        // FIXME. f64::MIN would be better!
+        assert!(col.min_value().is_nan());
+        assert!(col.max_value().is_nan());
+    }
+    assert!(num_acceptable_codecs > 0);
+}
+
 pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
     vals: &[u64],
     name: &str,
@@ -60,7 +116,7 @@ pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
             .map(|(pos, _)| pos as u32)
             .collect();
         let mut positions = Vec::new();
-        reader.get_docids_for_value_range(
+        reader.get_row_ids_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

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

columnar/src/columnar/column_type.rs

@@ -1,27 +1,27 @@
 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 and can fit on 6-bits.
-///
-/// - bits[0..3]: Column category type.
-/// - bits[3..6]: Numerical type if necessary.
-#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy, Ord, PartialOrd)]
+/// 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)]
 #[repr(u8)]
 pub enum ColumnType {
     I64 = 0u8,
     U64 = 1u8,
     F64 = 2u8,
-    Bytes = 10u8,
-    Str = 14u8,
-    Bool = 18u8,
-    IpAddr = 22u8,
-    DateTime = 26u8,
+    Bytes = 3u8,
+    Str = 4u8,
+    Bool = 5u8,
+    IpAddr = 6u8,
+    DateTime = 7u8,
 }
 
-#[cfg(test)]
+// The order needs to match _exactly_ the order in the enum
 const COLUMN_TYPES: [ColumnType; 8] = [
     ColumnType::I64,
     ColumnType::U64,
@@ -39,18 +39,7 @@ impl ColumnType {
     }
 
     pub(crate) fn try_from_code(code: u8) -> Result<ColumnType, InvalidData> {
-        use ColumnType::*;
-        match code {
-            0u8 => Ok(I64),
-            1u8 => Ok(U64),
-            2u8 => Ok(F64),
-            10u8 => Ok(Bytes),
-            14u8 => Ok(Str),
-            18u8 => Ok(Bool),
-            22u8 => Ok(IpAddr),
-            26u8 => Ok(Self::DateTime),
-            _ => Err(InvalidData),
-        }
+        COLUMN_TYPES.get(code as usize).copied().ok_or(InvalidData)
     }
 }
 
@@ -124,7 +113,7 @@ impl HasAssociatedColumnType for bool {
     }
 }
 
-impl HasAssociatedColumnType for crate::DateTime {
+impl HasAssociatedColumnType for common::DateTime {
     fn column_type() -> ColumnType {
         ColumnType::DateTime
     }
@@ -143,70 +132,20 @@ impl HasAssociatedColumnType for Ipv6Addr {
     }
 }
 
-/// Column types are grouped into different categories that
-/// corresponds to the different types of `JsonValue` types.
-///
-/// The columnar writer will apply coercion rules to make sure that
-/// at most one column exist per `ColumnTypeCategory`.
-///
-/// See also [README.md].
-#[derive(Copy, Clone, Ord, PartialOrd, Eq, PartialEq, Hash, Debug)]
-#[repr(u8)]
-pub enum ColumnTypeCategory {
-    Bool,
-    Str,
-    Numerical,
-    DateTime,
-    Bytes,
-    IpAddr,
-}
-
-impl From<ColumnType> for ColumnTypeCategory {
-    fn from(column_type: ColumnType) -> Self {
-        match column_type {
-            ColumnType::I64 => ColumnTypeCategory::Numerical,
-            ColumnType::U64 => ColumnTypeCategory::Numerical,
-            ColumnType::F64 => ColumnTypeCategory::Numerical,
-            ColumnType::Bytes => ColumnTypeCategory::Bytes,
-            ColumnType::Str => ColumnTypeCategory::Str,
-            ColumnType::Bool => ColumnTypeCategory::Bool,
-            ColumnType::IpAddr => ColumnTypeCategory::IpAddr,
-            ColumnType::DateTime => ColumnTypeCategory::DateTime,
-        }
-    }
-}
-
 #[cfg(test)]
 mod tests {
-    use std::collections::HashSet;
-
     use super::*;
     use crate::Cardinality;
 
     #[test]
     fn test_column_type_to_code() {
-        let mut column_type_set: HashSet<ColumnType> = HashSet::new();
-        for code in u8::MIN..=u8::MAX {
-            if let Ok(column_type) = ColumnType::try_from_code(code) {
-                assert_eq!(column_type.to_code(), code);
-                assert!(column_type_set.insert(column_type));
+        for (code, expected_column_type) in super::COLUMN_TYPES.iter().copied().enumerate() {
+            if let Ok(column_type) = ColumnType::try_from_code(code as u8) {
+                assert_eq!(column_type, expected_column_type);
             }
         }
-        assert_eq!(column_type_set.len(), super::COLUMN_TYPES.len());
-    }
-
-    #[test]
-    fn test_column_category_sort_consistent_with_column_type_sort() {
-        // This is a very important property because we
-        // we need to serialize colunmn in the right order.
-        let mut column_types: Vec<ColumnType> = super::COLUMN_TYPES.iter().copied().collect();
-        column_types.sort_by_key(|col| col.to_code());
-        let column_categories: Vec<ColumnTypeCategory> = column_types
-            .into_iter()
-            .map(ColumnTypeCategory::from)
-            .collect();
-        for (prev, next) in column_categories.iter().zip(column_categories.iter()) {
-            assert!(prev <= next);
+        for code in COLUMN_TYPES.len() as u8..=u8::MAX {
+            assert!(ColumnType::try_from_code(code).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, 066];
+const MAGIC_BYTES: [u8; 4] = [2, 113, 119, 66];
 
 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

@@ -1,68 +1,130 @@
 use std::io::{self, Write};
 
-use common::CountingWriter;
+use common::{BitSet, CountingWriter, ReadOnlyBitSet};
 use sstable::{SSTable, TermOrdinal};
 
 use super::term_merger::TermMerger;
 use crate::column::serialize_column_mappable_to_u64;
 use crate::column_index::SerializableColumnIndex;
 use crate::iterable::Iterable;
-use crate::BytesColumn;
+use crate::{BytesColumn, MergeRowOrder, ShuffleMergeOrder};
 
 // Serialize [Dictionary, Column, dictionary num bytes U32::LE]
 // Column: [Column Index, Column Values, column index num bytes U32::LE]
 pub fn merge_bytes_or_str_column(
     column_index: SerializableColumnIndex<'_>,
-    bytes_columns: &[BytesColumn],
+    bytes_columns: &[Option<BytesColumn>],
+    merge_row_order: &MergeRowOrder,
     output: &mut impl Write,
 ) -> io::Result<()> {
     // Serialize dict and generate mapping for values
     let mut output = CountingWriter::wrap(output);
-    let term_ord_mapping = serialize_merged_dict(bytes_columns, &mut output)?;
+    // TODO !!! Remove useless terms.
+    let term_ord_mapping = serialize_merged_dict(bytes_columns, merge_row_order, &mut output)?;
     let dictionary_num_bytes: u32 = output.written_bytes() as u32;
     let output = output.finish();
     let remapped_term_ordinals_values = RemappedTermOrdinalsValues {
         bytes_columns,
         term_ord_mapping: &term_ord_mapping,
+        merge_row_order,
     };
     serialize_column_mappable_to_u64(column_index, &remapped_term_ordinals_values, output)?;
-    // serialize_bytes_or_str_column(column_index, bytes_columns, &term_ord_mapping, output)?;
     output.write_all(&dictionary_num_bytes.to_le_bytes())?;
     Ok(())
 }
 
 struct RemappedTermOrdinalsValues<'a> {
-    bytes_columns: &'a [BytesColumn],
+    bytes_columns: &'a [Option<BytesColumn>],
     term_ord_mapping: &'a TermOrdinalMapping,
+    merge_row_order: &'a MergeRowOrder,
 }
 
 impl<'a> Iterable for RemappedTermOrdinalsValues<'a> {
     fn boxed_iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
+        match self.merge_row_order {
+            MergeRowOrder::Stack(_) => self.boxed_iter_stacked(),
+            MergeRowOrder::Shuffled(shuffle_merge_order) => {
+                self.boxed_iter_shuffled(shuffle_merge_order)
+            }
+        }
+    }
+}
+
+impl<'a> RemappedTermOrdinalsValues<'a> {
+    fn boxed_iter_stacked(&self) -> Box<dyn Iterator<Item = u64> + '_> {
         let iter = self
             .bytes_columns
             .iter()
             .enumerate()
             .flat_map(|(segment_ord, byte_column)| {
-                let segment_ord = self.term_ord_mapping.get_segment(segment_ord);
-                byte_column
-                    .ords()
-                    .values
-                    .iter()
-                    .map(move |term_ord| segment_ord[term_ord as usize])
+                let segment_ord = self.term_ord_mapping.get_segment(segment_ord as u32);
+                byte_column.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)
     }
+
+    fn boxed_iter_shuffled<'b>(
+        &'b self,
+        shuffle_merge_order: &'b ShuffleMergeOrder,
+    ) -> Box<dyn Iterator<Item = u64> + 'b> {
+        Box::new(
+            shuffle_merge_order
+                .iter_new_to_old_row_addrs()
+                .flat_map(move |old_addr| {
+                    let segment_ord = self.term_ord_mapping.get_segment(old_addr.segment_ord);
+                    self.bytes_columns[old_addr.segment_ord as usize]
+                        .as_ref()
+                        .into_iter()
+                        .flat_map(move |bytes_column| {
+                            bytes_column
+                                .term_ords(old_addr.row_id)
+                                .map(|old_term_ord: u64| segment_ord[old_term_ord as usize])
+                        })
+                }),
+        )
+    }
+}
+
+fn compute_term_bitset(column: &BytesColumn, row_bitset: &ReadOnlyBitSet) -> BitSet {
+    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) {
+            term_bitset.insert(term_ord as u32);
+        }
+    }
+    term_bitset
+}
+
+fn is_term_present(bitsets: &[Option<BitSet>], term_merger: &TermMerger) -> bool {
+    for (segment_ord, from_term_ord) in term_merger.matching_segments() {
+        if let Some(bitset) = bitsets[segment_ord].as_ref() {
+            if bitset.contains(from_term_ord as u32) {
+                return true;
+            }
+        } else {
+            return true;
+        }
+    }
+    false
 }
 
 fn serialize_merged_dict(
-    bytes_columns: &[BytesColumn],
+    bytes_columns: &[Option<BytesColumn>],
+    merge_row_order: &MergeRowOrder,
     output: &mut impl Write,
 ) -> io::Result<TermOrdinalMapping> {
     let mut term_ord_mapping = TermOrdinalMapping::default();
 
     let mut field_term_streams = Vec::new();
-    for column in bytes_columns {
+    for column in bytes_columns.iter().flatten() {
         term_ord_mapping.add_segment(column.dictionary.num_terms());
         let terms = column.dictionary.stream()?;
         field_term_streams.push(terms);
@@ -71,21 +133,57 @@ fn serialize_merged_dict(
     let mut merged_terms = TermMerger::new(field_term_streams);
     let mut sstable_builder = sstable::VoidSSTable::writer(output);
 
-    let mut current_term_ord = 0;
-    while merged_terms.advance() {
-        let term_bytes: &[u8] = merged_terms.key();
-
-        sstable_builder.insert(term_bytes, &())?;
-        for (segment_ord, from_term_ord) in merged_terms.matching_segments() {
-            term_ord_mapping.register_from_to(segment_ord, from_term_ord, current_term_ord);
+    // TODO support complex `merge_row_order`.
+    match merge_row_order {
+        MergeRowOrder::Stack(_) => {
+            let mut current_term_ord = 0;
+            while merged_terms.advance() {
+                let term_bytes: &[u8] = merged_terms.key();
+                sstable_builder.insert(term_bytes, &())?;
+                for (segment_ord, from_term_ord) in merged_terms.matching_segments() {
+                    term_ord_mapping.register_from_to(segment_ord, from_term_ord, current_term_ord);
+                }
+                current_term_ord += 1;
+            }
+            sstable_builder.finish()?;
+        }
+        MergeRowOrder::Shuffled(shuffle_merge_order) => {
+            assert_eq!(shuffle_merge_order.alive_bitsets.len(), bytes_columns.len());
+            let mut term_bitsets: Vec<Option<BitSet>> = Vec::with_capacity(bytes_columns.len());
+            for (alive_bitset_opt, bytes_column_opt) in shuffle_merge_order
+                .alive_bitsets
+                .iter()
+                .zip(bytes_columns.iter())
+            {
+                match (alive_bitset_opt, bytes_column_opt) {
+                    (Some(alive_bitset), Some(bytes_column)) => {
+                        let term_bitset = compute_term_bitset(bytes_column, alive_bitset);
+                        term_bitsets.push(Some(term_bitset));
+                    }
+                    _ => {
+                        term_bitsets.push(None);
+                    }
+                }
+            }
+            let mut current_term_ord = 0;
+            while merged_terms.advance() {
+                let term_bytes: &[u8] = merged_terms.key();
+                if !is_term_present(&term_bitsets[..], &merged_terms) {
+                    continue;
+                }
+                sstable_builder.insert(term_bytes, &())?;
+                for (segment_ord, from_term_ord) in merged_terms.matching_segments() {
+                    term_ord_mapping.register_from_to(segment_ord, from_term_ord, current_term_ord);
+                }
+                current_term_ord += 1;
+            }
+            sstable_builder.finish()?;
         }
-        current_term_ord += 1;
     }
-    sstable_builder.finish()?;
     Ok(term_ord_mapping)
 }
 
-#[derive(Default)]
+#[derive(Default, Debug)]
 struct TermOrdinalMapping {
     per_segment_new_term_ordinals: Vec<Vec<TermOrdinal>>,
 }
@@ -93,14 +191,14 @@ struct TermOrdinalMapping {
 impl TermOrdinalMapping {
     fn add_segment(&mut self, max_term_ord: usize) {
         self.per_segment_new_term_ordinals
-            .push(vec![TermOrdinal::default(); max_term_ord as usize]);
+            .push(vec![TermOrdinal::default(); max_term_ord]);
     }
 
     fn register_from_to(&mut self, segment_ord: usize, from_ord: TermOrdinal, to_ord: TermOrdinal) {
         self.per_segment_new_term_ordinals[segment_ord][from_ord as usize] = to_ord;
     }
 
-    fn get_segment(&self, segment_ord: usize) -> &[TermOrdinal] {
-        &(self.per_segment_new_term_ordinals[segment_ord])[..]
+    fn get_segment(&self, segment_ord: u32) -> &[TermOrdinal] {
+        &(self.per_segment_new_term_ordinals[segment_ord as usize])[..]
     }
 }

columnar/src/columnar/merge/merge_mapping.rs

@@ -1,6 +1,8 @@
 use std::ops::Range;
 
-use crate::{column, ColumnarReader, RowId};
+use common::{BitSet, OwnedBytes, ReadOnlyBitSet};
+
+use crate::{ColumnarReader, RowAddr, RowId};
 
 pub struct StackMergeOrder {
     // This does not start at 0. The first row is the number of
@@ -42,19 +44,75 @@ pub enum MergeRowOrder {
     /// rows [r0..n_row_0) contains the row of columnar_readers[0], in ordder
     /// rows [n_row_0..n_row_0 + n_row_1 contains the row of columnar_readers[1], in order.
     /// ..
+    /// No documents is deleted.
     Stack(StackMergeOrder),
-    /// Some more complex mapping, that can interleaves rows from the different readers and
-    /// possibly drop rows.
-    Complex(()),
+    /// Some more complex mapping, that may interleaves rows from the different readers and
+    /// drop rows, or do both.
+    Shuffled(ShuffleMergeOrder),
+}
+
+impl From<StackMergeOrder> for MergeRowOrder {
+    fn from(stack_merge_order: StackMergeOrder) -> MergeRowOrder {
+        MergeRowOrder::Stack(stack_merge_order)
+    }
+}
+
+impl From<ShuffleMergeOrder> for MergeRowOrder {
+    fn from(shuffle_merge_order: ShuffleMergeOrder) -> MergeRowOrder {
+        MergeRowOrder::Shuffled(shuffle_merge_order)
+    }
 }
 
 impl MergeRowOrder {
     pub fn num_rows(&self) -> RowId {
         match self {
             MergeRowOrder::Stack(stack_row_order) => stack_row_order.num_rows(),
-            MergeRowOrder::Complex(_) => {
-                todo!()
-            }
+            MergeRowOrder::Shuffled(complex_mapping) => complex_mapping.num_rows(),
         }
     }
 }
+
+pub struct ShuffleMergeOrder {
+    pub new_row_id_to_old_row_id: Vec<RowAddr>,
+    pub alive_bitsets: Vec<Option<ReadOnlyBitSet>>,
+}
+
+impl ShuffleMergeOrder {
+    pub fn for_test(
+        segment_num_rows: &[RowId],
+        new_row_id_to_old_row_id: Vec<RowAddr>,
+    ) -> ShuffleMergeOrder {
+        let mut alive_bitsets: Vec<BitSet> = segment_num_rows
+            .iter()
+            .map(|&num_rows| BitSet::with_max_value(num_rows))
+            .collect();
+        for &RowAddr {
+            segment_ord,
+            row_id,
+        } in &new_row_id_to_old_row_id
+        {
+            alive_bitsets[segment_ord as usize].insert(row_id);
+        }
+        let alive_bitsets: Vec<Option<ReadOnlyBitSet>> = alive_bitsets
+            .into_iter()
+            .map(|alive_bitset| {
+                let mut buffer = Vec::new();
+                alive_bitset.serialize(&mut buffer).unwrap();
+                let data = OwnedBytes::new(buffer);
+                Some(ReadOnlyBitSet::open(data))
+            })
+            .collect();
+        ShuffleMergeOrder {
+            new_row_id_to_old_row_id,
+            alive_bitsets,
+        }
+    }
+
+    pub fn num_rows(&self) -> RowId {
+        self.new_row_id_to_old_row_id.len() as RowId
+    }
+
+    pub fn iter_new_to_old_row_addrs(&self) -> impl Iterator<Item = RowAddr> + '_ {
+        self.new_row_id_to_old_row_id.iter().copied()
+    }
+}

columnar/src/columnar/merge/mod.rs

@@ -2,42 +2,95 @@ 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;
 use std::sync::Arc;
 
-pub use merge_mapping::{MergeRowOrder, StackMergeOrder};
+pub use merge_mapping::{MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};
 
 use super::writer::ColumnarSerializer;
 use crate::column::{serialize_column_mappable_to_u128, serialize_column_mappable_to_u64};
-use crate::column_index::stack_column_index;
-use crate::columnar::column_type::ColumnTypeCategory;
+use crate::column_values::MergedColumnValues;
 use crate::columnar::merge::merge_dict_column::merge_bytes_or_str_column;
 use crate::columnar::writer::CompatibleNumericalTypes;
 use crate::columnar::ColumnarReader;
 use crate::dynamic_column::DynamicColumn;
 use crate::{
-    BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, MonotonicallyMappableToU128,
-    NumericalType, NumericalValue,
+    BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, NumericalType, NumericalValue,
 };
 
+/// Column types are grouped into different categories.
+/// After merge, all columns belonging to the same category are coerced to
+/// the same column type.
+///
+/// In practise, today, only Numerical colummns are coerced into one type today.
+///
+/// See also [README.md].
+#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug)]
+enum ColumnTypeCategory {
+    Bool,
+    Str,
+    Numerical,
+    DateTime,
+    Bytes,
+    IpAddr,
+}
+
+impl From<ColumnType> for ColumnTypeCategory {
+    fn from(column_type: ColumnType) -> Self {
+        match column_type {
+            ColumnType::I64 => ColumnTypeCategory::Numerical,
+            ColumnType::U64 => ColumnTypeCategory::Numerical,
+            ColumnType::F64 => ColumnTypeCategory::Numerical,
+            ColumnType::Bytes => ColumnTypeCategory::Bytes,
+            ColumnType::Str => ColumnTypeCategory::Str,
+            ColumnType::Bool => ColumnTypeCategory::Bool,
+            ColumnType::IpAddr => ColumnTypeCategory::IpAddr,
+            ColumnType::DateTime => ColumnTypeCategory::DateTime,
+        }
+    }
+}
+
+/// 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],
-    mapping: MergeRowOrder,
+    required_columns: &[(String, ColumnType)],
+    merge_row_order: MergeRowOrder,
     output: &mut impl io::Write,
 ) -> io::Result<()> {
     let mut serializer = ColumnarSerializer::new(output);
 
-    let columns_to_merge = group_columns_for_merge(columnar_readers)?;
+    let columns_to_merge = group_columns_for_merge(columnar_readers, required_columns)?;
     for ((column_name, column_type), columns) in columns_to_merge {
         let mut column_serializer =
             serializer.serialize_column(column_name.as_bytes(), column_type);
-        merge_column(column_type, columns, &mapping, &mut column_serializer)?;
+        merge_column(
+            column_type,
+            columns,
+            &merge_row_order,
+            &mut column_serializer,
+        )?;
     }
-    serializer.finalize(mapping.num_rows())?;
+    serializer.finalize(merge_row_order.num_rows())?;
 
     Ok(())
 }
@@ -53,7 +106,7 @@ fn dynamic_column_to_u64_monotonic(dynamic_column: DynamicColumn) -> Option<Colu
     }
 }
 
-pub fn merge_column(
+fn merge_column(
     column_type: ColumnType,
     columns: Vec<Option<DynamicColumn>>,
     merge_row_order: &MergeRowOrder,
@@ -66,159 +119,256 @@ pub fn merge_column(
         | ColumnType::DateTime
         | ColumnType::Bool => {
             let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
-            let mut column_values: Vec<Arc<dyn ColumnValues>> = Vec::with_capacity(columns.len());
+            let mut column_values: Vec<Option<Arc<dyn ColumnValues>>> =
+                Vec::with_capacity(columns.len());
             for dynamic_column_opt in columns {
                 if let Some(Column { idx, values }) =
                     dynamic_column_opt.and_then(dynamic_column_to_u64_monotonic)
                 {
                     column_indexes.push(Some(idx));
-                    column_values.push(values);
+                    column_values.push(Some(values));
                 } else {
                     column_indexes.push(None);
+                    column_values.push(None);
                 }
             }
             let merged_column_index =
-                crate::column_index::stack_column_index(&column_indexes[..], merge_row_order);
-            serialize_column_mappable_to_u64(merged_column_index, &&column_values[..], wrt)?;
+                crate::column_index::merge_column_index(&column_indexes[..], merge_row_order);
+            let merge_column_values = MergedColumnValues {
+                column_indexes: &column_indexes[..],
+                column_values: &column_values[..],
+                merge_row_order,
+            };
+            serialize_column_mappable_to_u64(merged_column_index, &merge_column_values, wrt)?;
         }
         ColumnType::IpAddr => {
             let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
-            let mut column_values: Vec<Arc<dyn ColumnValues<Ipv6Addr>>> =
+            let mut column_values: Vec<Option<Arc<dyn ColumnValues<Ipv6Addr>>>> =
                 Vec::with_capacity(columns.len());
-            let mut num_values = 0;
             for dynamic_column_opt in columns {
                 if let Some(DynamicColumn::IpAddr(Column { idx, values })) = dynamic_column_opt {
-                    num_values += values.num_vals();
                     column_indexes.push(Some(idx));
-                    column_values.push(values);
+                    column_values.push(Some(values));
                 } else {
                     column_indexes.push(None);
+                    column_values.push(None);
                 }
             }
+
             let merged_column_index =
-                crate::column_index::stack_column_index(&column_indexes[..], merge_row_order);
-            serialize_column_mappable_to_u128(
-                merged_column_index,
-                &&column_values[..],
-                num_values,
-                wrt,
-            )?;
+                crate::column_index::merge_column_index(&column_indexes[..], merge_row_order);
+            let merge_column_values = MergedColumnValues {
+                column_indexes: &column_indexes[..],
+                column_values: &column_values,
+                merge_row_order,
+            };
+
+            serialize_column_mappable_to_u128(merged_column_index, &merge_column_values, wrt)?;
         }
         ColumnType::Bytes | ColumnType::Str => {
             let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
-            let mut bytes_columns: Vec<BytesColumn> = Vec::with_capacity(columns.len());
+            let mut bytes_columns: Vec<Option<BytesColumn>> = Vec::with_capacity(columns.len());
             for dynamic_column_opt in columns {
                 match dynamic_column_opt {
                     Some(DynamicColumn::Str(str_column)) => {
                         column_indexes.push(Some(str_column.term_ord_column.idx.clone()));
-                        bytes_columns.push(str_column.into());
+                        bytes_columns.push(Some(str_column.into()));
                     }
                     Some(DynamicColumn::Bytes(bytes_column)) => {
                         column_indexes.push(Some(bytes_column.term_ord_column.idx.clone()));
-                        bytes_columns.push(bytes_column);
+                        bytes_columns.push(Some(bytes_column));
+                    }
+                    _ => {
+                        column_indexes.push(None);
+                        bytes_columns.push(None);
                     }
-                    _ => column_indexes.push(None),
                 }
             }
             let merged_column_index =
-                crate::column_index::stack_column_index(&column_indexes[..], merge_row_order);
-            merge_bytes_or_str_column(merged_column_index, &bytes_columns, wrt)?;
+                crate::column_index::merge_column_index(&column_indexes[..], merge_row_order);
+            merge_bytes_or_str_column(merged_column_index, &bytes_columns, merge_row_order, wrt)?;
         }
     }
     Ok(())
 }
 
+struct GroupedColumns {
+    required_column_type: Option<ColumnType>,
+    columns: Vec<Option<DynamicColumn>>,
+    column_category: ColumnTypeCategory,
+}
+
+impl GroupedColumns {
+    fn for_category(column_category: ColumnTypeCategory, num_columnars: usize) -> Self {
+        GroupedColumns {
+            required_column_type: None,
+            columns: vec![None; num_columnars],
+            column_category,
+        }
+    }
+
+    /// Set the dynamic column for a given columnar.
+    fn set_column(&mut self, columnar_id: usize, column: DynamicColumn) {
+        self.columns[columnar_id] = Some(column);
+    }
+
+    /// Force the existence of a column, as well as its type.
+    fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
+        if let Some(existing_required_type) = self.required_column_type {
+            if existing_required_type == required_type {
+                // This was just a duplicate in the `required_columns`.
+                // Nothing to do.
+                return Ok(());
+            } else {
+                return Err(io::Error::new(
+                    io::ErrorKind::InvalidInput,
+                    "Required column conflicts with another required column of the same type \
+                     category.",
+                ));
+            }
+        }
+        self.required_column_type = Some(required_type);
+        Ok(())
+    }
+
+    /// Returns the column type after merge.
+    ///
+    /// This method does not check if the column types can actually be coerced to
+    /// this type.
+    fn column_type_after_merge(&self) -> ColumnType {
+        if let Some(required_type) = self.required_column_type {
+            return required_type;
+        }
+        let column_type: HashSet<ColumnType> = self
+            .columns
+            .iter()
+            .flatten()
+            .map(|column| column.column_type())
+            .collect();
+        if column_type.len() == 1 {
+            return column_type.into_iter().next().unwrap();
+        }
+        // At the moment, only the numerical categorical column type has more than one possible
+        // column type.
+        assert_eq!(self.column_category, ColumnTypeCategory::Numerical);
+        merged_numerical_columns_type(self.columns.iter().flatten()).into()
+    }
+}
+
+/// Returns the type of the merged numerical column.
+///
+/// This function picks the first numerical type out of i64, u64, f64 (order matters
+/// here), that is compatible with all the `columns`.
+///
+/// # Panics
+/// Panics if one of the column is not numerical.
+fn merged_numerical_columns_type<'a>(
+    columns: impl Iterator<Item = &'a DynamicColumn>,
+) -> NumericalType {
+    let mut compatible_numerical_types = CompatibleNumericalTypes::default();
+    for column in columns {
+        let (min_value, max_value) =
+            min_max_if_numerical(column).expect("All columns re required to be numerical");
+        compatible_numerical_types.accept_value(min_value);
+        compatible_numerical_types.accept_value(max_value);
+    }
+    compatible_numerical_types.to_numerical_type()
+}
+
+#[allow(clippy::type_complexity)]
 fn group_columns_for_merge(
     columnar_readers: &[&ColumnarReader],
+    required_columns: &[(String, ColumnType)],
 ) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
     // Each column name may have multiple types of column associated.
     // For merging we are interested in the same column type category since they can be merged.
-    let mut columns_grouped: HashMap<(String, ColumnTypeCategory), Vec<Option<DynamicColumn>>> =
-        HashMap::new();
+    let mut columns_grouped: HashMap<(String, ColumnTypeCategory), GroupedColumns> = HashMap::new();
 
-    let num_columnars = columnar_readers.len();
+    for &(ref column_name, column_type) in required_columns {
+        columns_grouped
+            .entry((column_name.clone(), column_type.into()))
+            .or_insert_with(|| {
+                GroupedColumns::for_category(column_type.into(), columnar_readers.len())
+            })
+            .require_type(column_type)?;
+    }
 
     for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
         let column_name_and_handle = columnar_reader.list_columns()?;
         for (column_name, handle) in column_name_and_handle {
-            let column_type_category: ColumnTypeCategory = handle.column_type().into();
-            let columns = columns_grouped
-                .entry((column_name, column_type_category))
-                .or_insert_with(|| vec![None; num_columnars]);
+            let column_category: ColumnTypeCategory = handle.column_type().into();
             let column = handle.open()?;
-            columns[columnar_id] = Some(column);
+            columns_grouped
+                .entry((column_name, column_category))
+                .or_insert_with(|| {
+                    GroupedColumns::for_category(column_category, columnar_readers.len())
+                })
+                .set_column(columnar_id, column);
         }
     }
 
     let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        BTreeMap::default();
+        Default::default();
 
-    for ((column_name, col_category), mut columns) in columns_grouped {
-        if col_category == ColumnTypeCategory::Numerical {
-            coerce_numerical_columns_to_same_type(&mut columns);
-        }
-        let column_type = columns
-            .iter()
-            .flatten()
-            .map(|col| col.column_type())
-            .next()
-            .unwrap();
-        merge_columns.insert((column_name, column_type), columns);
+    for ((column_name, _), mut grouped_columns) in columns_grouped {
+        let column_type = grouped_columns.column_type_after_merge();
+        coerce_columns(column_type, &mut grouped_columns.columns)?;
+        merge_columns.insert((column_name, column_type), grouped_columns.columns);
     }
 
     Ok(merge_columns)
 }
 
-/// Coerce a set of numerical columns to the same type.
-///
-/// If all columns are already from the same type, keep this type
-/// (even if they could all be coerced to i64).
-fn coerce_numerical_columns_to_same_type(columns: &mut [Option<DynamicColumn>]) {
-    let mut column_types: HashSet<NumericalType> = HashSet::default();
-    let mut compatible_numerical_types = CompatibleNumericalTypes::default();
-    for column in columns.iter().flatten() {
-        let min_value: NumericalValue;
-        let max_value: NumericalValue;
-        match column {
-            DynamicColumn::I64(column) => {
-                min_value = column.min_value().into();
-                max_value = column.max_value().into();
-            }
-            DynamicColumn::U64(column) => {
-                min_value = column.min_value().into();
-                max_value = column.min_value().into();
-            }
-            DynamicColumn::F64(column) => {
-                min_value = column.min_value().into();
-                max_value = column.min_value().into();
-            }
-            DynamicColumn::Bool(_)
-            | DynamicColumn::IpAddr(_)
-            | DynamicColumn::DateTime(_)
-            | DynamicColumn::Bytes(_)
-            | DynamicColumn::Str(_) => {
-                panic!("We expected only numerical columns.");
-            }
-        }
-        column_types.insert(column.column_type().numerical_type().unwrap());
-        compatible_numerical_types.accept_value(min_value);
-        compatible_numerical_types.accept_value(max_value);
-    }
-    if column_types.len() <= 1 {
-        // No need to do anything. The columns are already all from the same type.
-        // This is necessary to let use force a given type.
-
-        // TODO This works in a world where we do not allow a change of schema,
-        // but in the future, we will have to pass some kind of schema to enforce
-        // the logic.
-        return;
-    }
-    let coerce_type = compatible_numerical_types.to_numerical_type();
+fn coerce_columns(
+    column_type: ColumnType,
+    columns: &mut [Option<DynamicColumn>],
+) -> io::Result<()> {
     for column_opt in columns.iter_mut() {
         if let Some(column) = column_opt.take() {
-            *column_opt = column.coerce_numerical(coerce_type);
+            *column_opt = Some(coerce_column(column_type, column)?);
         }
     }
+    Ok(())
+}
+
+fn coerce_column(column_type: ColumnType, column: DynamicColumn) -> io::Result<DynamicColumn> {
+    if let Some(numerical_type) = column_type.numerical_type() {
+        column
+            .coerce_numerical(numerical_type)
+            .ok_or_else(|| io::Error::new(io::ErrorKind::InvalidInput, ""))
+    } else {
+        if column.column_type() != column_type {
+            return Err(io::Error::new(
+                io::ErrorKind::InvalidInput,
+                format!(
+                    "Cannot coerce column of type `{:?}` to `{column_type:?}`",
+                    column.column_type()
+                ),
+            ));
+        }
+        Ok(column)
+    }
+}
+
+/// Returns the (min, max) of a column provided it is numerical (i64, u64. f64).
+///
+/// The min and the max are simply the numerical value as defined by `ColumnValue::min_value()`,
+/// and `ColumnValue::max_value()`.
+///
+/// It is important to note that these values are only guaranteed to be lower/upper bound
+/// (as opposed to min/max value).
+/// If a column is empty, the min and max values are currently set to 0.
+fn min_max_if_numerical(column: &DynamicColumn) -> Option<(NumericalValue, NumericalValue)> {
+    match column {
+        DynamicColumn::I64(column) => Some((column.min_value().into(), column.max_value().into())),
+        DynamicColumn::U64(column) => Some((column.min_value().into(), column.min_value().into())),
+        DynamicColumn::F64(column) => Some((column.min_value().into(), column.min_value().into())),
+        DynamicColumn::Bool(_)
+        | DynamicColumn::IpAddr(_)
+        | DynamicColumn::DateTime(_)
+        | DynamicColumn::Bytes(_)
+        | DynamicColumn::Str(_) => None,
+    }
 }
 
 #[cfg(test)]

columnar/src/columnar/merge/sorted_doc_id_column.rs

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

columnar/src/columnar/merge/sorted_doc_id_multivalue_column.rs

@@ -1,169 +0,0 @@
-use std::cmp;
-
-use fastfield_codecs::Column;
-
-use super::flat_map_with_buffer::FlatMapWithBufferIter;
-use crate::fastfield::{MultiValueIndex, MultiValuedFastFieldReader};
-use crate::indexer::doc_id_mapping::SegmentDocIdMapping;
-use crate::{DocAddress, SegmentReader};
-
-pub(crate) struct RemappedDocIdMultiValueColumn<'a> {
-    doc_id_mapping: &'a SegmentDocIdMapping,
-    fast_field_readers: Vec<MultiValuedFastFieldReader<u64>>,
-    min_value: u64,
-    max_value: u64,
-    num_vals: u32,
-}
-
-impl<'a> RemappedDocIdMultiValueColumn<'a> {
-    pub(crate) fn new(
-        readers: &'a [SegmentReader],
-        doc_id_mapping: &'a SegmentDocIdMapping,
-        field: &str,
-    ) -> Self {
-        // Our values are bitpacked and we need to know what should be
-        // our bitwidth and our minimum value before serializing any values.
-        //
-        // Computing those is non-trivial if some documents are deleted.
-        // We go through a complete first pass to compute the minimum and the
-        // maximum value and initialize our Serializer.
-        let mut num_vals = 0;
-        let mut min_value = u64::MAX;
-        let mut max_value = u64::MIN;
-        let mut vals = Vec::new();
-        let mut fast_field_readers = Vec::with_capacity(readers.len());
-        for reader in readers {
-            let ff_reader: MultiValuedFastFieldReader<u64> = reader
-                .fast_fields()
-                .typed_fast_field_multi_reader::<u64>(field)
-                .expect(
-                    "Failed to find multivalued fast field reader. This is a bug in tantivy. \
-                     Please report.",
-                );
-            for doc in reader.doc_ids_alive() {
-                ff_reader.get_vals(doc, &mut vals);
-                for &val in &vals {
-                    min_value = cmp::min(val, min_value);
-                    max_value = cmp::max(val, max_value);
-                }
-                num_vals += vals.len();
-            }
-            fast_field_readers.push(ff_reader);
-            // TODO optimize when no deletes
-        }
-        if min_value > max_value {
-            min_value = 0;
-            max_value = 0;
-        }
-        RemappedDocIdMultiValueColumn {
-            doc_id_mapping,
-            fast_field_readers,
-            min_value,
-            max_value,
-            num_vals: num_vals as u32,
-        }
-    }
-}
-
-impl<'a> Column for RemappedDocIdMultiValueColumn<'a> {
-    fn get_val(&self, _pos: u32) -> u64 {
-        unimplemented!()
-    }
-
-    fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
-        Box::new(
-            self.doc_id_mapping
-                .iter_old_doc_addrs()
-                .flat_map_with_buffer(|old_doc_addr: DocAddress, buffer| {
-                    let ff_reader = &self.fast_field_readers[old_doc_addr.segment_ord as usize];
-                    ff_reader.get_vals(old_doc_addr.doc_id, buffer);
-                }),
-        )
-    }
-    fn min_value(&self) -> u64 {
-        self.min_value
-    }
-
-    fn max_value(&self) -> u64 {
-        self.max_value
-    }
-
-    fn num_vals(&self) -> u32 {
-        self.num_vals
-    }
-}
-
-pub(crate) struct RemappedDocIdMultiValueIndexColumn<'a> {
-    doc_id_mapping: &'a SegmentDocIdMapping,
-    multi_value_length_readers: Vec<&'a MultiValueIndex>,
-    min_value: u64,
-    max_value: u64,
-    num_vals: u32,
-}
-
-impl<'a> RemappedDocIdMultiValueIndexColumn<'a> {
-    pub(crate) fn new(
-        segment_and_ff_readers: &'a [(&'a SegmentReader, &'a MultiValueIndex)],
-        doc_id_mapping: &'a SegmentDocIdMapping,
-    ) -> Self {
-        // We go through a complete first pass to compute the minimum and the
-        // maximum value and initialize our Column.
-        let mut num_vals = 0;
-        let min_value = 0;
-        let mut max_value = 0;
-        let mut multi_value_length_readers = Vec::with_capacity(segment_and_ff_readers.len());
-        for segment_and_ff_reader in segment_and_ff_readers {
-            let segment_reader = segment_and_ff_reader.0;
-            let multi_value_length_reader = segment_and_ff_reader.1;
-            if !segment_reader.has_deletes() {
-                max_value += multi_value_length_reader.total_num_vals() as u64;
-            } else {
-                for doc in segment_reader.doc_ids_alive() {
-                    max_value += multi_value_length_reader.num_vals_for_doc(doc) as u64;
-                }
-            }
-            num_vals += segment_reader.num_docs();
-            multi_value_length_readers.push(multi_value_length_reader);
-        }
-        // The value range is always get_val(doc)..get_val(doc + 1)
-        num_vals += 1;
-        Self {
-            doc_id_mapping,
-            multi_value_length_readers,
-            min_value,
-            max_value,
-            num_vals,
-        }
-    }
-}
-
-impl<'a> Column for RemappedDocIdMultiValueIndexColumn<'a> {
-    fn get_val(&self, _pos: u32) -> u64 {
-        unimplemented!()
-    }
-
-    fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
-        let mut offset = 0;
-        Box::new(
-            std::iter::once(0).chain(self.doc_id_mapping.iter_old_doc_addrs().map(
-                move |old_doc_addr| {
-                    let ff_reader =
-                        &self.multi_value_length_readers[old_doc_addr.segment_ord as usize];
-                    offset += ff_reader.num_vals_for_doc(old_doc_addr.doc_id);
-                    offset as u64
-                },
-            )),
-        )
-    }
-    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

@@ -12,7 +12,7 @@ fn make_columnar<T: Into<NumericalValue> + HasAssociatedColumnType + Copy>(
     }
     let mut buffer: Vec<u8> = Vec::new();
     dataframe_writer
-        .serialize(vals.len() as RowId, &mut buffer)
+        .serialize(vals.len() as RowId, None, &mut buffer)
         .unwrap();
     ColumnarReader::open(buffer).unwrap()
 }
@@ -24,7 +24,7 @@ fn test_column_coercion_to_u64() {
     // u64 type
     let columnar2 = make_columnar("numbers", &[u64::MAX]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 1);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
 }
@@ -34,7 +34,7 @@ fn test_column_no_coercion_if_all_the_same() {
     let columnar1 = make_columnar("numbers", &[1u64]);
     let columnar2 = make_columnar("numbers", &[2u64]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 1);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
 }
@@ -44,17 +44,74 @@ fn test_column_coercion_to_i64() {
     let columnar1 = make_columnar("numbers", &[-1i64]);
     let columnar2 = make_columnar("numbers", &[2u64]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 1);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
 }
 
+#[test]
+fn test_impossible_coercion_returns_an_error() {
+    let columnar1 = make_columnar("numbers", &[u64::MAX]);
+    let group_error =
+        group_columns_for_merge(&[&columnar1], &[("numbers".to_string(), ColumnType::I64)])
+            .map(|_| ())
+            .unwrap_err();
+    assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
+}
+
+#[test]
+fn test_group_columns_with_required_column() {
+    let columnar1 = make_columnar("numbers", &[1i64]);
+    let columnar2 = make_columnar("numbers", &[2u64]);
+    let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
+        group_columns_for_merge(
+            &[&columnar1, &columnar2],
+            &[("numbers".to_string(), ColumnType::U64)],
+        )
+        .unwrap();
+    assert_eq!(column_map.len(), 1);
+    assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
+}
+
+#[test]
+fn test_group_columns_required_column_with_no_existing_columns() {
+    let columnar1 = make_columnar("numbers", &[2u64]);
+    let columnar2 = make_columnar("numbers", &[2u64]);
+    let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
+        group_columns_for_merge(
+            &[&columnar1, &columnar2],
+            &[("required_col".to_string(), ColumnType::Str)],
+        )
+        .unwrap();
+    assert_eq!(column_map.len(), 2);
+    let columns = column_map
+        .get(&("required_col".to_string(), ColumnType::Str))
+        .unwrap();
+    assert_eq!(columns.len(), 2);
+    assert!(columns[0].is_none());
+    assert!(columns[1].is_none());
+}
+
+#[test]
+fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_rule() {
+    let columnar1 = make_columnar("numbers", &[2i64]);
+    let columnar2 = make_columnar("numbers", &[2i64]);
+    let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
+        group_columns_for_merge(
+            &[&columnar1, &columnar2],
+            &[("numbers".to_string(), ColumnType::U64)],
+        )
+        .unwrap();
+    assert_eq!(column_map.len(), 1);
+    assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
+}
+
 #[test]
 fn test_missing_column() {
     let columnar1 = make_columnar("numbers", &[-1i64]);
     let columnar2 = make_columnar("numbers2", &[2u64]);
     let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
-        group_columns_for_merge(&[&columnar1, &columnar2]).unwrap();
+        group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
     assert_eq!(column_map.len(), 2);
     assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
     {
@@ -90,7 +147,9 @@ fn make_numerical_columnar_multiple_columns(
         .max()
         .unwrap_or(0u32);
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
+    dataframe_writer
+        .serialize(num_rows, None, &mut buffer)
+        .unwrap();
     ColumnarReader::open(buffer).unwrap()
 }
 
@@ -99,7 +158,7 @@ fn make_byte_columnar_multiple_columns(columns: &[(&str, &[&[&[u8]]])]) -> Colum
     for (column_name, column_values) in columns {
         for (row_id, vals) in column_values.iter().enumerate() {
             for val in vals.iter() {
-                dataframe_writer.record_bytes(row_id as u32, column_name, *val);
+                dataframe_writer.record_bytes(row_id as u32, column_name, val);
             }
         }
     }
@@ -109,7 +168,9 @@ fn make_byte_columnar_multiple_columns(columns: &[(&str, &[&[&[u8]]])]) -> Colum
         .max()
         .unwrap_or(0u32);
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
+    dataframe_writer
+        .serialize(num_rows, None, &mut buffer)
+        .unwrap();
     ColumnarReader::open(buffer).unwrap()
 }
 
@@ -118,7 +179,7 @@ fn make_text_columnar_multiple_columns(columns: &[(&str, &[&[&str]])]) -> Column
     for (column_name, column_values) in columns {
         for (row_id, vals) in column_values.iter().enumerate() {
             for val in vals.iter() {
-                dataframe_writer.record_str(row_id as u32, column_name, *val);
+                dataframe_writer.record_str(row_id as u32, column_name, val);
             }
         }
     }
@@ -128,7 +189,9 @@ fn make_text_columnar_multiple_columns(columns: &[(&str, &[&[&str]])]) -> Column
         .max()
         .unwrap_or(0u32);
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
+    dataframe_writer
+        .serialize(num_rows, None, &mut buffer)
+        .unwrap();
     ColumnarReader::open(buffer).unwrap()
 }
 
@@ -145,6 +208,7 @@ fn test_merge_columnar_numbers() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
+        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -170,6 +234,7 @@ fn test_merge_columnar_texts() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
+        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )
@@ -214,6 +279,7 @@ fn test_merge_columnar_byte() {
     let stack_merge_order = StackMergeOrder::stack(columnars);
     crate::columnar::merge_columnar(
         columnars,
+        &[],
         MergeRowOrder::Stack(stack_merge_order),
         &mut buffer,
     )

columnar/src/columnar/merge_index.rs

@@ -1 +0,0 @@
-

columnar/src/columnar/mod.rs

@@ -1,11 +1,10 @@
 mod column_type;
 mod format_version;
 mod merge;
-mod merge_index;
 mod reader;
 mod writer;
 
 pub use column_type::{ColumnType, HasAssociatedColumnType};
-pub use merge::{merge_columnar, MergeRowOrder, StackMergeOrder};
+pub use merge::{merge_columnar, MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};
 pub use reader::ColumnarReader;
 pub use writer::ColumnarWriter;

columnar/src/columnar/reader/mod.rs

@@ -21,6 +21,32 @@ pub struct ColumnarReader {
     num_rows: RowId,
 }
 
+/// Functions by both the async/sync code listing columns.
+/// It takes a stream from the column sstable and return the list of
+/// `DynamicColumn` available in it.
+fn read_all_columns_in_stream(
+    mut stream: sstable::Streamer<'_, RangeSSTable>,
+    column_data: &FileSlice,
+) -> io::Result<Vec<DynamicColumnHandle>> {
+    let mut results = Vec::new();
+    while stream.advance() {
+        let key_bytes: &[u8] = stream.key();
+        let Some(column_code) = key_bytes.last().copied() else {
+            return Err(io_invalid_data("Empty column name.".to_string()));
+        };
+        let column_type = ColumnType::try_from_code(column_code)
+            .map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
+        let range = stream.value();
+        let file_slice = column_data.slice(range.start as usize..range.end as usize);
+        let dynamic_column_handle = DynamicColumnHandle {
+            file_slice,
+            column_type,
+        };
+        results.push(dynamic_column_handle);
+    }
+    Ok(results)
+}
+
 impl ColumnarReader {
     /// Opens a new Columnar file.
     pub fn open<F>(file_slice: F) -> io::Result<ColumnarReader>
@@ -76,11 +102,7 @@ impl ColumnarReader {
         Ok(results)
     }
 
-    /// Get all columns for the given column name.
-    ///
-    /// There can be more than one column associated to a given column name, provided they have
-    /// different types.
-    pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
+    fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {
         // Each column is a associated to a given `column_key`,
         // that starts by `column_name\0column_header`.
         //
@@ -89,36 +111,35 @@ impl ColumnarReader {
         //
         // This is in turn equivalent to searching for the range
         // `[column_name,\0`..column_name\1)`.
-
-        // TODO can we get some more generic `prefix(..)` logic in the dictioanry.
+        // TODO can we get some more generic `prefix(..)` logic in the dictionary.
         let mut start_key = column_name.to_string();
         start_key.push('\0');
         let mut end_key = column_name.to_string();
         end_key.push(1u8 as char);
-        let mut stream = self
-            .column_dictionary
+        self.column_dictionary
             .range()
             .ge(start_key.as_bytes())
             .lt(end_key.as_bytes())
-            .into_stream()?;
-        let mut results = Vec::new();
-        while stream.advance() {
-            let key_bytes: &[u8] = stream.key();
-            assert!(key_bytes.starts_with(start_key.as_bytes()));
-            let column_code: u8 = key_bytes.last().cloned().unwrap();
-            let column_type = ColumnType::try_from_code(column_code)
-                .map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
-            let range = stream.value().clone();
-            let file_slice = self
-                .column_data
-                .slice(range.start as usize..range.end as usize);
-            let dynamic_column_handle = DynamicColumnHandle {
-                file_slice,
-                column_type,
-            };
-            results.push(dynamic_column_handle);
-        }
-        Ok(results)
+    }
+
+    pub async fn read_columns_async(
+        &self,
+        column_name: &str,
+    ) -> io::Result<Vec<DynamicColumnHandle>> {
+        let stream = self
+            .stream_for_column_range(column_name)
+            .into_stream_async()
+            .await?;
+        read_all_columns_in_stream(stream, &self.column_data)
+    }
+
+    /// Get all columns for the given column name.
+    ///
+    /// There can be more than one column associated to a given column name, provided they have
+    /// different types.
+    pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
+        let stream = self.stream_for_column_range(column_name).into_stream()?;
+        read_all_columns_in_stream(stream, &self.column_data)
     }
 
     /// Return the number of columns in the columnar.
@@ -137,7 +158,7 @@ mod tests {
         columnar_writer.record_column_type("col1", ColumnType::Str, false);
         columnar_writer.record_column_type("col2", ColumnType::U64, false);
         let mut buffer = Vec::new();
-        columnar_writer.serialize(1, &mut buffer).unwrap();
+        columnar_writer.serialize(1, None, &mut buffer).unwrap();
         let columnar = ColumnarReader::open(buffer).unwrap();
         let columns = columnar.list_columns().unwrap();
         assert_eq!(columns.len(), 2);
@@ -153,7 +174,7 @@ mod tests {
         columnar_writer.record_column_type("count", ColumnType::U64, false);
         columnar_writer.record_numerical(1, "count", 1u64);
         let mut buffer = Vec::new();
-        columnar_writer.serialize(2, &mut buffer).unwrap();
+        columnar_writer.serialize(2, None, &mut buffer).unwrap();
         let columnar = ColumnarReader::open(buffer).unwrap();
         let columns = columnar.list_columns().unwrap();
         assert_eq!(columns.len(), 1);
@@ -162,7 +183,7 @@ mod tests {
     }
 
     #[test]
-    #[should_panic(expect = "Input type forbidden")]
+    #[should_panic(expected = "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() as usize, buffer.len());
+        assert_eq!(bytes.len() + buf.as_ref().len(), buffer.len());
         assert_eq!(column_op, serdeser_symbol);
     }
 
@@ -341,7 +341,7 @@ mod tests {
     fn test_column_operation_unordered_aux(val: u32, expected_len: usize) {
         let column_op = ColumnOperation::Value(UnorderedId(val));
         let minibuf = column_op.serialize();
-        assert_eq!(minibuf.as_ref().len() as usize, expected_len);
+        assert_eq!({ minibuf.as_ref().len() }, expected_len);
         let mut buf = minibuf.as_ref().to_vec();
         buf.extend_from_slice(&[2, 2, 2, 2, 2, 2]);
         let mut cursor = &buf[..];

columnar/src/columnar/writer/column_writers.rs

@@ -41,10 +41,31 @@ impl ColumnWriter {
     pub(super) fn operation_iterator<'a, V: SymbolValue>(
         &self,
         arena: &MemoryArena,
+        old_to_new_ids_opt: Option<&[RowId]>,
         buffer: &'a mut Vec<u8>,
     ) -> impl Iterator<Item = ColumnOperation<V>> + 'a {
         buffer.clear();
         self.values.read_to_end(arena, buffer);
+        if let Some(old_to_new_ids) = old_to_new_ids_opt {
+            // TODO avoid the extra deserialization / serialization.
+            let mut sorted_ops: Vec<(RowId, ColumnOperation<V>)> = Vec::new();
+            let mut new_doc = 0u32;
+            let mut cursor = &buffer[..];
+            for op in std::iter::from_fn(|| ColumnOperation::<V>::deserialize(&mut cursor)) {
+                if let ColumnOperation::NewDoc(doc) = &op {
+                    new_doc = old_to_new_ids[*doc as usize];
+                    sorted_ops.push((new_doc, ColumnOperation::NewDoc(new_doc)));
+                } else {
+                    sorted_ops.push((new_doc, op));
+                }
+            }
+            // stable sort is crucial here.
+            sorted_ops.sort_by_key(|(new_doc_id, _)| *new_doc_id);
+            buffer.clear();
+            for (_, op) in sorted_ops {
+                buffer.extend_from_slice(op.serialize().as_ref());
+            }
+        }
         let mut cursor: &[u8] = &buffer[..];
         std::iter::from_fn(move || ColumnOperation::deserialize(&mut cursor))
     }
@@ -189,10 +210,12 @@ impl CompatibleNumericalTypes {
 }
 
 impl NumericalColumnWriter {
-    pub fn column_type_and_cardinality(&self, num_docs: RowId) -> (NumericalType, Cardinality) {
-        let numerical_type = self.compatible_numerical_types.to_numerical_type();
-        let cardinality = self.column_writer.get_cardinality(num_docs);
-        (numerical_type, cardinality)
+    pub fn numerical_type(&self) -> NumericalType {
+        self.compatible_numerical_types.to_numerical_type()
+    }
+
+    pub fn cardinality(&self, num_docs: RowId) -> Cardinality {
+        self.column_writer.get_cardinality(num_docs)
     }
 
     pub fn record_numerical_value(
@@ -208,9 +231,11 @@ impl NumericalColumnWriter {
     pub(super) fn operation_iterator<'a>(
         self,
         arena: &MemoryArena,
+        old_to_new_ids: Option<&[RowId]>,
         buffer: &'a mut Vec<u8>,
     ) -> impl Iterator<Item = ColumnOperation<NumericalValue>> + 'a {
-        self.column_writer.operation_iterator(arena, buffer)
+        self.column_writer
+            .operation_iterator(arena, old_to_new_ids, buffer)
     }
 }
 
@@ -251,9 +276,11 @@ impl StrOrBytesColumnWriter {
     pub(super) fn operation_iterator<'a>(
         &self,
         arena: &MemoryArena,
+        old_to_new_ids: Option<&[RowId]>,
         byte_buffer: &'a mut Vec<u8>,
     ) -> impl Iterator<Item = ColumnOperation<UnorderedId>> + 'a {
-        self.column_writer.operation_iterator(arena, byte_buffer)
+        self.column_writer
+            .operation_iterator(arena, old_to_new_ids, byte_buffer)
     }
 }
 

columnar/src/columnar/writer/mod.rs

@@ -16,7 +16,7 @@ use crate::column_index::SerializableColumnIndex;
 use crate::column_values::{
     ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
 };
-use crate::columnar::column_type::{ColumnType, ColumnTypeCategory};
+use crate::columnar::column_type::ColumnType;
 use crate::columnar::writer::column_writers::{
     ColumnWriter, NumericalColumnWriter, StrOrBytesColumnWriter,
 };
@@ -45,8 +45,9 @@ struct SpareBuffers {
 /// columnar_writer.record_str(1u32 /* doc id */, "product_name", "Apple");
 /// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10.5f64); //< uh oh we ended up mixing integer and floats.
 /// let mut wrt: Vec<u8> =  Vec::new();
-/// columnar_writer.serialize(2u32, &mut wrt).unwrap();
+/// columnar_writer.serialize(2u32, None, &mut wrt).unwrap();
 /// ```
+#[derive(Default)]
 pub struct ColumnarWriter {
     numerical_field_hash_map: ArenaHashMap,
     datetime_field_hash_map: ArenaHashMap,
@@ -60,22 +61,6 @@ 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,
@@ -104,6 +89,48 @@ impl ColumnarWriter {
             + self.datetime_field_hash_map.mem_usage()
     }
 
+    /// Returns the list of doc ids from 0..num_docs sorted by the `sort_field`
+    /// column.
+    ///
+    /// If the column is multivalued, use the first value for scoring.
+    /// If no value is associated to a specific row, the document is assigned
+    /// the lowest possible score.
+    ///
+    /// The sort applied is stable.
+    pub fn sort_order(&self, sort_field: &str, num_docs: RowId, reversed: bool) -> Vec<u32> {
+        let Some(numerical_col_writer) =
+            self.numerical_field_hash_map.get::<NumericalColumnWriter>(sort_field.as_bytes()) else {
+                return Vec::new();
+        };
+        let mut symbols_buffer = Vec::new();
+        let mut values = Vec::new();
+        let mut last_doc_opt: Option<RowId> = None;
+        for op in numerical_col_writer.operation_iterator(&self.arena, None, &mut symbols_buffer) {
+            match op {
+                ColumnOperation::NewDoc(doc) => {
+                    last_doc_opt = Some(doc);
+                }
+                ColumnOperation::Value(numerical_value) => {
+                    if let Some(last_doc) = last_doc_opt {
+                        let score: f32 = f64::coerce(numerical_value) as f32;
+                        values.push((score, last_doc));
+                    }
+                }
+            }
+        }
+        for doc in values.len() as u32..num_docs {
+            values.push((0.0f32, doc));
+        }
+        values.sort_by(|(left_score, _), (right_score, _)| {
+            if reversed {
+                right_score.partial_cmp(left_score).unwrap()
+            } else {
+                left_score.partial_cmp(right_score).unwrap()
+            }
+        });
+        values.into_iter().map(|(_score, doc)| doc).collect()
+    }
+
     /// Records a column type. This is useful to bypass the coercion process,
     /// makes sure the empty is present in the resulting columnar, or set
     /// the `sort_values_within_row`.
@@ -224,11 +251,15 @@ impl ColumnarWriter {
         });
     }
 
-    pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: crate::DateTime) {
+    pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: common::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.timestamp_micros), arena);
+            column.record(
+                doc,
+                NumericalValue::I64(datetime.into_timestamp_micros()),
+                arena,
+            );
             column
         });
     }
@@ -278,37 +309,47 @@ impl ColumnarWriter {
             },
         );
     }
-    pub fn serialize(&mut self, num_docs: RowId, wrt: &mut dyn io::Write) -> io::Result<()> {
+    pub fn serialize(
+        &mut self,
+        num_docs: RowId,
+        old_to_new_row_ids: Option<&[RowId]>,
+        wrt: &mut dyn io::Write,
+    ) -> io::Result<()> {
         let mut serializer = ColumnarSerializer::new(wrt);
-        let mut columns: Vec<(&[u8], ColumnTypeCategory, Addr)> = self
+        let mut columns: Vec<(&[u8], ColumnType, Addr)> = self
             .numerical_field_hash_map
             .iter()
-            .map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::Numerical, addr))
+            .map(|(column_name, addr, _)| {
+                let numerical_column_writer: NumericalColumnWriter =
+                    self.numerical_field_hash_map.read(addr);
+                let column_type = numerical_column_writer.numerical_type().into();
+                (column_name, column_type, addr)
+            })
             .collect();
         columns.extend(
             self.bytes_field_hash_map
                 .iter()
-                .map(|(term, addr, _)| (term, ColumnTypeCategory::Bytes, addr)),
+                .map(|(term, addr, _)| (term, ColumnType::Bytes, addr)),
         );
         columns.extend(
             self.str_field_hash_map
                 .iter()
-                .map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::Str, addr)),
+                .map(|(column_name, addr, _)| (column_name, ColumnType::Str, addr)),
         );
         columns.extend(
             self.bool_field_hash_map
                 .iter()
-                .map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::Bool, addr)),
+                .map(|(column_name, addr, _)| (column_name, ColumnType::Bool, addr)),
         );
         columns.extend(
             self.ip_addr_field_hash_map
                 .iter()
-                .map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::IpAddr, addr)),
+                .map(|(column_name, addr, _)| (column_name, ColumnType::IpAddr, addr)),
         );
         columns.extend(
             self.datetime_field_hash_map
                 .iter()
-                .map(|(column_name, addr, _)| (column_name, ColumnTypeCategory::DateTime, addr)),
+                .map(|(column_name, addr, _)| (column_name, ColumnType::DateTime, addr)),
         );
         columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
 
@@ -316,20 +357,24 @@ impl ColumnarWriter {
         let mut symbol_byte_buffer: Vec<u8> = Vec::new();
         for (column_name, column_type, addr) in columns {
             match column_type {
-                ColumnTypeCategory::Bool => {
+                ColumnType::Bool => {
                     let column_writer: ColumnWriter = self.bool_field_hash_map.read(addr);
                     let cardinality = column_writer.get_cardinality(num_docs);
                     let mut column_serializer =
-                        serializer.serialize_column(column_name, ColumnType::Bool);
+                        serializer.serialize_column(column_name, column_type);
                     serialize_bool_column(
                         cardinality,
                         num_docs,
-                        column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
+                        column_writer.operation_iterator(
+                            arena,
+                            old_to_new_row_ids,
+                            &mut symbol_byte_buffer,
+                        ),
                         buffers,
                         &mut column_serializer,
                     )?;
                 }
-                ColumnTypeCategory::IpAddr => {
+                ColumnType::IpAddr => {
                     let column_writer: ColumnWriter = self.ip_addr_field_hash_map.read(addr);
                     let cardinality = column_writer.get_cardinality(num_docs);
                     let mut column_serializer =
@@ -337,50 +382,64 @@ impl ColumnarWriter {
                     serialize_ip_addr_column(
                         cardinality,
                         num_docs,
-                        column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
+                        column_writer.operation_iterator(
+                            arena,
+                            old_to_new_row_ids,
+                            &mut symbol_byte_buffer,
+                        ),
                         buffers,
                         &mut column_serializer,
                     )?;
                 }
-                ColumnTypeCategory::Bytes | ColumnTypeCategory::Str => {
-                    let (column_type, str_column_writer): (ColumnType, StrOrBytesColumnWriter) =
-                        if column_type == ColumnTypeCategory::Bytes {
-                            (ColumnType::Bytes, self.bytes_field_hash_map.read(addr))
+                ColumnType::Bytes | ColumnType::Str => {
+                    let str_or_bytes_column_writer: StrOrBytesColumnWriter =
+                        if column_type == ColumnType::Bytes {
+                            self.bytes_field_hash_map.read(addr)
                         } else {
-                            (ColumnType::Str, self.str_field_hash_map.read(addr))
+                            self.str_field_hash_map.read(addr)
                         };
                     let dictionary_builder =
-                        &dictionaries[str_column_writer.dictionary_id as usize];
-                    let cardinality = str_column_writer.column_writer.get_cardinality(num_docs);
+                        &dictionaries[str_or_bytes_column_writer.dictionary_id as usize];
+                    let cardinality = str_or_bytes_column_writer
+                        .column_writer
+                        .get_cardinality(num_docs);
                     let mut column_serializer =
                         serializer.serialize_column(column_name, column_type);
                     serialize_bytes_or_str_column(
                         cardinality,
                         num_docs,
-                        str_column_writer.sort_values_within_row,
+                        str_or_bytes_column_writer.sort_values_within_row,
                         dictionary_builder,
-                        str_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
+                        str_or_bytes_column_writer.operation_iterator(
+                            arena,
+                            old_to_new_row_ids,
+                            &mut symbol_byte_buffer,
+                        ),
                         buffers,
                         &mut column_serializer,
                     )?;
                 }
-                ColumnTypeCategory::Numerical => {
+                ColumnType::F64 | ColumnType::I64 | ColumnType::U64 => {
                     let numerical_column_writer: NumericalColumnWriter =
                         self.numerical_field_hash_map.read(addr);
-                    let (numerical_type, cardinality) =
-                        numerical_column_writer.column_type_and_cardinality(num_docs);
+                    let cardinality = numerical_column_writer.cardinality(num_docs);
                     let mut column_serializer =
-                        serializer.serialize_column(column_name, ColumnType::from(numerical_type));
+                        serializer.serialize_column(column_name, column_type);
+                    let numerical_type = column_type.numerical_type().unwrap();
                     serialize_numerical_column(
                         cardinality,
                         num_docs,
                         numerical_type,
-                        numerical_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
+                        numerical_column_writer.operation_iterator(
+                            arena,
+                            old_to_new_row_ids,
+                            &mut symbol_byte_buffer,
+                        ),
                         buffers,
                         &mut column_serializer,
                     )?;
                 }
-                ColumnTypeCategory::DateTime => {
+                ColumnType::DateTime => {
                     let column_writer: ColumnWriter = self.datetime_field_hash_map.read(addr);
                     let cardinality = column_writer.get_cardinality(num_docs);
                     let mut column_serializer =
@@ -389,7 +448,11 @@ impl ColumnarWriter {
                         cardinality,
                         num_docs,
                         NumericalType::I64,
-                        column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
+                        column_writer.operation_iterator(
+                            arena,
+                            old_to_new_row_ids,
+                            &mut symbol_byte_buffer,
+                        ),
                         buffers,
                         &mut column_serializer,
                     )?;
@@ -588,13 +651,12 @@ where
     crate::column::serialize_column_mappable_to_u128(
         serializable_column_index,
         &&values[..],
-        values.len() as u32,
         &mut wrt,
     )?;
     Ok(())
 }
 
-fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut Vec<u64>) {
+fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut [u64]) {
     let mut start_index: usize = 0;
     for end_index in multivalued_index.iter().copied() {
         let end_index = end_index as usize;
@@ -699,7 +761,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(3), Cardinality::Full);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 6);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -728,7 +790,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(3), Cardinality::Optional);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 4);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
@@ -751,7 +813,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(2), Cardinality::Optional);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 2);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -770,7 +832,7 @@ mod tests {
         assert_eq!(column_writer.get_cardinality(1), Cardinality::Multivalued);
         let mut buffer = Vec::new();
         let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
-            .operation_iterator(&mut arena, &mut buffer)
+            .operation_iterator(&arena, None, &mut buffer)
             .collect();
         assert_eq!(symbols.len(), 3);
         assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));

columnar/src/columnar/writer/value_index.rs

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

columnar/src/dynamic_column.rs

@@ -3,12 +3,12 @@ use std::net::Ipv6Addr;
 use std::sync::Arc;
 
 use common::file_slice::FileSlice;
-use common::{HasLen, OwnedBytes};
+use common::{DateTime, HasLen, OwnedBytes};
 
 use crate::column::{BytesColumn, Column, StrColumn};
 use crate::column_values::{monotonic_map_column, StrictlyMonotonicFn};
 use crate::columnar::ColumnType;
-use crate::{Cardinality, DateTime, NumericalType};
+use crate::{Cardinality, NumericalType};
 
 #[derive(Clone)]
 pub enum DynamicColumn {
@@ -166,9 +166,9 @@ impl StrictlyMonotonicFn<i64, u64> for MapI64ToU64 {
 
 macro_rules! static_dynamic_conversions {
     ($typ:ty, $enum_name:ident) => {
-        impl Into<Option<$typ>> for DynamicColumn {
-            fn into(self) -> Option<$typ> {
-                if let DynamicColumn::$enum_name(col) = self {
+        impl From<DynamicColumn> for Option<$typ> {
+            fn from(dynamic_column: DynamicColumn) -> Option<$typ> {
+                if let DynamicColumn::$enum_name(col) = dynamic_column {
                     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<crate::DateTime>, DateTime);
+static_dynamic_conversions!(Column<DateTime>, DateTime);
 static_dynamic_conversions!(StrColumn, Str);
 static_dynamic_conversions!(BytesColumn, Bytes);
 static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
@@ -206,10 +206,9 @@ impl DynamicColumnHandle {
         self.open_internal(column_bytes)
     }
 
-    // TODO rename load_async
-    pub async fn open_async(&self) -> io::Result<DynamicColumn> {
-        let column_bytes: OwnedBytes = self.file_slice.read_bytes_async().await?;
-        self.open_internal(column_bytes)
+    #[doc(hidden)]
+    pub fn file_slice(&self) -> &FileSlice {
+        &self.file_slice
     }
 
     /// Returns the `u64` fast field reader reader associated with `fields` of types
@@ -235,17 +234,15 @@ impl DynamicColumnHandle {
 
     fn open_internal(&self, column_bytes: OwnedBytes) -> io::Result<DynamicColumn> {
         let dynamic_column: DynamicColumn = match self.column_type {
-            ColumnType::Bytes => {
-                crate::column::open_column_bytes::<BytesColumn>(column_bytes)?.into()
-            }
-            ColumnType::Str => crate::column::open_column_bytes::<StrColumn>(column_bytes)?.into(),
+            ColumnType::Bytes => crate::column::open_column_bytes(column_bytes)?.into(),
+            ColumnType::Str => crate::column::open_column_str(column_bytes)?.into(),
             ColumnType::I64 => crate::column::open_column_u64::<i64>(column_bytes)?.into(),
             ColumnType::U64 => crate::column::open_column_u64::<u64>(column_bytes)?.into(),
             ColumnType::F64 => crate::column::open_column_u64::<f64>(column_bytes)?.into(),
             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::<crate::DateTime>(column_bytes)?.into()
+                crate::column::open_column_u64::<DateTime>(column_bytes)?.into()
             }
         };
         Ok(dynamic_column)

columnar/src/lib.rs

@@ -24,7 +24,7 @@ pub use column_index::ColumnIndex;
 pub use column_values::{ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64};
 pub use columnar::{
     merge_columnar, ColumnType, ColumnarReader, ColumnarWriter, HasAssociatedColumnType,
-    MergeRowOrder, StackMergeOrder,
+    MergeRowOrder, ShuffleMergeOrder, StackMergeOrder,
 };
 use sstable::VoidSSTable;
 pub use value::{NumericalType, NumericalValue};
@@ -32,13 +32,18 @@ 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 {
+    pub segment_ord: u32,
+    pub row_id: RowId,
+}
+
 pub use sstable::Dictionary;
 pub type Streamer<'a> = sstable::Streamer<'a, VoidSSTable>;
 
-#[derive(Clone, Copy, PartialOrd, PartialEq, Default, Debug)]
-pub struct DateTime {
-    pub timestamp_micros: i64,
-}
+pub use common::DateTime;
 
 #[derive(Copy, Clone, Debug)]
 pub struct InvalidData;

columnar/src/tests.rs

@@ -12,7 +12,7 @@ fn test_dataframe_writer_str() {
     dataframe_writer.record_str(1u32, "my_string", "hello");
     dataframe_writer.record_str(3u32, "my_string", "helloeee");
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(5, &mut buffer).unwrap();
+    dataframe_writer.serialize(5, None, &mut buffer).unwrap();
     let columnar = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar.num_columns(), 1);
     let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
@@ -26,7 +26,7 @@ fn test_dataframe_writer_bytes() {
     dataframe_writer.record_bytes(1u32, "my_string", b"hello");
     dataframe_writer.record_bytes(3u32, "my_string", b"helloeee");
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(5, &mut buffer).unwrap();
+    dataframe_writer.serialize(5, None, &mut buffer).unwrap();
     let columnar = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar.num_columns(), 1);
     let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
@@ -40,7 +40,7 @@ fn test_dataframe_writer_bool() {
     dataframe_writer.record_bool(1u32, "bool.value", false);
     dataframe_writer.record_bool(3u32, "bool.value", true);
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(5, &mut buffer).unwrap();
+    dataframe_writer.serialize(5, None, &mut buffer).unwrap();
     let columnar = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar.num_columns(), 1);
     let cols: Vec<DynamicColumnHandle> = columnar.read_columns("bool.value").unwrap();
@@ -63,7 +63,7 @@ fn test_dataframe_writer_u64_multivalued() {
     dataframe_writer.record_numerical(6u32, "divisor", 2u64);
     dataframe_writer.record_numerical(6u32, "divisor", 3u64);
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(7, &mut buffer).unwrap();
+    dataframe_writer.serialize(7, None, &mut buffer).unwrap();
     let columnar = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar.num_columns(), 1);
     let cols: Vec<DynamicColumnHandle> = columnar.read_columns("divisor").unwrap();
@@ -75,7 +75,7 @@ fn test_dataframe_writer_u64_multivalued() {
         divisor_col.get_cardinality(),
         crate::Cardinality::Multivalued
     );
-    assert_eq!(divisor_col.num_rows(), 7);
+    assert_eq!(divisor_col.num_docs(), 7);
 }
 
 #[test]
@@ -84,7 +84,7 @@ fn test_dataframe_writer_ip_addr() {
     dataframe_writer.record_ip_addr(1, "ip_addr", Ipv6Addr::from_u128(1001));
     dataframe_writer.record_ip_addr(3, "ip_addr", Ipv6Addr::from_u128(1050));
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(5, &mut buffer).unwrap();
+    dataframe_writer.serialize(5, None, &mut buffer).unwrap();
     let columnar = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar.num_columns(), 1);
     let cols: Vec<DynamicColumnHandle> = columnar.read_columns("ip_addr").unwrap();
@@ -113,7 +113,7 @@ fn test_dataframe_writer_numerical() {
     dataframe_writer.record_numerical(2u32, "srical.value", NumericalValue::U64(13u64));
     dataframe_writer.record_numerical(4u32, "srical.value", NumericalValue::U64(15u64));
     let mut buffer: Vec<u8> = Vec::new();
-    dataframe_writer.serialize(6, &mut buffer).unwrap();
+    dataframe_writer.serialize(6, None, &mut buffer).unwrap();
     let columnar = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar.num_columns(), 1);
     let cols: Vec<DynamicColumnHandle> = columnar.read_columns("srical.value").unwrap();
@@ -144,7 +144,7 @@ fn test_dictionary_encoded_str() {
     columnar_writer.record_str(3, "my.column", "c");
     columnar_writer.record_str(3, "my.column2", "different_column!");
     columnar_writer.record_str(4, "my.column", "b");
-    columnar_writer.serialize(5, &mut buffer).unwrap();
+    columnar_writer.serialize(5, None, &mut buffer).unwrap();
     let columnar_reader = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar_reader.num_columns(), 2);
     let col_handles = columnar_reader.read_columns("my.column").unwrap();
@@ -176,7 +176,7 @@ fn test_dictionary_encoded_bytes() {
     columnar_writer.record_bytes(3, "my.column", b"c");
     columnar_writer.record_bytes(3, "my.column2", b"different_column!");
     columnar_writer.record_bytes(4, "my.column", b"b");
-    columnar_writer.serialize(5, &mut buffer).unwrap();
+    columnar_writer.serialize(5, None, &mut buffer).unwrap();
     let columnar_reader = ColumnarReader::open(buffer).unwrap();
     assert_eq!(columnar_reader.num_columns(), 2);
     let col_handles = columnar_reader.read_columns("my.column").unwrap();

columnar/src/value.rs

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

common/Cargo.toml

@@ -13,9 +13,10 @@ repository = "https://github.com/quickwit-oss/tantivy"
 # See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
 
 [dependencies]
-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/datetime.rs

@@ -0,0 +1,136 @@
+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/lib.rs

@@ -2,15 +2,15 @@
 
 use std::ops::Deref;
 
-pub use byteorder::LittleEndian as Endianness;
-
 mod bitset;
+mod datetime;
 pub mod file_slice;
 mod group_by;
 mod serialize;
 mod vint;
 mod writer;
 pub use bitset::*;
+pub use datetime::{DatePrecision, DateTime};
 pub use group_by::GroupByIteratorExtended;
 pub use ownedbytes::{OwnedBytes, StableDeref};
 pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
@@ -107,6 +107,21 @@ pub fn u64_to_f64(val: u64) -> f64 {
     })
 }
 
+/// Replaces a given byte in the `bytes` slice of bytes.
+///
+/// This function assumes that the needle is rarely contained in the bytes string
+/// and offers a fast path if the needle is not present.
+pub fn replace_in_place(needle: u8, replacement: u8, bytes: &mut [u8]) {
+    if !bytes.contains(&needle) {
+        return;
+    }
+    for b in bytes {
+        if *b == needle {
+            *b = replacement;
+        }
+    }
+}
+
 #[cfg(test)]
 pub mod test {
 
@@ -171,4 +186,20 @@ pub mod test {
         assert!(f64_to_u64(-2.0) < f64_to_u64(1.0));
         assert!(f64_to_u64(-2.0) < f64_to_u64(-1.5));
     }
+
+    #[test]
+    fn test_replace_in_place() {
+        let test_aux = |before_replacement: &[u8], expected: &[u8]| {
+            let mut bytes: Vec<u8> = before_replacement.to_vec();
+            super::replace_in_place(b'b', b'c', &mut bytes);
+            assert_eq!(&bytes[..], expected);
+        };
+        test_aux(b"", b"");
+        test_aux(b"b", b"c");
+        test_aux(b"baaa", b"caaa");
+        test_aux(b"aaab", b"aaac");
+        test_aux(b"aaabaa", b"aaacaa");
+        test_aux(b"aaaaaa", b"aaaaaa");
+        test_aux(b"bbbb", b"cccc");
+    }
 }

common/src/serialize.rs

@@ -1,9 +1,7 @@
 use std::io::{Read, Write};
 use std::{fmt, io};
 
-use byteorder::{ReadBytesExt, WriteBytesExt};
-
-use crate::{Endianness, VInt};
+use crate::VInt;
 
 #[derive(Default)]
 struct Counter(u64);
@@ -107,11 +105,13 @@ impl<Left: BinarySerializable + FixedSize, Right: BinarySerializable + FixedSize
 
 impl BinarySerializable for u32 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_u32::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
 
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<u32> {
-        reader.read_u32::<Endianness>()
+        let mut buf = [0u8; 4];
+        reader.read_exact(&mut buf)?;
+        Ok(u32::from_le_bytes(buf))
     }
 }
 
@@ -121,11 +121,13 @@ impl FixedSize for u32 {
 
 impl BinarySerializable for u16 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_u16::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
 
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<u16> {
-        reader.read_u16::<Endianness>()
+        let mut buf = [0u8; 2];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -135,10 +137,12 @@ impl FixedSize for u16 {
 
 impl BinarySerializable for u64 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_u64::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
-        reader.read_u64::<Endianness>()
+        let mut buf = [0u8; 8];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -148,10 +152,12 @@ impl FixedSize for u64 {
 
 impl BinarySerializable for u128 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_u128::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
-        reader.read_u128::<Endianness>()
+        let mut buf = [0u8; 16];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -161,10 +167,12 @@ impl FixedSize for u128 {
 
 impl BinarySerializable for f32 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_f32::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
-        reader.read_f32::<Endianness>()
+        let mut buf = [0u8; 4];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -174,10 +182,12 @@ impl FixedSize for f32 {
 
 impl BinarySerializable for i64 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_i64::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
-        reader.read_i64::<Endianness>()
+        let mut buf = [0u8; Self::SIZE_IN_BYTES];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -187,10 +197,12 @@ impl FixedSize for i64 {
 
 impl BinarySerializable for f64 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_f64::<Endianness>(*self)
+        writer.write_all(&self.to_le_bytes())
     }
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
-        reader.read_f64::<Endianness>()
+        let mut buf = [0u8; Self::SIZE_IN_BYTES];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -200,10 +212,12 @@ impl FixedSize for f64 {
 
 impl BinarySerializable for u8 {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_u8(*self)
+        writer.write_all(&self.to_le_bytes())
     }
-    fn deserialize<R: Read>(reader: &mut R) -> io::Result<u8> {
-        reader.read_u8()
+    fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
+        let mut buf = [0u8; Self::SIZE_IN_BYTES];
+        reader.read_exact(&mut buf)?;
+        Ok(Self::from_le_bytes(buf))
     }
 }
 
@@ -213,10 +227,10 @@ impl FixedSize for u8 {
 
 impl BinarySerializable for bool {
     fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
-        writer.write_u8(u8::from(*self))
+        (*self as u8).serialize(writer)
     }
     fn deserialize<R: Read>(reader: &mut R) -> io::Result<bool> {
-        let val = reader.read_u8()?;
+        let val = u8::deserialize(reader)?;
         match val {
             0 => Ok(false),
             1 => Ok(true),

common/src/vint.rs

@@ -1,8 +1,6 @@
 use std::io;
 use std::io::{Read, Write};
 
-use byteorder::{ByteOrder, LittleEndian};
-
 use super::BinarySerializable;
 
 /// Variable int serializes a u128 number
@@ -127,7 +125,7 @@ pub fn serialize_vint_u32(val: u32, buf: &mut [u8; 8]) -> &[u8] {
             5,
         ),
     };
-    LittleEndian::write_u64(&mut buf[..], res);
+    buf.copy_from_slice(&res.to_le_bytes());
     &buf[0..num_bytes]
 }
 

examples-disabled/aggregation.rs

@@ -1,130 +0,0 @@
-// # 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/ip_field.rs

@@ -1,73 +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
-    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/aggregation.rs

@@ -0,0 +1,319 @@
+// # 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, None);
+
+    let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
+    let res2: Value = serde_json::to_value(agg_res)?;
+
+    // ### Request Rust API
+    //
+    // This is exactly the same request as above, but via the rust structures.
+    //
+
+    let agg_req: Aggregations = vec![(
+        "group_by_stock".to_string(),
+        Aggregation::Bucket(BucketAggregation {
+            bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                field: "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, None);
+    // 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, None);
+
+    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/custom_collector.rs

@@ -7,9 +7,7 @@
 // Of course, you can have a look at the tantivy's built-in collectors
 // such as the `CountCollector` for more examples.
 
-use std::sync::Arc;
-
-use fastfield_codecs::Column;
+use columnar::Column;
 // ---
 // Importing tantivy...
 use tantivy::collector::{Collector, SegmentCollector};
@@ -97,7 +95,7 @@ impl Collector for StatsCollector {
 }
 
 struct StatsSegmentCollector {
-    fast_field_reader: Arc<dyn Column<u64>>,
+    fast_field_reader: Column,
     stats: Stats,
 }
 
@@ -105,10 +103,14 @@ impl SegmentCollector for StatsSegmentCollector {
     type Fruit = Option<Stats>;
 
     fn collect(&mut self, doc: u32, _score: Score) {
-        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;
+        // 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;
+        }
     }
 
     fn harvest(self) -> <Self as SegmentCollector>::Fruit {
@@ -169,7 +171,7 @@ fn main() -> tantivy::Result<()> {
     let searcher = reader.searcher();
     let query_parser = QueryParser::for_index(&index, vec![product_name, product_description]);
 
-    // here we want to get a hit on the 'ken' in Frankenstein
+    // here we want to search for `broom` and use `StatsCollector` on the hits.
     let query = query_parser.parse_query("broom")?;
     if let Some(stats) =
         searcher.search(&query, &StatsCollector::with_field("price".to_string()))?

examples/custom_tokenizer.rs

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

examples/date_time_field.rs

@@ -14,6 +14,7 @@ fn main() -> tantivy::Result<()> {
         .set_stored()
         .set_fast()
         .set_precision(tantivy::DatePrecision::Seconds);
+    // Add `occurred_at` date field type
     let occurred_at = schema_builder.add_date_field("occurred_at", opts);
     let event_type = schema_builder.add_text_field("event", STRING | STORED);
     let schema = schema_builder.build();
@@ -22,6 +23,7 @@ fn main() -> tantivy::Result<()> {
     let index = Index::create_in_ram(schema.clone());
 
     let mut index_writer = index.writer(50_000_000)?;
+    // The dates are passed as string in the RFC3339 format
     let doc = schema.parse_document(
         r#"{
         "occurred_at": "2022-06-22T12:53:50.53Z",
@@ -41,14 +43,16 @@ fn main() -> tantivy::Result<()> {
     let reader = index.reader()?;
     let searcher = reader.searcher();
 
-    // # Default fields: event_type
+    // # Search
     let query_parser = QueryParser::for_index(&index, vec![event_type]);
     {
-        let query = query_parser.parse_query("event:comment")?;
+        // Simple exact search on the date
+        let query = query_parser.parse_query("occurred_at:\"2022-06-22T12:53:50.53Z\"")?;
         let count_docs = searcher.search(&*query, &TopDocs::with_limit(5))?;
         assert_eq!(count_docs.len(), 1);
     }
     {
+        // Range query on the date field
         let query = query_parser
             .parse_query(r#"occurred_at:[2022-06-22T12:58:00Z TO 2022-06-23T00:00:00Z}"#)?;
         let count_docs = searcher.search(&*query, &TopDocs::with_limit(4))?;

examples/faceted_search.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/faceted_search_with_tweaked_score.rs

@@ -1,3 +1,12 @@
+// # Faceted Search With Tweak Score
+//
+// This example covers the faceted search functionalities of
+// tantivy.
+//
+// We will :
+// - define a text field "name" in our schema
+// - define a facet field "classification" in our schema
+
 use std::collections::HashSet;
 
 use tantivy::collector::TopDocs;
@@ -55,8 +64,9 @@ 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
@@ -64,12 +74,10 @@ 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| {
-                    ingredient_reader.facet_ords(doc, &mut facet_ords_buffer);
-                    let missing_ingredients = facet_ords_buffer
-                        .iter()
+                    // Update the original score with a tweaked score
+                    let missing_ingredients = ingredient_reader
+                        .facet_ords(doc)
                         .filter(|ord| !query_ords.contains(ord))
                         .count();
                     let tweak = 1.0 / 4_f32.powi(missing_ingredients as i32);

examples/fuzzy_search.rs

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

examples/ip_field.rs

@@ -0,0 +1,107 @@
+// # 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(())
+}

examples/warmer.rs

@@ -17,7 +17,6 @@ use tantivy::{
 
 type ProductId = u64;
 
-/// Price
 type Price = u32;
 
 pub trait PriceFetcher: Send + Sync + 'static {
@@ -48,7 +47,10 @@ 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)?;
+            let product_id_reader = segment
+                .fast_fields()
+                .u64(&self.field)?
+                .first_or_default_col(0);
             let product_ids: Vec<ProductId> = segment
                 .doc_ids_alive()
                 .map(|doc| product_id_reader.get_val(doc))
@@ -87,10 +89,10 @@ impl Warmer for DynamicPriceColumn {
     }
 }
 
-/// For the sake of this example, the table is just an editable HashMap behind a RwLock.
-/// This map represents a map (ProductId -> Price)
-///
-/// In practise, it could be fetching things from an external service, like a SQL table.
+// For the sake of this example, the table is just an editable HashMap behind a RwLock.
+// This map represents a map (ProductId -> Price)
+//
+// In practise, it could be fetching things from an external service, like a SQL table.
 #[derive(Default, Clone)]
 pub struct ExternalPriceTable {
     prices: Arc<RwLock<HashMap<ProductId, Price>>>,

src/aggregation/agg_req.rs

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

src/aggregation/agg_req_with_accessor.rs

@@ -2,21 +2,20 @@
 
 use std::rc::Rc;
 use std::sync::atomic::AtomicU32;
-use std::sync::Arc;
 
-use fastfield_codecs::Column;
+use columnar::{Column, ColumnType, StrColumn};
 
 use super::agg_req::{Aggregation, Aggregations, BucketAggregationType, MetricAggregation};
-use super::bucket::{HistogramAggregation, RangeAggregation, TermsAggregation};
+use super::bucket::{
+    DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
+};
 use super::metric::{
     AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
     SumAggregation,
 };
 use super::segment_agg_result::BucketCount;
 use super::VecWithNames;
-use crate::fastfield::{type_and_cardinality, MultiValuedFastFieldReader};
-use crate::schema::Type;
-use crate::{InvertedIndexReader, SegmentReader, TantivyError};
+use crate::{SegmentReader, TantivyError};
 
 #[derive(Clone, Default)]
 pub(crate) struct AggregationsWithAccessor {
@@ -37,39 +36,13 @@ impl AggregationsWithAccessor {
     }
 }
 
-#[derive(Clone)]
-pub(crate) enum FastFieldAccessor {
-    Multi(MultiValuedFastFieldReader<u64>),
-    Single(Arc<dyn Column<u64>>),
-}
-impl FastFieldAccessor {
-    pub fn as_single(&self) -> Option<&dyn Column<u64>> {
-        match self {
-            FastFieldAccessor::Multi(_) => None,
-            FastFieldAccessor::Single(reader) => Some(&**reader),
-        }
-    }
-    pub fn into_single(self) -> Option<Arc<dyn Column<u64>>> {
-        match self {
-            FastFieldAccessor::Multi(_) => None,
-            FastFieldAccessor::Single(reader) => Some(reader),
-        }
-    }
-    pub fn as_multi(&self) -> Option<&MultiValuedFastFieldReader<u64>> {
-        match self {
-            FastFieldAccessor::Multi(reader) => Some(reader),
-            FastFieldAccessor::Single(_) => None,
-        }
-    }
-}
-
 #[derive(Clone)]
 pub struct BucketAggregationWithAccessor {
     /// In general there can be buckets without fast field access, e.g. buckets that are created
     /// based on search terms. So eventually this needs to be Option or moved.
-    pub(crate) accessor: FastFieldAccessor,
-    pub(crate) inverted_index: Option<Arc<InvertedIndexReader>>,
-    pub(crate) field_type: Type,
+    pub(crate) accessor: Column<u64>,
+    pub(crate) str_dict_column: Option<StrColumn>,
+    pub(crate) field_type: ColumnType,
     pub(crate) bucket_agg: BucketAggregationType,
     pub(crate) sub_aggregation: AggregationsWithAccessor,
     pub(crate) bucket_count: BucketCount,
@@ -83,20 +56,23 @@ impl BucketAggregationWithAccessor {
         bucket_count: Rc<AtomicU32>,
         max_bucket_count: u32,
     ) -> crate::Result<BucketAggregationWithAccessor> {
-        let mut inverted_index = None;
+        let mut str_dict_column = None;
         let (accessor, field_type) = match &bucket {
             BucketAggregationType::Range(RangeAggregation {
                 field: field_name, ..
-            }) => get_ff_reader_and_validate(reader, field_name, Cardinality::SingleValue)?,
+            }) => get_ff_reader_and_validate(reader, field_name)?,
             BucketAggregationType::Histogram(HistogramAggregation {
                 field: field_name, ..
-            }) => get_ff_reader_and_validate(reader, field_name, Cardinality::SingleValue)?,
+            }) => 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, ..
             }) => {
-                let field = reader.schema().get_field(field_name)?;
-                inverted_index = Some(reader.inverted_index(field)?);
-                get_ff_reader_and_validate(reader, field_name, Cardinality::MultiValues)?
+                str_dict_column = reader.fast_fields().str(field_name)?;
+                get_ff_reader_and_validate(reader, field_name)?
             }
         };
         let sub_aggregation = sub_aggregation.clone();
@@ -110,7 +86,7 @@ impl BucketAggregationWithAccessor {
                 max_bucket_count,
             )?,
             bucket_agg: bucket.clone(),
-            inverted_index,
+            str_dict_column,
             bucket_count: BucketCount {
                 bucket_count,
                 max_bucket_count,
@@ -123,8 +99,8 @@ impl BucketAggregationWithAccessor {
 #[derive(Clone)]
 pub struct MetricAggregationWithAccessor {
     pub metric: MetricAggregation,
-    pub field_type: Type,
-    pub accessor: Arc<dyn Column>,
+    pub field_type: ColumnType,
+    pub accessor: Column<u64>,
 }
 
 impl MetricAggregationWithAccessor {
@@ -139,13 +115,10 @@ impl MetricAggregationWithAccessor {
             | MetricAggregation::Min(MinAggregation { field: field_name })
             | MetricAggregation::Stats(StatsAggregation { field: field_name })
             | MetricAggregation::Sum(SumAggregation { field: field_name }) => {
-                let (accessor, field_type) =
-                    get_ff_reader_and_validate(reader, field_name, Cardinality::SingleValue)?;
+                let (accessor, field_type) = get_ff_reader_and_validate(reader, field_name)?;
 
                 Ok(MetricAggregationWithAccessor {
-                    accessor: accessor
-                        .into_single()
-                        .expect("unexpected fast field cardinality"),
+                    accessor,
                     field_type,
                     metric: metric.clone(),
                 })
@@ -190,32 +163,12 @@ pub(crate) fn get_aggs_with_accessor_and_validate(
 fn get_ff_reader_and_validate(
     reader: &SegmentReader,
     field_name: &str,
-    cardinality: Cardinality,
-) -> crate::Result<(FastFieldAccessor, Type)> {
-    let field = reader.schema().get_field(field_name)?;
-    let field_type = reader.schema().get_field_entry(field).field_type();
-
-    if let Some((_ff_type, field_cardinality)) = type_and_cardinality(field_type) {
-        if cardinality != field_cardinality {
-            return Err(TantivyError::InvalidArgument(format!(
-                "Invalid field cardinality on field {} expected {:?}, but got {:?}",
-                field_name, cardinality, field_cardinality
-            )));
-        }
-    } else {
-        return Err(TantivyError::InvalidArgument(format!(
-            "Only fast fields of type f64, u64, i64 are supported, but got {:?} ",
-            field_type.value_type()
-        )));
-    };
-
+) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
     let ff_fields = reader.fast_fields();
-    match cardinality {
-        Cardinality::SingleValue => ff_fields
-            .u64_lenient(field_name)
-            .map(|field| (FastFieldAccessor::Single(field), field_type.value_type())),
-        Cardinality::MultiValues => ff_fields
-            .u64s_lenient(field_name)
-            .map(|field| (FastFieldAccessor::Multi(field), field_type.value_type())),
-    }
+    let ff_field_with_type = ff_fields
+        .u64_lenient_with_type(field_name)?
+        .ok_or_else(|| {
+            TantivyError::InvalidArgument(format!("No fast field found for field: {}", field_name))
+        })?;
+    Ok(ff_field_with_type)
 }

src/aggregation/agg_result.rs

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

src/aggregation/bucket/histogram/date_histogram.rs

@@ -0,0 +1,475 @@
+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.
+///
+/// Currently only **fixed time** intervals are supported. Calendar-aware time intervals are not
+/// supported.
+///
+/// Like the histogram, values are rounded down into the closest bucket.
+///
+/// For this calculation all fastfield values are converted to f64.
+///
+/// # Limitations/Compatibility
+/// Only fixed time intervals are supported.
+///
+/// # JSON Format
+/// ```json
+/// {
+///     "prices": {
+///         "date_histogram": {
+///             "field": "price",
+///             "fixed_interval": "30d"
+///         }
+///     }
+/// }
+/// ```
+///
+/// Response
+/// 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
+    ///
+    /// Fixed intervals are configured with the `fixed_interval` parameter.
+    /// In contrast to calendar-aware intervals, fixed intervals are a fixed number of SI units and
+    /// never deviate, regardless of where they fall on the calendar. One second is always
+    /// composed of 1000ms. This allows fixed intervals to be specified in any multiple of the
+    /// supported units. However, it means fixed intervals cannot express other units such as
+    /// months, since the duration of a month is not a fixed quantity. Attempting to specify a
+    /// calendar interval like month or quarter will return an Error.
+    ///
+    /// The accepted units for fixed intervals are:
+    /// * `ms`: milliseconds
+    /// * `s`: seconds. Defined as 1000 milliseconds each.
+    /// * `m`: minutes. Defined as 60 seconds each (60_000 milliseconds).
+    /// * `h`: hours. Defined as 60 minutes each (3_600_000 milliseconds).
+    /// * `d`: days. Defined as 24 hours (86_400_000 milliseconds).
+    ///
+    /// 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`).
+    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 f64,
+            offset: self
+                .offset
+                .as_ref()
+                .map(|offset| parse_offset_into_microseconds(offset))
+                .transpose()?
+                .map(|el| el as f64),
+            min_doc_count: self.min_doc_count,
+            hard_bounds: None,
+            extended_bounds: None,
+            keyed: self.keyed,
+        })
+    }
+
+    fn validate(&self) -> crate::Result<()> {
+        if self.interval.is_some() {
+            return Err(crate::TantivyError::InvalidArgument(format!(
+                "`interval` parameter {:?} in date histogram is unsupported, only \
+                 `fixed_interval` is supported",
+                self.interval
+            )));
+        }
+        if self.format.is_some() {
+            return Err(crate::TantivyError::InvalidArgument(
+                "format parameter on date_histogram is unsupported".to_string(),
+            ));
+        }
+
+        if self.date_interval.is_some() {
+            return Err(crate::TantivyError::InvalidArgument(
+                "date_interval in date histogram is unsupported, only `fixed_interval` is \
+                 supported"
+                    .to_string(),
+            ));
+        }
+
+        parse_into_microseconds(&self.fixed_interval)?;
+
+        Ok(())
+    }
+}
+
+#[derive(Debug, Clone, PartialEq, Eq, Error)]
+/// Errors when parsing the fixed interval for `DateHistogramAggregationReq`.
+pub enum DateHistogramParseError {
+    /// Unit not recognized in passed String
+    #[error("Unit not recognized in passed String {0:?}")]
+    UnitNotRecognized(String),
+    /// Number not found in passed String
+    #[error("Number not found in passed String {0:?}")]
+    NumberMissing(String),
+    /// Unit not found in passed String
+    #[error("Unit not found in passed String {0:?}")]
+    UnitMissing(String),
+    /// Offset invalid
+    #[error("passed offset is invalid {0:?}")]
+    InvalidOffset(String),
+}
+
+fn parse_offset_into_microseconds(input: &str) -> Result<i64, AggregationError> {
+    let is_sign = |byte| &[byte] == b"-" || &[byte] == b"+";
+    if input.is_empty() {
+        return Err(DateHistogramParseError::InvalidOffset(input.to_string()).into());
+    }
+
+    let has_sign = is_sign(input.as_bytes()[0]);
+    if has_sign {
+        let (sign, input) = input.split_at(1);
+        let val = parse_into_microseconds(input)?;
+        if sign == "-" {
+            Ok(-val)
+        } else {
+            Ok(val)
+        }
+    } else {
+        parse_into_microseconds(input)
+    }
+}
+
+fn parse_into_microseconds(input: &str) -> Result<i64, AggregationError> {
+    let split_boundary = input
+        .as_bytes()
+        .iter()
+        .take_while(|byte| byte.is_ascii_digit())
+        .count();
+    let (number, unit) = input.split_at(split_boundary);
+    if number.is_empty() {
+        return Err(DateHistogramParseError::NumberMissing(input.to_string()).into());
+    }
+    if unit.is_empty() {
+        return Err(DateHistogramParseError::UnitMissing(input.to_string()).into());
+    }
+    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 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()),
+    };
+
+    Ok(number * multiplier_from_unit * 1000)
+}
+
+#[cfg(test)]
+mod tests {
+    use pretty_assertions::assert_eq;
+
+    use super::*;
+    use crate::aggregation::agg_req::Aggregations;
+    use crate::aggregation::tests::exec_request;
+    use crate::indexer::NoMergePolicy;
+    use crate::schema::{Schema, FAST};
+    use crate::Index;
+
+    #[test]
+    fn test_parse_into_microseconds() {
+        assert_eq!(parse_into_microseconds("1m").unwrap(), 60_000_000);
+        assert_eq!(parse_into_microseconds("2m").unwrap(), 120_000_000);
+        assert_eq!(
+            parse_into_microseconds("2y").unwrap_err(),
+            DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
+        );
+        assert_eq!(
+            parse_into_microseconds("2000").unwrap_err(),
+            DateHistogramParseError::UnitMissing("2000".to_string()).into()
+        );
+        assert_eq!(
+            parse_into_microseconds("ms").unwrap_err(),
+            DateHistogramParseError::NumberMissing("ms".to_string()).into()
+        );
+    }
+
+    #[test]
+    fn test_parse_offset_into_microseconds() {
+        assert_eq!(parse_offset_into_microseconds("1m").unwrap(), 60_000_000);
+        assert_eq!(parse_offset_into_microseconds("+1m").unwrap(), 60_000_000);
+        assert_eq!(parse_offset_into_microseconds("-1m").unwrap(), -60_000_000);
+        assert_eq!(parse_offset_into_microseconds("2m").unwrap(), 120_000_000);
+        assert_eq!(parse_offset_into_microseconds("+2m").unwrap(), 120_000_000);
+        assert_eq!(parse_offset_into_microseconds("-2m").unwrap(), -120_000_000);
+        assert_eq!(parse_offset_into_microseconds("-2ms").unwrap(), -2_000);
+        assert_eq!(
+            parse_offset_into_microseconds("2y").unwrap_err(),
+            DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
+        );
+        assert_eq!(
+            parse_offset_into_microseconds("2000").unwrap_err(),
+            DateHistogramParseError::UnitMissing("2000".to_string()).into()
+        );
+        assert_eq!(
+            parse_offset_into_microseconds("ms").unwrap_err(),
+            DateHistogramParseError::NumberMissing("ms".to_string()).into()
+        );
+    }
+
+    #[test]
+    fn test_parse_into_milliseconds_do_not_accept_non_ascii() {
+        assert!(parse_into_microseconds("１m").is_err());
+    }
+
+    pub fn get_test_index_from_docs(
+        merge_segments: bool,
+        segment_and_docs: &[Vec<&str>],
+    ) -> crate::Result<Index> {
+        let mut schema_builder = Schema::builder();
+        schema_builder.add_date_field("date", FAST);
+        schema_builder.add_text_field("text", FAST);
+        let schema = schema_builder.build();
+        let index = Index::create_in_ram(schema.clone());
+        {
+            let mut index_writer = index.writer_with_num_threads(1, 30_000_000)?;
+            index_writer.set_merge_policy(Box::new(NoMergePolicy));
+            for values in segment_and_docs {
+                for doc_str in values {
+                    let doc = schema.parse_document(doc_str)?;
+                    index_writer.add_document(doc)?;
+                }
+                // writing the segment
+                index_writer.commit()?;
+            }
+        }
+        if merge_segments {
+            let segment_ids = index
+                .searchable_segment_ids()
+                .expect("Searchable segments failed.");
+            if segment_ids.len() > 1 {
+                let mut index_writer = index.writer_for_tests()?;
+                index_writer.merge(&segment_ids).wait()?;
+                index_writer.wait_merging_threads()?;
+            }
+        }
+
+        Ok(index)
+    }
+
+    #[test]
+    fn histogram_test_date_force_merge_segments() -> crate::Result<()> {
+        histogram_test_date_merge_segments(true)
+    }
+
+    #[test]
+    fn histogram_test_date() -> crate::Result<()> {
+        histogram_test_date_merge_segments(false)
+    }
+    fn histogram_test_date_merge_segments(merge_segments: bool) -> crate::Result<()> {
+        let docs = vec![
+            vec![r#"{ "date": "2015-01-01T12:10:30Z", "text": "aaa" }"#],
+            vec![r#"{ "date": "2015-01-01T11:11:30Z", "text": "bbb" }"#],
+            vec![r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb" }"#],
+            vec![r#"{ "date": "2015-01-06T00:00:00Z", "text": "ccc" }"#],
+        ];
+
+        let index = get_test_index_from_docs(merge_segments, &docs)?;
+        // 30day + offset
+        let elasticsearch_compatible_json = json!(
+            {
+              "sales_over_time": {
+                "date_histogram": {
+                  "field": "date",
+                  "fixed_interval": "30d",
+                  "offset": "-4d"
+                }
+              }
+            }
+        );
+
+        let agg_req: Aggregations =
+            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
+                .unwrap();
+        let res = exec_request(agg_req, &index)?;
+        let expected_res = json!({
+          "sales_over_time" : {
+          "buckets" : [
+            {
+              "key_as_string" : "2015-01-01T00:00:00Z",
+              "key" : 1420070400000000.0,
+              "doc_count" : 4
+            }
+          ]
+        }
+        });
+        assert_eq!(res, expected_res);
+
+        // 30day + offset + sub_agg
+        let elasticsearch_compatible_json = json!(
+            {
+              "sales_over_time": {
+                "date_histogram": {
+                  "field": "date",
+                  "fixed_interval": "30d",
+                  "offset": "-4d"
+                },
+                "aggs": {
+                    "texts": {
+                        "terms": {"field": "text"}
+                    }
+                }
+              }
+            }
+        );
+
+        let agg_req: Aggregations =
+            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
+                .unwrap();
+        let res = exec_request(agg_req, &index)?;
+        println!("{}", serde_json::to_string_pretty(&res).unwrap());
+        let expected_res = json!({
+          "sales_over_time" : {
+          "buckets" : [
+            {
+              "key_as_string" : "2015-01-01T00:00:00Z",
+              "key" : 1420070400000000.0,
+              "doc_count" : 4,
+              "texts": {
+                  "buckets": [
+                    {
+                      "doc_count": 2,
+                      "key": "bbb"
+                    },
+                    {
+                      "doc_count": 1,
+                      "key": "ccc"
+                    },
+                    {
+                      "doc_count": 1,
+                      "key": "aaa"
+                    }
+                  ],
+                  "doc_count_error_upper_bound": 0,
+                  "sum_other_doc_count": 0
+                }
+            }
+          ]
+        }
+        });
+        assert_eq!(res, expected_res);
+
+        // 1day
+        let elasticsearch_compatible_json = json!(
+            {
+              "sales_over_time": {
+                "date_histogram": {
+                  "field": "date",
+                  "fixed_interval": "1d"
+                }
+              }
+            }
+        );
+
+        let agg_req: Aggregations =
+            serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
+                .unwrap();
+        let res = exec_request(agg_req, &index)?;
+        let expected_res = json!( {
+          "sales_over_time": {
+            "buckets": [
+              {
+                "doc_count": 2,
+                "key": 1420070400000000.0,
+                "key_as_string": "2015-01-01T00:00:00Z"
+              },
+              {
+                "doc_count": 1,
+                "key": 1420156800000000.0,
+                "key_as_string": "2015-01-02T00:00:00Z"
+              },
+              {
+                "doc_count": 0,
+                "key": 1420243200000000.0,
+                "key_as_string": "2015-01-03T00:00:00Z"
+              },
+              {
+                "doc_count": 0,
+                "key": 1420329600000000.0,
+                "key_as_string": "2015-01-04T00:00:00Z"
+              },
+              {
+                "doc_count": 0,
+                "key": 1420416000000000.0,
+                "key_as_string": "2015-01-05T00:00:00Z"
+              },
+              {
+                "doc_count": 1,
+                "key": 1420502400000000.0,
+                "key_as_string": "2015-01-06T00:00:00Z"
+              }
+            ]
+          }
+        });
+        assert_eq!(res, expected_res);
+
+        Ok(())
+    }
+}

src/aggregation/bucket/histogram/histogram.rs

@@ -1,9 +1,11 @@
 use std::cmp::Ordering;
 use std::fmt::Display;
 
-use fastfield_codecs::Column;
+use columnar::ColumnType;
 use itertools::Itertools;
+use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
+use tantivy_bitpacker::minmax;
 
 use crate::aggregation::agg_req::AggregationsInternal;
 use crate::aggregation::agg_req_with_accessor::{
@@ -13,9 +15,10 @@ use crate::aggregation::agg_result::BucketEntry;
 use crate::aggregation::intermediate_agg_result::{
     IntermediateAggregationResults, IntermediateBucketResult, IntermediateHistogramBucketEntry,
 };
-use crate::aggregation::segment_agg_result::SegmentAggregationResultsCollector;
-use crate::aggregation::{f64_from_fastfield_u64, format_date};
-use crate::schema::{Schema, Type};
+use crate::aggregation::segment_agg_result::{
+    build_segment_agg_collector, SegmentAggregationCollector,
+};
+use crate::aggregation::{f64_from_fastfield_u64, format_date, VecWithNames};
 use crate::{DocId, TantivyError};
 
 /// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
@@ -62,7 +65,6 @@ use crate::{DocId, TantivyError};
 ///
 /// Response
 /// See [`BucketEntry`](crate::aggregation::agg_result::BucketEntry)
-
 #[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
 pub struct HistogramAggregation {
     /// The field to aggregate on.
@@ -175,7 +177,7 @@ impl HistogramBounds {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Default, Clone, Debug, PartialEq)]
 pub(crate) struct SegmentHistogramBucketEntry {
     pub key: f64,
     pub doc_count: u64,
@@ -184,7 +186,7 @@ pub(crate) struct SegmentHistogramBucketEntry {
 impl SegmentHistogramBucketEntry {
     pub(crate) fn into_intermediate_bucket_entry(
         self,
-        sub_aggregation: SegmentAggregationResultsCollector,
+        sub_aggregation: Box<dyn SegmentAggregationCollector>,
         agg_with_accessor: &AggregationsWithAccessor,
     ) -> crate::Result<IntermediateHistogramBucketEntry> {
         Ok(IntermediateHistogramBucketEntry {
@@ -198,17 +200,88 @@ impl SegmentHistogramBucketEntry {
 
 /// The collector puts values from the fast field into the correct buckets and does a conversion to
 /// the correct datatype.
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Clone, Debug)]
 pub struct SegmentHistogramCollector {
     /// The buckets containing the aggregation data.
-    buckets: Vec<SegmentHistogramBucketEntry>,
-    sub_aggregations: Option<Vec<SegmentAggregationResultsCollector>>,
-    field_type: Type,
+    buckets: FxHashMap<i64, SegmentHistogramBucketEntry>,
+    sub_aggregations: FxHashMap<i64, Box<dyn SegmentAggregationCollector>>,
+    sub_aggregation_blueprint: Option<Box<dyn SegmentAggregationCollector>>,
+    column_type: ColumnType,
     interval: f64,
     offset: f64,
-    min_doc_count: u64,
-    first_bucket_num: i64,
     bounds: HistogramBounds,
+    accessor_idx: usize,
+}
+
+impl SegmentAggregationCollector for SegmentHistogramCollector {
+    fn into_intermediate_aggregations_result(
+        self: Box<Self>,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<IntermediateAggregationResults> {
+        let name = agg_with_accessor.buckets.keys[self.accessor_idx].to_string();
+        let agg_with_accessor = &agg_with_accessor.buckets.values[self.accessor_idx];
+
+        let bucket = self.into_intermediate_bucket_result(agg_with_accessor)?;
+        let buckets = Some(VecWithNames::from_entries(vec![(name, bucket)]));
+
+        Ok(IntermediateAggregationResults {
+            metrics: None,
+            buckets,
+        })
+    }
+
+    fn collect(
+        &mut self,
+        doc: crate::DocId,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        self.collect_block(&[doc], agg_with_accessor)
+    }
+
+    fn collect_block(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        let accessor = &agg_with_accessor.buckets.values[self.accessor_idx].accessor;
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        let bounds = self.bounds;
+        let interval = self.interval;
+        let offset = self.offset;
+        let get_bucket_pos = |val| (get_bucket_pos_f64(val, interval, offset) as i64);
+
+        for doc in docs {
+            for val in accessor.values_for_doc(*doc) {
+                let val = self.f64_from_fastfield_u64(val);
+
+                let bucket_pos = get_bucket_pos(val);
+
+                if bounds.contains(val) {
+                    self.increment_bucket(
+                        bucket_pos,
+                        *doc,
+                        sub_aggregation_accessor,
+                        interval,
+                        offset,
+                    )?;
+                }
+            }
+        }
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        for sub_aggregation in self.sub_aggregations.values_mut() {
+            sub_aggregation.flush(sub_aggregation_accessor)?;
+        }
+
+        Ok(())
+    }
 }
 
 impl SegmentHistogramCollector {
@@ -216,254 +289,96 @@ impl SegmentHistogramCollector {
         self,
         agg_with_accessor: &BucketAggregationWithAccessor,
     ) -> crate::Result<IntermediateBucketResult> {
-        // Compute the number of buckets to validate against max num buckets
-        // Note: We use min_doc_count here, but it's only an lowerbound here, since were are on the
-        // intermediate level and after merging the number of documents of a bucket could exceed
-        // `min_doc_count`.
-        {
-            let cut_off_buckets_front = self
-                .buckets
-                .iter()
-                .take_while(|bucket| bucket.doc_count <= self.min_doc_count)
-                .count();
-            let cut_off_buckets_back = self.buckets[cut_off_buckets_front..]
-                .iter()
-                .rev()
-                .take_while(|bucket| bucket.doc_count <= self.min_doc_count)
-                .count();
-            let estimate_num_buckets =
-                self.buckets.len() - cut_off_buckets_front - cut_off_buckets_back;
+        let mut buckets = Vec::with_capacity(self.buckets.len());
 
-            agg_with_accessor
-                .bucket_count
-                .add_count(estimate_num_buckets as u32);
-            agg_with_accessor.bucket_count.validate_bucket_count()?;
-        }
+        if self.sub_aggregation_blueprint.is_some() {
+            for (bucket_pos, bucket) in self.buckets.into_iter() {
+                let bucket_res = bucket.into_intermediate_bucket_entry(
+                    self.sub_aggregations.get(&bucket_pos).unwrap().clone(),
+                    &agg_with_accessor.sub_aggregation,
+                );
 
-        let mut buckets = Vec::with_capacity(
-            self.buckets
-                .iter()
-                .filter(|bucket| bucket.doc_count != 0)
-                .count(),
-        );
-
-        // Below we remove empty buckets for two reasons
-        // 1. To reduce the size of the intermediate result, which may be passed on the wire.
-        // 2. To mimic elasticsearch, there are no empty buckets at the start and end.
-        //
-        // Empty buckets may be added later again in the final result, depending on the request.
-        if let Some(sub_aggregations) = self.sub_aggregations {
-            for bucket_res in self
-                .buckets
-                .into_iter()
-                .zip(sub_aggregations.into_iter())
-                .filter(|(bucket, _sub_aggregation)| bucket.doc_count != 0)
-                .map(|(bucket, sub_aggregation)| {
-                    bucket.into_intermediate_bucket_entry(
-                        sub_aggregation,
-                        &agg_with_accessor.sub_aggregation,
-                    )
-                })
-            {
                 buckets.push(bucket_res?);
             }
         } else {
-            buckets.extend(
-                self.buckets
-                    .into_iter()
-                    .filter(|bucket| bucket.doc_count != 0)
-                    .map(|bucket| bucket.into()),
-            );
+            buckets.extend(self.buckets.into_values().map(|bucket| bucket.into()));
         };
+        buckets.sort_unstable_by(|b1, b2| b1.key.partial_cmp(&b2.key).unwrap_or(Ordering::Equal));
 
-        Ok(IntermediateBucketResult::Histogram { buckets })
+        Ok(IntermediateBucketResult::Histogram {
+            buckets,
+            column_type: Some(self.column_type),
+        })
     }
 
     pub(crate) fn from_req_and_validate(
         req: &HistogramAggregation,
         sub_aggregation: &AggregationsWithAccessor,
-        field_type: Type,
-        accessor: &dyn Column<u64>,
+        field_type: ColumnType,
+        accessor_idx: usize,
     ) -> crate::Result<Self> {
         req.validate()?;
-        let min = f64_from_fastfield_u64(accessor.min_value(), &field_type);
-        let max = f64_from_fastfield_u64(accessor.max_value(), &field_type);
 
-        let (min, max) = get_req_min_max(req, Some((min, max)));
-
-        // We compute and generate the buckets range (min, max) based on the request and the min
-        // max in the fast field, but this is likely not ideal when this is a subbucket, where many
-        // unnecessary buckets may be generated.
-        let buckets = generate_buckets(req, min, max);
-
-        let sub_aggregations = if sub_aggregation.is_empty() {
+        let sub_aggregation_blueprint = if sub_aggregation.is_empty() {
             None
         } else {
-            let sub_aggregation =
-                SegmentAggregationResultsCollector::from_req_and_validate(sub_aggregation)?;
-            Some(buckets.iter().map(|_| sub_aggregation.clone()).collect())
+            let sub_aggregation = build_segment_agg_collector(sub_aggregation)?;
+            Some(sub_aggregation)
         };
 
-        let buckets = buckets
-            .iter()
-            .map(|bucket| SegmentHistogramBucketEntry {
-                key: *bucket,
-                doc_count: 0,
-            })
-            .collect();
-
-        let first_bucket_num =
-            get_bucket_num_f64(min, req.interval, req.offset.unwrap_or(0.0)) as i64;
-
         let bounds = req.hard_bounds.unwrap_or(HistogramBounds {
             min: f64::MIN,
             max: f64::MAX,
         });
 
         Ok(Self {
-            buckets,
-            field_type,
+            buckets: Default::default(),
+            column_type: field_type,
             interval: req.interval,
             offset: req.offset.unwrap_or(0.0),
-            first_bucket_num,
             bounds,
-            sub_aggregations,
-            min_doc_count: req.min_doc_count(),
+            sub_aggregations: Default::default(),
+            sub_aggregation_blueprint,
+            accessor_idx,
         })
     }
 
-    #[inline]
-    pub(crate) fn collect_block(
-        &mut self,
-        doc: &[DocId],
-        bucket_with_accessor: &BucketAggregationWithAccessor,
-        force_flush: bool,
-    ) -> crate::Result<()> {
-        let bounds = self.bounds;
-        let interval = self.interval;
-        let offset = self.offset;
-        let first_bucket_num = self.first_bucket_num;
-        let get_bucket_num =
-            |val| (get_bucket_num_f64(val, interval, offset) as i64 - first_bucket_num) as usize;
-
-        let accessor = bucket_with_accessor
-            .accessor
-            .as_single()
-            .expect("unexpected fast field cardinatility");
-        let mut iter = doc.chunks_exact(4);
-        for docs in iter.by_ref() {
-            let val0 = self.f64_from_fastfield_u64(accessor.get_val(docs[0]));
-            let val1 = self.f64_from_fastfield_u64(accessor.get_val(docs[1]));
-            let val2 = self.f64_from_fastfield_u64(accessor.get_val(docs[2]));
-            let val3 = self.f64_from_fastfield_u64(accessor.get_val(docs[3]));
-
-            let bucket_pos0 = get_bucket_num(val0);
-            let bucket_pos1 = get_bucket_num(val1);
-            let bucket_pos2 = get_bucket_num(val2);
-            let bucket_pos3 = get_bucket_num(val3);
-
-            self.increment_bucket_if_in_bounds(
-                val0,
-                &bounds,
-                bucket_pos0,
-                docs[0],
-                &bucket_with_accessor.sub_aggregation,
-            )?;
-            self.increment_bucket_if_in_bounds(
-                val1,
-                &bounds,
-                bucket_pos1,
-                docs[1],
-                &bucket_with_accessor.sub_aggregation,
-            )?;
-            self.increment_bucket_if_in_bounds(
-                val2,
-                &bounds,
-                bucket_pos2,
-                docs[2],
-                &bucket_with_accessor.sub_aggregation,
-            )?;
-            self.increment_bucket_if_in_bounds(
-                val3,
-                &bounds,
-                bucket_pos3,
-                docs[3],
-                &bucket_with_accessor.sub_aggregation,
-            )?;
-        }
-        for &doc in iter.remainder() {
-            let val = f64_from_fastfield_u64(accessor.get_val(doc), &self.field_type);
-            if !bounds.contains(val) {
-                continue;
-            }
-            let bucket_pos = (get_bucket_num_f64(val, self.interval, self.offset) as i64
-                - self.first_bucket_num) as usize;
-
-            debug_assert_eq!(
-                self.buckets[bucket_pos].key,
-                get_bucket_val(val, self.interval, self.offset)
-            );
-            self.increment_bucket(bucket_pos, doc, &bucket_with_accessor.sub_aggregation)?;
-        }
-        if force_flush {
-            if let Some(sub_aggregations) = self.sub_aggregations.as_mut() {
-                for sub_aggregation in sub_aggregations {
-                    sub_aggregation
-                        .flush_staged_docs(&bucket_with_accessor.sub_aggregation, force_flush)?;
-                }
-            }
-        }
-        Ok(())
-    }
-
-    #[inline]
-    fn increment_bucket_if_in_bounds(
-        &mut self,
-        val: f64,
-        bounds: &HistogramBounds,
-        bucket_pos: usize,
-        doc: DocId,
-        bucket_with_accessor: &AggregationsWithAccessor,
-    ) -> crate::Result<()> {
-        if bounds.contains(val) {
-            debug_assert_eq!(
-                self.buckets[bucket_pos].key,
-                get_bucket_val(val, self.interval, self.offset)
-            );
-
-            self.increment_bucket(bucket_pos, doc, bucket_with_accessor)?;
-        }
-        Ok(())
-    }
-
     #[inline]
     fn increment_bucket(
         &mut self,
-        bucket_pos: usize,
+        bucket_pos: i64,
         doc: DocId,
         bucket_with_accessor: &AggregationsWithAccessor,
+        interval: f64,
+        offset: f64,
     ) -> crate::Result<()> {
-        let bucket = &mut self.buckets[bucket_pos];
+        let bucket = self.buckets.entry(bucket_pos).or_insert_with(|| {
+            let key = get_bucket_key_from_pos(bucket_pos as f64, interval, offset);
+            SegmentHistogramBucketEntry { key, doc_count: 0 }
+        });
         bucket.doc_count += 1;
-        if let Some(sub_aggregation) = self.sub_aggregations.as_mut() {
-            sub_aggregation[bucket_pos].collect(doc, bucket_with_accessor)?;
+        if let Some(sub_aggregation_blueprint) = self.sub_aggregation_blueprint.as_mut() {
+            self.sub_aggregations
+                .entry(bucket_pos)
+                .or_insert_with(|| sub_aggregation_blueprint.clone())
+                .collect(doc, bucket_with_accessor)?;
         }
         Ok(())
     }
 
+    #[inline]
     fn f64_from_fastfield_u64(&self, val: u64) -> f64 {
-        f64_from_fastfield_u64(val, &self.field_type)
+        f64_from_fastfield_u64(val, &self.column_type)
     }
 }
 
 #[inline]
-fn get_bucket_num_f64(val: f64, interval: f64, offset: f64) -> f64 {
+fn get_bucket_pos_f64(val: f64, interval: f64, offset: f64) -> f64 {
     ((val - offset) / interval).floor()
 }
 
 #[inline]
-fn get_bucket_val(val: f64, interval: f64, offset: f64) -> f64 {
-    let bucket_pos = get_bucket_num_f64(val, interval, offset);
+fn get_bucket_key_from_pos(bucket_pos: f64, interval: f64, offset: f64) -> f64 {
     bucket_pos * interval + offset
 }
 
@@ -472,19 +387,14 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
     buckets: Vec<IntermediateHistogramBucketEntry>,
     histogram_req: &HistogramAggregation,
     sub_aggregation: &AggregationsInternal,
-    schema: &Schema,
 ) -> crate::Result<Vec<BucketEntry>> {
     // Generate the full list of buckets without gaps.
     //
     // The bounds are the min max from the current buckets, optionally extended by
     // extended_bounds from the request
-    let min_max = if buckets.is_empty() {
-        None
-    } else {
-        let min = buckets[0].key;
-        let max = buckets[buckets.len() - 1].key;
-        Some((min, max))
-    };
+    let min_max = minmax(buckets.iter().map(|bucket| bucket.key));
+
+    // TODO add memory check
     let fill_gaps_buckets = generate_buckets_with_opt_minmax(histogram_req, min_max);
 
     let empty_sub_aggregation = IntermediateAggregationResults::empty_from_req(sub_aggregation);
@@ -513,43 +423,33 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
                 sub_aggregation: empty_sub_aggregation.clone(),
             },
         })
-        .map(|intermediate_bucket| {
-            intermediate_bucket.into_final_bucket_entry(sub_aggregation, schema)
-        })
+        .map(|intermediate_bucket| intermediate_bucket.into_final_bucket_entry(sub_aggregation))
         .collect::<crate::Result<Vec<_>>>()
 }
 
 // Convert to BucketEntry
 pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
     buckets: Vec<IntermediateHistogramBucketEntry>,
+    column_type: Option<ColumnType>,
     histogram_req: &HistogramAggregation,
     sub_aggregation: &AggregationsInternal,
-    schema: &Schema,
 ) -> crate::Result<Vec<BucketEntry>> {
     let mut buckets = if histogram_req.min_doc_count() == 0 {
         // With min_doc_count != 0, we may need to add buckets, so that there are no
         // gaps, since intermediate result does not contain empty buckets (filtered to
         // reduce serialization size).
 
-        intermediate_buckets_to_final_buckets_fill_gaps(
-            buckets,
-            histogram_req,
-            sub_aggregation,
-            schema,
-        )?
+        intermediate_buckets_to_final_buckets_fill_gaps(buckets, histogram_req, sub_aggregation)?
     } else {
         buckets
             .into_iter()
             .filter(|histogram_bucket| histogram_bucket.doc_count >= histogram_req.min_doc_count())
-            .map(|histogram_bucket| {
-                histogram_bucket.into_final_bucket_entry(sub_aggregation, schema)
-            })
+            .map(|histogram_bucket| histogram_bucket.into_final_bucket_entry(sub_aggregation))
             .collect::<crate::Result<Vec<_>>>()?
     };
 
     // If we have a date type on the histogram buckets, we add the `key_as_string` field as rfc339
-    let field = schema.get_field(&histogram_req.field)?;
-    if schema.get_field_entry(field).field_type().is_date() {
+    if column_type == Some(ColumnType::DateTime) {
         for bucket in buckets.iter_mut() {
             if let crate::aggregation::Key::F64(val) = bucket.key {
                 let key_as_string = format_date(val as i64)?;
@@ -580,12 +480,6 @@ fn get_req_min_max(req: &HistogramAggregation, min_max: Option<(f64, f64)>) -> (
     (min, max)
 }
 
-/// Generates buckets with req.interval
-/// range is computed for provided min_max and request extended_bounds/hard_bounds
-pub(crate) fn generate_buckets(req: &HistogramAggregation, min: f64, max: f64) -> Vec<f64> {
-    generate_buckets_with_opt_minmax(req, Some((min, max)))
-}
-
 /// Generates buckets with req.interval
 /// Range is computed for provided min_max and request extended_bounds/hard_bounds
 /// returns empty vec when there is no range to span
@@ -596,8 +490,8 @@ pub(crate) fn generate_buckets_with_opt_minmax(
     let (min, max) = get_req_min_max(req, min_max);
 
     let offset = req.offset.unwrap_or(0.0);
-    let first_bucket_num = get_bucket_num_f64(min, req.interval, offset) as i64;
-    let last_bucket_num = get_bucket_num_f64(max, req.interval, offset) as i64;
+    let first_bucket_num = get_bucket_pos_f64(min, req.interval, offset) as i64;
+    let last_bucket_num = get_bucket_pos_f64(max, req.interval, offset) as i64;
     let mut buckets = Vec::with_capacity((first_bucket_num..=last_bucket_num).count());
     for bucket_pos in first_bucket_num..=last_bucket_num {
         let bucket_key = bucket_pos as f64 * req.interval + offset;
@@ -607,118 +501,6 @@ pub(crate) fn generate_buckets_with_opt_minmax(
     buckets
 }
 
-#[test]
-fn generate_buckets_test() {
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![2.0, 4.0]);
-
-    // Single bucket
-    let buckets = generate_buckets(&histogram_req, 0.5, 0.75);
-    assert_eq!(buckets, vec![0.0]);
-
-    // With offset
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        offset: Some(0.5),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![-1.5, 0.5, 2.5, 4.5, 6.5, 8.5]);
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![2.5, 4.5]);
-
-    // Single bucket
-    let buckets = generate_buckets(&histogram_req, 0.5, 0.75);
-    assert_eq!(buckets, vec![0.5]);
-
-    // no bucket
-    let buckets = generate_buckets(&histogram_req, f64::MAX, f64::MIN);
-    assert_eq!(buckets, vec![] as Vec<f64>);
-
-    // With extended_bounds
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        extended_bounds: Some(HistogramBounds {
-            min: 0.0,
-            max: 10.0,
-        }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // Single bucket, but extended_bounds
-    let buckets = generate_buckets(&histogram_req, 0.5, 0.75);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // no bucket, but extended_bounds
-    let buckets = generate_buckets(&histogram_req, f64::MAX, f64::MIN);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // With invalid extended_bounds
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        extended_bounds: Some(HistogramBounds { min: 3.0, max: 5.0 }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![0.0, 2.0, 4.0, 6.0, 8.0, 10.0]);
-
-    // With hard_bounds reducing
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        hard_bounds: Some(HistogramBounds { min: 3.0, max: 5.0 }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 0.0, 10.0);
-    assert_eq!(buckets, vec![2.0, 4.0]);
-
-    // With hard_bounds, extending has no effect
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        hard_bounds: Some(HistogramBounds {
-            min: 0.0,
-            max: 10.0,
-        }),
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 2.5, 5.5);
-    assert_eq!(buckets, vec![2.0, 4.0]);
-
-    // Blubber
-    let histogram_req = HistogramAggregation {
-        field: "dummy".to_string(),
-        interval: 2.0,
-        ..Default::default()
-    };
-
-    let buckets = generate_buckets(&histogram_req, 4.0, 10.0);
-    assert_eq!(buckets, vec![4.0, 6.0, 8.0, 10.0]);
-}
-
 #[cfg(test)]
 mod tests {
 
@@ -1539,36 +1321,4 @@ mod tests {
 
         Ok(())
     }
-
-    #[test]
-    fn histogram_test_max_buckets_segments() -> crate::Result<()> {
-        let values = vec![0.0, 70000.0];
-
-        let index = get_test_index_from_values(true, &values)?;
-
-        let agg_req: Aggregations = vec![(
-            "my_interval".to_string(),
-            Aggregation::Bucket(BucketAggregation {
-                bucket_agg: BucketAggregationType::Histogram(HistogramAggregation {
-                    field: "score_f64".to_string(),
-                    interval: 1.0,
-                    ..Default::default()
-                }),
-                sub_aggregation: Default::default(),
-            }),
-        )]
-        .into_iter()
-        .collect();
-
-        let res = exec_request(agg_req, &index);
-
-        assert_eq!(
-            res.unwrap_err().to_string(),
-            "An invalid argument was passed: 'Aborting aggregation because too many buckets were \
-             created'"
-                .to_string()
-        );
-
-        Ok(())
-    }
 }

src/aggregation/bucket/histogram/mod.rs

@@ -1,2 +1,4 @@
+mod date_histogram;
 mod histogram;
+pub use date_histogram::*;
 pub use histogram::*;

src/aggregation/bucket/mod.rs

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

src/aggregation/bucket/range.rs

@@ -1,22 +1,22 @@
 use std::fmt::Debug;
 use std::ops::Range;
 
-use fastfield_codecs::MonotonicallyMappableToU64;
+use columnar::{ColumnType, MonotonicallyMappableToU64};
 use rustc_hash::FxHashMap;
 use serde::{Deserialize, Serialize};
 
-use crate::aggregation::agg_req_with_accessor::{
-    AggregationsWithAccessor, BucketAggregationWithAccessor,
-};
+use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
 use crate::aggregation::intermediate_agg_result::{
-    IntermediateBucketResult, IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
+    IntermediateAggregationResults, IntermediateBucketResult, IntermediateRangeBucketEntry,
+    IntermediateRangeBucketResult,
+};
+use crate::aggregation::segment_agg_result::{
+    build_segment_agg_collector, BucketCount, SegmentAggregationCollector,
 };
-use crate::aggregation::segment_agg_result::{BucketCount, SegmentAggregationResultsCollector};
 use crate::aggregation::{
-    f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
+    f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey, VecWithNames,
 };
-use crate::schema::Type;
-use crate::{DocId, TantivyError};
+use crate::TantivyError;
 
 /// Provide user-defined buckets to aggregate on.
 /// Two special buckets will automatically be created to cover the whole range of values.
@@ -114,7 +114,7 @@ impl From<Range<u64>> for InternalRangeAggregationRange {
     }
 }
 
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Clone, Debug)]
 pub(crate) struct SegmentRangeAndBucketEntry {
     range: Range<u64>,
     bucket: SegmentRangeBucketEntry,
@@ -122,18 +122,19 @@ pub(crate) struct SegmentRangeAndBucketEntry {
 
 /// The collector puts values from the fast field into the correct buckets and does a conversion to
 /// the correct datatype.
-#[derive(Clone, Debug, PartialEq)]
+#[derive(Clone, Debug)]
 pub struct SegmentRangeCollector {
     /// The buckets containing the aggregation data.
     buckets: Vec<SegmentRangeAndBucketEntry>,
-    field_type: Type,
+    column_type: ColumnType,
+    pub(crate) accessor_idx: usize,
 }
 
-#[derive(Clone, PartialEq)]
+#[derive(Clone)]
 pub(crate) struct SegmentRangeBucketEntry {
     pub key: Key,
     pub doc_count: u64,
-    pub sub_aggregation: Option<SegmentAggregationResultsCollector>,
+    pub sub_aggregation: Option<Box<dyn SegmentAggregationCollector>>,
     /// The from range of the bucket. Equals `f64::MIN` when `None`.
     pub from: Option<f64>,
     /// The to range of the bucket. Equals `f64::MAX` when `None`. Open interval, `to` is not
@@ -172,12 +173,14 @@ impl SegmentRangeBucketEntry {
     }
 }
 
-impl SegmentRangeCollector {
-    pub fn into_intermediate_bucket_result(
-        self,
-        agg_with_accessor: &BucketAggregationWithAccessor,
-    ) -> crate::Result<IntermediateBucketResult> {
-        let field_type = self.field_type;
+impl SegmentAggregationCollector for SegmentRangeCollector {
+    fn into_intermediate_aggregations_result(
+        self: Box<Self>,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<IntermediateAggregationResults> {
+        let field_type = self.column_type;
+        let name = agg_with_accessor.buckets.keys[self.accessor_idx].to_string();
+        let sub_agg = &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
 
         let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
             .buckets
@@ -187,21 +190,77 @@ impl SegmentRangeCollector {
                     range_to_string(&range_bucket.range, &field_type)?,
                     range_bucket
                         .bucket
-                        .into_intermediate_bucket_entry(&agg_with_accessor.sub_aggregation)?,
+                        .into_intermediate_bucket_entry(sub_agg)?,
                 ))
             })
             .collect::<crate::Result<_>>()?;
 
-        Ok(IntermediateBucketResult::Range(
-            IntermediateRangeBucketResult { buckets },
-        ))
+        let bucket = IntermediateBucketResult::Range(IntermediateRangeBucketResult {
+            buckets,
+            column_type: Some(self.column_type),
+        });
+
+        let buckets = Some(VecWithNames::from_entries(vec![(name, bucket)]));
+
+        Ok(IntermediateAggregationResults {
+            metrics: None,
+            buckets,
+        })
     }
 
+    fn collect(
+        &mut self,
+        doc: crate::DocId,
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        self.collect_block(&[doc], agg_with_accessor)
+    }
+
+    fn collect_block(
+        &mut self,
+        docs: &[crate::DocId],
+        agg_with_accessor: &AggregationsWithAccessor,
+    ) -> crate::Result<()> {
+        let accessor = &agg_with_accessor.buckets.values[self.accessor_idx].accessor;
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+        for doc in docs {
+            for val in accessor.values_for_doc(*doc) {
+                let bucket_pos = self.get_bucket_pos(val);
+
+                let bucket = &mut self.buckets[bucket_pos];
+
+                bucket.bucket.doc_count += 1;
+                if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
+                    sub_aggregation.collect(*doc, sub_aggregation_accessor)?;
+                }
+            }
+        }
+
+        Ok(())
+    }
+
+    fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
+        let sub_aggregation_accessor =
+            &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
+
+        for bucket in self.buckets.iter_mut() {
+            if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
+                sub_agg.flush(sub_aggregation_accessor)?;
+            }
+        }
+
+        Ok(())
+    }
+}
+
+impl SegmentRangeCollector {
     pub(crate) fn from_req_and_validate(
         req: &RangeAggregation,
         sub_aggregation: &AggregationsWithAccessor,
         bucket_count: &BucketCount,
-        field_type: Type,
+        field_type: ColumnType,
+        accessor_idx: usize,
     ) -> crate::Result<Self> {
         // The range input on the request is f64.
         // We need to convert to u64 ranges, because we read the values as u64.
@@ -227,9 +286,7 @@ impl SegmentRangeCollector {
                 let sub_aggregation = if sub_aggregation.is_empty() {
                     None
                 } else {
-                    Some(SegmentAggregationResultsCollector::from_req_and_validate(
-                        sub_aggregation,
-                    )?)
+                    Some(build_segment_agg_collector(sub_aggregation)?)
                 };
 
                 Ok(SegmentRangeAndBucketEntry {
@@ -250,69 +307,11 @@ impl SegmentRangeCollector {
 
         Ok(SegmentRangeCollector {
             buckets,
-            field_type,
+            column_type: field_type,
+            accessor_idx,
         })
     }
 
-    #[inline]
-    pub(crate) fn collect_block(
-        &mut self,
-        doc: &[DocId],
-        bucket_with_accessor: &BucketAggregationWithAccessor,
-        force_flush: bool,
-    ) -> crate::Result<()> {
-        let mut iter = doc.chunks_exact(4);
-        let accessor = bucket_with_accessor
-            .accessor
-            .as_single()
-            .expect("unexpected fast field cardinality");
-        for docs in iter.by_ref() {
-            let val1 = accessor.get_val(docs[0]);
-            let val2 = accessor.get_val(docs[1]);
-            let val3 = accessor.get_val(docs[2]);
-            let val4 = accessor.get_val(docs[3]);
-            let bucket_pos1 = self.get_bucket_pos(val1);
-            let bucket_pos2 = self.get_bucket_pos(val2);
-            let bucket_pos3 = self.get_bucket_pos(val3);
-            let bucket_pos4 = self.get_bucket_pos(val4);
-
-            self.increment_bucket(bucket_pos1, docs[0], &bucket_with_accessor.sub_aggregation)?;
-            self.increment_bucket(bucket_pos2, docs[1], &bucket_with_accessor.sub_aggregation)?;
-            self.increment_bucket(bucket_pos3, docs[2], &bucket_with_accessor.sub_aggregation)?;
-            self.increment_bucket(bucket_pos4, docs[3], &bucket_with_accessor.sub_aggregation)?;
-        }
-        for &doc in iter.remainder() {
-            let val = accessor.get_val(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
@@ -338,7 +337,7 @@ impl SegmentRangeCollector {
 /// more computational expensive when many documents are hit.
 fn to_u64_range(
     range: &RangeAggregationRange,
-    field_type: &Type,
+    field_type: &ColumnType,
 ) -> crate::Result<InternalRangeAggregationRange> {
     let start = if let Some(from) = range.from {
         f64_to_fastfield_u64(from, field_type)
@@ -364,7 +363,7 @@ fn to_u64_range(
 /// beginning and end and filling gaps.
 fn extend_validate_ranges(
     buckets: &[RangeAggregationRange],
-    field_type: &Type,
+    field_type: &ColumnType,
 ) -> crate::Result<Vec<InternalRangeAggregationRange>> {
     let mut converted_buckets = buckets
         .iter()
@@ -406,13 +405,16 @@ fn extend_validate_ranges(
     Ok(converted_buckets)
 }
 
-pub(crate) fn range_to_string(range: &Range<u64>, field_type: &Type) -> crate::Result<String> {
+pub(crate) fn range_to_string(
+    range: &Range<u64>,
+    field_type: &ColumnType,
+) -> crate::Result<String> {
     // is_start is there for malformed requests, e.g. ig the user passes the range u64::MIN..0.0,
     // it should be rendered as "*-0" and not "*-*"
     let to_str = |val: u64, is_start: bool| {
         if (is_start && val == u64::MIN) || (!is_start && val == u64::MAX) {
             Ok("*".to_string())
-        } else if *field_type == Type::Date {
+        } else if *field_type == ColumnType::DateTime {
             let val = i64::from_u64(val);
             format_date(val)
         } else {
@@ -427,20 +429,21 @@ pub(crate) fn range_to_string(range: &Range<u64>, field_type: &Type) -> crate::R
     ))
 }
 
-pub(crate) fn range_to_key(range: &Range<u64>, field_type: &Type) -> crate::Result<Key> {
+pub(crate) fn range_to_key(range: &Range<u64>, field_type: &ColumnType) -> crate::Result<Key> {
     Ok(Key::Str(range_to_string(range, field_type)?))
 }
 
 #[cfg(test)]
 mod tests {
 
-    use fastfield_codecs::MonotonicallyMappableToU64;
+    use columnar::MonotonicallyMappableToU64;
     use serde_json::Value;
 
     use super::*;
     use crate::aggregation::agg_req::{
-        Aggregation, Aggregations, BucketAggregation, BucketAggregationType,
+        Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
     };
+    use crate::aggregation::metric::AverageAggregation;
     use crate::aggregation::tests::{
         exec_request, exec_request_with_query, get_test_index_2_segments,
         get_test_index_with_num_docs,
@@ -448,7 +451,7 @@ mod tests {
 
     pub fn get_collector_from_ranges(
         ranges: Vec<RangeAggregationRange>,
-        field_type: Type,
+        field_type: ColumnType,
     ) -> SegmentRangeCollector {
         let req = RangeAggregation {
             field: "dummy".to_string(),
@@ -461,6 +464,7 @@ mod tests {
             &Default::default(),
             &Default::default(),
             field_type,
+            0,
         )
         .expect("unexpected error")
     }
@@ -497,6 +501,47 @@ mod tests {
         Ok(())
     }
 
+    #[test]
+    fn range_fraction_test_with_sub_agg() -> crate::Result<()> {
+        let index = get_test_index_with_num_docs(false, 100)?;
+
+        let sub_agg_req: Aggregations = vec![(
+            "score_f64".to_string(),
+            Aggregation::Metric(MetricAggregation::Average(
+                AverageAggregation::from_field_name("score_f64".to_string()),
+            )),
+        )]
+        .into_iter()
+        .collect();
+
+        let agg_req: Aggregations = vec![(
+            "range".to_string(),
+            Aggregation::Bucket(BucketAggregation {
+                bucket_agg: BucketAggregationType::Range(RangeAggregation {
+                    field: "fraction_f64".to_string(),
+                    ranges: vec![(0f64..0.1f64).into(), (0.1f64..0.2f64).into()],
+                    ..Default::default()
+                }),
+                sub_aggregation: sub_agg_req,
+            }),
+        )]
+        .into_iter()
+        .collect();
+
+        let res = exec_request_with_query(agg_req, &index, None)?;
+
+        assert_eq!(res["range"]["buckets"][0]["key"], "*-0");
+        assert_eq!(res["range"]["buckets"][0]["doc_count"], 0);
+        assert_eq!(res["range"]["buckets"][1]["key"], "0-0.1");
+        assert_eq!(res["range"]["buckets"][1]["doc_count"], 10);
+        assert_eq!(res["range"]["buckets"][2]["key"], "0.1-0.2");
+        assert_eq!(res["range"]["buckets"][2]["doc_count"], 10);
+        assert_eq!(res["range"]["buckets"][3]["key"], "0.2-*");
+        assert_eq!(res["range"]["buckets"][3]["doc_count"], 80);
+
+        Ok(())
+    }
+
     #[test]
     fn range_keyed_buckets_test() -> crate::Result<()> {
         let index = get_test_index_with_num_docs(false, 100)?;
@@ -696,7 +741,7 @@ mod tests {
     #[test]
     fn bucket_test_extend_range_hole() {
         let buckets = vec![(10f64..20f64).into(), (30f64..40f64).into()];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(buckets[0].range.start, u64::MIN);
@@ -719,7 +764,7 @@ mod tests {
             (10f64..20f64).into(),
             (20f64..f64::MAX).into(),
         ];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(buckets[0].range.start, u64::MIN);
@@ -734,7 +779,7 @@ mod tests {
     #[test]
     fn bucket_range_test_negative_vals() {
         let buckets = vec![(-10f64..-1f64).into()];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(&buckets[0].bucket.key.to_string(), "*--10");
@@ -743,7 +788,7 @@ mod tests {
     #[test]
     fn bucket_range_test_positive_vals() {
         let buckets = vec![(0f64..10f64).into()];
-        let collector = get_collector_from_ranges(buckets, Type::F64);
+        let collector = get_collector_from_ranges(buckets, ColumnType::F64);
 
         let buckets = collector.buckets;
         assert_eq!(&buckets[0].bucket.key.to_string(), "*-0");
@@ -753,7 +798,7 @@ mod tests {
     #[test]
     fn range_binary_search_test_u64() {
         let check_ranges = |ranges: Vec<RangeAggregationRange>| {
-            let collector = get_collector_from_ranges(ranges, Type::U64);
+            let collector = get_collector_from_ranges(ranges, ColumnType::U64);
             let search = |val: u64| collector.get_bucket_pos(val);
 
             assert_eq!(search(u64::MIN), 0);
@@ -799,7 +844,7 @@ mod tests {
     fn range_binary_search_test_f64() {
         let ranges = vec![(10.0..100.0).into()];
 
-        let collector = get_collector_from_ranges(ranges, Type::F64);
+        let collector = get_collector_from_ranges(ranges, ColumnType::F64);
         let search = |val: u64| collector.get_bucket_pos(val);
 
         assert_eq!(search(u64::MIN), 0);
@@ -834,7 +879,7 @@ mod bench {
             buckets.push((bucket_start..bucket_start + bucket_size as f64).into())
         }
 
-        get_collector_from_ranges(buckets, Type::U64)
+        get_collector_from_ranges(buckets, ColumnType::U64)
     }
 
     fn get_rand_docs(total_docs: u64, num_docs_returned: u64) -> Vec<u64> {