mirror of
https://github.com/quickwit-oss/tantivy.git
synced 2025-12-23 02:29:57 +00:00
move bench to binggan (#2684)
This commit is contained in:
@@ -33,6 +33,29 @@ 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"]
|
||||
|
||||
@@ -19,7 +19,7 @@ fn main() {
|
||||
|
||||
let mut add_card = |card1: Card| {
|
||||
inputs.push((
|
||||
format!("{card1}"),
|
||||
card1.to_string(),
|
||||
generate_columnar_and_open(card1, NUM_DOCS),
|
||||
));
|
||||
};
|
||||
@@ -50,6 +50,7 @@ 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;
|
||||
}
|
||||
|
||||
61
columnar/benches/bench_column_values_get.rs
Normal file
61
columnar/benches/bench_column_values_get.rs
Normal file
@@ -0,0 +1,61 @@
|
||||
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();
|
||||
}
|
||||
44
columnar/benches/bench_create_column_values.rs
Normal file
44
columnar/benches/bench_create_column_values.rs
Normal file
@@ -0,0 +1,44 @@
|
||||
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();
|
||||
}
|
||||
@@ -1,12 +1,9 @@
|
||||
#![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,
|
||||
@@ -68,88 +65,45 @@ pub fn serialize_and_load(column: &[u64], codec_type: CodecType) -> Arc<dyn Colu
|
||||
serialize_and_load_u64_based_column_values(&column, &[codec_type])
|
||||
}
|
||||
|
||||
fn run_bench_on_column_full_scan(b: &mut Bencher, column: Column) {
|
||||
let num_iter = black_box(NUM_VALUES);
|
||||
b.iter(|| {
|
||||
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| {
|
||||
let mut sum = 0u64;
|
||||
for i in 0..num_iter as u32 {
|
||||
for i in 0..NUM_VALUES as u32 {
|
||||
let val = column.first(i);
|
||||
sum += val.unwrap_or(0);
|
||||
}
|
||||
sum
|
||||
black_box(sum);
|
||||
});
|
||||
}
|
||||
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 || {
|
||||
|
||||
group.register("first_block_fetch", |column| {
|
||||
let mut block: Vec<Option<u64>> = vec![None; 64];
|
||||
let fetch_docids = (0..64).collect::<Vec<_>>();
|
||||
column.first_vals(&fetch_docids, &mut block);
|
||||
block[0]
|
||||
black_box(block[0]);
|
||||
});
|
||||
}
|
||||
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 || {
|
||||
|
||||
group.register("first_block_single_calls", |column| {
|
||||
let mut block: Vec<Option<u64>> = vec![None; 64];
|
||||
let fetch_docids = (0..64).collect::<Vec<_>>();
|
||||
for i in 0..fetch_docids.len() {
|
||||
block[i] = column.first(fetch_docids[i]);
|
||||
}
|
||||
block[0]
|
||||
black_box(block[0]);
|
||||
});
|
||||
}
|
||||
|
||||
/// 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);
|
||||
group.run();
|
||||
}
|
||||
|
||||
106
columnar/benches/bench_optional_index.rs
Normal file
106
columnar/benches/bench_optional_index.rs
Normal file
@@ -0,0 +1,106 @@
|
||||
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();
|
||||
}
|
||||
@@ -1,15 +1,12 @@
|
||||
#![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> {
|
||||
@@ -47,78 +44,77 @@ fn get_data_50percent_item() -> Vec<u128> {
|
||||
}
|
||||
data.push(SINGLE_ITEM);
|
||||
data.shuffle(&mut rng);
|
||||
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
|
||||
data
|
||||
data.iter().map(|el| *el as u128).collect::<Vec<_>>()
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
|
||||
fn main() {
|
||||
let data = get_data_50percent_item();
|
||||
let column = get_u128_column_from_data(&data);
|
||||
let column_range = get_u128_column_from_data(&data);
|
||||
let column_random = get_u128_column_random();
|
||||
|
||||
b.iter(|| {
|
||||
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| {
|
||||
let mut positions = Vec::new();
|
||||
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(
|
||||
inp.column_range.get_row_ids_for_value_range(
|
||||
*SINGLE_ITEM_RANGE.start() as u128..=*SINGLE_ITEM_RANGE.end() as u128,
|
||||
0..data.len() as u32,
|
||||
0..inp.data.len() as u32,
|
||||
&mut positions,
|
||||
);
|
||||
positions
|
||||
black_box(positions.len());
|
||||
});
|
||||
}
|
||||
|
||||
#[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(|| {
|
||||
group.register("intfastfield_getrange_u128_hit_all", |inp: &Inputs| {
|
||||
let mut positions = Vec::new();
|
||||
column.get_row_ids_for_value_range(0..=u128::MAX, 0..data.len() as u32, &mut positions);
|
||||
positions
|
||||
inp.column_range.get_row_ids_for_value_range(
|
||||
0..=u128::MAX,
|
||||
0..inp.data.len() as u32,
|
||||
&mut positions,
|
||||
);
|
||||
black_box(positions.len());
|
||||
});
|
||||
}
|
||||
// U128 RANGE END
|
||||
|
||||
#[bench]
|
||||
fn bench_intfastfield_scan_all_fflookup_u128(b: &mut Bencher) {
|
||||
let column = get_u128_column_random();
|
||||
|
||||
b.iter(|| {
|
||||
group.register("intfastfield_scan_all_fflookup_u128", |inp: &Inputs| {
|
||||
let mut a = 0u128;
|
||||
for i in 0u64..column.num_vals() as u64 {
|
||||
a += column.get_val(i as u32);
|
||||
for i in 0u64..inp.column_random.num_vals() as u64 {
|
||||
a += inp.column_random.get_val(i as u32);
|
||||
}
|
||||
a
|
||||
black_box(a);
|
||||
});
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_intfastfield_jumpy_stride5_u128(b: &mut Bencher) {
|
||||
let column = get_u128_column_random();
|
||||
|
||||
b.iter(|| {
|
||||
let n = column.num_vals();
|
||||
group.register("intfastfield_jumpy_stride5_u128", |inp: &Inputs| {
|
||||
let n = inp.column_random.num_vals();
|
||||
let mut a = 0u128;
|
||||
for i in (0..n / 5).map(|val| val * 5) {
|
||||
a += column.get_val(i);
|
||||
a += inp.column_random.get_val(i);
|
||||
}
|
||||
a
|
||||
black_box(a);
|
||||
});
|
||||
|
||||
group.run();
|
||||
}
|
||||
|
||||
@@ -1,13 +1,10 @@
|
||||
#![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> {
|
||||
@@ -27,37 +24,11 @@ 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]);
|
||||
|
||||
@@ -69,135 +40,122 @@ fn get_data_50percent_item() -> Vec<u128> {
|
||||
data.push(SINGLE_ITEM);
|
||||
|
||||
data.shuffle(&mut rng);
|
||||
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
|
||||
data
|
||||
data.iter().map(|el| *el as u128).collect::<Vec<_>>()
|
||||
}
|
||||
|
||||
// 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
|
||||
});
|
||||
}
|
||||
type VecCol = (Vec<u64>, Arc<dyn ColumnValues<u64>>);
|
||||
|
||||
#[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) {
|
||||
fn bench_access() {
|
||||
let permutation = generate_permutation();
|
||||
let n = permutation.len();
|
||||
b.iter(|| {
|
||||
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 mut a = 0u64;
|
||||
for i in (0..n / 7).map(|val| val * 7) {
|
||||
a += permutation[i as usize];
|
||||
a += inp.0[i];
|
||||
}
|
||||
a
|
||||
black_box(a);
|
||||
});
|
||||
}
|
||||
|
||||
#[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;
|
||||
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;
|
||||
for i in (0..n / 7).map(|val| val * 7) {
|
||||
a += column.get_val(i as u32);
|
||||
a += inp.1.get_val(i as u32);
|
||||
}
|
||||
a
|
||||
black_box(a);
|
||||
});
|
||||
}
|
||||
|
||||
#[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(|| {
|
||||
group.register("fullscan_column_values", |inp: &VecCol| {
|
||||
let mut a = 0u64;
|
||||
let n = inp.1.num_vals() as usize;
|
||||
for i in 0..n {
|
||||
a += column.get_val(i as u32);
|
||||
a += inp.1.get_val(i as u32);
|
||||
}
|
||||
a
|
||||
black_box(a);
|
||||
});
|
||||
|
||||
group.run();
|
||||
}
|
||||
|
||||
#[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
|
||||
});
|
||||
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();
|
||||
}
|
||||
|
||||
@@ -219,170 +219,3 @@ 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);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,139 +0,0 @@
|
||||
use std::sync::Arc;
|
||||
|
||||
use common::OwnedBytes;
|
||||
use rand::rngs::StdRng;
|
||||
use rand::{Rng, SeedableRng};
|
||||
use test::{self, Bencher};
|
||||
|
||||
use super::*;
|
||||
use crate::column_values::u64_based::*;
|
||||
|
||||
fn get_data() -> Vec<u64> {
|
||||
let mut rng = StdRng::seed_from_u64(2u64);
|
||||
let mut data: Vec<_> = (100..55000_u64)
|
||||
.map(|num| num + rng.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);
|
||||
}
|
||||
@@ -242,6 +242,3 @@ 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;
|
||||
|
||||
@@ -17,15 +17,10 @@
|
||||
//! 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;
|
||||
|
||||
|
||||
Reference in New Issue
Block a user