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Author SHA1 Message Date
Paul Masurel
dc0aa3d734 Clippy and cleanups 2025-08-01 11:54:29 +09:00
44 changed files with 831 additions and 1138 deletions

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@@ -2,17 +2,13 @@ Tantivy 0.25
================================
## Bugfixes
- fix union performance regression in tantivy 0.24 [#2663](https://github.com/quickwit-oss/tantivy/pull/2663)(@PSeitz)
- fix union performance regression in tantivy 0.24 [#2663](https://github.com/quickwit-oss/tantivy/pull/2663)(@PSeitz-dd)
- make zstd optional in sstable [#2633](https://github.com/quickwit-oss/tantivy/pull/2633)(@Parth)
- Fix TopDocs::order_by_string_fast_field for asc order [#2672](https://github.com/quickwit-oss/tantivy/pull/2672)(@stuhood @PSeitz)
## Features/Improvements
- add docs/example and Vec<u32> values to sstable [#2660](https://github.com/quickwit-oss/tantivy/pull/2660)(@PSeitz)
- Add string fast field support to `TopDocs`. [#2642](https://github.com/quickwit-oss/tantivy/pull/2642)(@stuhood)
- update edition to 2024 [#2620](https://github.com/quickwit-oss/tantivy/pull/2620)(@PSeitz)
- Allow optional spaces between the field name and the value in the query parser [#2678](https://github.com/quickwit-oss/tantivy/pull/2678)(@Darkheir)
- Support mixed field types in query parser [#2676](https://github.com/quickwit-oss/tantivy/pull/2676)(@trinity-1686a)
- Add per-field size details [#2679](https://github.com/quickwit-oss/tantivy/pull/2679)(@fulmicoton)
Tantivy 0.24
================================

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@@ -1,6 +1,6 @@
[package]
name = "tantivy"
version = "0.25.0"
version = "0.24.0"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -57,13 +57,13 @@ measure_time = "0.9.0"
arc-swap = "1.5.0"
bon = "3.3.1"
columnar = { version = "0.6", path = "./columnar", package = "tantivy-columnar" }
sstable = { version = "0.6", path = "./sstable", package = "tantivy-sstable", optional = true }
stacker = { version = "0.6", path = "./stacker", package = "tantivy-stacker" }
query-grammar = { version = "0.25.0", path = "./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version = "0.9", path = "./bitpacker" }
common = { version = "0.10", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version = "0.6", path = "./tokenizer-api", package = "tantivy-tokenizer-api" }
columnar = { version = "0.5", path = "./columnar", package = "tantivy-columnar" }
sstable = { version = "0.5", path = "./sstable", package = "tantivy-sstable", optional = true }
stacker = { version = "0.5", path = "./stacker", package = "tantivy-stacker" }
query-grammar = { version = "0.24.0", path = "./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version = "0.8", path = "./bitpacker" }
common = { version = "0.9", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version = "0.5", path = "./tokenizer-api", package = "tantivy-tokenizer-api" }
sketches-ddsketch = { version = "0.3.0", features = ["use_serde"] }
hyperloglogplus = { version = "0.4.1", features = ["const-loop"] }
futures-util = { version = "0.3.28", optional = true }

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@@ -1,6 +1,6 @@
[package]
name = "tantivy-bitpacker"
version = "0.9.0"
version = "0.8.0"
edition = "2024"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"

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@@ -1,3 +1,7 @@
// manual divceil actually generates code that is not optimal (to accept the full range of u32) and
// perf matters here.
#![allow(clippy::manual_div_ceil)]
use std::io;
use std::ops::{Range, RangeInclusive};

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@@ -140,10 +140,9 @@ impl BlockedBitpacker {
pub fn iter(&self) -> impl Iterator<Item = u64> + '_ {
// todo performance: we could decompress a whole block and cache it instead
let bitpacked_elems = self.offset_and_bits.len() * BLOCK_SIZE;
let iter = (0..bitpacked_elems)
(0..bitpacked_elems)
.map(move |idx| self.get(idx))
.chain(self.buffer.iter().cloned());
iter
.chain(self.buffer.iter().cloned())
}
}

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@@ -1,3 +1,5 @@
// #[allow(clippy::manual_div_ceil)]
mod bitpacker;
mod blocked_bitpacker;
mod filter_vec;

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@@ -1,6 +1,6 @@
[package]
name = "tantivy-columnar"
version = "0.6.0"
version = "0.5.0"
edition = "2024"
license = "MIT"
homepage = "https://github.com/quickwit-oss/tantivy"
@@ -12,10 +12,10 @@ categories = ["database-implementations", "data-structures", "compression"]
itertools = "0.14.0"
fastdivide = "0.4.0"
stacker = { version= "0.6", path = "../stacker", package="tantivy-stacker"}
sstable = { version= "0.6", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.10", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.9", path = "../bitpacker/" }
stacker = { version= "0.5", path = "../stacker", package="tantivy-stacker"}
sstable = { version= "0.5", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.9", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.8", path = "../bitpacker/" }
serde = "1.0.152"
downcast-rs = "2.0.1"
@@ -33,29 +33,6 @@ harness = false
name = "bench_access"
harness = false
[[bench]]
name = "bench_first_vals"
harness = false
[[bench]]
name = "bench_values_u64"
harness = false
[[bench]]
name = "bench_values_u128"
harness = false
[[bench]]
name = "bench_create_column_values"
harness = false
[[bench]]
name = "bench_column_values_get"
harness = false
[[bench]]
name = "bench_optional_index"
harness = false
[features]
unstable = []
zstd-compression = ["sstable/zstd-compression"]

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@@ -19,7 +19,7 @@ fn main() {
let mut add_card = |card1: Card| {
inputs.push((
card1.to_string(),
format!("{card1}"),
generate_columnar_and_open(card1, NUM_DOCS),
));
};
@@ -50,7 +50,6 @@ fn bench_group(mut runner: InputGroup<Column>) {
let mut buffer = vec![None; BLOCK_SIZE];
for i in (0..NUM_DOCS).step_by(BLOCK_SIZE) {
// fill docs
#[allow(clippy::needless_range_loop)]
for idx in 0..BLOCK_SIZE {
docs[idx] = idx as u32 + i;
}

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@@ -1,61 +0,0 @@
use std::sync::Arc;
use binggan::{InputGroup, black_box};
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use tantivy_columnar::ColumnValues;
use tantivy_columnar::column_values::{CodecType, serialize_and_load_u64_based_column_values};
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55_000_u64)
.map(|num| num + rng.r#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
}
type Col = Arc<dyn ColumnValues<u64>>;
fn main() {
let data = get_data();
let inputs: Vec<(String, Col)> = vec![
(
"bitpacked".to_string(),
serialize_and_load_u64_based_column_values(&data.as_slice(), &[CodecType::Bitpacked]),
),
(
"linear".to_string(),
serialize_and_load_u64_based_column_values(&data.as_slice(), &[CodecType::Linear]),
),
(
"blockwise_linear".to_string(),
serialize_and_load_u64_based_column_values(
&data.as_slice(),
&[CodecType::BlockwiseLinear],
),
),
];
let mut group: InputGroup<Col> = InputGroup::new_with_inputs(inputs);
group.register("fastfield_get", |col: &Col| {
let mut sum = 0u64;
for pos in value_iter() {
sum = sum.wrapping_add(col.get_val(pos as u32));
}
black_box(sum);
});
group.run();
}

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@@ -1,44 +0,0 @@
use binggan::{InputGroup, black_box};
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use tantivy_columnar::column_values::{CodecType, serialize_u64_based_column_values};
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55_000_u64)
.map(|num| num + rng.r#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 main() {
let data = get_data();
let mut group: InputGroup<(CodecType, Vec<u64>)> = InputGroup::new_with_inputs(vec![
(
"bitpacked codec".to_string(),
(CodecType::Bitpacked, data.clone()),
),
(
"linear codec".to_string(),
(CodecType::Linear, data.clone()),
),
(
"blockwise linear codec".to_string(),
(CodecType::BlockwiseLinear, data.clone()),
),
]);
group.register("serialize column_values", |data| {
let mut buffer = Vec::new();
serialize_u64_based_column_values(&data.1.as_slice(), &[data.0], &mut buffer).unwrap();
black_box(buffer.len());
});
group.run();
}

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@@ -1,9 +1,12 @@
#![feature(test)]
extern crate test;
use std::sync::Arc;
use binggan::{InputGroup, black_box};
use rand::prelude::*;
use tantivy_columnar::column_values::{CodecType, serialize_and_load_u64_based_column_values};
use tantivy_columnar::*;
use test::{Bencher, black_box};
struct Columns {
pub optional: Column,
@@ -65,45 +68,88 @@ pub fn serialize_and_load(column: &[u64], codec_type: CodecType) -> Arc<dyn Colu
serialize_and_load_u64_based_column_values(&column, &[codec_type])
}
fn main() {
let Columns {
optional,
full,
multi,
} = get_test_columns();
let inputs = vec![
("full".to_string(), full),
("optional".to_string(), optional),
("multi".to_string(), multi),
];
let mut group = InputGroup::new_with_inputs(inputs);
group.register("first_full_scan", |column| {
fn run_bench_on_column_full_scan(b: &mut Bencher, column: Column) {
let num_iter = black_box(NUM_VALUES);
b.iter(|| {
let mut sum = 0u64;
for i in 0..NUM_VALUES as u32 {
for i in 0..num_iter as u32 {
let val = column.first(i);
sum += val.unwrap_or(0);
}
black_box(sum);
sum
});
group.register("first_block_fetch", |column| {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
}
fn run_bench_on_column_block_fetch(b: &mut Bencher, column: Column) {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
b.iter(move || {
column.first_vals(&fetch_docids, &mut block);
black_box(block[0]);
block[0]
});
group.register("first_block_single_calls", |column| {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
}
fn run_bench_on_column_block_single_calls(b: &mut Bencher, column: Column) {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
b.iter(move || {
for i in 0..fetch_docids.len() {
block[i] = column.first(fetch_docids[i]);
}
black_box(block[0]);
block[0]
});
group.run();
}
/// Column first method
#[bench]
fn bench_get_first_on_full_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_full_scan(b, column);
}
#[bench]
fn bench_get_first_on_optional_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_full_scan(b, column);
}
#[bench]
fn bench_get_first_on_multi_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_full_scan(b, column);
}
/// Block fetch column accessor
#[bench]
fn bench_get_block_first_on_optional_column(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_multi_column(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_full_column(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_optional_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_block_single_calls(b, column);
}
#[bench]
fn bench_get_block_first_on_multi_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_block_single_calls(b, column);
}
#[bench]
fn bench_get_block_first_on_full_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_block_single_calls(b, column);
}

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@@ -1,106 +0,0 @@
use binggan::{InputGroup, black_box};
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use tantivy_columnar::column_index::{OptionalIndex, Set};
const TOTAL_NUM_VALUES: u32 = 1_000_000;
fn gen_optional_index(fill_ratio: f64) -> OptionalIndex {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let vals: Vec<u32> = (0..TOTAL_NUM_VALUES)
.map(|_| rng.gen_bool(fill_ratio))
.enumerate()
.filter(|(_pos, val)| *val)
.map(|(pos, _)| pos as u32)
.collect();
OptionalIndex::for_test(TOTAL_NUM_VALUES, &vals)
}
fn random_range_iterator(
start: u32,
end: u32,
avg_step_size: u32,
avg_deviation: u32,
) -> impl Iterator<Item = u32> {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
if current >= end { None } else { Some(current) }
})
}
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
let ratio = percent / 100.0;
let step_size = (1f32 / ratio) as u32;
let deviation = step_size - 1;
random_range_iterator(0, num_values, step_size, deviation)
}
fn walk_over_data(codec: &OptionalIndex, avg_step_size: u32) -> Option<u32> {
walk_over_data_from_positions(
codec,
random_range_iterator(0, TOTAL_NUM_VALUES, avg_step_size, 0),
)
}
fn walk_over_data_from_positions(
codec: &OptionalIndex,
positions: impl Iterator<Item = u32>,
) -> Option<u32> {
let mut dense_idx: Option<u32> = None;
for idx in positions {
dense_idx = dense_idx.or(codec.rank_if_exists(idx));
}
dense_idx
}
fn main() {
// Build separate inputs for each fill ratio.
let inputs: Vec<(String, OptionalIndex)> = vec![
("fill=1%".to_string(), gen_optional_index(0.01)),
("fill=5%".to_string(), gen_optional_index(0.05)),
("fill=10%".to_string(), gen_optional_index(0.10)),
("fill=50%".to_string(), gen_optional_index(0.50)),
("fill=90%".to_string(), gen_optional_index(0.90)),
];
let mut group: InputGroup<OptionalIndex> = InputGroup::new_with_inputs(inputs);
// Translate orig->codec (rank_if_exists) with sampling
group.register("orig_to_codec_10pct_hit", |codec: &OptionalIndex| {
black_box(walk_over_data(codec, 100));
});
group.register("orig_to_codec_1pct_hit", |codec: &OptionalIndex| {
black_box(walk_over_data(codec, 1000));
});
group.register("orig_to_codec_full_scan", |codec: &OptionalIndex| {
black_box(walk_over_data_from_positions(codec, 0..TOTAL_NUM_VALUES));
});
// Translate codec->orig (select/select_batch) on sampled ranks
fn bench_translate_codec_to_orig_util(codec: &OptionalIndex, percent_hit: f32) {
let num_non_nulls = codec.num_non_nulls();
let idxs: Vec<u32> = if percent_hit == 100.0f32 {
(0..num_non_nulls).collect()
} else {
n_percent_step_iterator(percent_hit, num_non_nulls).collect()
};
let mut output = vec![0u32; idxs.len()];
output.copy_from_slice(&idxs[..]);
codec.select_batch(&mut output);
black_box(output);
}
group.register("codec_to_orig_0.005pct_hit", |codec: &OptionalIndex| {
bench_translate_codec_to_orig_util(codec, 0.005);
});
group.register("codec_to_orig_10pct_hit", |codec: &OptionalIndex| {
bench_translate_codec_to_orig_util(codec, 10.0);
});
group.register("codec_to_orig_full_scan", |codec: &OptionalIndex| {
bench_translate_codec_to_orig_util(codec, 100.0);
});
group.run();
}

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@@ -1,12 +1,15 @@
#![feature(test)]
use std::ops::RangeInclusive;
use std::sync::Arc;
use binggan::{InputGroup, black_box};
use common::OwnedBytes;
use rand::rngs::StdRng;
use rand::seq::SliceRandom;
use rand::{Rng, SeedableRng, random};
use tantivy_columnar::ColumnValues;
use test::Bencher;
extern crate test;
// TODO does this make sense for IPv6 ?
fn generate_random() -> Vec<u64> {
@@ -44,77 +47,78 @@ fn get_data_50percent_item() -> Vec<u128> {
}
data.push(SINGLE_ITEM);
data.shuffle(&mut rng);
data.iter().map(|el| *el as u128).collect::<Vec<_>>()
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
data
}
fn main() {
#[bench]
fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let column_range = get_u128_column_from_data(&data);
let column_random = get_u128_column_random();
let column = get_u128_column_from_data(&data);
struct Inputs {
data: Vec<u128>,
column_range: Arc<dyn ColumnValues<u128>>,
column_random: Arc<dyn ColumnValues<u128>>,
}
let inputs = Inputs {
data,
column_range,
column_random,
};
let mut group: InputGroup<Inputs> =
InputGroup::new_with_inputs(vec![("u128 benches".to_string(), inputs)]);
group.register(
"intfastfield_getrange_u128_50percent_hit",
|inp: &Inputs| {
let mut positions = Vec::new();
inp.column_range.get_row_ids_for_value_range(
*FIFTY_PERCENT_RANGE.start() as u128..=*FIFTY_PERCENT_RANGE.end() as u128,
0..inp.data.len() as u32,
&mut positions,
);
black_box(positions.len());
},
);
group.register("intfastfield_getrange_u128_single_hit", |inp: &Inputs| {
b.iter(|| {
let mut positions = Vec::new();
inp.column_range.get_row_ids_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,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_row_ids_for_value_range(
*SINGLE_ITEM_RANGE.start() as u128..=*SINGLE_ITEM_RANGE.end() as u128,
0..inp.data.len() as u32,
0..data.len() as u32,
&mut positions,
);
black_box(positions.len());
positions
});
}
group.register("intfastfield_getrange_u128_hit_all", |inp: &Inputs| {
#[bench]
fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
let data = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
let mut positions = Vec::new();
inp.column_range.get_row_ids_for_value_range(
0..=u128::MAX,
0..inp.data.len() as u32,
&mut positions,
);
black_box(positions.len());
column.get_row_ids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
positions
});
}
// U128 RANGE END
group.register("intfastfield_scan_all_fflookup_u128", |inp: &Inputs| {
#[bench]
fn bench_intfastfield_scan_all_fflookup_u128(b: &mut Bencher) {
let column = get_u128_column_random();
b.iter(|| {
let mut a = 0u128;
for i in 0u64..inp.column_random.num_vals() as u64 {
a += inp.column_random.get_val(i as u32);
for i in 0u64..column.num_vals() as u64 {
a += column.get_val(i as u32);
}
black_box(a);
a
});
}
group.register("intfastfield_jumpy_stride5_u128", |inp: &Inputs| {
let n = inp.column_random.num_vals();
#[bench]
fn bench_intfastfield_jumpy_stride5_u128(b: &mut Bencher) {
let column = get_u128_column_random();
b.iter(|| {
let n = column.num_vals();
let mut a = 0u128;
for i in (0..n / 5).map(|val| val * 5) {
a += inp.column_random.get_val(i);
a += column.get_val(i);
}
black_box(a);
a
});
group.run();
}

View File

@@ -1,10 +1,13 @@
#![feature(test)]
extern crate test;
use std::ops::RangeInclusive;
use std::sync::Arc;
use binggan::{InputGroup, black_box};
use rand::prelude::*;
use tantivy_columnar::column_values::{CodecType, serialize_and_load_u64_based_column_values};
use tantivy_columnar::*;
use test::Bencher;
// Warning: this generates the same permutation at each call
fn generate_permutation() -> Vec<u64> {
@@ -24,11 +27,37 @@ pub fn serialize_and_load(column: &[u64], codec_type: CodecType) -> Arc<dyn Colu
serialize_and_load_u64_based_column_values(&column, &[codec_type])
}
#[bench]
fn bench_intfastfield_jumpy_veclookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = permutation[a as usize];
}
a
});
}
#[bench]
fn bench_intfastfield_jumpy_fflookup_bitpacked(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = column.get_val(a as u32);
}
a
});
}
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]);
@@ -40,122 +69,135 @@ fn get_data_50percent_item() -> Vec<u128> {
data.push(SINGLE_ITEM);
data.shuffle(&mut rng);
data.iter().map(|el| *el as u128).collect::<Vec<_>>()
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
data
}
type VecCol = (Vec<u64>, Arc<dyn ColumnValues<u64>>);
// U64 RANGE START
#[bench]
fn bench_intfastfield_getrange_u64_50percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_row_ids_for_value_range(
FIFTY_PERCENT_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
fn bench_access() {
#[bench]
fn bench_intfastfield_getrange_u64_1percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_row_ids_for_value_range(
ONE_PERCENT_ITEM_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_single_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_row_ids_for_value_range(SINGLE_ITEM_RANGE, 0..data.len() as u32, &mut positions);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_hit_all(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&data, CodecType::Bitpacked);
b.iter(|| {
let mut positions = Vec::new();
column.get_row_ids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
positions
});
}
// U64 RANGE END
#[bench]
fn bench_intfastfield_stride7_vec(b: &mut Bencher) {
let permutation = generate_permutation();
let column_perm: Arc<dyn ColumnValues<u64>> =
serialize_and_load(&permutation, CodecType::Bitpacked);
let permutation_gcd = generate_permutation_gcd();
let column_perm_gcd: Arc<dyn ColumnValues<u64>> =
serialize_and_load(&permutation_gcd, CodecType::Bitpacked);
let mut group: InputGroup<VecCol> = InputGroup::new_with_inputs(vec![
(
"access".to_string(),
(permutation.clone(), column_perm.clone()),
),
(
"access_gcd".to_string(),
(permutation_gcd.clone(), column_perm_gcd.clone()),
),
]);
group.register("stride7_vec", |inp: &VecCol| {
let n = inp.0.len();
let n = permutation.len();
b.iter(|| {
let mut a = 0u64;
for i in (0..n / 7).map(|val| val * 7) {
a += inp.0[i];
a += permutation[i as usize];
}
black_box(a);
a
});
}
group.register("fullscan_vec", |inp: &VecCol| {
let mut a = 0u64;
for i in 0..inp.0.len() {
a += inp.0[i];
}
black_box(a);
});
group.register("stride7_column_values", |inp: &VecCol| {
let n = inp.1.num_vals() as usize;
let mut a = 0u64;
#[bench]
fn bench_intfastfield_stride7_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
b.iter(|| {
let mut a = 0;
for i in (0..n / 7).map(|val| val * 7) {
a += inp.1.get_val(i as u32);
a += column.get_val(i as u32);
}
black_box(a);
a
});
}
group.register("fullscan_column_values", |inp: &VecCol| {
#[bench]
fn bench_intfastfield_scan_all_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
let column_ref = column.as_ref();
b.iter(|| {
let mut a = 0u64;
for i in 0u32..n as u32 {
a += column_ref.get_val(i);
}
a
});
}
#[bench]
fn bench_intfastfield_scan_all_fflookup_gcd(b: &mut Bencher) {
let permutation = generate_permutation_gcd();
let n = permutation.len();
let column: Arc<dyn ColumnValues<u64>> = serialize_and_load(&permutation, CodecType::Bitpacked);
b.iter(|| {
let mut a = 0u64;
let n = inp.1.num_vals() as usize;
for i in 0..n {
a += inp.1.get_val(i as u32);
a += column.get_val(i as u32);
}
black_box(a);
a
});
group.run();
}
fn bench_range() {
let data_50 = get_data_50percent_item();
let data_u64 = data_50.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column_data: Arc<dyn ColumnValues<u64>> =
serialize_and_load(&data_u64, CodecType::Bitpacked);
let mut group: InputGroup<Arc<dyn ColumnValues<u64>>> =
InputGroup::new_with_inputs(vec![("dist_50pct_item".to_string(), column_data.clone())]);
group.register(
"fastfield_getrange_u64_50percent_hit",
|col: &Arc<dyn ColumnValues<u64>>| {
let mut positions = Vec::new();
col.get_row_ids_for_value_range(FIFTY_PERCENT_RANGE, 0..col.num_vals(), &mut positions);
black_box(positions.len());
},
);
group.register(
"fastfield_getrange_u64_1percent_hit",
|col: &Arc<dyn ColumnValues<u64>>| {
let mut positions = Vec::new();
col.get_row_ids_for_value_range(
ONE_PERCENT_ITEM_RANGE,
0..col.num_vals(),
&mut positions,
);
black_box(positions.len());
},
);
group.register(
"fastfield_getrange_u64_single_hit",
|col: &Arc<dyn ColumnValues<u64>>| {
let mut positions = Vec::new();
col.get_row_ids_for_value_range(SINGLE_ITEM_RANGE, 0..col.num_vals(), &mut positions);
black_box(positions.len());
},
);
group.register(
"fastfield_getrange_u64_hit_all",
|col: &Arc<dyn ColumnValues<u64>>| {
let mut positions = Vec::new();
col.get_row_ids_for_value_range(0..=u64::MAX, 0..col.num_vals(), &mut positions);
black_box(positions.len());
},
);
group.run();
}
fn main() {
bench_access();
bench_range();
#[bench]
fn bench_intfastfield_scan_all_vec(b: &mut Bencher) {
let permutation = generate_permutation();
b.iter(|| {
let mut a = 0u64;
for i in 0..permutation.len() {
a += permutation[i as usize] as u64;
}
a
});
}

View File

@@ -219,3 +219,170 @@ fn test_optional_index_for_tests() {
assert!(!optional_index.contains(3));
assert_eq!(optional_index.num_docs(), 4);
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::Bencher;
use super::*;
const TOTAL_NUM_VALUES: u32 = 1_000_000;
fn gen_bools(fill_ratio: f64) -> OptionalIndex {
let mut out = Vec::new();
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let vals: Vec<RowId> = (0..TOTAL_NUM_VALUES)
.map(|_| rng.gen_bool(fill_ratio))
.enumerate()
.filter(|(_pos, val)| *val)
.map(|(pos, _)| pos as RowId)
.collect();
serialize_optional_index(&&vals[..], TOTAL_NUM_VALUES, &mut out).unwrap();
open_optional_index(OwnedBytes::new(out)).unwrap()
}
fn random_range_iterator(
start: u32,
end: u32,
avg_step_size: u32,
avg_deviation: u32,
) -> impl Iterator<Item = u32> {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
if current >= end { None } else { Some(current) }
})
}
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
let ratio = percent / 100.0;
let step_size = (1f32 / ratio) as u32;
let deviation = step_size - 1;
random_range_iterator(0, num_values, step_size, deviation)
}
fn walk_over_data(codec: &OptionalIndex, avg_step_size: u32) -> Option<u32> {
walk_over_data_from_positions(
codec,
random_range_iterator(0, TOTAL_NUM_VALUES, avg_step_size, 0),
)
}
fn walk_over_data_from_positions(
codec: &OptionalIndex,
positions: impl Iterator<Item = u32>,
) -> Option<u32> {
let mut dense_idx: Option<u32> = None;
for idx in positions {
dense_idx = dense_idx.or(codec.rank_if_exists(idx));
}
dense_idx
}
#[bench]
fn bench_translate_orig_to_codec_1percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 1000));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_1percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_10percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_90percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_10percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_50percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.5f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_90percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_0comma005percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.01f64, 0.005f32, bench);
}
#[bench]
fn bench_translate_codec_to_orig_10percent_filled_0comma005percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.1f64, 0.005f32, bench);
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_10percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.01f64, 10f32, bench);
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_full_scan(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.01f64, 100f32, bench);
}
fn bench_translate_codec_to_orig_util(
percent_filled: f64,
percent_hit: f32,
bench: &mut Bencher,
) {
let codec = gen_bools(percent_filled);
let num_non_nulls = codec.num_non_nulls();
let idxs: Vec<u32> = if percent_hit == 100.0f32 {
(0..num_non_nulls).collect()
} else {
n_percent_step_iterator(percent_hit, num_non_nulls).collect()
};
let mut output = vec![0u32; idxs.len()];
bench.iter(|| {
output.copy_from_slice(&idxs[..]);
codec.select_batch(&mut output);
});
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_0comma005percent_hit(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.9f64, 0.005, bench);
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_full_scan(bench: &mut Bencher) {
bench_translate_codec_to_orig_util(0.9f64, 100.0f32, bench);
}
}

View File

@@ -0,0 +1,139 @@
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.r#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)
.unwrap();
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);
}

View File

@@ -242,3 +242,6 @@ impl<T: Copy + PartialOrd + Debug + 'static> ColumnValues<T> for Arc<dyn ColumnV
.get_row_ids_for_value_range(range, doc_id_range, positions)
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench;

View File

@@ -1,3 +1,5 @@
#![allow(clippy::manual_div_ceil)]
mod column_type;
mod format_version;
mod merge;

View File

@@ -17,10 +17,15 @@
//! column.
//! - [column_values]: Stores the values of a column in a dense format.
// #![cfg_attr(all(feature = "unstable", test), feature(test))]
#[cfg(test)]
#[macro_use]
extern crate more_asserts;
#[cfg(all(test, feature = "unstable"))]
extern crate test;
use std::fmt::Display;
use std::io;

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-common"
version = "0.10.0"
version = "0.9.0"
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
license = "MIT"
edition = "2024"

View File

@@ -9,7 +9,7 @@ use crate::ByteCount;
pub struct TinySet(u64);
impl fmt::Debug for TinySet {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
self.into_iter().collect::<Vec<u32>>().fmt(f)
}
}
@@ -182,6 +182,7 @@ pub struct BitSet {
max_value: u32,
}
#[inline(always)]
fn num_buckets(max_val: u32) -> u32 {
(max_val + 63u32) / 64u32
}

View File

@@ -1,4 +1,6 @@
#![allow(clippy::len_without_is_empty)]
// manual divceil actually generates code that is not optimal (to accept the full range of u32) and
// perf matters here.
#![allow(clippy::len_without_is_empty, clippy::manual_div_ceil)]
use std::ops::Deref;

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-query-grammar"
version = "0.25.0"
version = "0.24.0"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]

View File

@@ -36,7 +36,7 @@ fn field_name(inp: &str) -> IResult<&str, String> {
alt((first_char, escape_sequence())),
many0(alt((simple_char, escape_sequence(), char('\\')))),
)),
tuple((multispace0, char(':'), multispace0)),
char(':'),
),
|(first_char, next)| once(first_char).chain(next).collect(),
)(inp)
@@ -305,15 +305,14 @@ fn term_group_infallible(inp: &str) -> JResult<&str, UserInputAst> {
let (inp, (field_name, _, _, _)) =
tuple((field_name, multispace0, char('('), multispace0))(inp).expect("precondition failed");
let res = delimited_infallible(
delimited_infallible(
nothing,
map(ast_infallible, |(mut ast, errors)| {
ast.set_default_field(field_name.to_string());
(ast, errors)
}),
opt_i_err(char(')'), "expected ')'"),
)(inp);
res
)(inp)
}
fn exists(inp: &str) -> IResult<&str, UserInputLeaf> {
@@ -1283,10 +1282,6 @@ mod test {
super::field_name("~my~field:a"),
Ok(("a", "~my~field".to_string()))
);
assert_eq!(
super::field_name(".my.field.name : a"),
Ok(("a", ".my.field.name".to_string()))
);
for special_char in SPECIAL_CHARS.iter() {
let query = &format!("\\{special_char}my\\{special_char}field:a");
assert_eq!(
@@ -1693,15 +1688,4 @@ mod test {
fn test_invalid_field() {
test_is_parse_err(r#"!bc:def"#, "!bc:def");
}
#[test]
fn test_space_before_value() {
test_parse_query_to_ast_helper("field : a", r#""field":a"#);
test_parse_query_to_ast_helper("field: a", r#""field":a"#);
test_parse_query_to_ast_helper("field :a", r#""field":a"#);
test_parse_query_to_ast_helper(
"field : 'happy tax payer' AND other_field : 1",
r#"(+"field":'happy tax payer' +"other_field":1)"#,
);
}
}

View File

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

View File

@@ -1293,220 +1293,6 @@ mod tests {
assert_eq!(page_0, &page_2[..page_0.len()]);
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(20))]
/// Build multiple segments with equal-scoring docs and verify stable ordering
/// across pages when increasing limit or offset.
#[test]
fn proptest_stable_ordering_across_segments_with_pagination(
docs_per_segment in proptest::collection::vec(1usize..50, 2..5)
) {
use crate::indexer::NoMergePolicy;
// Build an index with multiple segments; all docs will have the same score using AllQuery.
let mut schema_builder = Schema::builder();
let text = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer.set_merge_policy(Box::new(NoMergePolicy));
for num_docs in &docs_per_segment {
for _ in 0..*num_docs {
writer.add_document(doc!(text => "x")).unwrap();
}
writer.commit().unwrap();
}
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let total_docs: usize = docs_per_segment.iter().sum();
// Full result set, first assert all scores are identical.
let full_with_scores: Vec<(Score, DocAddress)> = searcher
.search(&AllQuery, &TopDocs::with_limit(total_docs))
.unwrap();
// Sanity: at least one document was returned.
prop_assert!(!full_with_scores.is_empty());
let first_score = full_with_scores[0].0;
prop_assert!(full_with_scores.iter().all(|(score, _)| *score == first_score));
// Keep only the addresses for the remaining checks.
let full: Vec<DocAddress> = full_with_scores
.into_iter()
.map(|(_score, addr)| addr)
.collect();
// Sanity: we actually created multiple segments and have documents.
prop_assert!(docs_per_segment.len() >= 2);
prop_assert!(total_docs >= 2);
// 1) Increasing limit should preserve prefix ordering.
for k in 1..=total_docs {
let page: Vec<DocAddress> = searcher
.search(&AllQuery, &TopDocs::with_limit(k))
.unwrap()
.into_iter()
.map(|(_score, addr)| addr)
.collect();
prop_assert_eq!(page, full[..k].to_vec());
}
// 2) Offset + limit pages should always match the corresponding slice.
// For each offset, check three representative page sizes:
// - first page (size 1)
// - a middle page (roughly half of remaining)
// - the last page (size = remaining)
for offset in 0..total_docs {
let remaining = total_docs - offset;
let assert_page_eq = |limit: usize| -> proptest::test_runner::TestCaseResult {
let page: Vec<DocAddress> = searcher
.search(&AllQuery, &TopDocs::with_limit(limit).and_offset(offset))
.unwrap()
.into_iter()
.map(|(_score, addr)| addr)
.collect();
prop_assert_eq!(page, full[offset..offset + limit].to_vec());
Ok(())
};
// Smallest page.
assert_page_eq(1)?;
// A middle-sized page (dedupes to 1 if remaining == 1).
assert_page_eq((remaining / 2).max(1))?;
// Largest page for this offset.
assert_page_eq(remaining)?;
}
// 3) Concatenating fixed-size pages by offset reproduces the full order.
for page_size in 1..=total_docs.min(5) {
let mut concat: Vec<DocAddress> = Vec::new();
let mut offset = 0;
while offset < total_docs {
let size = page_size.min(total_docs - offset);
let page: Vec<DocAddress> = searcher
.search(&AllQuery, &TopDocs::with_limit(size).and_offset(offset))
.unwrap()
.into_iter()
.map(|(_score, addr)| addr)
.collect();
concat.extend(page);
offset += size;
}
// Avoid moving `full` across loop iterations.
prop_assert_eq!(concat, full.clone());
}
}
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(20))]
/// Build multiple segments with same-scoring term matches and verify stable ordering
/// across pages for a real scoring query (TermQuery with identical TF and fieldnorm).
#[test]
fn proptest_stable_ordering_across_segments_with_term_query_and_pagination(
docs_per_segment in proptest::collection::vec(1usize..50, 2..5)
) {
use crate::indexer::NoMergePolicy;
use crate::schema::IndexRecordOption;
use crate::query::TermQuery;
use crate::Term;
// Build an index with multiple segments; each doc has exactly one token "x",
// ensuring equal BM25 scores across all matching docs (same TF=1 and fieldnorm=1).
let mut schema_builder = Schema::builder();
let text = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer.set_merge_policy(Box::new(NoMergePolicy));
for num_docs in &docs_per_segment {
for _ in 0..*num_docs {
writer.add_document(doc!(text => "x")).unwrap();
}
writer.commit().unwrap();
}
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let total_docs: usize = docs_per_segment.iter().sum();
let term = Term::from_field_text(text, "x");
let tq = TermQuery::new(term, IndexRecordOption::WithFreqs);
// Full result set, first assert all scores are identical across docs.
let full_with_scores: Vec<(Score, DocAddress)> = searcher
.search(&tq, &TopDocs::with_limit(total_docs))
.unwrap();
// Sanity: at least one document was returned.
prop_assert!(!full_with_scores.is_empty());
let first_score = full_with_scores[0].0;
prop_assert!(full_with_scores.iter().all(|(score, _)| *score == first_score));
// Keep only the addresses for the remaining checks.
let full: Vec<DocAddress> = full_with_scores
.into_iter()
.map(|(_score, addr)| addr)
.collect();
// Sanity: we actually created multiple segments and have documents.
prop_assert!(docs_per_segment.len() >= 2);
prop_assert!(total_docs >= 2);
// 1) Increasing limit should preserve prefix ordering.
for k in 1..=total_docs {
let page: Vec<DocAddress> = searcher
.search(&tq, &TopDocs::with_limit(k))
.unwrap()
.into_iter()
.map(|(_score, addr)| addr)
.collect();
prop_assert_eq!(page, full[..k].to_vec());
}
// 2) Offset + limit pages should always match the corresponding slice.
// Check three representative page sizes for each offset: 1, ~half, and remaining.
for offset in 0..total_docs {
let remaining = total_docs - offset;
let assert_page_eq = |limit: usize| -> proptest::test_runner::TestCaseResult {
let page: Vec<DocAddress> = searcher
.search(&tq, &TopDocs::with_limit(limit).and_offset(offset))
.unwrap()
.into_iter()
.map(|(_score, addr)| addr)
.collect();
prop_assert_eq!(page, full[offset..offset + limit].to_vec());
Ok(())
};
assert_page_eq(1)?;
assert_page_eq((remaining / 2).max(1))?;
assert_page_eq(remaining)?;
}
// 3) Concatenating fixed-size pages by offset reproduces the full order.
for page_size in 1..=total_docs.min(5) {
let mut concat: Vec<DocAddress> = Vec::new();
let mut offset = 0;
while offset < total_docs {
let size = page_size.min(total_docs - offset);
let page: Vec<DocAddress> = searcher
.search(&tq, &TopDocs::with_limit(size).and_offset(offset))
.unwrap()
.into_iter()
.map(|(_score, addr)| addr)
.collect();
concat.extend(page);
offset += size;
}
prop_assert_eq!(concat, full.clone());
}
}
}
#[test]
#[should_panic]
fn test_top_0() {

View File

@@ -216,7 +216,7 @@ impl IndexBuilder {
/// Opens or creates a new index in the provided directory
pub fn open_or_create<T: Into<Box<dyn Directory>>>(self, dir: T) -> crate::Result<Index> {
let dir: Box<dyn Directory> = dir.into();
let dir = dir.into();
if !Index::exists(&*dir)? {
return self.create(dir);
}
@@ -494,7 +494,7 @@ impl Index {
.into_iter()
.map(|segment| SegmentReader::open(&segment)?.fields_metadata())
.collect::<Result<_, _>>()?;
Ok(merge_field_meta_data(fields_metadata))
Ok(merge_field_meta_data(fields_metadata, &self.schema()))
}
/// Creates a new segment_meta (Advanced user only).

View File

@@ -1,7 +1,8 @@
use std::io;
use common::json_path_writer::JSON_END_OF_PATH;
use common::{BinarySerializable, ByteCount};
use common::BinarySerializable;
use fnv::FnvHashSet;
#[cfg(feature = "quickwit")]
use futures_util::{FutureExt, StreamExt, TryStreamExt};
#[cfg(feature = "quickwit")]
@@ -35,33 +36,6 @@ pub struct InvertedIndexReader {
total_num_tokens: u64,
}
/// Object that records the amount of space used by a field in an inverted index.
pub(crate) struct InvertedIndexFieldSpace {
pub field_name: String,
pub field_type: Type,
pub postings_size: ByteCount,
pub positions_size: ByteCount,
pub num_terms: u64,
}
/// Returns None if the term is not a valid JSON path.
fn extract_field_name_and_field_type_from_json_path(term: &[u8]) -> Option<(String, Type)> {
let index = term.iter().position(|&byte| byte == JSON_END_OF_PATH)?;
let field_type_code = term.get(index + 1).copied()?;
let field_type = Type::from_code(field_type_code)?;
// Let's flush the current field.
let field_name = String::from_utf8_lossy(&term[..index]).to_string();
Some((field_name, field_type))
}
impl InvertedIndexFieldSpace {
fn record(&mut self, term_info: &TermInfo) {
self.postings_size += ByteCount::from(term_info.posting_num_bytes() as u64);
self.positions_size += ByteCount::from(term_info.positions_num_bytes() as u64);
self.num_terms += 1;
}
}
impl InvertedIndexReader {
pub(crate) fn new(
termdict: TermDictionary,
@@ -107,56 +81,20 @@ impl InvertedIndexReader {
///
/// Notice: This requires a full scan and therefore **very expensive**.
/// TODO: Move to sstable to use the index.
pub(crate) fn list_encoded_json_fields(&self) -> io::Result<Vec<InvertedIndexFieldSpace>> {
pub fn list_encoded_fields(&self) -> io::Result<Vec<(String, Type)>> {
let mut stream = self.termdict.stream()?;
let mut fields: Vec<InvertedIndexFieldSpace> = Vec::new();
let mut current_field_opt: Option<InvertedIndexFieldSpace> = None;
// Current field bytes, including the JSON_END_OF_PATH.
let mut current_field_bytes: Vec<u8> = Vec::new();
while let Some((term, term_info)) = stream.next() {
if let Some(current_field) = &mut current_field_opt {
if term.starts_with(&current_field_bytes) {
// We are still in the same field.
current_field.record(term_info);
continue;
let mut fields = Vec::new();
let mut fields_set = FnvHashSet::default();
while let Some((term, _term_info)) = stream.next() {
if let Some(index) = term.iter().position(|&byte| byte == JSON_END_OF_PATH) {
if !fields_set.contains(&term[..index + 2]) {
fields_set.insert(term[..index + 2].to_vec());
let typ = Type::from_code(term[index + 1]).unwrap();
fields.push((String::from_utf8_lossy(&term[..index]).to_string(), typ));
}
}
// This is a new field!
// Let's flush the current field.
fields.extend(current_field_opt.take());
current_field_bytes.clear();
// And create a new one.
let Some((field_name, field_type)) =
extract_field_name_and_field_type_from_json_path(term)
else {
error!(
"invalid term bytes encountered {term:?}. this only happens if the term \
dictionary is corrupted. please report"
);
continue;
};
let mut field_space = InvertedIndexFieldSpace {
field_name,
field_type,
postings_size: ByteCount::default(),
positions_size: ByteCount::default(),
num_terms: 0u64,
};
field_space.record(&term_info);
// We include the json type and the json end of path to make sure the prefix check
// is meaningful.
current_field_bytes.extend_from_slice(&term[..field_space.field_name.len() + 2]);
current_field_opt = Some(field_space);
}
// We need to flush the last field as well.
fields.extend(current_field_opt.take());
Ok(fields)
}

View File

@@ -1,8 +1,8 @@
use std::collections::HashMap;
use std::ops::BitOrAssign;
use std::sync::{Arc, RwLock};
use std::{fmt, io};
use common::{ByteCount, HasLen};
use fnv::FnvHashMap;
use itertools::Itertools;
@@ -304,16 +304,12 @@ impl SegmentReader {
for (field, field_entry) in self.schema().fields() {
let field_name = field_entry.name().to_string();
let is_indexed = field_entry.is_indexed();
if is_indexed {
let is_json = field_entry.field_type().value_type() == Type::Json;
if is_json {
let term_dictionary_json_field_num_bytes: u64 = self
.termdict_composite
.open_read(field)
.map(|file_slice| file_slice.len() as u64)
.unwrap_or(0u64);
let inv_index = self.inverted_index(field)?;
let encoded_fields_in_index = inv_index.list_encoded_json_fields()?;
let encoded_fields_in_index = inv_index.list_encoded_fields()?;
let mut build_path = |field_name: &str, mut json_path: String| {
// In this case we need to map the potential fast field to the field name
// accepted by the query parser.
@@ -332,65 +328,30 @@ impl SegmentReader {
format!("{field_name}.{json_path}")
}
};
let total_num_terms = encoded_fields_in_index
.iter()
.map(|field_space| field_space.num_terms)
.sum();
indexed_fields.extend(encoded_fields_in_index.into_iter().map(|field_space| {
let field_name = build_path(&field_name, field_space.field_name);
// It is complex to attribute the exact amount of bytes required by specific
// field in the json field. Instead, as a proxy, we
// attribute the total amount of bytes for the entire json field,
// proportionally to the number of terms in each
// fields.
let term_dictionary_size = (term_dictionary_json_field_num_bytes
* field_space.num_terms)
.checked_div(total_num_terms)
.unwrap_or(0);
FieldMetadata {
postings_size: Some(field_space.postings_size),
positions_size: Some(field_space.positions_size),
term_dictionary_size: Some(ByteCount::from(term_dictionary_size)),
fast_size: None,
// The stored flag will be set at the end of this function!
stored: field_entry.is_stored(),
field_name,
typ: field_space.field_type,
}
}));
indexed_fields.extend(
encoded_fields_in_index
.into_iter()
.map(|(name, typ)| (build_path(&field_name, name), typ))
.map(|(field_name, typ)| FieldMetadata {
indexed: true,
stored: false,
field_name,
fast: false,
typ,
}),
);
} else {
let postings_size: ByteCount = self
.postings_composite
.open_read(field)
.map(|posting_fileslice| posting_fileslice.len())
.unwrap_or(0)
.into();
let positions_size: ByteCount = self
.positions_composite
.open_read(field)
.map(|positions_fileslice| positions_fileslice.len())
.unwrap_or(0)
.into();
let term_dictionary_size: ByteCount = self
.termdict_composite
.open_read(field)
.map(|term_dictionary_fileslice| term_dictionary_fileslice.len())
.unwrap_or(0)
.into();
indexed_fields.push(FieldMetadata {
indexed: true,
stored: false,
field_name: field_name.to_string(),
fast: false,
typ: field_entry.field_type().value_type(),
// The stored flag will be set at the end of this function!
stored: field_entry.is_stored(),
fast_size: None,
term_dictionary_size: Some(term_dictionary_size),
postings_size: Some(postings_size),
positions_size: Some(positions_size),
});
}
}
}
let fast_fields: Vec<FieldMetadata> = self
let mut fast_fields: Vec<FieldMetadata> = self
.fast_fields()
.columnar()
.iter_columns()?
@@ -402,21 +363,23 @@ impl SegmentReader {
.get(&field_name)
.unwrap_or(&field_name)
.to_string();
let stored = is_field_stored(&field_name, &self.schema);
FieldMetadata {
indexed: false,
stored: false,
field_name,
fast: true,
typ: Type::from(handle.column_type()),
stored,
fast_size: Some(handle.num_bytes()),
term_dictionary_size: None,
postings_size: None,
positions_size: None,
}
})
.collect();
let merged_field_metadatas: Vec<FieldMetadata> =
merge_field_meta_data(vec![indexed_fields, fast_fields]);
Ok(merged_field_metadatas)
// Since the type is encoded differently in the fast field and in the inverted index,
// the order of the fields is not guaranteed to be the same. Therefore, we sort the fields.
// If we are sure that the order is the same, we can remove this sort.
indexed_fields.sort_unstable();
fast_fields.sort_unstable();
let merged = merge_field_meta_data(vec![indexed_fields, fast_fields], &self.schema);
Ok(merged)
}
/// Returns the segment id
@@ -480,47 +443,20 @@ pub struct FieldMetadata {
// Notice: Don't reorder the declaration of 1.field_name 2.typ, as it is used for ordering by
// field_name then typ.
pub typ: Type,
/// Is the field indexed for search
pub indexed: bool,
/// Is the field stored in the doc store
pub stored: bool,
/// Size occupied in the columnar storage (None if not fast)
pub fast_size: Option<ByteCount>,
/// term_dictionary
pub term_dictionary_size: Option<ByteCount>,
/// Size occupied in the index postings storage (None if not indexed)
pub postings_size: Option<ByteCount>,
/// Size occupied in the index postings storage (None if positions are not recorded)
pub positions_size: Option<ByteCount>,
/// Is the field stored in the columnar storage
pub fast: bool,
}
fn merge_options(left: Option<ByteCount>, right: Option<ByteCount>) -> Option<ByteCount> {
match (left, right) {
(Some(l), Some(r)) => Some(l + r),
(None, right) => right,
(left, None) => left,
}
}
impl FieldMetadata {
/// Returns true if and only if the field is indexed.
pub fn is_indexed(&self) -> bool {
self.postings_size.is_some()
}
/// Returns true if and only if the field is a fast field (i.e.: recorded in columnar format).
pub fn is_fast(&self) -> bool {
self.fast_size.is_some()
}
/// Merges two field metadata.
pub fn merge(&mut self, rhs: Self) {
assert_eq!(self.field_name, rhs.field_name);
assert_eq!(self.typ, rhs.typ);
impl BitOrAssign for FieldMetadata {
fn bitor_assign(&mut self, rhs: Self) {
assert!(self.field_name == rhs.field_name);
assert!(self.typ == rhs.typ);
self.indexed |= rhs.indexed;
self.stored |= rhs.stored;
self.fast_size = merge_options(self.fast_size, rhs.fast_size);
self.term_dictionary_size =
merge_options(self.term_dictionary_size, rhs.term_dictionary_size);
self.postings_size = merge_options(self.postings_size, rhs.postings_size);
self.positions_size = merge_options(self.positions_size, rhs.positions_size);
self.fast |= rhs.fast;
}
}
@@ -533,29 +469,23 @@ fn is_field_stored(field_name: &str, schema: &Schema) -> bool {
}
/// Helper to merge the field metadata from multiple segments.
pub fn merge_field_meta_data(mut field_metadatas: Vec<Vec<FieldMetadata>>) -> Vec<FieldMetadata> {
// READ BEFORE REMOVING THIS!
//
// Because we replace field sep by `.`, fields are not always sorted.
// Also, to enforce such an implicit contract, we would have to add
// assert here.
//
// Sorting is linear time on pre-sorted data, so we are simply better off sorting data here.
for field_metadatas in &mut field_metadatas {
field_metadatas.sort_unstable();
}
pub fn merge_field_meta_data(
field_metadatas: Vec<Vec<FieldMetadata>>,
schema: &Schema,
) -> Vec<FieldMetadata> {
let mut merged_field_metadata = Vec::new();
for (_key, mut group) in &field_metadatas
.into_iter()
.kmerge()
.kmerge_by(|left, right| left < right)
// TODO: Remove allocation
.chunk_by(|el| (el.field_name.to_string(), el.typ))
{
let mut merged: FieldMetadata = group.next().unwrap();
for el in group {
merged.merge(el);
merged |= el;
}
// Currently is_field_stored is maybe too slow for the high cardinality case
merged.stored = is_field_stored(&merged.field_name, schema);
merged_field_metadata.push(merged);
}
merged_field_metadata
@@ -577,7 +507,7 @@ fn intersect_alive_bitset(
}
impl fmt::Debug for SegmentReader {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "SegmentReader({:?})", self.segment_id)
}
}
@@ -586,168 +516,122 @@ impl fmt::Debug for SegmentReader {
mod test {
use super::*;
use crate::index::Index;
use crate::schema::{Term, STORED, TEXT};
use crate::schema::{SchemaBuilder, Term, STORED, TEXT};
use crate::IndexWriter;
#[track_caller]
fn assert_merge(fields_metadatas: &[Vec<FieldMetadata>], expected: &[FieldMetadata]) {
use itertools::Itertools;
let num_els = fields_metadatas.len();
for permutation in fields_metadatas.iter().cloned().permutations(num_els) {
let res = merge_field_meta_data(permutation);
assert_eq!(&res, &expected);
}
}
#[test]
fn test_merge_field_meta_data_same_field() {
fn test_merge_field_meta_data_same() {
let schema = SchemaBuilder::new().build();
let field_metadata1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
term_dictionary_size: Some(ByteCount::from(100u64)),
postings_size: Some(ByteCount::from(1_000u64)),
positions_size: Some(ByteCount::from(2_000u64)),
fast_size: Some(ByteCount::from(1_000u64).into()),
fast: true,
};
let field_metadata2 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
term_dictionary_size: Some(ByteCount::from(80u64)),
postings_size: Some(ByteCount::from(1_500u64)),
positions_size: Some(ByteCount::from(2_500u64)),
fast_size: Some(ByteCount::from(3_000u64).into()),
fast: true,
};
let expected = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
stored: false,
term_dictionary_size: Some(ByteCount::from(180u64)),
postings_size: Some(ByteCount::from(2_500u64)),
positions_size: Some(ByteCount::from(4_500u64)),
fast_size: Some(ByteCount::from(4_000u64).into()),
};
assert_merge(
&[vec![field_metadata1.clone()], vec![field_metadata2]],
&[expected],
let res = merge_field_meta_data(
vec![vec![field_metadata1.clone()], vec![field_metadata2]],
&schema,
);
assert_eq!(res, vec![field_metadata1]);
}
#[track_caller]
#[test]
fn test_merge_field_meta_data_different() {
let schema = SchemaBuilder::new().build();
let field_metadata1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: false,
stored: false,
fast_size: Some(1_000u64.into()),
term_dictionary_size: Some(100u64.into()),
postings_size: Some(2_000u64.into()),
positions_size: Some(4_000u64.into()),
fast: true,
};
let field_metadata2 = FieldMetadata {
field_name: "b".to_string(),
typ: crate::schema::Type::Str,
indexed: false,
stored: false,
fast_size: Some(1_002u64.into()),
term_dictionary_size: None,
postings_size: None,
positions_size: None,
fast: true,
};
let field_metadata3 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
term_dictionary_size: Some(101u64.into()),
postings_size: Some(2_001u64.into()),
positions_size: Some(4_001u64.into()),
indexed: true,
stored: false,
fast_size: None,
fast: false,
};
let expected = vec![
FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
stored: false,
term_dictionary_size: Some(201u64.into()),
postings_size: Some(4_001u64.into()),
positions_size: Some(8_001u64.into()),
fast_size: Some(1_000u64.into()),
},
FieldMetadata {
field_name: "b".to_string(),
typ: crate::schema::Type::Str,
stored: false,
term_dictionary_size: None,
postings_size: None,
positions_size: None,
fast_size: Some(1_002u64.into()),
},
];
assert_merge(
&[
let res = merge_field_meta_data(
vec![
vec![field_metadata1.clone(), field_metadata2.clone()],
vec![field_metadata3],
],
&expected,
&schema,
);
let field_metadata_expected1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: true,
};
assert_eq!(res, vec![field_metadata_expected1, field_metadata2.clone()]);
}
#[test]
fn test_merge_field_meta_data_merge() {
use pretty_assertions::assert_eq;
let get_meta_data = |name: &str, typ: Type| FieldMetadata {
field_name: name.to_string(),
typ,
term_dictionary_size: None,
postings_size: None,
positions_size: None,
indexed: false,
stored: false,
fast_size: Some(1u64.into()),
fast: true,
};
let metas = vec![get_meta_data("d", Type::Str), get_meta_data("e", Type::U64)];
assert_merge(
&[vec![get_meta_data("e", Type::Str)], metas],
&[
let schema = SchemaBuilder::new().build();
let mut metas = vec![get_meta_data("d", Type::Str), get_meta_data("e", Type::U64)];
metas.sort();
let res = merge_field_meta_data(vec![vec![get_meta_data("e", Type::Str)], metas], &schema);
assert_eq!(
res,
vec![
get_meta_data("d", Type::Str),
get_meta_data("e", Type::Str),
get_meta_data("e", Type::U64),
],
]
);
}
#[test]
fn test_merge_field_meta_data_bitxor() {
let field_metadata1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
term_dictionary_size: None,
postings_size: None,
positions_size: None,
indexed: false,
stored: false,
fast_size: Some(10u64.into()),
fast: true,
};
let field_metadata2 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
term_dictionary_size: Some(10u64.into()),
postings_size: Some(11u64.into()),
positions_size: Some(12u64.into()),
indexed: true,
stored: false,
fast_size: None,
fast: false,
};
let field_metadata_expected = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
term_dictionary_size: Some(10u64.into()),
postings_size: Some(11u64.into()),
positions_size: Some(12u64.into()),
indexed: true,
stored: false,
fast_size: Some(10u64.into()),
fast: true,
};
let mut res1 = field_metadata1.clone();
res1.merge(field_metadata2.clone());
res1 |= field_metadata2.clone();
let mut res2 = field_metadata2.clone();
res2.merge(field_metadata1);
res2 |= field_metadata1;
assert_eq!(res1, field_metadata_expected);
assert_eq!(res2, field_metadata_expected);
}
@@ -778,7 +662,6 @@ mod test {
assert_eq!(4, searcher.segment_reader(0).max_doc());
Ok(())
}
#[test]
fn test_alive_docs_iterator() -> crate::Result<()> {
let mut schema_builder = Schema::builder();

View File

@@ -61,8 +61,6 @@ type AddBatchReceiver<D> = channel::Receiver<AddBatch<D>>;
#[cfg(test)]
mod tests_mmap {
use common::ByteCount;
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::AggregationCollector;
@@ -282,14 +280,11 @@ mod tests_mmap {
field_name_out
};
let mut fields: Vec<(String, Type)> = reader.searcher().segment_readers()[0]
let mut fields = reader.searcher().segment_readers()[0]
.inverted_index(field)
.unwrap()
.list_encoded_json_fields()
.unwrap()
.into_iter()
.map(|field_space| (field_space.field_name, field_space.field_type))
.collect();
.list_encoded_fields()
.unwrap();
assert_eq!(fields.len(), 8);
fields.sort();
let mut expected_fields = vec![
@@ -390,12 +385,7 @@ mod tests_mmap {
let reader = &searcher.segment_readers()[0];
let inverted_index = reader.inverted_index(json_field).unwrap();
assert_eq!(
inverted_index
.list_encoded_json_fields()
.unwrap()
.into_iter()
.map(|field_space| (field_space.field_name, field_space.field_type))
.collect::<Vec<_>>(),
inverted_index.list_encoded_fields().unwrap(),
[
("k8s.container.name".to_string(), Type::Str),
("sub\u{1}a".to_string(), Type::I64),
@@ -412,41 +402,19 @@ mod tests_mmap {
fn test_json_fields_metadata_expanded_dots_one_segment() {
test_json_fields_metadata(true, true);
}
#[test]
fn test_json_fields_metadata_expanded_dots_multi_segment() {
test_json_fields_metadata(true, false);
}
#[test]
fn test_json_fields_metadata_no_expanded_dots_one_segment() {
test_json_fields_metadata(false, true);
}
#[test]
fn test_json_fields_metadata_no_expanded_dots_multi_segment() {
test_json_fields_metadata(false, false);
}
#[track_caller]
fn assert_size_eq(lhs: Option<ByteCount>, rhs: Option<ByteCount>) {
let ignore_actual_values = |size_opt: Option<ByteCount>| size_opt.map(|val| val > 0);
assert_eq!(ignore_actual_values(lhs), ignore_actual_values(rhs));
}
#[track_caller]
fn assert_field_metadata_eq_but_ignore_field_size(
expected: &FieldMetadata,
actual: &FieldMetadata,
) {
assert_eq!(&expected.field_name, &actual.field_name);
assert_eq!(&expected.typ, &actual.typ);
assert_eq!(&expected.stored, &actual.stored);
assert_size_eq(expected.postings_size, actual.postings_size);
assert_size_eq(expected.positions_size, actual.positions_size);
assert_size_eq(expected.fast_size, actual.fast_size);
}
fn test_json_fields_metadata(expanded_dots: bool, one_segment: bool) {
use pretty_assertions::assert_eq;
let mut schema_builder = Schema::builder();
@@ -485,101 +453,81 @@ mod tests_mmap {
assert_eq!(searcher.num_docs(), 3);
let fields_metadata = index.fields_metadata().unwrap();
let expected_fields = &[
FieldMetadata {
field_name: "empty".to_string(),
stored: true,
typ: Type::U64,
term_dictionary_size: Some(0u64.into()),
fast_size: Some(1u64.into()),
postings_size: Some(0u64.into()),
positions_size: Some(0u64.into()),
},
FieldMetadata {
field_name: if expanded_dots {
"json.shadow.k8s.container.name".to_string()
} else {
"json.shadow.k8s\\.container\\.name".to_string()
assert_eq!(
fields_metadata,
[
FieldMetadata {
field_name: "empty".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::U64
},
stored: true,
typ: Type::Str,
term_dictionary_size: Some(1u64.into()),
fast_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "json.shadow.sub.a".to_string(),
typ: Type::I64,
stored: true,
fast_size: Some(1u64.into()),
term_dictionary_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "json.shadow.sub.b".to_string(),
typ: Type::I64,
stored: true,
fast_size: Some(1u64.into()),
term_dictionary_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "json.shadow.suber.a".to_string(),
stored: true,
typ: Type::I64,
fast_size: Some(1u64.into()),
term_dictionary_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "json.shadow.suber.a".to_string(),
typ: Type::Str,
stored: true,
fast_size: Some(1u64.into()),
term_dictionary_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "json.shadow.suber.b".to_string(),
typ: Type::I64,
stored: true,
fast_size: Some(1u64.into()),
term_dictionary_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "json.shadow.val".to_string(),
typ: Type::Str,
stored: true,
fast_size: Some(1u64.into()),
term_dictionary_size: Some(1u64.into()),
postings_size: Some(1u64.into()),
positions_size: Some(1u64.into()),
},
FieldMetadata {
field_name: "numbers".to_string(),
stored: false,
typ: Type::U64,
fast_size: Some(1u64.into()),
term_dictionary_size: None,
postings_size: None,
positions_size: None,
},
];
assert_eq!(fields_metadata.len(), expected_fields.len());
for (expected, value) in expected_fields.iter().zip(fields_metadata.iter()) {
assert_field_metadata_eq_but_ignore_field_size(expected, value);
}
FieldMetadata {
field_name: if expanded_dots {
"json.shadow.k8s.container.name".to_string()
} else {
"json.shadow.k8s\\.container\\.name".to_string()
},
indexed: true,
stored: true,
fast: true,
typ: Type::Str
},
FieldMetadata {
field_name: "json.shadow.sub.a".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.sub.b".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.suber.a".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.suber.a".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::Str
},
FieldMetadata {
field_name: "json.shadow.suber.b".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.val".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::Str
},
FieldMetadata {
field_name: "numbers".to_string(),
indexed: false,
stored: false,
fast: true,
typ: Type::U64
}
]
);
let query_parser = QueryParser::for_index(&index, vec![]);
// Test if returned field name can be queried
for indexed_field in fields_metadata.iter().filter(|meta| meta.is_indexed()) {
for indexed_field in fields_metadata.iter().filter(|meta| meta.indexed) {
let val = if indexed_field.typ == Type::Str {
"a"
} else {
@@ -595,10 +543,7 @@ mod tests_mmap {
}
}
// Test if returned field name can be used for aggregation
for fast_field in fields_metadata
.iter()
.filter(|field_metadata| field_metadata.is_fast())
{
for fast_field in fields_metadata.iter().filter(|meta| meta.fast) {
let agg_req_str = json!(
{
"termagg": {

View File

@@ -165,7 +165,7 @@ mod macros;
mod future_result;
// Re-exports
pub use common::{ByteCount, DateTime};
pub use common::DateTime;
pub use {columnar, query_grammar, time};
pub use crate::error::TantivyError;

View File

@@ -40,9 +40,6 @@ const COMPRESSION_BLOCK_SIZE: usize = BitPacker4x::BLOCK_LEN;
#[cfg(test)]
pub(crate) mod tests {
use std::iter;
use proptest::prelude::*;
use proptest::sample::select;

View File

@@ -302,7 +302,6 @@ fn is_sorted<I: Iterator<Item = DocId>>(mut it: I) -> bool {
mod tests {
use std::cmp::Ordering;
use std::collections::BinaryHeap;
use std::iter;
use proptest::prelude::*;

View File

@@ -1790,15 +1790,6 @@ mod test {
}
}
#[test]
fn test_space_before_value() {
test_parse_query_to_logical_ast_helper(
"title: a",
r#"Term(field=0, type=Str, "a")"#,
false,
);
}
#[test]
fn test_escaped_field() {
let mut schema_builder = Schema::builder();

View File

@@ -41,7 +41,6 @@
//! use tantivy::schema::document::{DeserializeError, DocumentDeserialize, DocumentDeserializer};
//!
//! /// Our custom document to let us use a map of `serde_json::Values`.
//! #[allow(dead_code)]
//! pub struct MyCustomDocument {
//! // Tantivy provides trait implementations for common `serde_json` types.
//! fields: BTreeMap<Field, serde_json::Value>

View File

@@ -1561,8 +1561,6 @@ fn to_ascii(text: &str, output: &mut String) {
#[cfg(test)]
mod tests {
use std::iter;
use super::to_ascii;
use crate::tokenizer::{AsciiFoldingFilter, RawTokenizer, SimpleTokenizer, TextAnalyzer};

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-sstable"
version = "0.6.0"
version = "0.5.0"
edition = "2024"
license = "MIT"
homepage = "https://github.com/quickwit-oss/tantivy"
@@ -10,10 +10,10 @@ categories = ["database-implementations", "data-structures", "compression"]
description = "sstables for tantivy"
[dependencies]
common = {version= "0.10", path="../common", package="tantivy-common"}
common = {version= "0.9", path="../common", package="tantivy-common"}
futures-util = "0.3.30"
itertools = "0.14.0"
tantivy-bitpacker = { version= "0.9", path="../bitpacker" }
tantivy-bitpacker = { version= "0.8", path="../bitpacker" }
tantivy-fst = "0.5"
# experimental gives us access to Decompressor::upper_bound
zstd = { version = "0.13", optional = true, features = ["experimental"] }

View File

@@ -308,10 +308,9 @@ impl<TSSTable: SSTable> Dictionary<TSSTable> {
}
}
_ => {
return Err(io::Error::new(
io::ErrorKind::Other,
format!("Unsupported sstable version, expected one of [2, 3], found {version}"),
));
return Err(io::Error::other(format!(
"Unsupported sstable version, expected one of [2, 3], found {version}"
)));
}
};
@@ -697,10 +696,9 @@ mod tests {
fn read_bytes(&self, range: Range<usize>) -> std::io::Result<OwnedBytes> {
let allowed_range = self.allowed_range.lock().unwrap();
if !allowed_range.contains(&range.start) || !allowed_range.contains(&(range.end - 1)) {
return Err(std::io::Error::new(
std::io::ErrorKind::Other,
format!("invalid range, allowed {allowed_range:?}, requested {range:?}"),
));
return Err(std::io::Error::other(format!(
"invalid range, allowed {allowed_range:?}, requested {range:?}"
)));
}
Ok(self.bytes.slice(range))

View File

@@ -1,3 +1,5 @@
#![allow(clippy::manual_div_ceil)]
//! `tantivy_sstable` is a crate that provides a sorted string table data structure.
//!
//! It is used in `tantivy` to store the term dictionary.

View File

@@ -394,7 +394,7 @@ impl SSTableIndexBuilder {
fn fst_error_to_io_error(error: tantivy_fst::Error) -> io::Error {
match error {
tantivy_fst::Error::Fst(fst_error) => io::Error::new(io::ErrorKind::Other, fst_error),
tantivy_fst::Error::Fst(fst_error) => io::Error::other(fst_error),
tantivy_fst::Error::Io(ioerror) => ioerror,
}
}

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-stacker"
version = "0.6.0"
version = "0.5.0"
edition = "2024"
license = "MIT"
homepage = "https://github.com/quickwit-oss/tantivy"
@@ -9,7 +9,7 @@ description = "term hashmap used for indexing"
[dependencies]
murmurhash32 = "0.3"
common = { version = "0.10", path = "../common/", package = "tantivy-common" }
common = { version = "0.9", path = "../common/", package = "tantivy-common" }
ahash = { version = "0.8.11", default-features = false, optional = true }
rand_distr = "0.4.3"

View File

@@ -10,8 +10,7 @@ pub fn fast_short_slice_copy(src: &[u8], dst: &mut [u8]) {
#[track_caller]
fn len_mismatch_fail(dst_len: usize, src_len: usize) -> ! {
panic!(
"source slice length ({}) does not match destination slice length ({})",
src_len, dst_len,
"source slice length ({src_len}) does not match destination slice length ({dst_len})",
);
}

View File

@@ -1,5 +1,3 @@
#![cfg_attr(all(feature = "unstable", test), feature(test))]
#[cfg(all(test, feature = "unstable"))]
extern crate test;

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-tokenizer-api"
version = "0.6.0"
version = "0.5.0"
license = "MIT"
edition = "2021"
description = "Tokenizer API of tantivy"