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Author SHA1 Message Date
Paul Masurel
4a072e3c18 Introducing a column trait 2022-09-02 11:24:04 +09:00
125 changed files with 3128 additions and 4952 deletions

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@@ -95,7 +95,7 @@ called [`Directory`](src/directory/directory.rs).
Contrary to Lucene however, "files" are quite different from some kind of `io::Read` object.
Check out [`src/directory/directory.rs`](src/directory/directory.rs) trait for more details.
Tantivy ships two main directory implementation: the `MmapDirectory` and the `RamDirectory`,
Tantivy ships two main directory implementation: the `MMapDirectory` and the `RAMDirectory`,
but users can extend tantivy with their own implementation.
## [schema/](src/schema): What are documents?

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@@ -30,7 +30,7 @@ log = "0.4.16"
serde = { version = "1.0.136", features = ["derive"] }
serde_json = "1.0.79"
num_cpus = "1.13.1"
fs2 = { version = "0.4.3", optional = true }
fs2={ version = "0.4.3", optional = true }
levenshtein_automata = "0.2.1"
uuid = { version = "1.0.0", features = ["v4", "serde"] }
crossbeam-channel = "0.5.4"
@@ -56,6 +56,7 @@ lru = "0.7.5"
fastdivide = "0.4.0"
itertools = "0.10.3"
measure_time = "0.8.2"
pretty_assertions = "1.2.1"
serde_cbor = { version = "0.11.2", optional = true }
async-trait = "0.1.53"
arc-swap = "1.5.0"
@@ -67,7 +68,6 @@ winapi = "0.3.9"
rand = "0.8.5"
maplit = "1.0.2"
matches = "0.1.9"
pretty_assertions = "1.2.1"
proptest = "1.0.0"
criterion = "0.3.5"
test-log = "0.2.10"

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@@ -127,7 +127,6 @@ $ gdb run
# Companies Using Tantivy
<p align="left">
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />&nbsp;
<img align="center" src="doc/assets/images/Nuclia.png#gh-light-mode-only" alt="Nuclia" height="25" width="auto" /> &nbsp;
<img align="center" src="doc/assets/images/humanfirst.png#gh-light-mode-only" alt="Humanfirst.ai" height="30" width="auto" />
<img align="center" src="doc/assets/images/element.io.svg#gh-light-mode-only" alt="Element.io" height="25" width="auto" />

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@@ -259,7 +259,11 @@ impl BitSet {
// we do not check saturated els.
let higher = el / 64u32;
let lower = el % 64u32;
self.len += u64::from(self.tinysets[higher as usize].insert_mut(lower));
self.len += if self.tinysets[higher as usize].insert_mut(lower) {
1
} else {
0
};
}
/// Inserts an element in the `BitSet`
@@ -268,7 +272,11 @@ impl BitSet {
// we do not check saturated els.
let higher = el / 64u32;
let lower = el % 64u32;
self.len -= u64::from(self.tinysets[higher as usize].remove_mut(lower));
self.len -= if self.tinysets[higher as usize].remove_mut(lower) {
1
} else {
0
};
}
/// Returns true iff the elements is in the `BitSet`.

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@@ -11,10 +11,7 @@ mod writer;
pub use bitset::*;
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
pub use vint::{
deserialize_vint_u128, read_u32_vint, read_u32_vint_no_advance, serialize_vint_u128,
serialize_vint_u32, write_u32_vint, VInt, VIntU128,
};
pub use vint::{read_u32_vint, read_u32_vint_no_advance, serialize_vint_u32, write_u32_vint, VInt};
pub use writer::{AntiCallToken, CountingWriter, TerminatingWrite};
/// Has length trait
@@ -55,13 +52,13 @@ const HIGHEST_BIT: u64 = 1 << 63;
/// to values over 2^63, and all values end up requiring 64 bits.
///
/// # See also
/// The reverse mapping is [`u64_to_i64()`].
/// The [reverse mapping is `u64_to_i64`](./fn.u64_to_i64.html).
#[inline]
pub fn i64_to_u64(val: i64) -> u64 {
(val as u64) ^ HIGHEST_BIT
}
/// Reverse the mapping given by [`i64_to_u64()`].
/// Reverse the mapping given by [`i64_to_u64`](./fn.i64_to_u64.html).
#[inline]
pub fn u64_to_i64(val: u64) -> i64 {
(val ^ HIGHEST_BIT) as i64
@@ -83,7 +80,7 @@ pub fn u64_to_i64(val: u64) -> i64 {
/// explains the mapping in a clear manner.
///
/// # See also
/// The reverse mapping is [`u64_to_f64()`].
/// The [reverse mapping is `u64_to_f64`](./fn.u64_to_f64.html).
#[inline]
pub fn f64_to_u64(val: f64) -> u64 {
let bits = val.to_bits();
@@ -94,7 +91,7 @@ pub fn f64_to_u64(val: f64) -> u64 {
}
}
/// Reverse the mapping given by [`f64_to_u64()`].
/// Reverse the mapping given by [`i64_to_u64`](./fn.i64_to_u64.html).
#[inline]
pub fn u64_to_f64(val: u64) -> f64 {
f64::from_bits(if val & HIGHEST_BIT != 0 {

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@@ -161,7 +161,8 @@ impl FixedSize for u8 {
impl BinarySerializable for bool {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
writer.write_u8(u8::from(*self))
let val = if *self { 1 } else { 0 };
writer.write_u8(val)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<bool> {
let val = reader.read_u8()?;

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@@ -5,75 +5,6 @@ use byteorder::{ByteOrder, LittleEndian};
use super::BinarySerializable;
/// Variable int serializes a u128 number
pub fn serialize_vint_u128(mut val: u128, output: &mut Vec<u8>) {
loop {
let next_byte: u8 = (val % 128u128) as u8;
val /= 128u128;
if val == 0 {
output.push(next_byte | STOP_BIT);
return;
} else {
output.push(next_byte);
}
}
}
/// Deserializes a u128 number
///
/// Returns the number and the slice after the vint
pub fn deserialize_vint_u128(data: &[u8]) -> io::Result<(u128, &[u8])> {
let mut result = 0u128;
let mut shift = 0u64;
for i in 0..19 {
let b = data[i];
result |= u128::from(b % 128u8) << shift;
if b >= STOP_BIT {
return Ok((result, &data[i + 1..]));
}
shift += 7;
}
Err(io::Error::new(
io::ErrorKind::InvalidData,
"Failed to deserialize u128 vint",
))
}
/// Wrapper over a `u128` that serializes as a variable int.
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
pub struct VIntU128(pub u128);
impl BinarySerializable for VIntU128 {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
let mut buffer = vec![];
serialize_vint_u128(self.0, &mut buffer);
writer.write_all(&buffer)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Self> {
let mut bytes = reader.bytes();
let mut result = 0u128;
let mut shift = 0u64;
loop {
match bytes.next() {
Some(Ok(b)) => {
result |= u128::from(b % 128u8) << shift;
if b >= STOP_BIT {
return Ok(VIntU128(result));
}
shift += 7;
}
_ => {
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"Reach end of buffer while reading VInt",
));
}
}
}
}
}
/// Wrapper over a `u64` that serializes as a variable int.
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
pub struct VInt(pub u64);
@@ -245,7 +176,6 @@ impl BinarySerializable for VInt {
mod tests {
use super::{serialize_vint_u32, BinarySerializable, VInt};
use crate::vint::{deserialize_vint_u128, serialize_vint_u128, VIntU128};
fn aux_test_vint(val: u64) {
let mut v = [14u8; 10];
@@ -287,26 +217,6 @@ mod tests {
assert_eq!(&buffer[..len_vint], res2, "array wrong for {}", val);
}
fn aux_test_vint_u128(val: u128) {
let mut data = vec![];
serialize_vint_u128(val, &mut data);
let (deser_val, _data) = deserialize_vint_u128(&data).unwrap();
assert_eq!(val, deser_val);
let mut out = vec![];
VIntU128(val).serialize(&mut out).unwrap();
let deser_val = VIntU128::deserialize(&mut &out[..]).unwrap();
assert_eq!(val, deser_val.0);
}
#[test]
fn test_vint_u128() {
aux_test_vint_u128(0);
aux_test_vint_u128(1);
aux_test_vint_u128(u128::MAX / 3);
aux_test_vint_u128(u128::MAX);
}
#[test]
fn test_vint_u32() {
aux_test_serialize_vint_u32(0);

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@@ -55,7 +55,7 @@ impl<W: TerminatingWrite> TerminatingWrite for CountingWriter<W> {
}
/// Struct used to prevent from calling
/// [`terminate_ref`](TerminatingWrite::terminate_ref) directly
/// [`terminate_ref`](trait.TerminatingWrite.html#tymethod.terminate_ref) directly
///
/// The point is that while the type is public, it cannot be built by anyone
/// outside of this module.

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@@ -7,12 +7,11 @@
// Of course, you can have a look at the tantivy's built-in collectors
// such as the `CountCollector` for more examples.
use std::sync::Arc;
use fastfield_codecs::Column;
// ---
// Importing tantivy...
use tantivy::collector::{Collector, SegmentCollector};
use tantivy::fastfield::DynamicFastFieldReader;
use tantivy::query::QueryParser;
use tantivy::schema::{Field, Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index, Score, SegmentReader};
@@ -97,7 +96,7 @@ impl Collector for StatsCollector {
}
struct StatsSegmentCollector {
fast_field_reader: Arc<dyn Column<u64>>,
fast_field_reader: DynamicFastFieldReader<u64>,
stats: Stats,
}

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@@ -36,7 +36,8 @@ fn main() -> tantivy::Result<()> {
// need to be able to be able to retrieve it
// for our application.
//
// We can make our index lighter by omitting the `STORED` flag.
// We can make our index lighter and
// by omitting `STORED` flag.
let body = schema_builder.add_text_field("body", TEXT);
let schema = schema_builder.build();

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@@ -2,6 +2,7 @@ use std::cmp::Reverse;
use std::collections::{HashMap, HashSet};
use std::sync::{Arc, RwLock, Weak};
use fastfield_codecs::Column;
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{Field, Schema, FAST, TEXT};

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@@ -14,10 +14,6 @@ tantivy-bitpacker = { version="0.2", path = "../bitpacker/" }
ownedbytes = { version = "0.3.0", path = "../ownedbytes" }
prettytable-rs = {version="0.9.0", optional= true}
rand = {version="0.8.3", optional= true}
fastdivide = "0.4"
log = "0.4"
itertools = { version = "0.10.3" }
measure_time = { version="0.8.2" }
[dev-dependencies]
more-asserts = "0.3.0"
@@ -27,5 +23,4 @@ rand = "0.8.3"
[features]
bin = ["prettytable-rs", "rand"]
default = ["bin"]
unstable = []

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@@ -4,222 +4,88 @@ extern crate test;
#[cfg(test)]
mod tests {
use std::iter;
use std::sync::Arc;
use fastfield_codecs::bitpacked::BitpackedCodec;
use fastfield_codecs::blockwise_linear::BlockwiseLinearCodec;
use fastfield_codecs::linear::LinearCodec;
use fastfield_codecs::*;
use ownedbytes::OwnedBytes;
use rand::prelude::*;
use test::Bencher;
use super::*;
// Warning: this generates the same permutation at each call
fn generate_permutation() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64).collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
fn generate_random() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64)
.map(|el| el + random::<u16>() as u64)
fn get_data() -> Vec<u64> {
let mut data: Vec<_> = (100..55000_u64)
.map(|num| num + rand::random::<u8>() as u64)
.collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
// Warning: this generates the same permutation at each call
fn generate_permutation_gcd() -> Vec<u64> {
let mut permutation: Vec<u64> = (1u64..100_000u64).map(|el| el * 1000).collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
pub fn serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default>(
column: &[T],
) -> Arc<dyn Column<T>> {
let mut buffer = Vec::new();
serialize(VecColumn::from(&column), &mut buffer, &ALL_CODEC_TYPES).unwrap();
open(OwnedBytes::new(buffer)).unwrap()
}
#[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(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = column.get_val(a as u64);
}
a
});
}
fn get_exp_data() -> Vec<u64> {
let mut data = vec![];
for i in 0..100 {
let num = i * i;
data.extend(iter::repeat(i as u64).take(num));
}
data.shuffle(&mut StdRng::from_seed([1u8; 32]));
// lengt = 328350
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 get_data_50percent_item() -> (u128, u128, Vec<u128>) {
let mut permutation = get_exp_data();
let major_item = 20;
let minor_item = 10;
permutation.extend(iter::repeat(major_item).take(permutation.len()));
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
let permutation = permutation.iter().map(|el| *el as u128).collect::<Vec<_>>();
(major_item as u128, minor_item as u128, permutation)
fn value_iter() -> impl Iterator<Item = u64> {
0..20_000
}
fn get_u128_column_random() -> Arc<dyn Column<u128>> {
let permutation = generate_random();
let permutation = permutation.iter().map(|el| *el as u128).collect::<Vec<_>>();
get_u128_column_from_data(&permutation)
}
fn get_u128_column_from_data(data: &[u128]) -> Arc<dyn Column<u128>> {
let mut out = vec![];
serialize_u128(VecColumn::from(&data), &mut out).unwrap();
let out = OwnedBytes::new(out);
open_u128(out).unwrap()
}
#[bench]
fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
let (major_item, _minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| column.get_between_vals(major_item..=major_item));
}
#[bench]
fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
let (_major_item, minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| column.get_between_vals(minor_item..=minor_item));
}
#[bench]
fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
let (_major_item, _minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| column.get_between_vals(0..=u128::MAX));
}
#[bench]
fn bench_intfastfield_scan_all_fflookup_u128(b: &mut Bencher) {
let column = get_u128_column_random();
fn bench_get<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let mut bytes = vec![];
Codec::serialize(&mut bytes, &data).unwrap();
let reader = Codec::open_from_bytes(OwnedBytes::new(bytes)).unwrap();
b.iter(|| {
let mut a = 0u128;
for i in 0u64..column.num_vals() as u64 {
a += column.get_val(i);
let mut sum = 0u64;
for pos in value_iter() {
let val = reader.get_val(pos as u64);
debug_assert_eq!(data[pos as usize], val);
sum = sum.wrapping_add(val);
}
a
sum
});
}
fn bench_create<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let mut bytes = Vec::new();
b.iter(|| {
bytes.clear();
Codec::serialize(&mut bytes, &data).unwrap();
});
}
use ownedbytes::OwnedBytes;
use test::Bencher;
#[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 += column.get_val(i as u64);
}
a
});
fn bench_fastfield_bitpack_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_intfastfield_stride7_vec(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
b.iter(|| {
let mut a = 0u64;
for i in (0..n / 7).map(|val| val * 7) {
a += permutation[i as usize];
}
a
});
fn bench_fastfield_linearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<LinearCodec>(b, &data);
}
#[bench]
fn bench_intfastfield_stride7_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for i in (0..n / 7).map(|val| val * 7) {
a += column.get_val(i as u64);
}
a
});
fn bench_fastfield_multilinearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BlockwiseLinearCodec>(b, &data);
}
#[bench]
fn bench_intfastfield_scan_all_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for i in 0u64..n as u64 {
a += column.get_val(i);
}
a
});
fn bench_fastfield_bitpack_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_intfastfield_scan_all_fflookup_gcd(b: &mut Bencher) {
let permutation = generate_permutation_gcd();
let n = permutation.len();
let column: Arc<dyn Column<u64>> = serialize_and_load(&permutation);
b.iter(|| {
let mut a = 0u64;
for i in 0..n as u64 {
a += column.get_val(i);
}
a
});
fn bench_fastfield_linearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<LinearCodec>(b, &data);
}
#[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_fastfield_multilinearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BlockwiseLinearCodec>(b, &data);
}
pub fn stats_from_vec(data: &[u64]) -> FastFieldStats {
let min_value = data.iter().cloned().min().unwrap_or(0);
let max_value = data.iter().cloned().max().unwrap_or(0);
FastFieldStats {
min_value,
max_value,
num_vals: data.len() as u64,
}
}
}

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@@ -1,9 +1,9 @@
use std::io::{self, Write};
use common::BinarySerializable;
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType};
/// Depending on the field type, a different
@@ -12,26 +12,80 @@ use crate::{Column, FastFieldCodec, FastFieldCodecType};
pub struct BitpackedReader {
data: OwnedBytes,
bit_unpacker: BitUnpacker,
normalized_header: NormalizedHeader,
min_value_u64: u64,
max_value_u64: u64,
num_vals: u64,
}
impl Column for BitpackedReader {
#[inline]
fn get_val(&self, doc: u64) -> u64 {
self.bit_unpacker.get(doc, &self.data)
self.min_value_u64 + self.bit_unpacker.get(doc, &self.data)
}
#[inline]
fn min_value(&self) -> u64 {
// The BitpackedReader assumes a normalized vector.
0
self.min_value_u64
}
#[inline]
fn max_value(&self) -> u64 {
self.normalized_header.max_value
self.max_value_u64
}
#[inline]
fn num_vals(&self) -> u64 {
self.normalized_header.num_vals
self.num_vals
}
}
pub struct BitpackedSerializerLegacy<'a, W: 'a + Write> {
bit_packer: BitPacker,
write: &'a mut W,
min_value: u64,
num_vals: u64,
amplitude: u64,
num_bits: u8,
}
impl<'a, W: Write> BitpackedSerializerLegacy<'a, W> {
/// Creates a new fast field serializer.
///
/// The serializer in fact encode the values by bitpacking
/// `(val - min_value)`.
///
/// It requires a `min_value` and a `max_value` to compute
/// compute the minimum number of bits required to encode
/// values.
pub fn open(
write: &'a mut W,
min_value: u64,
max_value: u64,
) -> io::Result<BitpackedSerializerLegacy<'a, W>> {
assert!(min_value <= max_value);
let amplitude = max_value - min_value;
let num_bits = compute_num_bits(amplitude);
let bit_packer = BitPacker::new();
Ok(BitpackedSerializerLegacy {
bit_packer,
write,
min_value,
num_vals: 0,
amplitude,
num_bits,
})
}
/// Pushes a new value to the currently open u64 fast field.
#[inline]
pub fn add_val(&mut self, val: u64) -> io::Result<()> {
let val_to_write: u64 = val - self.min_value;
self.bit_packer
.write(val_to_write, self.num_bits, &mut self.write)?;
self.num_vals += 1;
Ok(())
}
pub fn close_field(mut self) -> io::Result<()> {
self.bit_packer.close(&mut self.write)?;
self.min_value.serialize(&mut self.write)?;
self.amplitude.serialize(&mut self.write)?;
self.num_vals.serialize(&mut self.write)?;
Ok(())
}
}
@@ -44,39 +98,50 @@ impl FastFieldCodec for BitpackedCodec {
type Reader = BitpackedReader;
/// Opens a fast field given a file.
fn open_from_bytes(
data: OwnedBytes,
normalized_header: NormalizedHeader,
) -> io::Result<Self::Reader> {
let num_bits = compute_num_bits(normalized_header.max_value);
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self::Reader> {
let footer_offset = bytes.len() - 24;
let (data, mut footer) = bytes.split(footer_offset);
let min_value = u64::deserialize(&mut footer)?;
let amplitude = u64::deserialize(&mut footer)?;
let num_vals = u64::deserialize(&mut footer)?;
let max_value = min_value + amplitude;
let num_bits = compute_num_bits(amplitude);
let bit_unpacker = BitUnpacker::new(num_bits);
Ok(BitpackedReader {
data,
bit_unpacker,
normalized_header,
min_value_u64: min_value,
max_value_u64: max_value,
num_vals,
})
}
/// Serializes data with the BitpackedFastFieldSerializer.
///
/// The bitpacker assumes that the column has been normalized.
/// i.e. It has already been shifted by its minimum value, so that its
/// current minimum value is 0.
/// The serializer in fact encode the values by bitpacking
/// `(val - min_value)`.
///
/// Ideally, we made a shift upstream on the column so that `col.min_value() == 0`.
fn serialize(column: &dyn Column, write: &mut impl Write) -> io::Result<()> {
assert_eq!(column.min_value(), 0u64);
let num_bits = compute_num_bits(column.max_value());
let mut bit_packer = BitPacker::new();
for val in column.iter() {
bit_packer.write(val, num_bits, write)?;
/// It requires a `min_value` and a `max_value` to compute
/// compute the minimum number of bits required to encode
/// values.
fn serialize(write: &mut impl Write, fastfield_accessor: &dyn Column) -> io::Result<()> {
let mut serializer = BitpackedSerializerLegacy::open(
write,
fastfield_accessor.min_value(),
fastfield_accessor.max_value(),
)?;
for val in fastfield_accessor.iter() {
serializer.add_val(val)?;
}
bit_packer.close(write)?;
serializer.close_field()?;
Ok(())
}
fn estimate(column: &dyn Column) -> Option<f32> {
let num_bits = compute_num_bits(column.max_value());
fn estimate(fastfield_accessor: &impl Column) -> Option<f32> {
let amplitude = fastfield_accessor.max_value() - fastfield_accessor.min_value();
let num_bits = compute_num_bits(amplitude);
let num_bits_uncompressed = 64;
Some(num_bits as f32 / num_bits_uncompressed as f32)
}

View File

@@ -1,186 +1,436 @@
use std::sync::Arc;
use std::{io, iter};
//! The BlockwiseLinear codec uses linear interpolation to guess a values and stores the
//! offset, but in blocks of 512.
//!
//! With a CHUNK_SIZE of 512 and 29 byte metadata per block, we get a overhead for metadata of 232 /
//! 512 = 0,45 bits per element. The additional space required per element in a block is the the
//! maximum deviation of the linear interpolation estimation function.
//!
//! E.g. if the maximum deviation of an element is 12, all elements cost 4bits.
//!
//! Size per block:
//! Num Elements * Maximum Deviation from Interpolation + 29 Byte Metadata
use std::io::{self, Read, Write};
use std::ops::Sub;
use common::{BinarySerializable, CountingWriter, DeserializeFrom};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::line::Line;
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType, VecColumn};
use crate::linear::{get_calculated_value, get_slope};
use crate::{Column, FastFieldCodec, FastFieldCodecType};
const CHUNK_SIZE: usize = 512;
#[derive(Debug, Default)]
struct Block {
line: Line,
bit_unpacker: BitUnpacker,
data_start_offset: usize,
}
impl BinarySerializable for Block {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
self.line.serialize(writer)?;
self.bit_unpacker.bit_width().serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let line = Line::deserialize(reader)?;
let bit_width = u8::deserialize(reader)?;
Ok(Block {
line,
bit_unpacker: BitUnpacker::new(bit_width),
data_start_offset: 0,
})
}
}
fn compute_num_blocks(num_vals: u64) -> usize {
(num_vals as usize + CHUNK_SIZE - 1) / CHUNK_SIZE
}
pub struct BlockwiseLinearCodec;
impl FastFieldCodec for BlockwiseLinearCodec {
const CODEC_TYPE: crate::FastFieldCodecType = FastFieldCodecType::BlockwiseLinear;
type Reader = BlockwiseLinearReader;
fn open_from_bytes(
bytes: ownedbytes::OwnedBytes,
normalized_header: NormalizedHeader,
) -> io::Result<Self::Reader> {
let footer_len: u32 = (&bytes[bytes.len() - 4..]).deserialize()?;
let footer_offset = bytes.len() - 4 - footer_len as usize;
let (data, mut footer) = bytes.split(footer_offset);
let num_blocks = compute_num_blocks(normalized_header.num_vals);
let mut blocks: Vec<Block> = iter::repeat_with(|| Block::deserialize(&mut footer))
.take(num_blocks)
.collect::<io::Result<_>>()?;
let mut start_offset = 0;
for block in &mut blocks {
block.data_start_offset = start_offset;
start_offset += (block.bit_unpacker.bit_width() as usize) * CHUNK_SIZE / 8;
}
Ok(BlockwiseLinearReader {
blocks: Arc::new(blocks),
data,
normalized_header,
})
}
// Estimate first_chunk and extrapolate
fn estimate(column: &dyn crate::Column) -> Option<f32> {
if column.num_vals() < 10 * CHUNK_SIZE as u64 {
return None;
}
let mut first_chunk: Vec<u64> = column.iter().take(CHUNK_SIZE as usize).collect();
let line = Line::train(&VecColumn::from(&first_chunk));
for (i, buffer_val) in first_chunk.iter_mut().enumerate() {
let interpolated_val = line.eval(i as u64);
*buffer_val = buffer_val.wrapping_sub(interpolated_val);
}
let estimated_bit_width = first_chunk
.iter()
.map(|el| ((el + 1) as f32 * 3.0) as u64)
.map(compute_num_bits)
.max()
.unwrap();
let metadata_per_block = {
let mut out = vec![];
Block::default().serialize(&mut out).unwrap();
out.len()
};
let num_bits = estimated_bit_width as u64 * column.num_vals() as u64
// function metadata per block
+ metadata_per_block as u64 * (column.num_vals() / CHUNK_SIZE as u64);
let num_bits_uncompressed = 64 * column.num_vals();
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
fn serialize(column: &dyn Column, wrt: &mut impl io::Write) -> io::Result<()> {
// The BitpackedReader assumes a normalized vector.
assert_eq!(column.min_value(), 0);
let mut buffer = Vec::with_capacity(CHUNK_SIZE);
let num_vals = column.num_vals();
let num_blocks = compute_num_blocks(num_vals);
let mut blocks = Vec::with_capacity(num_blocks);
let mut vals = column.iter();
let mut bit_packer = BitPacker::new();
for _ in 0..num_blocks {
buffer.clear();
buffer.extend((&mut vals).take(CHUNK_SIZE));
let line = Line::train(&VecColumn::from(&buffer));
assert!(!buffer.is_empty());
for (i, buffer_val) in buffer.iter_mut().enumerate() {
let interpolated_val = line.eval(i as u64);
*buffer_val = buffer_val.wrapping_sub(interpolated_val);
}
let bit_width = buffer.iter().copied().map(compute_num_bits).max().unwrap();
for &buffer_val in &buffer {
bit_packer.write(buffer_val, bit_width, wrt)?;
}
blocks.push(Block {
line,
bit_unpacker: BitUnpacker::new(bit_width),
data_start_offset: 0,
});
}
bit_packer.close(wrt)?;
assert_eq!(blocks.len(), compute_num_blocks(num_vals));
let mut counting_wrt = CountingWriter::wrap(wrt);
for block in &blocks {
block.serialize(&mut counting_wrt)?;
}
let footer_len = counting_wrt.written_bytes();
(footer_len as u32).serialize(&mut counting_wrt)?;
Ok(())
}
}
const CHUNK_SIZE: u64 = 512;
/// Depending on the field type, a different
/// fast field is required.
#[derive(Clone)]
pub struct BlockwiseLinearReader {
blocks: Arc<Vec<Block>>,
normalized_header: NormalizedHeader,
data: OwnedBytes,
pub footer: BlockwiseLinearFooter,
}
#[derive(Clone, Debug, Default)]
struct Function {
// The offset in the data is required, because we have different bit_widths per block
data_start_offset: u64,
// start_pos in the block will be CHUNK_SIZE * BLOCK_NUM
start_pos: u64,
// only used during serialization, 0 after deserialization
end_pos: u64,
// only used during serialization, 0 after deserialization
value_start_pos: u64,
// only used during serialization, 0 after deserialization
value_end_pos: u64,
slope: f32,
// The offset so that all values are positive when writing them
positive_val_offset: u64,
num_bits: u8,
bit_unpacker: BitUnpacker,
}
impl Function {
fn calc_slope(&mut self) {
let num_vals = self.end_pos - self.start_pos;
self.slope = get_slope(self.value_start_pos, self.value_end_pos, num_vals);
}
// split the interpolation into two function, change self and return the second split
fn split(&mut self, split_pos: u64, split_pos_value: u64) -> Function {
let mut new_function = Function {
start_pos: split_pos,
end_pos: self.end_pos,
value_start_pos: split_pos_value,
value_end_pos: self.value_end_pos,
..Default::default()
};
new_function.calc_slope();
self.end_pos = split_pos;
self.value_end_pos = split_pos_value;
self.calc_slope();
new_function
}
}
impl BinarySerializable for Function {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
self.data_start_offset.serialize(write)?;
self.value_start_pos.serialize(write)?;
self.positive_val_offset.serialize(write)?;
self.slope.serialize(write)?;
self.num_bits.serialize(write)?;
Ok(())
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Function> {
let data_start_offset = u64::deserialize(reader)?;
let value_start_pos = u64::deserialize(reader)?;
let offset = u64::deserialize(reader)?;
let slope = f32::deserialize(reader)?;
let num_bits = u8::deserialize(reader)?;
let interpolation = Function {
data_start_offset,
value_start_pos,
positive_val_offset: offset,
num_bits,
bit_unpacker: BitUnpacker::new(num_bits),
slope,
..Default::default()
};
Ok(interpolation)
}
}
#[derive(Clone, Debug)]
pub struct BlockwiseLinearFooter {
pub num_vals: u64,
pub min_value: u64,
pub max_value: u64,
interpolations: Vec<Function>,
}
impl BinarySerializable for BlockwiseLinearFooter {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
let mut out = vec![];
self.num_vals.serialize(&mut out)?;
self.min_value.serialize(&mut out)?;
self.max_value.serialize(&mut out)?;
self.interpolations.serialize(&mut out)?;
write.write_all(&out)?;
(out.len() as u32).serialize(write)?;
Ok(())
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<BlockwiseLinearFooter> {
let mut footer = BlockwiseLinearFooter {
num_vals: u64::deserialize(reader)?,
min_value: u64::deserialize(reader)?,
max_value: u64::deserialize(reader)?,
interpolations: Vec::<Function>::deserialize(reader)?,
};
for (num, interpol) in footer.interpolations.iter_mut().enumerate() {
interpol.start_pos = CHUNK_SIZE * num as u64;
}
Ok(footer)
}
}
#[inline]
fn get_interpolation_position(doc: u64) -> usize {
let index = doc / CHUNK_SIZE;
index as usize
}
#[inline]
fn get_interpolation_function(doc: u64, interpolations: &[Function]) -> &Function {
&interpolations[get_interpolation_position(doc)]
}
impl Column for BlockwiseLinearReader {
#[inline(always)]
#[inline]
fn get_val(&self, idx: u64) -> u64 {
let block_id = (idx / CHUNK_SIZE as u64) as usize;
let idx_within_block = idx % (CHUNK_SIZE as u64);
let block = &self.blocks[block_id];
let interpoled_val: u64 = block.line.eval(idx_within_block);
let block_bytes = &self.data[block.data_start_offset..];
let bitpacked_diff = block.bit_unpacker.get(idx_within_block, block_bytes);
interpoled_val.wrapping_add(bitpacked_diff)
let interpolation = get_interpolation_function(idx, &self.footer.interpolations);
let in_block_idx = idx - interpolation.start_pos;
let calculated_value = get_calculated_value(
interpolation.value_start_pos,
in_block_idx,
interpolation.slope,
);
let diff = interpolation.bit_unpacker.get(
in_block_idx,
&self.data[interpolation.data_start_offset as usize..],
);
(calculated_value + diff) - interpolation.positive_val_offset
}
#[inline]
fn min_value(&self) -> u64 {
// The BlockwiseLinearReader assumes a normalized vector.
0u64
self.footer.min_value
}
#[inline]
fn max_value(&self) -> u64 {
self.normalized_header.max_value
self.footer.max_value
}
#[inline]
fn num_vals(&self) -> u64 {
self.normalized_header.num_vals
self.footer.num_vals
}
}
/// Same as LinearSerializer, but working on chunks of CHUNK_SIZE elements.
pub struct BlockwiseLinearCodec;
impl FastFieldCodec for BlockwiseLinearCodec {
const CODEC_TYPE: FastFieldCodecType = FastFieldCodecType::BlockwiseLinear;
type Reader = BlockwiseLinearReader;
/// Opens a fast field given a file.
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self::Reader> {
let footer_len: u32 = (&bytes[bytes.len() - 4..]).deserialize()?;
let footer_offset = bytes.len() - 4 - footer_len as usize;
let (data, mut footer) = bytes.split(footer_offset);
let footer = BlockwiseLinearFooter::deserialize(&mut footer)?;
Ok(BlockwiseLinearReader { data, footer })
}
/// Creates a new fast field serializer.
fn serialize(write: &mut impl Write, fastfield_accessor: &dyn Column) -> io::Result<()> {
assert!(fastfield_accessor.min_value() <= fastfield_accessor.max_value());
let first_val = fastfield_accessor.get_val(0);
let last_val = fastfield_accessor.get_val(fastfield_accessor.num_vals() as u64 - 1);
let mut first_function = Function {
end_pos: fastfield_accessor.num_vals(),
value_start_pos: first_val,
value_end_pos: last_val,
..Default::default()
};
first_function.calc_slope();
let mut interpolations = vec![first_function];
// Since we potentially apply multiple passes over the data, the data is cached.
// Multiple iteration can be expensive (merge with index sorting can add lot of overhead per
// iteration)
let data = fastfield_accessor.iter().collect::<Vec<_>>();
//// let's split this into chunks of CHUNK_SIZE
for data_pos in (0..data.len() as u64).step_by(CHUNK_SIZE as usize).skip(1) {
let new_fun = {
let current_interpolation = interpolations.last_mut().unwrap();
current_interpolation.split(data_pos, data[data_pos as usize])
};
interpolations.push(new_fun);
}
// calculate offset and max (-> numbits) for each function
for interpolation in &mut interpolations {
let mut offset = 0;
let mut rel_positive_max = 0;
for (pos, actual_value) in data
[interpolation.start_pos as usize..interpolation.end_pos as usize]
.iter()
.cloned()
.enumerate()
{
let calculated_value = get_calculated_value(
interpolation.value_start_pos,
pos as u64,
interpolation.slope,
);
if calculated_value > actual_value {
// negative value we need to apply an offset
// we ignore negative values in the max value calculation, because negative
// values will be offset to 0
offset = offset.max(calculated_value - actual_value);
} else {
// positive value no offset reuqired
rel_positive_max = rel_positive_max.max(actual_value - calculated_value);
}
}
interpolation.positive_val_offset = offset;
interpolation.num_bits = compute_num_bits(rel_positive_max + offset);
}
let mut bit_packer = BitPacker::new();
let write = &mut CountingWriter::wrap(write);
for interpolation in &mut interpolations {
interpolation.data_start_offset = write.written_bytes();
let num_bits = interpolation.num_bits;
for (pos, actual_value) in data
[interpolation.start_pos as usize..interpolation.end_pos as usize]
.iter()
.cloned()
.enumerate()
{
let calculated_value = get_calculated_value(
interpolation.value_start_pos,
pos as u64,
interpolation.slope,
);
let diff = (actual_value + interpolation.positive_val_offset) - calculated_value;
bit_packer.write(diff, num_bits, write)?;
}
bit_packer.flush(write)?;
}
bit_packer.close(write)?;
let footer = BlockwiseLinearFooter {
num_vals: fastfield_accessor.num_vals(),
min_value: fastfield_accessor.min_value(),
max_value: fastfield_accessor.max_value(),
interpolations,
};
footer.serialize(write)?;
Ok(())
}
/// estimation for linear interpolation is hard because, you don't know
/// where the local maxima are for the deviation of the calculated value and
/// the offset is also unknown.
#[allow(clippy::question_mark)]
fn estimate(fastfield_accessor: &impl Column) -> Option<f32> {
if fastfield_accessor.num_vals() < 10 * CHUNK_SIZE {
return None;
}
// On serialization the offset is added to the actual value.
// We need to make sure this won't run into overflow calculation issues.
// For this we take the maximum theroretical offset and add this to the max value.
// If this doesn't overflow the algorithm should be fine
let theorethical_maximum_offset =
fastfield_accessor.max_value() - fastfield_accessor.min_value();
if fastfield_accessor
.max_value()
.checked_add(theorethical_maximum_offset)
.is_none()
{
return None;
}
let first_val_in_first_block = fastfield_accessor.get_val(0);
let last_elem_in_first_chunk = CHUNK_SIZE.min(fastfield_accessor.num_vals());
let last_val_in_first_block =
fastfield_accessor.get_val(last_elem_in_first_chunk as u64 - 1);
let slope = get_slope(
first_val_in_first_block,
last_val_in_first_block,
fastfield_accessor.num_vals(),
);
// let's sample at 0%, 5%, 10% .. 95%, 100%, but for the first block only
let sample_positions = (0..20)
.map(|pos| (last_elem_in_first_chunk as f32 / 100.0 * pos as f32 * 5.0) as usize)
.collect::<Vec<_>>();
let max_distance = sample_positions
.iter()
.map(|pos| {
let calculated_value =
get_calculated_value(first_val_in_first_block, *pos as u64, slope);
let actual_value = fastfield_accessor.get_val(*pos as u64);
distance(calculated_value, actual_value)
})
.max()
.unwrap();
// Estimate one block and extrapolate the cost to all blocks.
// the theory would be that we don't have the actual max_distance, but we are close within
// 50% threshold.
// It is multiplied by 2 because in a log case scenario the line would be as much above as
// below. So the offset would = max_distance
//
let relative_max_value = (max_distance as f32 * 1.5) * 2.0;
let num_bits = compute_num_bits(relative_max_value as u64) as u64 * fastfield_accessor.num_vals() as u64
// function metadata per block
+ 29 * (fastfield_accessor.num_vals() / CHUNK_SIZE);
let num_bits_uncompressed = 64 * fastfield_accessor.num_vals();
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
}
fn distance<T: Sub<Output = T> + Ord>(x: T, y: T) -> T {
if x < y {
y - x
} else {
x - y
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::tests::get_codec_test_datasets;
fn create_and_validate(data: &[u64], name: &str) -> Option<(f32, f32)> {
crate::tests::create_and_validate::<BlockwiseLinearCodec>(data, name)
}
const HIGHEST_BIT: u64 = 1 << 63;
pub fn i64_to_u64(val: i64) -> u64 {
(val as u64) ^ HIGHEST_BIT
}
#[test]
fn test_compression_i64() {
let data = (i64::MAX - 600_000..=i64::MAX - 550_000)
.map(i64_to_u64)
.collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate(&data, "simple monotonically large i64").unwrap();
assert!(actual_compression < 0.2);
assert!(estimate < 0.20);
assert!(estimate > 0.15);
assert!(actual_compression > 0.01);
}
#[test]
fn test_compression() {
let data = (10..=6_000_u64).collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate(&data, "simple monotonically large").unwrap();
assert!(actual_compression < 0.2);
assert!(estimate < 0.20);
assert!(estimate > 0.15);
assert!(actual_compression > 0.01);
}
#[test]
fn test_with_codec_data_sets() {
let data_sets = get_codec_test_datasets();
for (mut data, name) in data_sets {
create_and_validate(&data, name);
data.reverse();
create_and_validate(&data, name);
}
}
#[test]
fn test_simple() {
let data = (10..=20_u64).collect::<Vec<_>>();
create_and_validate(&data, "simple monotonically");
}
#[test]
fn border_cases_1() {
let data = (0..1024).collect::<Vec<_>>();
create_and_validate(&data, "border case");
}
#[test]
fn border_case_2() {
let data = (0..1025).collect::<Vec<_>>();
create_and_validate(&data, "border case");
}
#[test]
fn rand() {
for _ in 0..10 {
let mut data = (5_000..20_000)
.map(|_| rand::random::<u32>() as u64)
.collect::<Vec<_>>();
let _ = create_and_validate(&data, "random");
data.reverse();
create_and_validate(&data, "random");
}
}
}

View File

@@ -1,9 +1,4 @@
use std::marker::PhantomData;
use std::ops::RangeInclusive;
use tantivy_bitpacker::minmax;
pub trait Column<T: PartialOrd = u64>: Send + Sync {
pub trait Column<T = u64> {
/// Return the value associated to the given idx.
///
/// This accessor should return as fast as possible.
@@ -17,274 +12,38 @@ pub trait Column<T: PartialOrd = u64>: Send + Sync {
/// associated with the `DocId` going from
/// `start` to `start + output.len()`.
///
/// Regardless of the type of `Item`, this method works
/// - transmuting the output array
/// - extracting the `Item`s as if they were `u64`
/// - possibly converting the `u64` value to the right type.
///
/// # Panics
///
/// Must panic if `start + output.len()` is greater than
/// May panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
#[inline]
fn get_range(&self, start: u64, output: &mut [T]) {
for (out, idx) in output.iter_mut().zip(start..) {
*out = self.get_val(idx);
}
}
/// Return the positions of values which are in the provided range.
#[inline]
fn get_between_vals(&self, range: RangeInclusive<T>) -> Vec<u64> {
let mut vals = Vec::new();
for idx in 0..self.num_vals() {
let val = self.get_val(idx);
if range.contains(&val) {
vals.push(idx);
}
}
vals
}
/// Returns the minimum value for this fast field.
///
/// This min_value may not be exact.
/// For instance, the min value does not take in account of possible
/// deleted document. All values are however guaranteed to be higher than
/// `.min_value()`.
/// The min value does not take in account of possible
/// deleted document, and should be considered as a lower bound
/// of the actual minimum value.
fn min_value(&self) -> T;
/// Returns the maximum value for this fast field.
///
/// This max_value may not be exact.
/// For instance, the max value does not take in account of possible
/// deleted document. All values are however guaranteed to be higher than
/// `.max_value()`.
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value
fn max_value(&self) -> T;
fn num_vals(&self) -> u64;
/// Returns a iterator over the data
fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = T> + 'a> {
Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
}
}
pub struct VecColumn<'a, T = u64> {
values: &'a [T],
min_value: T,
max_value: T,
}
impl<'a, C: Column<T>, T: Copy + PartialOrd> Column<T> for &'a C {
fn get_val(&self, idx: u64) -> T {
(*self).get_val(idx)
}
fn min_value(&self) -> T {
(*self).min_value()
}
fn max_value(&self) -> T {
(*self).max_value()
}
fn num_vals(&self) -> u64 {
(*self).num_vals()
}
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = T> + 'b> {
(*self).iter()
}
fn get_range(&self, start: u64, output: &mut [T]) {
(*self).get_range(start, output)
}
}
impl<'a, T: Copy + PartialOrd + Send + Sync> Column<T> for VecColumn<'a, T> {
fn get_val(&self, position: u64) -> T {
self.values[position as usize]
}
fn iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
Box::new(self.values.iter().copied())
}
fn min_value(&self) -> T {
self.min_value
}
fn max_value(&self) -> T {
self.max_value
}
fn num_vals(&self) -> u64 {
self.values.len() as u64
}
fn get_range(&self, start: u64, output: &mut [T]) {
output.copy_from_slice(&self.values[start as usize..][..output.len()])
}
}
impl<'a, T: Copy + Ord + Default, V> From<&'a V> for VecColumn<'a, T>
where V: AsRef<[T]> + ?Sized
{
fn from(values: &'a V) -> Self {
let values = values.as_ref();
let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
Self {
values,
min_value,
max_value,
}
}
}
struct MonotonicMappingColumn<C, T, Input> {
from_column: C,
monotonic_mapping: T,
_phantom: PhantomData<Input>,
}
/// Creates a view of a column transformed by a monotonic mapping.
pub fn monotonic_map_column<C, T, Input: PartialOrd, Output: PartialOrd>(
from_column: C,
monotonic_mapping: T,
) -> impl Column<Output>
where
C: Column<Input>,
T: Fn(Input) -> Output + Send + Sync,
Input: Send + Sync,
Output: Send + Sync,
{
MonotonicMappingColumn {
from_column,
monotonic_mapping,
_phantom: PhantomData,
}
}
impl<C, T, Input: PartialOrd, Output: PartialOrd> Column<Output>
for MonotonicMappingColumn<C, T, Input>
where
C: Column<Input>,
T: Fn(Input) -> Output + Send + Sync,
Input: Send + Sync,
Output: Send + Sync,
{
#[inline]
fn get_val(&self, idx: u64) -> Output {
let from_val = self.from_column.get_val(idx);
(self.monotonic_mapping)(from_val)
}
fn min_value(&self) -> Output {
let from_min_value = self.from_column.min_value();
(self.monotonic_mapping)(from_min_value)
}
fn max_value(&self) -> Output {
let from_max_value = self.from_column.max_value();
(self.monotonic_mapping)(from_max_value)
}
fn num_vals(&self) -> u64 {
self.from_column.num_vals()
}
fn iter(&self) -> Box<dyn Iterator<Item = Output> + '_> {
Box::new(self.from_column.iter().map(&self.monotonic_mapping))
}
// We voluntarily do not implement get_range as it yields a regression,
// and we do not have any specialized implementation anyway.
}
pub struct IterColumn<T>(T);
impl<T> From<T> for IterColumn<T>
where T: Iterator + Clone + ExactSizeIterator
{
fn from(iter: T) -> Self {
IterColumn(iter)
}
}
impl<T> Column<T::Item> for IterColumn<T>
where
T: Iterator + Clone + ExactSizeIterator + Send + Sync,
T::Item: PartialOrd,
{
fn get_val(&self, idx: u64) -> T::Item {
self.0.clone().nth(idx as usize).unwrap()
}
fn min_value(&self) -> T::Item {
self.0.clone().next().unwrap()
}
fn max_value(&self) -> T::Item {
self.0.clone().last().unwrap()
}
fn num_vals(&self) -> u64 {
self.0.len() as u64
}
fn iter(&self) -> Box<dyn Iterator<Item = T::Item> + '_> {
Box::new(self.0.clone())
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::MonotonicallyMappableToU64;
#[test]
fn test_monotonic_mapping() {
let vals = &[1u64, 3u64][..];
let col = VecColumn::from(vals);
let mapped = monotonic_map_column(col, |el| el + 4);
assert_eq!(mapped.min_value(), 5u64);
assert_eq!(mapped.max_value(), 7u64);
assert_eq!(mapped.num_vals(), 2);
assert_eq!(mapped.num_vals(), 2);
assert_eq!(mapped.get_val(0), 5);
assert_eq!(mapped.get_val(1), 7);
}
#[test]
fn test_range_as_col() {
let col = IterColumn::from(10..100);
assert_eq!(col.num_vals(), 90);
assert_eq!(col.max_value(), 99);
}
#[test]
fn test_monotonic_mapping_iter() {
let vals: Vec<u64> = (-1..99).map(i64::to_u64).collect();
let col = VecColumn::from(&vals);
let mapped = monotonic_map_column(col, |el| i64::from_u64(el) * 10i64);
let val_i64s: Vec<i64> = mapped.iter().collect();
for i in 0..100 {
assert_eq!(val_i64s[i as usize], mapped.get_val(i));
}
}
#[test]
fn test_monotonic_mapping_get_range() {
let vals: Vec<u64> = (-1..99).map(i64::to_u64).collect();
let col = VecColumn::from(&vals);
let mapped = monotonic_map_column(col, |el| i64::from_u64(el) * 10i64);
assert_eq!(mapped.min_value(), -10i64);
assert_eq!(mapped.max_value(), 980i64);
assert_eq!(mapped.num_vals(), 100);
let val_i64s: Vec<i64> = mapped.iter().collect();
assert_eq!(val_i64s.len(), 100);
for i in 0..100 {
assert_eq!(val_i64s[i as usize], mapped.get_val(i));
assert_eq!(val_i64s[i as usize], i64::from_u64(vals[i as usize]) * 10);
}
let mut buf = [0i64; 20];
mapped.get_range(7, &mut buf[..]);
assert_eq!(&val_i64s[7..][..20], &buf);
}
}

View File

@@ -1,43 +0,0 @@
use std::ops::RangeInclusive;
/// The range of a blank in value space.
///
/// A blank is an unoccupied space in the data.
/// Use try_into() to construct.
/// A range has to have at least length of 3. Invalid ranges will be rejected.
///
/// Ordered by range length.
#[derive(Debug, Eq, PartialEq, Clone)]
pub(crate) struct BlankRange {
blank_range: RangeInclusive<u128>,
}
impl TryFrom<RangeInclusive<u128>> for BlankRange {
type Error = &'static str;
fn try_from(range: RangeInclusive<u128>) -> Result<Self, Self::Error> {
let blank_size = range.end().saturating_sub(*range.start());
if blank_size < 2 {
Err("invalid range")
} else {
Ok(BlankRange { blank_range: range })
}
}
}
impl BlankRange {
pub(crate) fn blank_size(&self) -> u128 {
self.blank_range.end() - self.blank_range.start() + 1
}
pub(crate) fn blank_range(&self) -> RangeInclusive<u128> {
self.blank_range.clone()
}
}
impl Ord for BlankRange {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
self.blank_size().cmp(&other.blank_size())
}
}
impl PartialOrd for BlankRange {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.blank_size().cmp(&other.blank_size()))
}
}

View File

@@ -1,231 +0,0 @@
use std::collections::{BTreeSet, BinaryHeap};
use std::iter;
use std::ops::RangeInclusive;
use itertools::Itertools;
use super::blank_range::BlankRange;
use super::{CompactSpace, RangeMapping};
/// Put the blanks for the sorted values into a binary heap
fn get_blanks(values_sorted: &BTreeSet<u128>) -> BinaryHeap<BlankRange> {
let mut blanks: BinaryHeap<BlankRange> = BinaryHeap::new();
for (first, second) in values_sorted.iter().tuple_windows() {
// Correctness Overflow: the values are deduped and sorted (BTreeSet property), that means
// there's always space between two values.
let blank_range = first + 1..=second - 1;
let blank_range: Result<BlankRange, _> = blank_range.try_into();
if let Ok(blank_range) = blank_range {
blanks.push(blank_range);
}
}
blanks
}
struct BlankCollector {
blanks: Vec<BlankRange>,
staged_blanks_sum: u128,
}
impl BlankCollector {
fn new() -> Self {
Self {
blanks: vec![],
staged_blanks_sum: 0,
}
}
fn stage_blank(&mut self, blank: BlankRange) {
self.staged_blanks_sum += blank.blank_size();
self.blanks.push(blank);
}
fn drain(&mut self) -> impl Iterator<Item = BlankRange> + '_ {
self.staged_blanks_sum = 0;
self.blanks.drain(..)
}
fn staged_blanks_sum(&self) -> u128 {
self.staged_blanks_sum
}
fn num_staged_blanks(&self) -> usize {
self.blanks.len()
}
}
fn num_bits(val: u128) -> u8 {
(128u32 - val.leading_zeros()) as u8
}
/// Will collect blanks and add them to compact space if more bits are saved than cost from
/// metadata.
pub fn get_compact_space(
values_deduped_sorted: &BTreeSet<u128>,
total_num_values: u64,
cost_per_blank: usize,
) -> CompactSpace {
let mut compact_space_builder = CompactSpaceBuilder::new();
if values_deduped_sorted.is_empty() {
return compact_space_builder.finish();
}
let mut blanks: BinaryHeap<BlankRange> = get_blanks(values_deduped_sorted);
// Replace after stabilization of https://github.com/rust-lang/rust/issues/62924
// We start by space that's limited to min_value..=max_value
let min_value = *values_deduped_sorted.iter().next().unwrap_or(&0);
let max_value = *values_deduped_sorted.iter().last().unwrap_or(&0);
// +1 for null, in case min and max covers the whole space, we are off by one.
let mut amplitude_compact_space = (max_value - min_value).saturating_add(1);
if min_value != 0 {
compact_space_builder.add_blanks(iter::once(0..=min_value - 1));
}
if max_value != u128::MAX {
compact_space_builder.add_blanks(iter::once(max_value + 1..=u128::MAX));
}
let mut amplitude_bits: u8 = num_bits(amplitude_compact_space);
let mut blank_collector = BlankCollector::new();
// We will stage blanks until they reduce the compact space by at least 1 bit and then flush
// them if the metadata cost is lower than the total number of saved bits.
// Binary heap to process the gaps by their size
while let Some(blank_range) = blanks.pop() {
blank_collector.stage_blank(blank_range);
let staged_spaces_sum: u128 = blank_collector.staged_blanks_sum();
let amplitude_new_compact_space = amplitude_compact_space - staged_spaces_sum;
let amplitude_new_bits = num_bits(amplitude_new_compact_space);
if amplitude_bits == amplitude_new_bits {
continue;
}
let saved_bits = (amplitude_bits - amplitude_new_bits) as usize * total_num_values as usize;
// TODO: Maybe calculate exact cost of blanks and run this more expensive computation only,
// when amplitude_new_bits changes
let cost = blank_collector.num_staged_blanks() * cost_per_blank;
if cost >= saved_bits {
// Continue here, since although we walk over the blanks by size,
// we can potentially save a lot at the last bits, which are smaller blanks
//
// E.g. if the first range reduces the compact space by 1000 from 2000 to 1000, which
// saves 11-10=1 bit and the next range reduces the compact space by 950 to
// 50, which saves 10-6=4 bit
continue;
}
amplitude_compact_space = amplitude_new_compact_space;
amplitude_bits = amplitude_new_bits;
compact_space_builder.add_blanks(blank_collector.drain().map(|blank| blank.blank_range()));
}
// special case, when we don't collected any blanks because:
// * the data is empty (early exit)
// * the algorithm did decide it's not worth the cost, which can be the case for single values
//
// We drain one collected blank unconditionally, so the empty case is reserved for empty
// data, and therefore empty compact_space means the data is empty and no data is covered
// (conversely to all data) and we can assign null to it.
if compact_space_builder.is_empty() {
compact_space_builder.add_blanks(
blank_collector
.drain()
.map(|blank| blank.blank_range())
.take(1),
);
}
let compact_space = compact_space_builder.finish();
if max_value - min_value != u128::MAX {
debug_assert_eq!(
compact_space.amplitude_compact_space(),
amplitude_compact_space
);
}
compact_space
}
#[derive(Debug, Clone, Eq, PartialEq)]
struct CompactSpaceBuilder {
blanks: Vec<RangeInclusive<u128>>,
}
impl CompactSpaceBuilder {
/// Creates a new compact space builder which will initially cover the whole space.
fn new() -> Self {
Self { blanks: Vec::new() }
}
/// Assumes that repeated add_blank calls don't overlap and are not adjacent,
/// e.g. [3..=5, 5..=10] is not allowed
///
/// Both of those assumptions are true when blanks are produced from sorted values.
fn add_blanks(&mut self, blank: impl Iterator<Item = RangeInclusive<u128>>) {
self.blanks.extend(blank);
}
fn is_empty(&self) -> bool {
self.blanks.is_empty()
}
/// Convert blanks to covered space and assign null value
fn finish(mut self) -> CompactSpace {
// sort by start. ranges are not allowed to overlap
self.blanks.sort_unstable_by_key(|blank| *blank.start());
let mut covered_space = Vec::with_capacity(self.blanks.len());
// begining of the blanks
if let Some(first_blank_start) = self.blanks.first().map(RangeInclusive::start) {
if *first_blank_start != 0 {
covered_space.push(0..=first_blank_start - 1);
}
}
// Between the blanks
let between_blanks = self.blanks.iter().tuple_windows().map(|(left, right)| {
assert!(
left.end() < right.start(),
"overlapping or adjacent ranges detected"
);
*left.end() + 1..=*right.start() - 1
});
covered_space.extend(between_blanks);
// end of the blanks
if let Some(last_blank_end) = self.blanks.last().map(RangeInclusive::end) {
if *last_blank_end != u128::MAX {
covered_space.push(last_blank_end + 1..=u128::MAX);
}
}
if covered_space.is_empty() {
covered_space.push(0..=0); // empty data case
};
let mut compact_start: u64 = 1; // 0 is reserved for `null`
let mut ranges_mapping: Vec<RangeMapping> = Vec::with_capacity(covered_space.len());
for cov in covered_space {
let range_mapping = super::RangeMapping {
value_range: cov,
compact_start,
};
let covered_range_len = range_mapping.range_length();
ranges_mapping.push(range_mapping);
compact_start += covered_range_len as u64;
}
// println!("num ranges {}", ranges_mapping.len());
CompactSpace { ranges_mapping }
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_binary_heap_pop_order() {
let mut blanks: BinaryHeap<BlankRange> = BinaryHeap::new();
blanks.push((0..=10).try_into().unwrap());
blanks.push((100..=200).try_into().unwrap());
blanks.push((100..=110).try_into().unwrap());
assert_eq!(blanks.pop().unwrap().blank_size(), 101);
assert_eq!(blanks.pop().unwrap().blank_size(), 11);
}
}

View File

@@ -1,666 +0,0 @@
/// This codec takes a large number space (u128) and reduces it to a compact number space.
///
/// It will find spaces in the number range. For example:
///
/// 100, 101, 102, 103, 104, 50000, 50001
/// could be mapped to
/// 100..104 -> 0..4
/// 50000..50001 -> 5..6
///
/// Compact space 0..=6 requires much less bits than 100..=50001
///
/// The codec is created to compress ip addresses, but may be employed in other use cases.
use std::{
cmp::Ordering,
collections::BTreeSet,
io::{self, Write},
ops::RangeInclusive,
};
use common::{BinarySerializable, CountingWriter, VInt, VIntU128};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
use crate::compact_space::build_compact_space::get_compact_space;
use crate::Column;
mod blank_range;
mod build_compact_space;
/// The cost per blank is quite hard actually, since blanks are delta encoded, the actual cost of
/// blanks depends on the number of blanks.
///
/// The number is taken by looking at a real dataset. It is optimized for larger datasets.
const COST_PER_BLANK_IN_BITS: usize = 36;
#[derive(Debug, Clone, Eq, PartialEq)]
pub struct CompactSpace {
ranges_mapping: Vec<RangeMapping>,
}
/// Maps the range from the original space to compact_start + range.len()
#[derive(Debug, Clone, Eq, PartialEq)]
struct RangeMapping {
value_range: RangeInclusive<u128>,
compact_start: u64,
}
impl RangeMapping {
fn range_length(&self) -> u64 {
(self.value_range.end() - self.value_range.start()) as u64 + 1
}
// The last value of the compact space in this range
fn compact_end(&self) -> u64 {
self.compact_start + self.range_length() - 1
}
}
impl BinarySerializable for CompactSpace {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.ranges_mapping.len() as u64).serialize(writer)?;
let mut prev_value = 0;
for value_range in self
.ranges_mapping
.iter()
.map(|range_mapping| &range_mapping.value_range)
{
let blank_delta_start = value_range.start() - prev_value;
VIntU128(blank_delta_start).serialize(writer)?;
prev_value = *value_range.start();
let blank_delta_end = value_range.end() - prev_value;
VIntU128(blank_delta_end).serialize(writer)?;
prev_value = *value_range.end();
}
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let num_ranges = VInt::deserialize(reader)?.0;
let mut ranges_mapping: Vec<RangeMapping> = vec![];
let mut value = 0u128;
let mut compact_start = 1u64; // 0 is reserved for `null`
for _ in 0..num_ranges {
let blank_delta_start = VIntU128::deserialize(reader)?.0;
value += blank_delta_start;
let blank_start = value;
let blank_delta_end = VIntU128::deserialize(reader)?.0;
value += blank_delta_end;
let blank_end = value;
let range_mapping = RangeMapping {
value_range: blank_start..=blank_end,
compact_start,
};
let range_length = range_mapping.range_length();
ranges_mapping.push(range_mapping);
compact_start += range_length as u64;
}
Ok(Self { ranges_mapping })
}
}
impl CompactSpace {
/// Amplitude is the value range of the compact space including the sentinel value used to
/// identify null values. The compact space is 0..=amplitude .
///
/// It's only used to verify we don't exceed u64 number space, which would indicate a bug.
fn amplitude_compact_space(&self) -> u128 {
self.ranges_mapping
.last()
.map(|last_range| last_range.compact_end() as u128)
.unwrap_or(1) // compact space starts at 1, 0 == null
}
fn get_range_mapping(&self, pos: usize) -> &RangeMapping {
&self.ranges_mapping[pos]
}
/// Returns either Ok(the value in the compact space) or if it is outside the compact space the
/// Err(position where it would be inserted)
fn u128_to_compact(&self, value: u128) -> Result<u64, usize> {
self.ranges_mapping
.binary_search_by(|probe| {
let value_range = &probe.value_range;
if value < *value_range.start() {
Ordering::Greater
} else if value > *value_range.end() {
Ordering::Less
} else {
Ordering::Equal
}
})
.map(|pos| {
let range_mapping = &self.ranges_mapping[pos];
let pos_in_range = (value - range_mapping.value_range.start()) as u64;
range_mapping.compact_start + pos_in_range
})
}
/// Unpacks a value from compact space u64 to u128 space
fn compact_to_u128(&self, compact: u64) -> u128 {
let pos = self
.ranges_mapping
.binary_search_by_key(&compact, |range_mapping| range_mapping.compact_start)
// Correctness: Overflow. The first range starts at compact space 0, the error from
// binary search can never be 0
.map_or_else(|e| e - 1, |v| v);
let range_mapping = &self.ranges_mapping[pos];
let diff = compact - range_mapping.compact_start;
range_mapping.value_range.start() + diff as u128
}
}
pub struct CompactSpaceCompressor {
params: IPCodecParams,
}
#[derive(Debug, Clone)]
pub struct IPCodecParams {
compact_space: CompactSpace,
bit_unpacker: BitUnpacker,
min_value: u128,
max_value: u128,
num_vals: u64,
num_bits: u8,
}
impl CompactSpaceCompressor {
/// Taking the vals as Vec may cost a lot of memory. It is used to sort the vals.
pub fn train_from(column: &impl Column<u128>) -> Self {
let mut values_sorted = BTreeSet::new();
values_sorted.extend(column.iter());
let total_num_values = column.num_vals();
let compact_space =
get_compact_space(&values_sorted, total_num_values, COST_PER_BLANK_IN_BITS);
let amplitude_compact_space = compact_space.amplitude_compact_space();
assert!(
amplitude_compact_space <= u64::MAX as u128,
"case unsupported."
);
let num_bits = tantivy_bitpacker::compute_num_bits(amplitude_compact_space as u64);
let min_value = *values_sorted.iter().next().unwrap_or(&0);
let max_value = *values_sorted.iter().last().unwrap_or(&0);
assert_eq!(
compact_space
.u128_to_compact(max_value)
.expect("could not convert max value to compact space"),
amplitude_compact_space as u64
);
CompactSpaceCompressor {
params: IPCodecParams {
compact_space,
bit_unpacker: BitUnpacker::new(num_bits),
min_value,
max_value,
num_vals: total_num_values as u64,
num_bits,
},
}
}
fn write_footer(self, writer: &mut impl Write) -> io::Result<()> {
let writer = &mut CountingWriter::wrap(writer);
self.params.serialize(writer)?;
let footer_len = writer.written_bytes() as u32;
footer_len.serialize(writer)?;
Ok(())
}
pub fn compress_into(
self,
vals: impl Iterator<Item = u128>,
write: &mut impl Write,
) -> io::Result<()> {
let mut bitpacker = BitPacker::default();
for val in vals {
let compact = self
.params
.compact_space
.u128_to_compact(val)
.map_err(|_| {
io::Error::new(
io::ErrorKind::InvalidData,
"Could not convert value to compact_space. This is a bug.",
)
})?;
bitpacker.write(compact, self.params.num_bits, write)?;
}
bitpacker.close(write)?;
self.write_footer(write)?;
Ok(())
}
}
#[derive(Debug, Clone)]
pub struct CompactSpaceDecompressor {
data: OwnedBytes,
params: IPCodecParams,
}
impl BinarySerializable for IPCodecParams {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
// header flags for future optional dictionary encoding
let footer_flags = 0u64;
footer_flags.serialize(writer)?;
VIntU128(self.min_value).serialize(writer)?;
VIntU128(self.max_value).serialize(writer)?;
VIntU128(self.num_vals as u128).serialize(writer)?;
self.num_bits.serialize(writer)?;
self.compact_space.serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let _header_flags = u64::deserialize(reader)?;
let min_value = VIntU128::deserialize(reader)?.0;
let max_value = VIntU128::deserialize(reader)?.0;
let num_vals = VIntU128::deserialize(reader)?.0 as u64;
let num_bits = u8::deserialize(reader)?;
let compact_space = CompactSpace::deserialize(reader)?;
Ok(Self {
compact_space,
bit_unpacker: BitUnpacker::new(num_bits),
min_value,
max_value,
num_vals,
num_bits,
})
}
}
impl Column<u128> for CompactSpaceDecompressor {
#[inline]
fn get_val(&self, doc: u64) -> u128 {
self.get(doc)
}
fn min_value(&self) -> u128 {
self.min_value()
}
fn max_value(&self) -> u128 {
self.max_value()
}
fn num_vals(&self) -> u64 {
self.params.num_vals
}
#[inline]
fn iter(&self) -> Box<dyn Iterator<Item = u128> + '_> {
Box::new(self.iter())
}
fn get_between_vals(&self, range: RangeInclusive<u128>) -> Vec<u64> {
self.get_between_vals(range)
}
}
impl CompactSpaceDecompressor {
pub fn open(data: OwnedBytes) -> io::Result<CompactSpaceDecompressor> {
let (data_slice, footer_len_bytes) = data.split_at(data.len() - 4);
let footer_len = u32::deserialize(&mut &footer_len_bytes[..])?;
let data_footer = &data_slice[data_slice.len() - footer_len as usize..];
let params = IPCodecParams::deserialize(&mut &data_footer[..])?;
let decompressor = CompactSpaceDecompressor { data, params };
Ok(decompressor)
}
/// Converting to compact space for the decompressor is more complex, since we may get values
/// which are outside the compact space. e.g. if we map
/// 1000 => 5
/// 2000 => 6
///
/// and we want a mapping for 1005, there is no equivalent compact space. We instead return an
/// error with the index of the next range.
fn u128_to_compact(&self, value: u128) -> Result<u64, usize> {
self.params.compact_space.u128_to_compact(value)
}
fn compact_to_u128(&self, compact: u64) -> u128 {
self.params.compact_space.compact_to_u128(compact)
}
/// Comparing on compact space: Random dataset 0,24 (50% random hit) - 1.05 GElements/s
/// Comparing on compact space: Real dataset 1.08 GElements/s
///
/// Comparing on original space: Real dataset .06 GElements/s (not completely optimized)
pub fn get_between_vals(&self, range: RangeInclusive<u128>) -> Vec<u64> {
if range.start() > range.end() {
return Vec::new();
}
let from_value = *range.start();
let to_value = *range.end();
assert!(to_value >= from_value);
let compact_from = self.u128_to_compact(from_value);
let compact_to = self.u128_to_compact(to_value);
// Quick return, if both ranges fall into the same non-mapped space, the range can't cover
// any values, so we can early exit
match (compact_to, compact_from) {
(Err(pos1), Err(pos2)) if pos1 == pos2 => return Vec::new(),
_ => {}
}
let compact_from = compact_from.unwrap_or_else(|pos| {
// Correctness: Out of bounds, if this value is Err(last_index + 1), we early exit,
// since the to_value also mapps into the same non-mapped space
let range_mapping = self.params.compact_space.get_range_mapping(pos);
range_mapping.compact_start
});
// If there is no compact space, we go to the closest upperbound compact space
let compact_to = compact_to.unwrap_or_else(|pos| {
// Correctness: Overflow, if this value is Err(0), we early exit,
// since the from_value also mapps into the same non-mapped space
// Get end of previous range
let pos = pos - 1;
let range_mapping = self.params.compact_space.get_range_mapping(pos);
range_mapping.compact_end()
});
let range = compact_from..=compact_to;
let mut positions = Vec::new();
let step_size = 4;
let cutoff = self.params.num_vals - self.params.num_vals % step_size;
let mut push_if_in_range = |idx, val| {
if range.contains(&val) {
positions.push(idx);
}
};
let get_val = |idx| self.params.bit_unpacker.get(idx as u64, &self.data);
// unrolled loop
for idx in (0..cutoff).step_by(step_size as usize) {
let idx1 = idx;
let idx2 = idx + 1;
let idx3 = idx + 2;
let idx4 = idx + 3;
let val1 = get_val(idx1);
let val2 = get_val(idx2);
let val3 = get_val(idx3);
let val4 = get_val(idx4);
push_if_in_range(idx1, val1);
push_if_in_range(idx2, val2);
push_if_in_range(idx3, val3);
push_if_in_range(idx4, val4);
}
// handle rest
for idx in cutoff..self.params.num_vals {
push_if_in_range(idx, get_val(idx));
}
positions
}
#[inline]
fn iter_compact(&self) -> impl Iterator<Item = u64> + '_ {
(0..self.params.num_vals)
.map(move |idx| self.params.bit_unpacker.get(idx as u64, &self.data) as u64)
}
#[inline]
fn iter(&self) -> impl Iterator<Item = u128> + '_ {
// TODO: Performance. It would be better to iterate on the ranges and check existence via
// the bit_unpacker.
self.iter_compact()
.map(|compact| self.compact_to_u128(compact))
}
#[inline]
pub fn get(&self, idx: u64) -> u128 {
let compact = self.params.bit_unpacker.get(idx, &self.data);
self.compact_to_u128(compact)
}
pub fn min_value(&self) -> u128 {
self.params.min_value
}
pub fn max_value(&self) -> u128 {
self.params.max_value
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::{open_u128, serialize_u128, VecColumn};
#[test]
fn compact_space_test() {
let ips = &[
2u128, 4u128, 1000, 1001, 1002, 1003, 1004, 1005, 1008, 1010, 1012, 1260,
]
.into_iter()
.collect();
let compact_space = get_compact_space(ips, ips.len() as u64, 11);
let amplitude = compact_space.amplitude_compact_space();
assert_eq!(amplitude, 17);
assert_eq!(1, compact_space.u128_to_compact(2).unwrap());
assert_eq!(2, compact_space.u128_to_compact(3).unwrap());
assert_eq!(compact_space.u128_to_compact(100).unwrap_err(), 1);
for (num1, num2) in (0..3).tuple_windows() {
assert_eq!(
compact_space.get_range_mapping(num1).compact_end() + 1,
compact_space.get_range_mapping(num2).compact_start
);
}
let mut output: Vec<u8> = Vec::new();
compact_space.serialize(&mut output).unwrap();
assert_eq!(
compact_space,
CompactSpace::deserialize(&mut &output[..]).unwrap()
);
for ip in ips {
let compact = compact_space.u128_to_compact(*ip).unwrap();
assert_eq!(compact_space.compact_to_u128(compact), *ip);
}
}
#[test]
fn compact_space_amplitude_test() {
let ips = &[100000u128, 1000000].into_iter().collect();
let compact_space = get_compact_space(ips, ips.len() as u64, 1);
let amplitude = compact_space.amplitude_compact_space();
assert_eq!(amplitude, 2);
}
fn test_all(data: OwnedBytes, expected: &[u128]) {
let decompressor = CompactSpaceDecompressor::open(data).unwrap();
for (idx, expected_val) in expected.iter().cloned().enumerate() {
let val = decompressor.get(idx as u64);
assert_eq!(val, expected_val);
let test_range = |range: RangeInclusive<u128>| {
let expected_positions = expected
.iter()
.positions(|val| range.contains(val))
.map(|pos| pos as u64)
.collect::<Vec<_>>();
let positions = decompressor.get_between_vals(range);
assert_eq!(positions, expected_positions);
};
test_range(expected_val.saturating_sub(1)..=expected_val);
test_range(expected_val..=expected_val);
test_range(expected_val..=expected_val.saturating_add(1));
test_range(expected_val.saturating_sub(1)..=expected_val.saturating_add(1));
}
}
fn test_aux_vals(u128_vals: &[u128]) -> OwnedBytes {
let mut out = Vec::new();
serialize_u128(VecColumn::from(u128_vals), &mut out).unwrap();
let data = OwnedBytes::new(out);
test_all(data.clone(), u128_vals);
data
}
#[test]
fn test_range_1() {
let vals = &[
1u128,
100u128,
3u128,
99999u128,
100000u128,
100001u128,
4_000_211_221u128,
4_000_211_222u128,
333u128,
];
let data = test_aux_vals(vals);
let decomp = CompactSpaceDecompressor::open(data).unwrap();
let positions = decomp.get_between_vals(0..=1);
assert_eq!(positions, vec![0]);
let positions = decomp.get_between_vals(0..=2);
assert_eq!(positions, vec![0]);
let positions = decomp.get_between_vals(0..=3);
assert_eq!(positions, vec![0, 2]);
assert_eq!(decomp.get_between_vals(99999u128..=99999u128), vec![3]);
assert_eq!(decomp.get_between_vals(99999u128..=100000u128), vec![3, 4]);
assert_eq!(decomp.get_between_vals(99998u128..=100000u128), vec![3, 4]);
assert_eq!(decomp.get_between_vals(99998u128..=99999u128), vec![3]);
assert_eq!(decomp.get_between_vals(99998u128..=99998u128), vec![]);
assert_eq!(decomp.get_between_vals(333u128..=333u128), vec![8]);
assert_eq!(decomp.get_between_vals(332u128..=333u128), vec![8]);
assert_eq!(decomp.get_between_vals(332u128..=334u128), vec![8]);
assert_eq!(decomp.get_between_vals(333u128..=334u128), vec![8]);
assert_eq!(
decomp.get_between_vals(4_000_211_221u128..=5_000_000_000u128),
vec![6, 7]
);
}
#[test]
fn test_empty() {
let vals = &[];
let data = test_aux_vals(vals);
let _decomp = CompactSpaceDecompressor::open(data).unwrap();
}
#[test]
fn test_range_2() {
let vals = &[
100u128,
99999u128,
100000u128,
100001u128,
4_000_211_221u128,
4_000_211_222u128,
333u128,
];
let data = test_aux_vals(vals);
let decomp = CompactSpaceDecompressor::open(data).unwrap();
let positions = decomp.get_between_vals(0..=5);
assert_eq!(positions, vec![]);
let positions = decomp.get_between_vals(0..=100);
assert_eq!(positions, vec![0]);
let positions = decomp.get_between_vals(0..=105);
assert_eq!(positions, vec![0]);
}
#[test]
fn test_range_3() {
let vals = &[
200u128,
201,
202,
203,
204,
204,
206,
207,
208,
209,
210,
1_000_000,
5_000_000_000,
];
let mut out = Vec::new();
serialize_u128(VecColumn::from(vals), &mut out).unwrap();
let decomp = open_u128(OwnedBytes::new(out)).unwrap();
assert_eq!(decomp.get_between_vals(199..=200), vec![0]);
assert_eq!(decomp.get_between_vals(199..=201), vec![0, 1]);
assert_eq!(decomp.get_between_vals(200..=200), vec![0]);
assert_eq!(decomp.get_between_vals(1_000_000..=1_000_000), vec![11]);
}
#[test]
fn test_bug1() {
let vals = &[9223372036854775806];
let _data = test_aux_vals(vals);
}
#[test]
fn test_bug2() {
let vals = &[340282366920938463463374607431768211455u128];
let _data = test_aux_vals(vals);
}
#[test]
fn test_bug3() {
let vals = &[340282366920938463463374607431768211454];
let _data = test_aux_vals(vals);
}
#[test]
fn test_bug4() {
let vals = &[340282366920938463463374607431768211455, 0];
let _data = test_aux_vals(vals);
}
#[test]
fn test_first_large_gaps() {
let vals = &[1_000_000_000u128; 100];
let _data = test_aux_vals(vals);
}
use itertools::Itertools;
use proptest::prelude::*;
fn num_strategy() -> impl Strategy<Value = u128> {
prop_oneof![
1 => prop::num::u128::ANY.prop_map(|num| u128::MAX - (num % 10) ),
1 => prop::num::u128::ANY.prop_map(|num| i64::MAX as u128 + 5 - (num % 10) ),
1 => prop::num::u128::ANY.prop_map(|num| i128::MAX as u128 + 5 - (num % 10) ),
1 => prop::num::u128::ANY.prop_map(|num| num % 10 ),
20 => prop::num::u128::ANY,
]
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(10))]
#[test]
fn compress_decompress_random(vals in proptest::collection::vec(num_strategy()
, 1..1000)) {
let _data = test_aux_vals(&vals);
}
}
}

View File

@@ -1,170 +0,0 @@
use std::num::NonZeroU64;
use fastdivide::DividerU64;
/// Compute the gcd of two non null numbers.
///
/// It is recommended, but not required, to feed values such that `large >= small`.
fn compute_gcd(mut large: NonZeroU64, mut small: NonZeroU64) -> NonZeroU64 {
loop {
let rem: u64 = large.get() % small;
if let Some(new_small) = NonZeroU64::new(rem) {
(large, small) = (small, new_small);
} else {
return small;
}
}
}
// Find GCD for iterator of numbers
pub fn find_gcd(numbers: impl Iterator<Item = u64>) -> Option<NonZeroU64> {
let mut numbers = numbers.flat_map(NonZeroU64::new);
let mut gcd: NonZeroU64 = numbers.next()?;
if gcd.get() == 1 {
return Some(gcd);
}
let mut gcd_divider = DividerU64::divide_by(gcd.get());
for val in numbers {
let remainder = val.get() - (gcd_divider.divide(val.get())) * gcd.get();
if remainder == 0 {
continue;
}
gcd = compute_gcd(val, gcd);
if gcd.get() == 1 {
return Some(gcd);
}
gcd_divider = DividerU64::divide_by(gcd.get());
}
Some(gcd)
}
#[cfg(test)]
mod tests {
use std::io;
use std::num::NonZeroU64;
use ownedbytes::OwnedBytes;
use crate::gcd::{compute_gcd, find_gcd};
use crate::{FastFieldCodecType, VecColumn};
fn test_fastfield_gcd_i64_with_codec(
codec_type: FastFieldCodecType,
num_vals: usize,
) -> io::Result<()> {
let mut vals: Vec<i64> = (-4..=(num_vals as i64) - 5).map(|val| val * 1000).collect();
let mut buffer: Vec<u8> = Vec::new();
crate::serialize(VecColumn::from(&vals), &mut buffer, &[codec_type])?;
let buffer = OwnedBytes::new(buffer);
let column = crate::open::<i64>(buffer.clone())?;
assert_eq!(column.get_val(0), -4000i64);
assert_eq!(column.get_val(1), -3000i64);
assert_eq!(column.get_val(2), -2000i64);
assert_eq!(column.max_value(), (num_vals as i64 - 5) * 1000);
assert_eq!(column.min_value(), -4000i64);
// Can't apply gcd
let mut buffer_without_gcd = Vec::new();
vals.pop();
vals.push(1001i64);
crate::serialize(
VecColumn::from(&vals),
&mut buffer_without_gcd,
&[codec_type],
)?;
let buffer_without_gcd = OwnedBytes::new(buffer_without_gcd);
assert!(buffer_without_gcd.len() > buffer.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_i64() -> io::Result<()> {
for &codec_type in &[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
FastFieldCodecType::Linear,
] {
test_fastfield_gcd_i64_with_codec(codec_type, 5500)?;
}
Ok(())
}
fn test_fastfield_gcd_u64_with_codec(
codec_type: FastFieldCodecType,
num_vals: usize,
) -> io::Result<()> {
let mut vals: Vec<u64> = (1..=num_vals).map(|i| i as u64 * 1000u64).collect();
let mut buffer: Vec<u8> = Vec::new();
crate::serialize(VecColumn::from(&vals), &mut buffer, &[codec_type])?;
let buffer = OwnedBytes::new(buffer);
let column = crate::open::<u64>(buffer.clone())?;
assert_eq!(column.get_val(0), 1000u64);
assert_eq!(column.get_val(1), 2000u64);
assert_eq!(column.get_val(2), 3000u64);
assert_eq!(column.max_value(), num_vals as u64 * 1000);
assert_eq!(column.min_value(), 1000u64);
// Can't apply gcd
let mut buffer_without_gcd = Vec::new();
vals.pop();
vals.push(1001u64);
crate::serialize(
VecColumn::from(&vals),
&mut buffer_without_gcd,
&[codec_type],
)?;
let buffer_without_gcd = OwnedBytes::new(buffer_without_gcd);
assert!(buffer_without_gcd.len() > buffer.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_u64() -> io::Result<()> {
for &codec_type in &[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
FastFieldCodecType::Linear,
] {
test_fastfield_gcd_u64_with_codec(codec_type, 5500)?;
}
Ok(())
}
#[test]
pub fn test_fastfield2() {
let test_fastfield = crate::serialize_and_load(&[100u64, 200u64, 300u64]);
assert_eq!(test_fastfield.get_val(0), 100);
assert_eq!(test_fastfield.get_val(1), 200);
assert_eq!(test_fastfield.get_val(2), 300);
}
#[test]
fn test_compute_gcd() {
let test_compute_gcd_aux = |large, small, expected| {
let large = NonZeroU64::new(large).unwrap();
let small = NonZeroU64::new(small).unwrap();
let expected = NonZeroU64::new(expected).unwrap();
assert_eq!(compute_gcd(small, large), expected);
assert_eq!(compute_gcd(large, small), expected);
};
test_compute_gcd_aux(1, 4, 1);
test_compute_gcd_aux(2, 4, 2);
test_compute_gcd_aux(10, 25, 5);
test_compute_gcd_aux(25, 25, 25);
}
#[test]
fn find_gcd_test() {
assert_eq!(find_gcd([0].into_iter()), None);
assert_eq!(find_gcd([0, 10].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([10, 0].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([].into_iter()), None);
assert_eq!(find_gcd([15, 30, 5, 10].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([15, 16, 10].into_iter()), NonZeroU64::new(1));
assert_eq!(find_gcd([0, 5, 5, 5].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([0, 0].into_iter()), None);
}
}

View File

@@ -1,40 +1,20 @@
#![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::io;
use std::io::Write;
use std::sync::Arc;
use common::BinarySerializable;
use compact_space::CompactSpaceDecompressor;
use ownedbytes::OwnedBytes;
use serialize::Header;
mod bitpacked;
mod blockwise_linear;
mod compact_space;
mod line;
mod linear;
mod monotonic_mapping;
pub mod bitpacked;
pub mod blockwise_linear;
pub mod linear;
mod column;
mod gcd;
mod serialize;
use self::bitpacked::BitpackedCodec;
use self::blockwise_linear::BlockwiseLinearCodec;
pub use self::column::{monotonic_map_column, Column, VecColumn};
use self::linear::LinearCodec;
pub use self::monotonic_mapping::MonotonicallyMappableToU64;
pub use self::serialize::{
estimate, serialize, serialize_and_load, serialize_u128, NormalizedHeader,
};
pub use self::column::Column;
#[derive(PartialEq, Eq, PartialOrd, Ord, Debug, Clone, Copy)]
#[repr(u8)]
@@ -42,6 +22,7 @@ pub enum FastFieldCodecType {
Bitpacked = 1,
Linear = 2,
BlockwiseLinear = 3,
Gcd = 4,
}
impl BinarySerializable for FastFieldCodecType {
@@ -67,63 +48,29 @@ impl FastFieldCodecType {
1 => Some(Self::Bitpacked),
2 => Some(Self::Linear),
3 => Some(Self::BlockwiseLinear),
4 => Some(Self::Gcd),
_ => None,
}
}
}
/// Returns the correct codec reader wrapped in the `Arc` for the data.
pub fn open_u128(bytes: OwnedBytes) -> io::Result<Arc<dyn Column<u128>>> {
Ok(Arc::new(CompactSpaceDecompressor::open(bytes)?))
}
/// Returns the correct codec reader wrapped in the `Arc` for the data.
pub fn open<T: MonotonicallyMappableToU64>(
mut bytes: OwnedBytes,
) -> io::Result<Arc<dyn Column<T>>> {
let header = Header::deserialize(&mut bytes)?;
match header.codec_type {
FastFieldCodecType::Bitpacked => open_specific_codec::<BitpackedCodec, _>(bytes, &header),
FastFieldCodecType::Linear => open_specific_codec::<LinearCodec, _>(bytes, &header),
FastFieldCodecType::BlockwiseLinear => {
open_specific_codec::<BlockwiseLinearCodec, _>(bytes, &header)
}
}
}
fn open_specific_codec<C: FastFieldCodec, Item: MonotonicallyMappableToU64>(
bytes: OwnedBytes,
header: &Header,
) -> io::Result<Arc<dyn Column<Item>>> {
let normalized_header = header.normalized();
let reader = C::open_from_bytes(bytes, normalized_header)?;
let min_value = header.min_value;
if let Some(gcd) = header.gcd {
let monotonic_mapping = move |val: u64| Item::from_u64(min_value + val * gcd.get());
Ok(Arc::new(monotonic_map_column(reader, monotonic_mapping)))
} else {
let monotonic_mapping = move |val: u64| Item::from_u64(min_value + val);
Ok(Arc::new(monotonic_map_column(reader, monotonic_mapping)))
}
}
/// The FastFieldSerializerEstimate trait is required on all variants
/// of fast field compressions, to decide which one to choose.
trait FastFieldCodec: 'static {
pub trait FastFieldCodec {
/// A codex needs to provide a unique name and id, which is
/// used for debugging and de/serialization.
const CODEC_TYPE: FastFieldCodecType;
type Reader: Column<u64> + 'static;
type Reader: Column<u64>;
/// Reads the metadata and returns the CodecReader
fn open_from_bytes(bytes: OwnedBytes, header: NormalizedHeader) -> io::Result<Self::Reader>;
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self::Reader>;
/// Serializes the data using the serializer into write.
///
/// The column iterator should be preferred over using column `get_val` method for
/// The fastfield_accessor iterator should be preferred over using fastfield_accessor for
/// performance reasons.
fn serialize(column: &dyn Column, write: &mut impl Write) -> io::Result<()>;
fn serialize(write: &mut impl Write, fastfield_accessor: &dyn Column<u64>) -> io::Result<()>;
/// Returns an estimate of the compression ratio.
/// If the codec is not applicable, returns `None`.
@@ -132,14 +79,46 @@ trait FastFieldCodec: 'static {
///
/// It could make sense to also return a value representing
/// computational complexity.
fn estimate(column: &dyn Column) -> Option<f32>;
fn estimate(fastfield_accessor: &impl Column) -> Option<f32>;
}
pub const ALL_CODEC_TYPES: [FastFieldCodecType; 3] = [
FastFieldCodecType::Bitpacked,
FastFieldCodecType::BlockwiseLinear,
FastFieldCodecType::Linear,
];
#[derive(Debug, Clone)]
/// Statistics are used in codec detection and stored in the fast field footer.
pub struct FastFieldStats {
pub min_value: u64,
pub max_value: u64,
pub num_vals: u64,
}
struct VecColum<'a>(&'a [u64]);
impl<'a> Column for VecColum<'a> {
fn get_val(&self, position: u64) -> u64 {
self.0[position as usize]
}
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = u64> + 'b> {
Box::new(self.0.iter().cloned())
}
fn min_value(&self) -> u64 {
self.0.iter().min().cloned().unwrap_or(0)
}
fn max_value(&self) -> u64 {
self.0.iter().max().cloned().unwrap_or(0)
}
fn num_vals(&self) -> u64 {
self.0.len() as u64
}
}
impl<'a> From<&'a [u64]> for VecColum<'a> {
fn from(data: &'a [u64]) -> Self {
Self(data)
}
}
#[cfg(test)]
mod tests {
@@ -150,24 +129,19 @@ mod tests {
use crate::bitpacked::BitpackedCodec;
use crate::blockwise_linear::BlockwiseLinearCodec;
use crate::linear::LinearCodec;
use crate::serialize::Header;
pub(crate) fn create_and_validate<Codec: FastFieldCodec>(
pub fn create_and_validate<Codec: FastFieldCodec>(
data: &[u64],
name: &str,
) -> Option<(f32, f32)> {
let col = &VecColumn::from(data);
let header = Header::compute_header(col, &[Codec::CODEC_TYPE])?;
let normalized_col = header.normalize_column(col);
let estimation = Codec::estimate(&normalized_col)?;
let estimation = Codec::estimate(&VecColum::from(data))?;
let mut out = Vec::new();
let col = VecColumn::from(data);
serialize(col, &mut out, &[Codec::CODEC_TYPE]).unwrap();
let mut out: Vec<u8> = Vec::new();
Codec::serialize(&mut out, &VecColum::from(data)).unwrap();
let actual_compression = out.len() as f32 / (data.len() as f32 * 8.0);
let reader = crate::open::<u64>(OwnedBytes::new(out)).unwrap();
let reader = Codec::open_from_bytes(OwnedBytes::new(out)).unwrap();
assert_eq!(reader.num_vals(), data.len() as u64);
for (doc, orig_val) in data.iter().copied().enumerate() {
let val = reader.get_val(doc as u64);
@@ -182,42 +156,24 @@ mod tests {
proptest! {
#![proptest_config(ProptestConfig::with_cases(100))]
#[test]
fn test_proptest_small_bitpacked(data in proptest::collection::vec(num_strategy(), 1..10)) {
create_and_validate::<BitpackedCodec>(&data, "proptest bitpacked");
}
#[test]
fn test_proptest_small_linear(data in proptest::collection::vec(num_strategy(), 1..10)) {
fn test_proptest_small(data in proptest::collection::vec(num_strategy(), 1..10)) {
create_and_validate::<LinearCodec>(&data, "proptest linearinterpol");
}
#[test]
fn test_proptest_small_blockwise_linear(data in proptest::collection::vec(num_strategy(), 1..10)) {
create_and_validate::<BlockwiseLinearCodec>(&data, "proptest multilinearinterpol");
create_and_validate::<BitpackedCodec>(&data, "proptest bitpacked");
}
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(10))]
#[test]
fn test_proptest_large_bitpacked(data in proptest::collection::vec(num_strategy(), 1..6000)) {
fn test_proptest_large(data in proptest::collection::vec(num_strategy(), 1..6000)) {
create_and_validate::<LinearCodec>(&data, "proptest linearinterpol");
create_and_validate::<BlockwiseLinearCodec>(&data, "proptest multilinearinterpol");
create_and_validate::<BitpackedCodec>(&data, "proptest bitpacked");
}
#[test]
fn test_proptest_large_linear(data in proptest::collection::vec(num_strategy(), 1..6000)) {
create_and_validate::<LinearCodec>(&data, "proptest linearinterpol");
}
#[test]
fn test_proptest_large_blockwise_linear(data in proptest::collection::vec(num_strategy(), 1..6000)) {
create_and_validate::<BlockwiseLinearCodec>(&data, "proptest multilinearinterpol");
}
}
fn num_strategy() -> impl Strategy<Value = u64> {
prop_oneof![
1 => prop::num::u64::ANY.prop_map(|num| u64::MAX - (num % 10) ),
@@ -278,43 +234,34 @@ mod tests {
#[test]
fn estimation_good_interpolation_case() {
let data = (10..=20000_u64).collect::<Vec<_>>();
let data: VecColumn = data.as_slice().into();
let data: VecColum = data.as_slice().into();
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
assert_le!(linear_interpol_estimation, 0.01);
let multi_linear_interpol_estimation = BlockwiseLinearCodec::estimate(&data).unwrap();
assert_le!(multi_linear_interpol_estimation, 0.2);
assert_lt!(linear_interpol_estimation, multi_linear_interpol_estimation);
assert_le!(linear_interpol_estimation, multi_linear_interpol_estimation);
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_lt!(linear_interpol_estimation, bitpacked_estimation);
assert_le!(linear_interpol_estimation, bitpacked_estimation);
}
#[test]
fn estimation_test_bad_interpolation_case() {
let data: &[u64] = &[200, 10, 10, 10, 10, 1000, 20];
let data: VecColumn = data.into();
let data: VecColum = data.into();
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
assert_le!(linear_interpol_estimation, 0.34);
assert_le!(linear_interpol_estimation, 0.32);
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_lt!(bitpacked_estimation, linear_interpol_estimation);
assert_le!(bitpacked_estimation, linear_interpol_estimation);
}
#[test]
fn estimation_prefer_bitpacked() {
let data = VecColumn::from(&[10, 10, 10, 10]);
let linear_interpol_estimation = LinearCodec::estimate(&data).unwrap();
let bitpacked_estimation = BitpackedCodec::estimate(&data).unwrap();
assert_lt!(bitpacked_estimation, linear_interpol_estimation);
}
#[test]
fn estimation_test_bad_interpolation_case_monotonically_increasing() {
let mut data: Vec<u64> = (200..=20000_u64).collect();
data.push(1_000_000);
let data: VecColumn = data.as_slice().into();
let data: VecColum = data.as_slice().into();
// in this case the linear interpolation can't in fact not be worse than bitpacking,
// but the estimator adds some threshold, which leads to estimated worse behavior
@@ -335,134 +282,6 @@ mod tests {
count_codec += 1;
}
}
assert_eq!(count_codec, 3);
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use std::sync::Arc;
use ownedbytes::OwnedBytes;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::{self, Bencher};
use super::*;
use crate::Column;
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55000_u64)
.map(|num| num + rng.gen::<u8>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);
data.insert(2000, 100);
data.insert(3000, 4100);
data.insert(4000, 100);
data.insert(5000, 800);
data
}
#[inline(never)]
fn value_iter() -> impl Iterator<Item = u64> {
0..20_000
}
fn get_reader_for_bench<Codec: FastFieldCodec>(data: &[u64]) -> Codec::Reader {
let mut bytes = Vec::new();
let min_value = *data.iter().min().unwrap();
let data = data.iter().map(|el| *el - min_value).collect::<Vec<_>>();
let col = VecColumn::from(&data);
let normalized_header = crate::NormalizedHeader {
num_vals: col.num_vals(),
max_value: col.max_value(),
};
Codec::serialize(&VecColumn::from(&data), &mut bytes).unwrap();
Codec::open_from_bytes(OwnedBytes::new(bytes), normalized_header).unwrap()
}
fn bench_get<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let col = get_reader_for_bench::<Codec>(data);
b.iter(|| {
let mut sum = 0u64;
for pos in value_iter() {
let val = col.get_val(pos as u64);
sum = sum.wrapping_add(val);
}
sum
});
}
#[inline(never)]
fn bench_get_dynamic_helper(b: &mut Bencher, col: Arc<dyn Column>) {
b.iter(|| {
let mut sum = 0u64;
for pos in value_iter() {
let val = col.get_val(pos as u64);
sum = sum.wrapping_add(val);
}
sum
});
}
fn bench_get_dynamic<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let col = Arc::new(get_reader_for_bench::<Codec>(data));
bench_get_dynamic_helper(b, col);
}
fn bench_create<Codec: FastFieldCodec>(b: &mut Bencher, data: &[u64]) {
let min_value = *data.iter().min().unwrap();
let data = data.iter().map(|el| *el - min_value).collect::<Vec<_>>();
let mut bytes = Vec::new();
b.iter(|| {
bytes.clear();
Codec::serialize(&VecColumn::from(&data), &mut bytes).unwrap();
});
}
#[bench]
fn bench_fastfield_bitpack_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_fastfield_linearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<LinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_multilinearinterpol_create(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_create::<BlockwiseLinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_bitpack_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_fastfield_bitpack_get_dynamic(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get_dynamic::<BitpackedCodec>(b, &data);
}
#[bench]
fn bench_fastfield_linearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<LinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_linearinterpol_get_dynamic(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get_dynamic::<LinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_multilinearinterpol_get(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get::<BlockwiseLinearCodec>(b, &data);
}
#[bench]
fn bench_fastfield_multilinearinterpol_get_dynamic(b: &mut Bencher) {
let data: Vec<_> = get_data();
bench_get_dynamic::<BlockwiseLinearCodec>(b, &data);
assert_eq!(count_codec, 4);
}
}

View File

@@ -1,210 +0,0 @@
use std::io;
use std::num::NonZeroU64;
use common::{BinarySerializable, VInt};
use crate::Column;
const MID_POINT: u64 = (1u64 << 32) - 1u64;
/// `Line` describes a line function `y: ax + b` using integer
/// arithmetics.
///
/// The slope is in fact a decimal split into a 32 bit integer value,
/// and a 32-bit decimal value.
///
/// The multiplication then becomes.
/// `y = m * x >> 32 + b`
#[derive(Debug, Clone, Copy, Default)]
pub struct Line {
slope: u64,
intercept: u64,
}
/// Compute the line slope.
///
/// This function has the nice property of being
/// invariant by translation.
/// `
/// compute_slope(y0, y1)
/// = compute_slope(y0 + X % 2^64, y1 + X % 2^64)
/// `
fn compute_slope(y0: u64, y1: u64, num_vals: NonZeroU64) -> u64 {
let dy = y1.wrapping_sub(y0);
let sign = dy <= (1 << 63);
let abs_dy = if sign {
y1.wrapping_sub(y0)
} else {
y0.wrapping_sub(y1)
};
if abs_dy >= 1 << 32 {
// This is outside of realm we handle.
// Let's just bail.
return 0u64;
}
let abs_slope = (abs_dy << 32) / num_vals.get();
if sign {
abs_slope
} else {
// The complement does indeed create the
// opposite decreasing slope...
//
// Intuitively (without the bitshifts and % u64::MAX)
// ```
// (x + shift)*(u64::MAX - abs_slope)
// - (x * (u64::MAX - abs_slope))
// = - shift * abs_slope
// ```
u64::MAX - abs_slope
}
}
impl Line {
#[inline(always)]
pub fn eval(&self, x: u64) -> u64 {
let linear_part = (x.wrapping_mul(self.slope) >> 32) as i32 as u64;
self.intercept.wrapping_add(linear_part)
}
// Same as train, but the intercept is only estimated from provided sample positions
pub fn estimate(ys: &dyn Column, sample_positions: &[u64]) -> Self {
Self::train_from(
ys,
sample_positions
.iter()
.cloned()
.map(|pos| (pos, ys.get_val(pos))),
)
}
// Intercept is only computed from provided positions
fn train_from(ys: &dyn Column, positions_and_values: impl Iterator<Item = (u64, u64)>) -> Self {
let num_vals = if let Some(num_vals) = NonZeroU64::new(ys.num_vals() - 1) {
num_vals
} else {
return Line::default();
};
let y0 = ys.get_val(0);
let y1 = ys.get_val(num_vals.get());
// We first independently pick our slope.
let slope = compute_slope(y0, y1, num_vals);
// We picked our slope. Note that it does not have to be perfect.
// Now we need to compute the best intercept.
//
// Intuitively, the best intercept is such that line passes through one of the
// `(i, ys[])`.
//
// The best intercept therefore has the form
// `y[i] - line.eval(i)` (using wrapping arithmetics).
// In other words, the best intercept is one of the `y - Line::eval(ys[i])`
// and our task is just to pick the one that minimizes our error.
//
// Without sorting our values, this is a difficult problem.
// We however rely on the following trick...
//
// We only focus on the case where the interpolation is half decent.
// If the line interpolation is doing its job on a dataset suited for it,
// we can hope that the maximum error won't be larger than `u64::MAX / 2`.
//
// In other words, even without the intercept the values `y - Line::eval(ys[i])` will all be
// within an interval that takes less than half of the modulo space of `u64`.
//
// Our task is therefore to identify this interval.
// Here we simply translate all of our values by `y0 - 2^63` and pick the min.
let mut line = Line {
slope,
intercept: 0,
};
let heuristic_shift = y0.wrapping_sub(MID_POINT);
line.intercept = positions_and_values
.map(|(pos, y)| y.wrapping_sub(line.eval(pos)))
.min_by_key(|&val| val.wrapping_sub(heuristic_shift))
.unwrap_or(0u64); //< Never happens.
line
}
/// Returns a line that attemps to approximate a function
/// f: i in 0..[ys.num_vals()) -> ys[i].
///
/// - The approximation is always lower than the actual value.
/// Or more rigorously, formally `f(i).wrapping_sub(ys[i])` is small
/// for any i in [0..ys.len()).
/// - It computes without panicking for any value of it.
///
/// This function is only invariable by translation if all of the
/// `ys` are packaged into half of the space. (See heuristic below)
pub fn train(ys: &dyn Column) -> Self {
Self::train_from(
ys,
ys.iter().enumerate().map(|(pos, val)| (pos as u64, val)),
)
}
}
impl BinarySerializable for Line {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.slope).serialize(writer)?;
VInt(self.intercept).serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let slope = VInt::deserialize(reader)?.0;
let intercept = VInt::deserialize(reader)?.0;
Ok(Line { slope, intercept })
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::VecColumn;
/// Test training a line and ensuring that the maximum difference between
/// the data points and the line is `expected`.
///
/// This function operates translation over the data for better coverage.
#[track_caller]
fn test_line_interpol_with_translation(ys: &[u64], expected: Option<u64>) {
let mut translations = vec![0, 100, u64::MAX / 2, u64::MAX, u64::MAX - 1];
translations.extend_from_slice(ys);
for translation in translations {
let translated_ys: Vec<u64> = ys
.iter()
.copied()
.map(|y| y.wrapping_add(translation))
.collect();
let largest_err = test_eval_max_err(&translated_ys);
assert_eq!(largest_err, expected);
}
}
fn test_eval_max_err(ys: &[u64]) -> Option<u64> {
let line = Line::train(&VecColumn::from(&ys));
ys.iter()
.enumerate()
.map(|(x, y)| y.wrapping_sub(line.eval(x as u64)))
.max()
}
#[test]
fn test_train() {
test_line_interpol_with_translation(&[11, 11, 11, 12, 12, 13], Some(1));
test_line_interpol_with_translation(&[13, 12, 12, 11, 11, 11], Some(1));
test_line_interpol_with_translation(&[13, 13, 12, 11, 11, 11], Some(1));
test_line_interpol_with_translation(&[13, 13, 12, 11, 11, 11], Some(1));
test_line_interpol_with_translation(&[u64::MAX - 1, 0, 0, 1], Some(1));
test_line_interpol_with_translation(&[u64::MAX - 1, u64::MAX, 0, 1], Some(0));
test_line_interpol_with_translation(&[0, 1, 2, 3, 5], Some(0));
test_line_interpol_with_translation(&[1, 2, 3, 4], Some(0));
let data: Vec<u64> = (0..255).collect();
test_line_interpol_with_translation(&data, Some(0));
let data: Vec<u64> = (0..255).map(|el| el * 2).collect();
test_line_interpol_with_translation(&data, Some(0));
}
}

View File

@@ -1,11 +1,10 @@
use std::io::{self, Write};
use std::io::{self, Read, Write};
use std::ops::Sub;
use common::BinarySerializable;
use common::{BinarySerializable, FixedSize};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::line::Line;
use crate::serialize::NormalizedHeader;
use crate::{Column, FastFieldCodec, FastFieldCodecType};
/// Depending on the field type, a different
@@ -13,32 +12,69 @@ use crate::{Column, FastFieldCodec, FastFieldCodecType};
#[derive(Clone)]
pub struct LinearReader {
data: OwnedBytes,
linear_params: LinearParams,
header: NormalizedHeader,
bit_unpacker: BitUnpacker,
pub footer: LinearFooter,
pub slope: f32,
}
#[derive(Clone, Debug)]
pub struct LinearFooter {
pub relative_max_value: u64,
pub offset: u64,
pub first_val: u64,
pub last_val: u64,
pub num_vals: u64,
pub min_value: u64,
pub max_value: u64,
}
impl BinarySerializable for LinearFooter {
fn serialize<W: Write>(&self, write: &mut W) -> io::Result<()> {
self.relative_max_value.serialize(write)?;
self.offset.serialize(write)?;
self.first_val.serialize(write)?;
self.last_val.serialize(write)?;
self.num_vals.serialize(write)?;
self.min_value.serialize(write)?;
self.max_value.serialize(write)?;
Ok(())
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<LinearFooter> {
Ok(LinearFooter {
relative_max_value: u64::deserialize(reader)?,
offset: u64::deserialize(reader)?,
first_val: u64::deserialize(reader)?,
last_val: u64::deserialize(reader)?,
num_vals: u64::deserialize(reader)?,
min_value: u64::deserialize(reader)?,
max_value: u64::deserialize(reader)?,
})
}
}
impl FixedSize for LinearFooter {
const SIZE_IN_BYTES: usize = 56;
}
impl Column for LinearReader {
#[inline]
fn get_val(&self, doc: u64) -> u64 {
let interpoled_val: u64 = self.linear_params.line.eval(doc);
let bitpacked_diff = self.linear_params.bit_unpacker.get(doc, &self.data);
interpoled_val.wrapping_add(bitpacked_diff)
let calculated_value = get_calculated_value(self.footer.first_val, doc, self.slope);
(calculated_value + self.bit_unpacker.get(doc, &self.data)) - self.footer.offset
}
#[inline]
fn min_value(&self) -> u64 {
// The LinearReader assumes a normalized vector.
0u64
self.footer.min_value
}
#[inline]
fn max_value(&self) -> u64 {
self.header.max_value
self.footer.max_value
}
#[inline]
fn num_vals(&self) -> u64 {
self.header.num_vals
self.footer.num_vals
}
}
@@ -46,26 +82,42 @@ impl Column for LinearReader {
/// and stores the difference bitpacked.
pub struct LinearCodec;
#[derive(Debug, Clone)]
struct LinearParams {
line: Line,
bit_unpacker: BitUnpacker,
#[inline]
pub(crate) fn get_slope(first_val: u64, last_val: u64, num_vals: u64) -> f32 {
if num_vals <= 1 {
return 0.0;
}
// We calculate the slope with f64 high precision and use the result in lower precision f32
// This is done in order to handle estimations for very large values like i64::MAX
let diff = diff(last_val, first_val);
(diff / (num_vals - 1) as f64) as f32
}
impl BinarySerializable for LinearParams {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
self.line.serialize(writer)?;
self.bit_unpacker.bit_width().serialize(writer)?;
Ok(())
/// Delay the cast, to improve precision for very large u64 values.
///
/// Since i64 is mapped monotonically to u64 space, 0i64 is after the mapping i64::MAX.
/// So very large values are not uncommon.
///
/// ```rust
/// let val1 = i64::MAX;
/// let val2 = i64::MAX - 100;
/// assert_eq!(val1 - val2, 100);
/// assert_eq!(val1 as f64 - val2 as f64, 0.0);
/// ```
fn diff(val1: u64, val2: u64) -> f64 {
if val1 >= val2 {
(val1 - val2) as f64
} else {
(val2 - val1) as f64 * -1.0
}
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let line = Line::deserialize(reader)?;
let bit_width = u8::deserialize(reader)?;
Ok(Self {
line,
bit_unpacker: BitUnpacker::new(bit_width),
})
#[inline]
pub fn get_calculated_value(first_val: u64, pos: u64, slope: f32) -> u64 {
if slope < 0.0 {
first_val.saturating_sub((pos as f32 * -slope) as u64)
} else {
first_val.saturating_add((pos as f32 * slope) as u64)
}
}
@@ -75,45 +127,66 @@ impl FastFieldCodec for LinearCodec {
type Reader = LinearReader;
/// Opens a fast field given a file.
fn open_from_bytes(mut data: OwnedBytes, header: NormalizedHeader) -> io::Result<Self::Reader> {
let linear_params = LinearParams::deserialize(&mut data)?;
fn open_from_bytes(bytes: OwnedBytes) -> io::Result<Self::Reader> {
let footer_offset = bytes.len() - LinearFooter::SIZE_IN_BYTES;
let (data, mut footer) = bytes.split(footer_offset);
let footer = LinearFooter::deserialize(&mut footer)?;
let slope = get_slope(footer.first_val, footer.last_val, footer.num_vals);
let num_bits = compute_num_bits(footer.relative_max_value);
let bit_unpacker = BitUnpacker::new(num_bits);
Ok(LinearReader {
data,
linear_params,
header,
bit_unpacker,
footer,
slope,
})
}
/// Creates a new fast field serializer.
fn serialize(column: &dyn Column, write: &mut impl Write) -> io::Result<()> {
assert_eq!(column.min_value(), 0);
let line = Line::train(column);
fn serialize(write: &mut impl Write, fastfield_accessor: &dyn Column) -> io::Result<()> {
assert!(fastfield_accessor.min_value() <= fastfield_accessor.max_value());
let max_offset_from_line = column
.iter()
.enumerate()
.map(|(pos, actual_value)| {
let calculated_value = line.eval(pos as u64);
actual_value.wrapping_sub(calculated_value)
})
.max()
.unwrap();
let first_val = fastfield_accessor.get_val(0);
let last_val = fastfield_accessor.get_val(fastfield_accessor.num_vals() as u64 - 1);
let slope = get_slope(first_val, last_val, fastfield_accessor.num_vals());
// calculate offset to ensure all values are positive
let mut offset = 0;
let mut rel_positive_max = 0;
for (pos, actual_value) in fastfield_accessor.iter().enumerate() {
let calculated_value = get_calculated_value(first_val, pos as u64, slope);
if calculated_value > actual_value {
// negative value we need to apply an offset
// we ignore negative values in the max value calculation, because negative values
// will be offset to 0
offset = offset.max(calculated_value - actual_value);
} else {
// positive value no offset reuqired
rel_positive_max = rel_positive_max.max(actual_value - calculated_value);
}
}
let num_bits = compute_num_bits(max_offset_from_line);
let linear_params = LinearParams {
line,
bit_unpacker: BitUnpacker::new(num_bits),
};
linear_params.serialize(write)?;
// rel_positive_max will be adjusted by offset
let relative_max_value = rel_positive_max + offset;
let num_bits = compute_num_bits(relative_max_value);
let mut bit_packer = BitPacker::new();
for (pos, actual_value) in column.iter().enumerate() {
let calculated_value = line.eval(pos as u64);
let offset = actual_value.wrapping_sub(calculated_value);
bit_packer.write(offset, num_bits, write)?;
for (pos, val) in fastfield_accessor.iter().enumerate() {
let calculated_value = get_calculated_value(first_val, pos as u64, slope);
let diff = (val + offset) - calculated_value;
bit_packer.write(diff, num_bits, write)?;
}
bit_packer.close(write)?;
let footer = LinearFooter {
relative_max_value,
offset,
first_val,
last_val,
num_vals: fastfield_accessor.num_vals(),
min_value: fastfield_accessor.min_value(),
max_value: fastfield_accessor.max_value(),
};
footer.serialize(write)?;
Ok(())
}
@@ -121,37 +194,69 @@ impl FastFieldCodec for LinearCodec {
/// where the local maxima for the deviation of the calculated value are and
/// the offset to shift all values to >=0 is also unknown.
#[allow(clippy::question_mark)]
fn estimate(column: &dyn Column) -> Option<f32> {
if column.num_vals() < 3 {
fn estimate(fastfield_accessor: &impl Column) -> Option<f32> {
if fastfield_accessor.num_vals() < 3 {
return None; // disable compressor for this case
}
// On serialisation the offset is added to the actual value.
// We need to make sure this won't run into overflow calculation issues.
// For this we take the maximum theroretical offset and add this to the max value.
// If this doesn't overflow the algorithm should be fine
let theorethical_maximum_offset =
fastfield_accessor.max_value() - fastfield_accessor.min_value();
if fastfield_accessor
.max_value()
.checked_add(theorethical_maximum_offset)
.is_none()
{
return None;
}
let first_val = fastfield_accessor.get_val(0);
let last_val = fastfield_accessor.get_val(fastfield_accessor.num_vals() as u64 - 1);
let slope = get_slope(first_val, last_val, fastfield_accessor.num_vals());
// let's sample at 0%, 5%, 10% .. 95%, 100%
let num_vals = column.num_vals() as f32 / 100.0;
let num_vals = fastfield_accessor.num_vals() as f32 / 100.0;
let sample_positions = (0..20)
.map(|pos| (num_vals * pos as f32 * 5.0) as u64)
.map(|pos| (num_vals * pos as f32 * 5.0) as usize)
.collect::<Vec<_>>();
let line = Line::estimate(column, &sample_positions);
let estimated_bit_width = sample_positions
.into_iter()
let max_distance = sample_positions
.iter()
.map(|pos| {
let actual_value = column.get_val(pos);
let interpolated_val = line.eval(pos as u64);
actual_value.wrapping_sub(interpolated_val)
let calculated_value = get_calculated_value(first_val, *pos as u64, slope);
let actual_value = fastfield_accessor.get_val(*pos as u64);
distance(calculated_value, actual_value)
})
.map(|diff| ((diff as f32 * 1.5) * 2.0) as u64)
.map(compute_num_bits)
.max()
.unwrap_or(0);
let num_bits = (estimated_bit_width as u64 * column.num_vals() as u64) + 64;
let num_bits_uncompressed = 64 * column.num_vals();
// the theory would be that we don't have the actual max_distance, but we are close within
// 50% threshold.
// It is multiplied by 2 because in a log case scenario the line would be as much above as
// below. So the offset would = max_distance
//
let relative_max_value = (max_distance as f32 * 1.5) * 2.0;
let num_bits = compute_num_bits(relative_max_value as u64) as u64
* fastfield_accessor.num_vals()
+ LinearFooter::SIZE_IN_BYTES as u64;
let num_bits_uncompressed = 64 * fastfield_accessor.num_vals();
Some(num_bits as f32 / num_bits_uncompressed as f32)
}
}
#[inline]
fn distance<T: Sub<Output = T> + Ord>(x: T, y: T) -> T {
if x < y {
y - x
} else {
x - y
}
}
#[cfg(test)]
mod tests {
use rand::RngCore;
@@ -163,14 +268,34 @@ mod tests {
crate::tests::create_and_validate::<LinearCodec>(data, name)
}
#[test]
fn get_calculated_value_test() {
// pos slope
assert_eq!(get_calculated_value(100, 10, 5.0), 150);
// neg slope
assert_eq!(get_calculated_value(100, 10, -5.0), 50);
// pos slope, very high values
assert_eq!(
get_calculated_value(i64::MAX as u64, 10, 5.0),
i64::MAX as u64 + 50
);
// neg slope, very high values
assert_eq!(
get_calculated_value(i64::MAX as u64, 10, -5.0),
i64::MAX as u64 - 50
);
}
#[test]
fn test_compression() {
let data = (10..=6_000_u64).collect::<Vec<_>>();
let (estimate, actual_compression) =
create_and_validate(&data, "simple monotonically large").unwrap();
assert_le!(actual_compression, 0.001);
assert_le!(estimate, 0.02);
assert!(actual_compression < 0.01);
assert!(estimate < 0.01);
}
#[test]
@@ -212,6 +337,7 @@ mod tests {
#[test]
fn linear_interpol_fast_field_test_simple() {
let data = (10..=20_u64).collect::<Vec<_>>();
create_and_validate(&data, "simple monotonically");
}

View File

@@ -1,130 +1,36 @@
#[macro_use]
extern crate prettytable;
use std::collections::HashSet;
use std::env;
use std::io::BufRead;
use std::net::{IpAddr, Ipv6Addr};
use std::str::FromStr;
use fastfield_codecs::{open_u128, serialize_u128, Column, FastFieldCodecType, VecColumn};
use itertools::Itertools;
use measure_time::print_time;
use ownedbytes::OwnedBytes;
use fastfield_codecs::bitpacked::BitpackedCodec;
use fastfield_codecs::blockwise_linear::BlockwiseLinearCodec;
use fastfield_codecs::linear::LinearCodec;
use fastfield_codecs::{Column, FastFieldCodec, FastFieldCodecType, FastFieldStats};
use prettytable::{Cell, Row, Table};
fn print_set_stats(ip_addrs: &[u128]) {
println!("NumIps\t{}", ip_addrs.len());
let ip_addr_set: HashSet<u128> = ip_addrs.iter().cloned().collect();
println!("NumUniqueIps\t{}", ip_addr_set.len());
let ratio_unique = ip_addr_set.len() as f64 / ip_addrs.len() as f64;
println!("RatioUniqueOverTotal\t{ratio_unique:.4}");
struct Data<'a>(&'a [u64]);
// histogram
let mut ip_addrs = ip_addrs.to_vec();
ip_addrs.sort();
let mut cnts: Vec<usize> = ip_addrs
.into_iter()
.dedup_with_count()
.map(|(cnt, _)| cnt)
.collect();
cnts.sort();
let top_256_cnt: usize = cnts.iter().rev().take(256).sum();
let top_128_cnt: usize = cnts.iter().rev().take(128).sum();
let top_64_cnt: usize = cnts.iter().rev().take(64).sum();
let top_8_cnt: usize = cnts.iter().rev().take(8).sum();
let total: usize = cnts.iter().sum();
println!("{}", total);
println!("{}", top_256_cnt);
println!("{}", top_128_cnt);
println!("Percentage Top8 {:02}", top_8_cnt as f32 / total as f32);
println!("Percentage Top64 {:02}", top_64_cnt as f32 / total as f32);
println!("Percentage Top128 {:02}", top_128_cnt as f32 / total as f32);
println!("Percentage Top256 {:02}", top_256_cnt as f32 / total as f32);
let mut cnts: Vec<(usize, usize)> = cnts.into_iter().dedup_with_count().collect();
cnts.sort_by(|a, b| {
if a.1 == b.1 {
a.0.cmp(&b.0)
} else {
b.1.cmp(&a.1)
}
});
}
fn ip_dataset() -> Vec<u128> {
let mut ip_addr_v4 = 0;
let stdin = std::io::stdin();
let ip_addrs: Vec<u128> = stdin
.lock()
.lines()
.flat_map(|line| {
let line = line.unwrap();
let line = line.trim();
let ip_addr = IpAddr::from_str(line.trim()).ok()?;
if ip_addr.is_ipv4() {
ip_addr_v4 += 1;
}
let ip_addr_v6: Ipv6Addr = match ip_addr {
IpAddr::V4(v4) => v4.to_ipv6_mapped(),
IpAddr::V6(v6) => v6,
};
Some(ip_addr_v6)
})
.map(|ip_v6| u128::from_be_bytes(ip_v6.octets()))
.collect();
println!("IpAddrsAny\t{}", ip_addrs.len());
println!("IpAddrsV4\t{}", ip_addr_v4);
ip_addrs
}
fn bench_ip() {
let dataset = ip_dataset();
print_set_stats(&dataset);
// Chunks
{
let mut data = vec![];
for dataset in dataset.chunks(500_000) {
serialize_u128(VecColumn::from(dataset), &mut data).unwrap();
}
let compression = data.len() as f64 / (dataset.len() * 16) as f64;
println!("Compression 50_000 chunks {:.4}", compression);
println!(
"Num Bits per elem {:.2}",
(data.len() * 8) as f32 / dataset.len() as f32
);
impl<'a> Column for Data<'a> {
fn get_val(&self, position: u64) -> u64 {
self.0[position as usize]
}
let mut data = vec![];
serialize_u128(VecColumn::from(&dataset), &mut data).unwrap();
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = u64> + 'b> {
Box::new(self.0.iter().cloned())
}
let compression = data.len() as f64 / (dataset.len() * 16) as f64;
println!("Compression {:.2}", compression);
println!(
"Num Bits per elem {:.2}",
(data.len() * 8) as f32 / dataset.len() as f32
);
fn min_value(&self) -> u64 {
*self.0.iter().min().unwrap_or(&0)
}
let decompressor = open_u128(OwnedBytes::new(data)).unwrap();
// Sample some ranges
for value in dataset.iter().take(1110).skip(1100).cloned() {
print_time!("get range");
let doc_values = decompressor.get_between_vals(value..=value);
println!("{:?}", doc_values.len());
fn max_value(&self) -> u64 {
*self.0.iter().max().unwrap_or(&0)
}
fn num_vals(&self) -> u64 {
self.0.len() as u64
}
}
fn main() {
if env::args().nth(1).unwrap() == "bench_ip" {
bench_ip();
return;
}
let mut table = Table::new();
// Add a row per time
@@ -132,9 +38,10 @@ fn main() {
for (data, data_set_name) in get_codec_test_data_sets() {
let results: Vec<(f32, f32, FastFieldCodecType)> = [
serialize_with_codec(&data, FastFieldCodecType::Bitpacked),
serialize_with_codec(&data, FastFieldCodecType::Linear),
serialize_with_codec(&data, FastFieldCodecType::BlockwiseLinear),
serialize_with_codec::<LinearCodec>(&data),
serialize_with_codec::<BlockwiseLinearCodec>(&data),
serialize_with_codec::<BlockwiseLinearCodec>(&data),
serialize_with_codec::<BitpackedCodec>(&data),
]
.into_iter()
.flatten()
@@ -200,14 +107,23 @@ pub fn get_codec_test_data_sets() -> Vec<(Vec<u64>, &'static str)> {
data_and_names
}
pub fn serialize_with_codec(
pub fn serialize_with_codec<C: FastFieldCodec>(
data: &[u64],
codec_type: FastFieldCodecType,
) -> Option<(f32, f32, FastFieldCodecType)> {
let col = VecColumn::from(data);
let estimation = fastfield_codecs::estimate(&col, codec_type)?;
let data = Data(data);
let estimation = C::estimate(&data)?;
let mut out = Vec::new();
fastfield_codecs::serialize(&col, &mut out, &[codec_type]).ok()?;
let actual_compression = out.len() as f32 / (col.num_vals() * 8) as f32;
Some((estimation, actual_compression, codec_type))
C::serialize(&mut out, &data).unwrap();
let actual_compression = out.len() as f32 / (data.num_vals() * 8) as f32;
Some((estimation, actual_compression, C::CODEC_TYPE))
}
pub fn stats_from_vec(data: &[u64]) -> FastFieldStats {
let min_value = data.iter().cloned().min().unwrap_or(0);
let max_value = data.iter().cloned().max().unwrap_or(0);
FastFieldStats {
min_value,
max_value,
num_vals: data.len() as u64,
}
}

View File

@@ -1,56 +0,0 @@
pub trait MonotonicallyMappableToU64: 'static + PartialOrd + Copy + Send + Sync {
/// Converts a value to u64.
///
/// Internally all fast field values are encoded as u64.
fn to_u64(self) -> u64;
/// Converts a value from u64
///
/// Internally all fast field values are encoded as u64.
/// **Note: To be used for converting encoded Term, Posting values.**
fn from_u64(val: u64) -> Self;
}
impl MonotonicallyMappableToU64 for u64 {
fn to_u64(self) -> u64 {
self
}
fn from_u64(val: u64) -> Self {
val
}
}
impl MonotonicallyMappableToU64 for i64 {
#[inline(always)]
fn to_u64(self) -> u64 {
common::i64_to_u64(self)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
common::u64_to_i64(val)
}
}
impl MonotonicallyMappableToU64 for bool {
#[inline(always)]
fn to_u64(self) -> u64 {
u64::from(self)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
val > 0
}
}
impl MonotonicallyMappableToU64 for f64 {
fn to_u64(self) -> u64 {
common::f64_to_u64(self)
}
fn from_u64(val: u64) -> Self {
common::u64_to_f64(val)
}
}

View File

@@ -1,283 +0,0 @@
// Copyright (C) 2022 Quickwit, Inc.
//
// Quickwit is offered under the AGPL v3.0 and as commercial software.
// For commercial licensing, contact us at hello@quickwit.io.
//
// AGPL:
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as
// published by the Free Software Foundation, either version 3 of the
// License, or (at your option) any later version.
//
// This program is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
use std::io;
use std::num::NonZeroU64;
use std::sync::Arc;
use common::{BinarySerializable, VInt};
use fastdivide::DividerU64;
use log::{trace, warn};
use measure_time::trace_time;
use ownedbytes::OwnedBytes;
use crate::bitpacked::BitpackedCodec;
use crate::blockwise_linear::BlockwiseLinearCodec;
use crate::compact_space::CompactSpaceCompressor;
use crate::linear::LinearCodec;
use crate::{
monotonic_map_column, Column, FastFieldCodec, FastFieldCodecType, MonotonicallyMappableToU64,
VecColumn, ALL_CODEC_TYPES,
};
/// The normalized header gives some parameters after applying the following
/// normalization of the vector:
/// val -> (val - min_value) / gcd
///
/// By design, after normalization, `min_value = 0` and `gcd = 1`.
#[derive(Debug, Copy, Clone)]
pub struct NormalizedHeader {
pub num_vals: u64,
pub max_value: u64,
}
#[derive(Debug, Copy, Clone)]
pub(crate) struct Header {
pub num_vals: u64,
pub min_value: u64,
pub max_value: u64,
pub gcd: Option<NonZeroU64>,
pub codec_type: FastFieldCodecType,
}
impl Header {
pub fn normalized(self) -> NormalizedHeader {
let max_value =
(self.max_value - self.min_value) / self.gcd.map(|gcd| gcd.get()).unwrap_or(1);
NormalizedHeader {
num_vals: self.num_vals,
max_value,
}
}
pub fn normalize_column<C: Column>(&self, from_column: C) -> impl Column {
let min_value = self.min_value;
let gcd = self.gcd.map(|gcd| gcd.get()).unwrap_or(1);
let divider = DividerU64::divide_by(gcd);
monotonic_map_column(from_column, move |val| divider.divide(val - min_value))
}
pub fn compute_header(
column: impl Column<u64>,
codecs: &[FastFieldCodecType],
) -> Option<Header> {
let num_vals = column.num_vals();
let min_value = column.min_value();
let max_value = column.max_value();
let gcd = crate::gcd::find_gcd(column.iter().map(|val| val - min_value))
.filter(|gcd| gcd.get() > 1u64);
let divider = DividerU64::divide_by(gcd.map(|gcd| gcd.get()).unwrap_or(1u64));
let shifted_column = monotonic_map_column(&column, |val| divider.divide(val - min_value));
let codec_type = detect_codec(shifted_column, codecs)?;
Some(Header {
num_vals,
min_value,
max_value,
gcd,
codec_type,
})
}
}
impl BinarySerializable for Header {
fn serialize<W: io::Write>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.num_vals).serialize(writer)?;
VInt(self.min_value).serialize(writer)?;
VInt(self.max_value - self.min_value).serialize(writer)?;
if let Some(gcd) = self.gcd {
VInt(gcd.get()).serialize(writer)?;
} else {
VInt(0u64).serialize(writer)?;
}
self.codec_type.serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let num_vals = VInt::deserialize(reader)?.0;
let min_value = VInt::deserialize(reader)?.0;
let amplitude = VInt::deserialize(reader)?.0;
let max_value = min_value + amplitude;
let gcd_u64 = VInt::deserialize(reader)?.0;
let codec_type = FastFieldCodecType::deserialize(reader)?;
Ok(Header {
num_vals,
min_value,
max_value,
gcd: NonZeroU64::new(gcd_u64),
codec_type,
})
}
}
pub fn estimate<T: MonotonicallyMappableToU64>(
typed_column: impl Column<T>,
codec_type: FastFieldCodecType,
) -> Option<f32> {
let column = monotonic_map_column(typed_column, T::to_u64);
let min_value = column.min_value();
let gcd = crate::gcd::find_gcd(column.iter().map(|val| val - min_value))
.filter(|gcd| gcd.get() > 1u64);
let divider = DividerU64::divide_by(gcd.map(|gcd| gcd.get()).unwrap_or(1u64));
let normalized_column = monotonic_map_column(&column, |val| divider.divide(val - min_value));
match codec_type {
FastFieldCodecType::Bitpacked => BitpackedCodec::estimate(&normalized_column),
FastFieldCodecType::Linear => LinearCodec::estimate(&normalized_column),
FastFieldCodecType::BlockwiseLinear => BlockwiseLinearCodec::estimate(&normalized_column),
}
}
pub fn serialize_u128(
typed_column: impl Column<u128>,
output: &mut impl io::Write,
) -> io::Result<()> {
// TODO write header, to later support more codecs
let compressor = CompactSpaceCompressor::train_from(&typed_column);
compressor
.compress_into(typed_column.iter(), output)
.unwrap();
Ok(())
}
pub fn serialize<T: MonotonicallyMappableToU64>(
typed_column: impl Column<T>,
output: &mut impl io::Write,
codecs: &[FastFieldCodecType],
) -> io::Result<()> {
let column = monotonic_map_column(typed_column, T::to_u64);
let header = Header::compute_header(&column, codecs).ok_or_else(|| {
io::Error::new(
io::ErrorKind::InvalidInput,
format!(
"Data cannot be serialized with this list of codec. {:?}",
codecs
),
)
})?;
header.serialize(output)?;
let normalized_column = header.normalize_column(column);
assert_eq!(normalized_column.min_value(), 0u64);
serialize_given_codec(normalized_column, header.codec_type, output)?;
Ok(())
}
fn detect_codec(
column: impl Column<u64>,
codecs: &[FastFieldCodecType],
) -> Option<FastFieldCodecType> {
let mut estimations = Vec::new();
for &codec in codecs {
trace_time!("estimate time for codec: {:?}", codec);
let estimation_opt = match codec {
FastFieldCodecType::Bitpacked => BitpackedCodec::estimate(&column),
FastFieldCodecType::Linear => LinearCodec::estimate(&column),
FastFieldCodecType::BlockwiseLinear => BlockwiseLinearCodec::estimate(&column),
};
if let Some(estimation) = estimation_opt {
estimations.push((estimation, codec));
}
}
if let Some(broken_estimation) = estimations.iter().find(|estimation| estimation.0.is_nan()) {
warn!(
"broken estimation for fast field codec {:?}",
broken_estimation.1
);
}
// removing nan values for codecs with broken calculations, and max values which disables
// codecs
estimations.retain(|estimation| !estimation.0.is_nan() && estimation.0 != f32::MAX);
estimations.sort_by(|(score_left, _), (score_right, _)| score_left.total_cmp(score_right));
trace!("Chosen Codec {:?}", estimations.first()?.1);
Some(estimations.first()?.1)
}
fn serialize_given_codec(
column: impl Column<u64>,
codec_type: FastFieldCodecType,
output: &mut impl io::Write,
) -> io::Result<()> {
trace_time!(
"Serialize time for codec: {:?}, num_vals {}",
codec_type,
column.num_vals()
);
match codec_type {
FastFieldCodecType::Bitpacked => {
BitpackedCodec::serialize(&column, output)?;
}
FastFieldCodecType::Linear => {
LinearCodec::serialize(&column, output)?;
}
FastFieldCodecType::BlockwiseLinear => {
BlockwiseLinearCodec::serialize(&column, output)?;
}
}
output.flush()?;
Ok(())
}
pub fn serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default>(
column: &[T],
) -> Arc<dyn Column<T>> {
let mut buffer = Vec::new();
super::serialize(VecColumn::from(&column), &mut buffer, &ALL_CODEC_TYPES).unwrap();
super::open(OwnedBytes::new(buffer)).unwrap()
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_serialize_deserialize() {
let original = [1u64, 5u64, 10u64];
let restored: Vec<u64> = serialize_and_load(&original[..]).iter().collect();
assert_eq!(&restored, &original[..]);
}
#[test]
fn test_fastfield_bool_size_bitwidth_1() {
let mut buffer = Vec::new();
let col = VecColumn::from(&[false, true][..]);
serialize(col, &mut buffer, &ALL_CODEC_TYPES).unwrap();
// 5 bytes of header, 1 byte of value, 7 bytes of padding.
assert_eq!(buffer.len(), 5 + 8);
}
#[test]
fn test_fastfield_bool_bit_size_bitwidth_0() {
let mut buffer = Vec::new();
let col = VecColumn::from(&[true][..]);
serialize(col, &mut buffer, &ALL_CODEC_TYPES).unwrap();
// 5 bytes of header, 0 bytes of value, 7 bytes of padding.
assert_eq!(buffer.len(), 5 + 7);
}
#[test]
fn test_fastfield_gcd() {
let mut buffer = Vec::new();
let vals: Vec<u64> = (0..80).map(|val| (val % 7) * 1_000u64).collect();
let col = VecColumn::from(&vals[..]);
serialize(col, &mut buffer, &[FastFieldCodecType::Bitpacked]).unwrap();
// Values are stored over 3 bits.
assert_eq!(buffer.len(), 7 + (3 * 80 / 8) + 7);
}
}

View File

@@ -23,7 +23,7 @@ const ESCAPED_SPECIAL_CHARS_PATTERN: &str = r#"\\(\+|\^|`|:|\{|\}|"|\[|\]|\(|\)|
/// Parses a field_name
/// A field name must have at least one character and be followed by a colon.
/// All characters are allowed including special characters `SPECIAL_CHARS`, but these
/// need to be escaped with a backslash character '\'.
/// need to be escaped with a backslack character '\'.
fn field_name<'a>() -> impl Parser<&'a str, Output = String> {
static ESCAPED_SPECIAL_CHARS_RE: Lazy<Regex> =
Lazy::new(|| Regex::new(ESCAPED_SPECIAL_CHARS_PATTERN).unwrap());
@@ -68,7 +68,7 @@ fn word<'a>() -> impl Parser<&'a str, Output = String> {
///
/// NOTE: also accepts 999999-99-99T99:99:99.266051969+99:99
/// We delegate rejecting such invalid dates to the logical AST computation code
/// which invokes `time::OffsetDateTime::parse(..., &Rfc3339)` on the value to actually parse
/// which invokes time::OffsetDateTime::parse(..., &Rfc3339) on the value to actually parse
/// it (instead of merely extracting the datetime value as string as done here).
fn date_time<'a>() -> impl Parser<&'a str, Output = String> {
let two_digits = || recognize::<String, _, _>((digit(), digit()));

View File

@@ -1,7 +1,7 @@
//! Contains the aggregation request tree. Used to build an
//! [`AggregationCollector`](super::AggregationCollector).
//! [AggregationCollector](super::AggregationCollector).
//!
//! [`Aggregations`] is the top level entry point to create a request, which is a `HashMap<String,
//! [Aggregations] is the top level entry point to create a request, which is a `HashMap<String,
//! Aggregation>`.
//!
//! Requests are compatible with the json format of elasticsearch.
@@ -54,8 +54,8 @@ use super::bucket::{HistogramAggregation, TermsAggregation};
use super::metric::{AverageAggregation, StatsAggregation};
use super::VecWithNames;
/// The top-level aggregation request structure, which contains [`Aggregation`] and their user
/// defined names. It is also used in [buckets](BucketAggregation) to define sub-aggregations.
/// The top-level aggregation request structure, which contains [Aggregation] and their user defined
/// names. It is also used in [buckets](BucketAggregation) to define sub-aggregations.
///
/// The key is the user defined name of the aggregation.
pub type Aggregations = HashMap<String, Aggregation>;
@@ -139,15 +139,15 @@ pub fn get_fast_field_names(aggs: &Aggregations) -> HashSet<String> {
fast_field_names
}
/// Aggregation request of [`BucketAggregation`] or [`MetricAggregation`].
/// Aggregation request of [BucketAggregation] or [MetricAggregation].
///
/// An aggregation is either a bucket or a metric.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
#[serde(untagged)]
pub enum Aggregation {
/// Bucket aggregation, see [`BucketAggregation`] for details.
/// Bucket aggregation, see [BucketAggregation] for details.
Bucket(BucketAggregation),
/// Metric aggregation, see [`MetricAggregation`] for details.
/// Metric aggregation, see [MetricAggregation] for details.
Metric(MetricAggregation),
}

View File

@@ -4,14 +4,14 @@ use std::rc::Rc;
use std::sync::atomic::AtomicU32;
use std::sync::Arc;
use fastfield_codecs::Column;
use super::agg_req::{Aggregation, Aggregations, BucketAggregationType, MetricAggregation};
use super::bucket::{HistogramAggregation, RangeAggregation, TermsAggregation};
use super::metric::{AverageAggregation, StatsAggregation};
use super::segment_agg_result::BucketCount;
use super::VecWithNames;
use crate::fastfield::{type_and_cardinality, FastType, MultiValuedFastFieldReader};
use crate::fastfield::{
type_and_cardinality, DynamicFastFieldReader, FastType, MultiValuedFastFieldReader,
};
use crate::schema::{Cardinality, Type};
use crate::{InvertedIndexReader, SegmentReader, TantivyError};
@@ -37,16 +37,10 @@ impl AggregationsWithAccessor {
#[derive(Clone)]
pub(crate) enum FastFieldAccessor {
Multi(MultiValuedFastFieldReader<u64>),
Single(Arc<dyn Column<u64>>),
Single(DynamicFastFieldReader<u64>),
}
impl FastFieldAccessor {
pub fn as_single(&self) -> Option<&dyn Column<u64>> {
match self {
FastFieldAccessor::Multi(_) => None,
FastFieldAccessor::Single(reader) => Some(&**reader),
}
}
pub fn into_single(self) -> Option<Arc<dyn Column<u64>>> {
pub fn as_single(&self) -> Option<&DynamicFastFieldReader<u64>> {
match self {
FastFieldAccessor::Multi(_) => None,
FastFieldAccessor::Single(reader) => Some(reader),
@@ -124,7 +118,7 @@ impl BucketAggregationWithAccessor {
pub struct MetricAggregationWithAccessor {
pub metric: MetricAggregation,
pub field_type: Type,
pub accessor: Arc<dyn Column>,
pub accessor: DynamicFastFieldReader<u64>,
}
impl MetricAggregationWithAccessor {
@@ -140,8 +134,9 @@ impl MetricAggregationWithAccessor {
Ok(MetricAggregationWithAccessor {
accessor: accessor
.into_single()
.expect("unexpected fast field cardinality"),
.as_single()
.expect("unexpected fast field cardinality")
.clone(),
field_type,
metric: metric.clone(),
})

View File

@@ -113,14 +113,14 @@ pub enum BucketResult {
///
/// If there are holes depends on the request, if min_doc_count is 0, then there are no
/// holes between the first and last bucket.
/// See [`HistogramAggregation`](super::bucket::HistogramAggregation)
/// See [HistogramAggregation](super::bucket::HistogramAggregation)
buckets: BucketEntries<BucketEntry>,
},
/// This is the term result
Terms {
/// The buckets.
///
/// See [`TermsAggregation`](super::bucket::TermsAggregation)
/// See [TermsAggregation](super::bucket::TermsAggregation)
buckets: Vec<BucketEntry>,
/// The number of documents that didnt make it into to TOP N due to shard_size or size
sum_other_doc_count: u64,
@@ -234,10 +234,10 @@ pub struct RangeBucketEntry {
#[serde(flatten)]
/// sub-aggregations in this bucket.
pub sub_aggregation: AggregationResults,
/// The from range of the bucket. Equals `f64::MIN` when `None`.
/// The from range of the bucket. Equals f64::MIN when None.
#[serde(skip_serializing_if = "Option::is_none")]
pub from: Option<f64>,
/// The to range of the bucket. Equals `f64::MAX` when `None`.
/// The to range of the bucket. Equals f64::MAX when None.
#[serde(skip_serializing_if = "Option::is_none")]
pub to: Option<f64>,
}

View File

@@ -15,6 +15,7 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResults, IntermediateBucketResult, IntermediateHistogramBucketEntry,
};
use crate::aggregation::segment_agg_result::SegmentAggregationResultsCollector;
use crate::fastfield::DynamicFastFieldReader;
use crate::schema::Type;
use crate::{DocId, TantivyError};
@@ -37,14 +38,14 @@ use crate::{DocId, TantivyError};
/// [hard_bounds](HistogramAggregation::hard_bounds).
///
/// # Result
/// Result type is [`BucketResult`](crate::aggregation::agg_result::BucketResult) with
/// [`BucketEntry`](crate::aggregation::agg_result::BucketEntry) on the
/// `AggregationCollector`.
/// Result type is [BucketResult](crate::aggregation::agg_result::BucketResult) with
/// [BucketEntry](crate::aggregation::agg_result::BucketEntry) on the
/// AggregationCollector.
///
/// Result type is
/// [`IntermediateBucketResult`](crate::aggregation::intermediate_agg_result::IntermediateBucketResult) with
/// [`IntermediateHistogramBucketEntry`](crate::aggregation::intermediate_agg_result::IntermediateHistogramBucketEntry) on the
/// `DistributedAggregationCollector`.
/// [crate::aggregation::intermediate_agg_result::IntermediateBucketResult] with
/// [crate::aggregation::intermediate_agg_result::IntermediateHistogramBucketEntry] on the
/// DistributedAggregationCollector.
///
/// # Limitations/Compatibility
///
@@ -61,7 +62,7 @@ use crate::{DocId, TantivyError};
/// ```
///
/// Response
/// See [`BucketEntry`](crate::aggregation::agg_result::BucketEntry)
/// See [BucketEntry](crate::aggregation::agg_result::BucketEntry)
#[derive(Clone, Debug, Default, PartialEq, Serialize, Deserialize)]
pub struct HistogramAggregation {
@@ -263,7 +264,7 @@ impl SegmentHistogramCollector {
req: &HistogramAggregation,
sub_aggregation: &AggregationsWithAccessor,
field_type: Type,
accessor: &dyn Column<u64>,
accessor: &DynamicFastFieldReader<u64>,
) -> crate::Result<Self> {
req.validate()?;
let min = f64_from_fastfield_u64(accessor.min_value(), &field_type);
@@ -425,7 +426,7 @@ impl SegmentHistogramCollector {
let bucket = &mut self.buckets[bucket_pos];
bucket.doc_count += 1;
if let Some(sub_aggregation) = self.sub_aggregations.as_mut() {
sub_aggregation[bucket_pos].collect(doc, bucket_with_accessor)?;
(&mut sub_aggregation[bucket_pos]).collect(doc, bucket_with_accessor)?;
}
Ok(())
}
@@ -518,7 +519,7 @@ pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
/// Applies req extended_bounds/hard_bounds on the min_max value
///
/// May return `(f64::MAX, f64::MIN)`, if there is no range.
/// May return (f64::MAX, f64::MIN), if there is no range.
fn get_req_min_max(req: &HistogramAggregation, min_max: Option<(f64, f64)>) -> (f64, f64) {
let (mut min, mut max) = min_max.unwrap_or((f64::MAX, f64::MIN));

View File

@@ -1,11 +1,11 @@
//! Module for all bucket aggregations.
//!
//! BucketAggregations create buckets of documents
//! [`BucketAggregation`](super::agg_req::BucketAggregation).
//! [BucketAggregation](super::agg_req::BucketAggregation).
//!
//! Results of final buckets are [`BucketResult`](super::agg_result::BucketResult).
//! Results of final buckets are [BucketResult](super::agg_result::BucketResult).
//! Results of intermediate buckets are
//! [`IntermediateBucketResult`](super::intermediate_agg_result::IntermediateBucketResult)
//! [IntermediateBucketResult](super::intermediate_agg_result::IntermediateBucketResult)
mod histogram;
mod range;

View File

@@ -1,6 +1,7 @@
use std::fmt::Debug;
use std::ops::Range;
use fastfield_codecs::Column;
use fnv::FnvHashMap;
use serde::{Deserialize, Serialize};
@@ -22,14 +23,14 @@ use crate::{DocId, TantivyError};
/// against each bucket range. Note that this aggregation includes the from value and excludes the
/// to value for each range.
///
/// Result type is [`BucketResult`](crate::aggregation::agg_result::BucketResult) with
/// [`RangeBucketEntry`](crate::aggregation::agg_result::RangeBucketEntry) on the
/// `AggregationCollector`.
/// Result type is [BucketResult](crate::aggregation::agg_result::BucketResult) with
/// [RangeBucketEntry](crate::aggregation::agg_result::RangeBucketEntry) on the
/// AggregationCollector.
///
/// Result type is
/// [`IntermediateBucketResult`](crate::aggregation::intermediate_agg_result::IntermediateBucketResult) with
/// [`IntermediateRangeBucketEntry`](crate::aggregation::intermediate_agg_result::IntermediateRangeBucketEntry) on the
/// `DistributedAggregationCollector`.
/// [crate::aggregation::intermediate_agg_result::IntermediateBucketResult] with
/// [crate::aggregation::intermediate_agg_result::IntermediateRangeBucketEntry] on the
/// DistributedAggregationCollector.
///
/// # Limitations/Compatibility
/// Overlapping ranges are not yet supported.
@@ -67,11 +68,11 @@ pub struct RangeAggregationRange {
#[serde(skip_serializing_if = "Option::is_none", default)]
pub key: Option<String>,
/// The from range value, which is inclusive in the range.
/// `None` equals to an open ended interval.
/// None equals to an open ended interval.
#[serde(skip_serializing_if = "Option::is_none", default)]
pub from: Option<f64>,
/// The to range value, which is not inclusive in the range.
/// `None` equals to an open ended interval.
/// None equals to an open ended interval.
#[serde(skip_serializing_if = "Option::is_none", default)]
pub to: Option<f64>,
}
@@ -101,7 +102,7 @@ impl From<Range<f64>> for RangeAggregationRange {
pub(crate) struct InternalRangeAggregationRange {
/// Custom key for the range bucket
key: Option<String>,
/// `u64` range value
/// u64 range value
range: Range<u64>,
}
@@ -131,9 +132,9 @@ pub(crate) struct SegmentRangeBucketEntry {
pub key: Key,
pub doc_count: u64,
pub sub_aggregation: Option<SegmentAggregationResultsCollector>,
/// The from range of the bucket. Equals `f64::MIN` when `None`.
/// The from range of the bucket. Equals f64::MIN when None.
pub from: Option<f64>,
/// The to range of the bucket. Equals `f64::MAX` when `None`. Open interval, `to` is not
/// The to range of the bucket. Equals f64::MAX when None. Open interval, `to` is not
/// inclusive.
pub to: Option<f64>,
}
@@ -261,7 +262,7 @@ impl SegmentRangeCollector {
let accessor = bucket_with_accessor
.accessor
.as_single()
.expect("unexpected fast field cardinality");
.expect("unexpected fast field cardinatility");
for docs in iter.by_ref() {
let val1 = accessor.get_val(docs[0] as u64);
let val2 = accessor.get_val(docs[1] as u64);
@@ -423,13 +424,12 @@ pub(crate) fn range_to_key(range: &Range<u64>, field_type: &Type) -> Key {
#[cfg(test)]
mod tests {
use fastfield_codecs::MonotonicallyMappableToU64;
use super::*;
use crate::aggregation::agg_req::{
Aggregation, Aggregations, BucketAggregation, BucketAggregationType,
};
use crate::aggregation::tests::{exec_request_with_query, get_test_index_with_num_docs};
use crate::fastfield::FastValue;
pub fn get_collector_from_ranges(
ranges: Vec<RangeAggregationRange>,

View File

@@ -31,7 +31,7 @@ use crate::{DocId, TantivyError};
///
/// Even with a larger `segment_size` value, doc_count values for a terms aggregation may be
/// approximate. As a result, any sub-aggregations on the terms aggregation may also be approximate.
/// `sum_other_doc_count` is the number of documents that didnt make it into the top size
/// `sum_other_doc_count` is the number of documents that didnt make it into the the top size
/// terms. If this is greater than 0, you can be sure that the terms agg had to throw away some
/// buckets, either because they didnt fit into size on the root node or they didnt fit into
/// `segment_size` on the segment node.
@@ -42,14 +42,14 @@ use crate::{DocId, TantivyError};
/// each segment. Its the sum of the size of the largest bucket on each segment that didnt fit
/// into segment_size.
///
/// Result type is [`BucketResult`](crate::aggregation::agg_result::BucketResult) with
/// [`TermBucketEntry`](crate::aggregation::agg_result::BucketEntry) on the
/// `AggregationCollector`.
/// Result type is [BucketResult](crate::aggregation::agg_result::BucketResult) with
/// [TermBucketEntry](crate::aggregation::agg_result::BucketEntry) on the
/// AggregationCollector.
///
/// Result type is
/// [`IntermediateBucketResult`](crate::aggregation::intermediate_agg_result::IntermediateBucketResult) with
/// [`IntermediateTermBucketEntry`](crate::aggregation::intermediate_agg_result::IntermediateTermBucketEntry) on the
/// `DistributedAggregationCollector`.
/// [crate::aggregation::intermediate_agg_result::IntermediateBucketResult] with
/// [crate::aggregation::intermediate_agg_result::IntermediateTermBucketEntry] on the
/// DistributedAggregationCollector.
///
/// # Limitations/Compatibility
///

View File

@@ -131,7 +131,7 @@ fn merge_fruits(
}
}
/// `AggregationSegmentCollector` does the aggregation collection on a segment.
/// AggregationSegmentCollector does the aggregation collection on a segment.
pub struct AggregationSegmentCollector {
aggs_with_accessor: AggregationsWithAccessor,
result: SegmentAggregationResultsCollector,
@@ -139,8 +139,8 @@ pub struct AggregationSegmentCollector {
}
impl AggregationSegmentCollector {
/// Creates an `AggregationSegmentCollector from` an [`Aggregations`] request and a segment
/// reader. Also includes validation, e.g. checking field types and existence.
/// Creates an AggregationSegmentCollector from an [Aggregations] request and a segment reader.
/// Also includes validation, e.g. checking field types and existence.
pub fn from_agg_req_and_reader(
agg: &Aggregations,
reader: &SegmentReader,

View File

@@ -108,10 +108,10 @@ impl IntermediateAggregationResults {
Self { metrics, buckets }
}
/// Merge another intermediate aggregation result into this result.
/// Merge an other intermediate aggregation result into this result.
///
/// The order of the values need to be the same on both results. This is ensured when the same
/// (key values) are present on the underlying `VecWithNames` struct.
/// (key values) are present on the underlying VecWithNames struct.
pub fn merge_fruits(&mut self, other: IntermediateAggregationResults) {
if let (Some(buckets_left), Some(buckets_right)) = (&mut self.buckets, other.buckets) {
for (bucket_left, bucket_right) in
@@ -560,10 +560,10 @@ pub struct IntermediateRangeBucketEntry {
pub doc_count: u64,
/// The sub_aggregation in this bucket.
pub sub_aggregation: IntermediateAggregationResults,
/// The from range of the bucket. Equals `f64::MIN` when `None`.
/// The from range of the bucket. Equals f64::MIN when None.
#[serde(skip_serializing_if = "Option::is_none")]
pub from: Option<f64>,
/// The to range of the bucket. Equals `f64::MAX` when `None`.
/// The to range of the bucket. Equals f64::MAX when None.
#[serde(skip_serializing_if = "Option::is_none")]
pub to: Option<f64>,
}

View File

@@ -4,6 +4,7 @@ use fastfield_codecs::Column;
use serde::{Deserialize, Serialize};
use crate::aggregation::f64_from_fastfield_u64;
use crate::fastfield::DynamicFastFieldReader;
use crate::schema::Type;
use crate::DocId;
@@ -57,7 +58,7 @@ impl SegmentAverageCollector {
data: Default::default(),
}
}
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &dyn Column<u64>) {
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &DynamicFastFieldReader<u64>) {
let mut iter = doc.chunks_exact(4);
for docs in iter.by_ref() {
let val1 = field.get_val(docs[0] as u64);

View File

@@ -2,13 +2,14 @@ use fastfield_codecs::Column;
use serde::{Deserialize, Serialize};
use crate::aggregation::f64_from_fastfield_u64;
use crate::fastfield::DynamicFastFieldReader;
use crate::schema::Type;
use crate::{DocId, TantivyError};
/// A multi-value metric aggregation that computes stats of numeric values that are
/// extracted from the aggregated documents.
/// Supported field types are `u64`, `i64`, and `f64`.
/// See [`Stats`] for returned statistics.
/// Supported field types are u64, i64, and f64.
/// See [Stats] for returned statistics.
///
/// # JSON Format
/// ```json
@@ -43,13 +44,13 @@ pub struct Stats {
pub count: usize,
/// The sum of the fast field values.
pub sum: f64,
/// The standard deviation of the fast field values. `None` for count == 0.
/// The standard deviation of the fast field values. None for count == 0.
pub standard_deviation: Option<f64>,
/// The min value of the fast field values.
pub min: Option<f64>,
/// The max value of the fast field values.
pub max: Option<f64>,
/// The average of the values. `None` for count == 0.
/// The average of the values. None for count == 0.
pub avg: Option<f64>,
}
@@ -70,7 +71,7 @@ impl Stats {
}
}
/// `IntermediateStats` contains the mergeable version for stats.
/// IntermediateStats contains the mergeable version for stats.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct IntermediateStats {
count: usize,
@@ -163,7 +164,7 @@ impl SegmentStatsCollector {
stats: IntermediateStats::default(),
}
}
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &dyn Column<u64>) {
pub(crate) fn collect_block(&mut self, doc: &[DocId], field: &DynamicFastFieldReader<u64>) {
let mut iter = doc.chunks_exact(4);
for docs in iter.by_ref() {
let val1 = field.get_val(docs[0] as u64);

View File

@@ -14,14 +14,13 @@
//!
//!
//! To use aggregations, build an aggregation request by constructing
//! [`Aggregations`](agg_req::Aggregations).
//! Create an [`AggregationCollector`] from this request. `AggregationCollector` implements the
//! [`Collector`](crate::collector::Collector) trait and can be passed as collector into
//! [`Searcher::search()`](crate::Searcher::search).
//! [Aggregations](agg_req::Aggregations).
//! Create an [AggregationCollector] from this request. AggregationCollector implements the
//! `Collector` trait and can be passed as collector into `searcher.search()`.
//!
//! #### Limitations
//!
//! Currently aggregations work only on single value fast fields of type `u64`, `f64`, `i64` and
//! Currently aggregations work only on single value fast fields of type u64, f64, i64 and
//! fast fields on text fields.
//!
//! # JSON Format
@@ -45,8 +44,8 @@
//! - [Stats](metric::StatsAggregation)
//!
//! # Example
//! Compute the average metric, by building [`agg_req::Aggregations`], which is built from an
//! `(String, agg_req::Aggregation)` iterator.
//! Compute the average metric, by building [agg_req::Aggregations], which is built from an (String,
//! [agg_req::Aggregation]) iterator.
//!
//! ```
//! use tantivy::aggregation::agg_req::{Aggregations, Aggregation, MetricAggregation};
@@ -144,15 +143,15 @@
//! ```
//!
//! # Distributed Aggregation
//! When the data is distributed on different [`Index`](crate::Index) instances, the
//! [`DistributedAggregationCollector`] provides functionality to merge data between independent
//! When the data is distributed on different [crate::Index] instances, the
//! [DistributedAggregationCollector] provides functionality to merge data between independent
//! search calls by returning
//! [`IntermediateAggregationResults`](intermediate_agg_result::IntermediateAggregationResults).
//! `IntermediateAggregationResults` provides the
//! [`merge_fruits`](intermediate_agg_result::IntermediateAggregationResults::merge_fruits) method
//! to merge multiple results. The merged result can then be converted into
//! [`AggregationResults`](agg_result::AggregationResults) via the
//! [`into_final_bucket_result`](intermediate_agg_result::IntermediateAggregationResults::into_final_bucket_result) method.
//! [IntermediateAggregationResults](intermediate_agg_result::IntermediateAggregationResults).
//! IntermediateAggregationResults provides the
//! [merge_fruits](intermediate_agg_result::IntermediateAggregationResults::merge_fruits) method to
//! merge multiple results. The merged result can then be converted into
//! [agg_result::AggregationResults] via the
//! [agg_result::AggregationResults::from_intermediate_and_req] method.
pub mod agg_req;
mod agg_req_with_accessor;
@@ -162,6 +161,7 @@ mod collector;
pub mod intermediate_agg_result;
pub mod metric;
mod segment_agg_result;
use std::collections::HashMap;
use std::fmt::Display;
@@ -169,10 +169,10 @@ pub use collector::{
AggregationCollector, AggregationSegmentCollector, DistributedAggregationCollector,
MAX_BUCKET_COUNT,
};
use fastfield_codecs::MonotonicallyMappableToU64;
use itertools::Itertools;
use serde::{Deserialize, Serialize};
use crate::fastfield::FastValue;
use crate::schema::Type;
/// Represents an associative array `(key => values)` in a very efficient manner.
@@ -260,7 +260,7 @@ impl<T: Clone> VecWithNames<T> {
}
}
/// The serialized key is used in a `HashMap`.
/// The serialized key is used in a HashMap.
pub type SerializedKey = String;
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize, PartialOrd)]
@@ -269,7 +269,7 @@ pub type SerializedKey = String;
pub enum Key {
/// String key
Str(String),
/// `f64` key
/// f64 key
F64(f64),
}
@@ -282,10 +282,10 @@ impl Display for Key {
}
}
/// Inverse of `to_fastfield_u64`. Used to convert to `f64` for metrics.
/// Invert of to_fastfield_u64. Used to convert to f64 for metrics.
///
/// # Panics
/// Only `u64`, `f64`, and `i64` are supported.
/// Only u64, f64, i64 is supported
pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &Type) -> f64 {
match field_type {
Type::U64 => val as f64,
@@ -297,15 +297,15 @@ pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &Type) -> f64 {
}
}
/// Converts the `f64` value to fast field value space.
/// Converts the f64 value to fast field value space.
///
/// If the fast field has `u64`, values are stored as `u64` in the fast field.
/// A `f64` value of e.g. `2.0` therefore needs to be converted to `1u64`.
/// If the fast field has u64, values are stored as u64 in the fast field.
/// A f64 value of e.g. 2.0 therefore needs to be converted to 1u64
///
/// If the fast field has `f64` values are converted and stored to `u64` using a
/// If the fast field has f64 values are converted and stored to u64 using a
/// monotonic mapping.
/// A `f64` value of e.g. `2.0` needs to be converted using the same monotonic
/// conversion function, so that the value matches the `u64` value stored in the fast
/// A f64 value of e.g. 2.0 needs to be converted using the same monotonic
/// conversion function, so that the value matches the u64 value stored in the fast
/// field.
pub(crate) fn f64_to_fastfield_u64(val: f64, field_type: &Type) -> Option<u64> {
match field_type {

View File

@@ -185,10 +185,10 @@ impl SegmentMetricResultCollector {
pub(crate) fn collect_block(&mut self, doc: &[DocId], metric: &MetricAggregationWithAccessor) {
match self {
SegmentMetricResultCollector::Average(avg_collector) => {
avg_collector.collect_block(doc, &*metric.accessor);
avg_collector.collect_block(doc, &metric.accessor);
}
SegmentMetricResultCollector::Stats(stats_collector) => {
stats_collector.collect_block(doc, &*metric.accessor);
stats_collector.collect_block(doc, &metric.accessor);
}
}
}

View File

@@ -24,7 +24,7 @@ where TScore: Clone + PartialOrd
/// A custom segment scorer makes it possible to define any kind of score
/// for a given document belonging to a specific segment.
///
/// It is the segment local version of the [`CustomScorer`].
/// It is the segment local version of the [`CustomScorer`](./trait.CustomScorer.html).
pub trait CustomSegmentScorer<TScore>: 'static {
/// Computes the score of a specific `doc`.
fn score(&mut self, doc: DocId) -> TScore;
@@ -36,7 +36,7 @@ pub trait CustomSegmentScorer<TScore>: 'static {
/// Instead, it helps constructing `Self::Child` instances that will compute
/// the score at a segment scale.
pub trait CustomScorer<TScore>: Sync {
/// Type of the associated [`CustomSegmentScorer`].
/// Type of the associated [`CustomSegmentScorer`](./trait.CustomSegmentScorer.html).
type Child: CustomSegmentScorer<TScore>;
/// Builds a child scorer for a specific segment. The child scorer is associated to
/// a specific segment.

View File

@@ -67,10 +67,10 @@ fn facet_depth(facet_bytes: &[u8]) -> usize {
/// (e.g. `/category/fiction`, `/category/biography`, `/category/personal_development`).
///
/// Once collection is finished, you can harvest its results in the form
/// of a [`FacetCounts`] object, and extract your facet counts from it.
/// of a `FacetCounts` object, and extract your face t counts from it.
///
/// This implementation assumes you are working with a number of facets that
/// is many hundreds of times smaller than your number of documents.
/// is much hundreds of time lower than your number of documents.
///
///
/// ```rust
@@ -231,7 +231,7 @@ impl FacetCollector {
///
/// Adding two facets within which one is the prefix of the other is forbidden.
/// If you need the correct number of unique documents for two such facets,
/// just add them in a separate `FacetCollector`.
/// just add them in separate `FacetCollector`.
pub fn add_facet<T>(&mut self, facet_from: T)
where Facet: From<T> {
let facet = Facet::from(facet_from);
@@ -391,7 +391,7 @@ impl<'a> Iterator for FacetChildIterator<'a> {
impl FacetCounts {
/// Returns an iterator over all of the facet count pairs inside this result.
/// See the documentation for [`FacetCollector`] for a usage example.
/// See the documentation for [FacetCollector] for a usage example.
pub fn get<T>(&self, facet_from: T) -> FacetChildIterator<'_>
where Facet: From<T> {
let facet = Facet::from(facet_from);
@@ -410,7 +410,7 @@ impl FacetCounts {
}
/// Returns a vector of top `k` facets with their counts, sorted highest-to-lowest by counts.
/// See the documentation for [`FacetCollector`] for a usage example.
/// See the documentation for [FacetCollector] for a usage example.
pub fn top_k<T>(&self, facet: T, k: usize) -> Vec<(&Facet, u64)>
where Facet: From<T> {
let mut heap = BinaryHeap::with_capacity(k);

View File

@@ -10,12 +10,11 @@
// ---
// Importing tantivy...
use std::marker::PhantomData;
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::collector::{Collector, SegmentCollector};
use crate::fastfield::FastValue;
use crate::fastfield::{DynamicFastFieldReader, FastValue};
use crate::schema::Field;
use crate::{Score, SegmentReader, TantivyError};
@@ -161,7 +160,7 @@ where
TPredicate: 'static,
TPredicateValue: FastValue,
{
fast_field_reader: Arc<dyn Column<TPredicateValue>>,
fast_field_reader: DynamicFastFieldReader<TPredicateValue>,
segment_collector: TSegmentCollector,
predicate: TPredicate,
t_predicate_value: PhantomData<TPredicateValue>,

View File

@@ -1,10 +1,8 @@
use std::sync::Arc;
use fastdivide::DividerU64;
use fastfield_codecs::Column;
use crate::collector::{Collector, SegmentCollector};
use crate::fastfield::FastValue;
use crate::fastfield::{DynamicFastFieldReader, FastValue};
use crate::schema::{Field, Type};
use crate::{DocId, Score};
@@ -87,7 +85,7 @@ impl HistogramComputer {
}
pub struct SegmentHistogramCollector {
histogram_computer: HistogramComputer,
ff_reader: Arc<dyn Column<u64>>,
ff_reader: DynamicFastFieldReader<u64>,
}
impl SegmentCollector for SegmentHistogramCollector {

View File

@@ -4,13 +4,13 @@
//! In tantivy jargon, we call this information your search "fruit".
//!
//! Your fruit could for instance be :
//! - [the count of matching documents](crate::collector::Count)
//! - [the top 10 documents, by relevancy or by a fast field](crate::collector::TopDocs)
//! - [facet counts](FacetCollector)
//! - [the count of matching documents](./struct.Count.html)
//! - [the top 10 documents, by relevancy or by a fast field](./struct.TopDocs.html)
//! - [facet counts](./struct.FacetCollector.html)
//!
//! At some point in your code, you will trigger the actual search operation by calling
//! [`Searcher::search()`](crate::Searcher::search).
//! This call will look like this:
//! At one point in your code, you will trigger the actual search operation by calling
//! [the `search(...)` method of your `Searcher` object](../struct.Searcher.html#method.search).
//! This call will look like this.
//!
//! ```verbatim
//! let fruit = searcher.search(&query, &collector)?;
@@ -64,7 +64,7 @@
//!
//! The `Collector` trait is implemented for up to 4 collectors.
//! If you have more than 4 collectors, you can either group them into
//! tuples of tuples `(a,(b,(c,d)))`, or rely on [`MultiCollector`].
//! tuples of tuples `(a,(b,(c,d)))`, or rely on [`MultiCollector`](./struct.MultiCollector.html).
//!
//! # Combining several collectors dynamically
//!
@@ -74,7 +74,7 @@
//!
//! Unfortunately it requires you to know at compile time your collector types.
//! If on the other hand, the collectors depend on some query parameter,
//! you can rely on [`MultiCollector`]'s.
//! you can rely on `MultiCollector`'s.
//!
//!
//! # Implementing your own collectors.

View File

@@ -1,11 +1,9 @@
use std::sync::Arc;
use fastfield_codecs::Column;
use super::*;
use crate::collector::{Count, FilterCollector, TopDocs};
use crate::core::SegmentReader;
use crate::fastfield::BytesFastFieldReader;
use crate::fastfield::{BytesFastFieldReader, DynamicFastFieldReader};
use crate::query::{AllQuery, QueryParser};
use crate::schema::{Field, Schema, FAST, TEXT};
use crate::time::format_description::well_known::Rfc3339;
@@ -160,7 +158,7 @@ pub struct FastFieldTestCollector {
pub struct FastFieldSegmentCollector {
vals: Vec<u64>,
reader: Arc<dyn Column<u64>>,
reader: DynamicFastFieldReader<u64>,
}
impl FastFieldTestCollector {

View File

@@ -1,7 +1,6 @@
use std::collections::BinaryHeap;
use std::fmt;
use std::marker::PhantomData;
use std::sync::Arc;
use fastfield_codecs::Column;
@@ -12,7 +11,7 @@ use crate::collector::tweak_score_top_collector::TweakedScoreTopCollector;
use crate::collector::{
CustomScorer, CustomSegmentScorer, ScoreSegmentTweaker, ScoreTweaker, SegmentCollector,
};
use crate::fastfield::FastValue;
use crate::fastfield::{DynamicFastFieldReader, FastValue};
use crate::query::Weight;
use crate::schema::Field;
use crate::{DocAddress, DocId, Score, SegmentOrdinal, SegmentReader, TantivyError};
@@ -132,7 +131,7 @@ impl fmt::Debug for TopDocs {
}
struct ScorerByFastFieldReader {
ff_reader: Arc<dyn Column<u64>>,
ff_reader: DynamicFastFieldReader<u64>,
}
impl CustomSegmentScorer<u64> for ScorerByFastFieldReader {
@@ -287,7 +286,7 @@ impl TopDocs {
/// # See also
///
/// To comfortably work with `u64`s, `i64`s, `f64`s, or `date`s, please refer to
/// the [.order_by_fast_field(...)](TopDocs::order_by_fast_field) method.
/// [.order_by_fast_field(...)](#method.order_by_fast_field) method.
pub fn order_by_u64_field(
self,
field: Field,
@@ -384,7 +383,7 @@ impl TopDocs {
///
/// This method offers a convenient way to tweak or replace
/// the documents score. As suggested by the prototype you can
/// manually define your own [`ScoreTweaker`]
/// manually define your own [`ScoreTweaker`](./trait.ScoreTweaker.html)
/// and pass it as an argument, but there is a much simpler way to
/// tweak your score: you can use a closure as in the following
/// example.
@@ -401,7 +400,7 @@ impl TopDocs {
/// In the following example will will tweak our ranking a bit by
/// boosting popular products a notch.
///
/// In more serious application, this tweaking could involve running a
/// In more serious application, this tweaking could involved running a
/// learning-to-rank model over various features
///
/// ```rust
@@ -410,6 +409,7 @@ impl TopDocs {
/// # use tantivy::query::QueryParser;
/// use tantivy::SegmentReader;
/// use tantivy::collector::TopDocs;
/// use tantivy::fastfield::Column;
/// use tantivy::schema::Field;
///
/// fn create_schema() -> Schema {
@@ -474,7 +474,7 @@ impl TopDocs {
/// ```
///
/// # See also
/// - [custom_score(...)](TopDocs::custom_score)
/// [custom_score(...)](#method.custom_score).
pub fn tweak_score<TScore, TScoreSegmentTweaker, TScoreTweaker>(
self,
score_tweaker: TScoreTweaker,
@@ -491,7 +491,8 @@ impl TopDocs {
///
/// This method offers a convenient way to use a different score.
///
/// As suggested by the prototype you can manually define your own [`CustomScorer`]
/// As suggested by the prototype you can manually define your
/// own [`CustomScorer`](./trait.CustomScorer.html)
/// and pass it as an argument, but there is a much simpler way to
/// tweak your score: you can use a closure as in the following
/// example.
@@ -516,6 +517,7 @@ impl TopDocs {
/// use tantivy::SegmentReader;
/// use tantivy::collector::TopDocs;
/// use tantivy::schema::Field;
/// use fastfield_codecs::Column;
///
/// # fn create_schema() -> Schema {
/// # let mut schema_builder = Schema::builder();
@@ -587,7 +589,7 @@ impl TopDocs {
/// ```
///
/// # See also
/// - [tweak_score(...)](TopDocs::tweak_score)
/// [tweak_score(...)](#method.tweak_score).
pub fn custom_score<TScore, TCustomSegmentScorer, TCustomScorer>(
self,
custom_score: TCustomScorer,

View File

@@ -24,7 +24,7 @@ where TScore: Clone + PartialOrd
/// A `ScoreSegmentTweaker` makes it possible to modify the default score
/// for a given document belonging to a specific segment.
///
/// It is the segment local version of the [`ScoreTweaker`].
/// It is the segment local version of the [`ScoreTweaker`](./trait.ScoreTweaker.html).
pub trait ScoreSegmentTweaker<TScore>: 'static {
/// Tweak the given `score` for the document `doc`.
fn score(&mut self, doc: DocId, score: Score) -> TScore;
@@ -37,7 +37,7 @@ pub trait ScoreSegmentTweaker<TScore>: 'static {
/// Instead, it helps constructing `Self::Child` instances that will compute
/// the score at a segment scale.
pub trait ScoreTweaker<TScore>: Sync {
/// Type of the associated [`ScoreSegmentTweaker`].
/// Type of the associated [`ScoreSegmentTweaker`](./trait.ScoreSegmentTweaker.html).
type Child: ScoreSegmentTweaker<TScore>;
/// Builds a child tweaker for a specific segment. The child scorer is associated to

View File

@@ -78,8 +78,8 @@ fn save_new_metas(
/// IndexBuilder can be used to create an index.
///
/// Use in conjunction with [`SchemaBuilder`][crate::schema::SchemaBuilder].
/// Global index settings can be configured with [`IndexSettings`].
/// Use in conjunction with `SchemaBuilder`. Global index settings
/// can be configured with `IndexSettings`
///
/// # Examples
///
@@ -97,13 +97,7 @@ fn save_new_metas(
/// );
///
/// let schema = schema_builder.build();
/// let settings = IndexSettings{
/// sort_by_field: Some(IndexSortByField{
/// field: "number".to_string(),
/// order: Order::Asc
/// }),
/// ..Default::default()
/// };
/// let settings = IndexSettings{sort_by_field: Some(IndexSortByField{field:"number".to_string(), order:Order::Asc}), ..Default::default()};
/// let index = Index::builder().schema(schema).settings(settings).create_in_ram();
/// ```
pub struct IndexBuilder {
@@ -146,7 +140,7 @@ impl IndexBuilder {
self
}
/// Creates a new index using the [`RamDirectory`].
/// Creates a new index using the `RAMDirectory`.
///
/// The index will be allocated in anonymous memory.
/// This should only be used for unit tests.
@@ -154,14 +148,13 @@ impl IndexBuilder {
let ram_directory = RamDirectory::create();
Ok(self
.create(ram_directory)
.expect("Creating a RamDirectory should never fail"))
.expect("Creating a RAMDirectory should never fail"))
}
/// Creates a new index in a given filepath.
/// The index will use the [`MmapDirectory`].
/// The index will use the `MMapDirectory`.
///
/// If a previous index was in this directory, it returns an
/// [`TantivyError::IndexAlreadyExists`] error.
/// If a previous index was in this directory, it returns an `IndexAlreadyExists` error.
#[cfg(feature = "mmap")]
pub fn create_in_dir<P: AsRef<Path>>(self, directory_path: P) -> crate::Result<Index> {
let mmap_directory: Box<dyn Directory> = Box::new(MmapDirectory::open(directory_path)?);
@@ -192,13 +185,12 @@ impl IndexBuilder {
/// Creates a new index in a temp directory.
///
/// The index will use the [`MmapDirectory`] in a newly created directory.
/// The temp directory will be destroyed automatically when the [`Index`] object
/// The index will use the `MMapDirectory` in a newly created directory.
/// The temp directory will be destroyed automatically when the `Index` object
/// is destroyed.
///
/// The temp directory is only used for testing the [`MmapDirectory`].
/// For other unit tests, prefer the [`RamDirectory`], see:
/// [`IndexBuilder::create_in_ram()`].
/// The temp directory is only used for testing the `MmapDirectory`.
/// For other unit tests, prefer the `RAMDirectory`, see: `create_in_ram`.
#[cfg(feature = "mmap")]
pub fn create_from_tempdir(self) -> crate::Result<Index> {
let mmap_directory: Box<dyn Directory> = Box::new(MmapDirectory::create_from_tempdir()?);
@@ -294,7 +286,7 @@ impl Index {
self.set_multithread_executor(default_num_threads)
}
/// Creates a new index using the [`RamDirectory`].
/// Creates a new index using the `RamDirectory`.
///
/// The index will be allocated in anonymous memory.
/// This is useful for indexing small set of documents
@@ -304,10 +296,9 @@ impl Index {
}
/// Creates a new index in a given filepath.
/// The index will use the [`MmapDirectory`].
/// The index will use the `MMapDirectory`.
///
/// If a previous index was in this directory, then it returns
/// a [`TantivyError::IndexAlreadyExists`] error.
/// If a previous index was in this directory, then it returns an `IndexAlreadyExists` error.
#[cfg(feature = "mmap")]
pub fn create_in_dir<P: AsRef<Path>>(
directory_path: P,
@@ -329,13 +320,12 @@ impl Index {
/// Creates a new index in a temp directory.
///
/// The index will use the [`MmapDirectory`] in a newly created directory.
/// The temp directory will be destroyed automatically when the [`Index`] object
/// The index will use the `MMapDirectory` in a newly created directory.
/// The temp directory will be destroyed automatically when the `Index` object
/// is destroyed.
///
/// The temp directory is only used for testing the [`MmapDirectory`].
/// For other unit tests, prefer the [`RamDirectory`],
/// see: [`IndexBuilder::create_in_ram()`].
/// The temp directory is only used for testing the `MmapDirectory`.
/// For other unit tests, prefer the `RamDirectory`, see: `create_in_ram`.
#[cfg(feature = "mmap")]
pub fn create_from_tempdir(schema: Schema) -> crate::Result<Index> {
IndexBuilder::new().schema(schema).create_from_tempdir()
@@ -355,7 +345,7 @@ impl Index {
builder.create(dir)
}
/// Creates a new index given a directory and an [`IndexMeta`].
/// Creates a new index given a directory and an `IndexMeta`.
fn open_from_metas(
directory: ManagedDirectory,
metas: &IndexMeta,
@@ -382,7 +372,7 @@ impl Index {
&self.tokenizers
}
/// Get the tokenizer associated with a specific field.
/// Helper to access the tokenizer associated to a specific field.
pub fn tokenizer_for_field(&self, field: Field) -> crate::Result<TextAnalyzer> {
let field_entry = self.schema.get_field_entry(field);
let field_type = field_entry.field_type();
@@ -414,14 +404,14 @@ impl Index {
})
}
/// Create a default [`IndexReader`] for the given index.
/// Create a default `IndexReader` for the given index.
///
/// See [`Index.reader_builder()`].
/// See [`Index.reader_builder()`](#method.reader_builder).
pub fn reader(&self) -> crate::Result<IndexReader> {
self.reader_builder().try_into()
}
/// Create a [`IndexReader`] for the given index.
/// Create a `IndexReader` for the given index.
///
/// Most project should create at most one reader for a given index.
/// This method is typically called only once per `Index` instance.

View File

@@ -235,14 +235,6 @@ impl InnerSegmentMeta {
}
}
fn return_true() -> bool {
true
}
fn is_true(val: &bool) -> bool {
*val
}
/// Search Index Settings.
///
/// Contains settings which are applied on the whole
@@ -256,12 +248,6 @@ pub struct IndexSettings {
/// The `Compressor` used to compress the doc store.
#[serde(default)]
pub docstore_compression: Compressor,
/// If set to true, docstore compression will happen on a dedicated thread.
/// (defaults: true)
#[doc(hidden)]
#[serde(default = "return_true")]
#[serde(skip_serializing_if = "is_true")]
pub docstore_compress_dedicated_thread: bool,
#[serde(default = "default_docstore_blocksize")]
/// The size of each block that will be compressed and written to disk
pub docstore_blocksize: usize,
@@ -278,7 +264,6 @@ impl Default for IndexSettings {
sort_by_field: None,
docstore_compression: Compressor::default(),
docstore_blocksize: default_docstore_blocksize(),
docstore_compress_dedicated_thread: true,
}
}
}
@@ -410,7 +395,7 @@ mod tests {
use super::IndexMeta;
use crate::core::index_meta::UntrackedIndexMeta;
use crate::schema::{Schema, TEXT};
use crate::store::{Compressor, ZstdCompressor};
use crate::store::ZstdCompressor;
use crate::{IndexSettings, IndexSortByField, Order};
#[test]
@@ -462,7 +447,6 @@ mod tests {
compression_level: Some(4),
}),
docstore_blocksize: 1_000_000,
docstore_compress_dedicated_thread: true,
},
segments: Vec::new(),
schema,
@@ -501,47 +485,4 @@ mod tests {
"unknown zstd option \"bla\" at line 1 column 103".to_string()
);
}
#[test]
#[cfg(feature = "lz4-compression")]
fn test_index_settings_default() {
let mut index_settings = IndexSettings::default();
assert_eq!(
index_settings,
IndexSettings {
sort_by_field: None,
docstore_compression: Compressor::default(),
docstore_compress_dedicated_thread: true,
docstore_blocksize: 16_384
}
);
{
let index_settings_json = serde_json::to_value(&index_settings).unwrap();
assert_eq!(
index_settings_json,
serde_json::json!({
"docstore_compression": "lz4",
"docstore_blocksize": 16384
})
);
let index_settings_deser: IndexSettings =
serde_json::from_value(index_settings_json).unwrap();
assert_eq!(index_settings_deser, index_settings);
}
{
index_settings.docstore_compress_dedicated_thread = false;
let index_settings_json = serde_json::to_value(&index_settings).unwrap();
assert_eq!(
index_settings_json,
serde_json::json!({
"docstore_compression": "lz4",
"docstore_blocksize": 16384,
"docstore_compress_dedicated_thread": false,
})
);
let index_settings_deser: IndexSettings =
serde_json::from_value(index_settings_json).unwrap();
assert_eq!(index_settings_deser, index_settings);
}
}
}

View File

@@ -10,12 +10,12 @@ use crate::space_usage::SearcherSpaceUsage;
use crate::store::{CacheStats, StoreReader};
use crate::{DocAddress, Index, Opstamp, SegmentId, TrackedObject};
/// Identifies the searcher generation accessed by a [`Searcher`].
/// Identifies the searcher generation accessed by a [Searcher].
///
/// While this might seem redundant, a [`SearcherGeneration`] contains
/// While this might seem redundant, a [SearcherGeneration] contains
/// both a `generation_id` AND a list of `(SegmentId, DeleteOpstamp)`.
///
/// This is on purpose. This object is used by the [`Warmer`](crate::reader::Warmer) API.
/// This is on purpose. This object is used by the `Warmer` API.
/// Having both information makes it possible to identify which
/// artifact should be refreshed or garbage collected.
///
@@ -74,15 +74,15 @@ impl Searcher {
&self.inner.index
}
/// [`SearcherGeneration`] which identifies the version of the snapshot held by this `Searcher`.
/// [SearcherGeneration] which identifies the version of the snapshot held by this `Searcher`.
pub fn generation(&self) -> &SearcherGeneration {
self.inner.generation.as_ref()
}
/// Fetches a document from tantivy's store given a [`DocAddress`].
/// Fetches a document from tantivy's store given a `DocAddress`.
///
/// The searcher uses the segment ordinal to route the
/// request to the right `Segment`.
/// the request to the right `Segment`.
pub fn doc(&self, doc_address: DocAddress) -> crate::Result<Document> {
let store_reader = &self.inner.store_readers[doc_address.segment_ord as usize];
store_reader.get(doc_address.doc_id)
@@ -180,7 +180,7 @@ impl Searcher {
self.search_with_executor(query, collector, executor)
}
/// Same as [`search(...)`](Searcher::search) but multithreaded.
/// Same as [`search(...)`](#method.search) but multithreaded.
///
/// The current implementation is rather naive :
/// multithreading is by splitting search into as many task

View File

@@ -57,7 +57,7 @@ impl SegmentId {
/// Picking the first 8 chars is ok to identify
/// segments in a display message (e.g. a5c4dfcb).
pub fn short_uuid_string(&self) -> String {
self.0.as_simple().to_string()[..8].to_string()
(&self.0.as_simple().to_string()[..8]).to_string()
}
/// Returns a segment uuid string.

View File

@@ -21,10 +21,6 @@ impl SingleSegmentIndexWriter {
})
}
pub fn mem_usage(&self) -> usize {
self.segment_writer.mem_usage()
}
pub fn add_document(&mut self, document: Document) -> crate::Result<()> {
let opstamp = self.opstamp;
self.opstamp += 1;

View File

@@ -117,9 +117,9 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
/// change.
///
/// Specifically, subsequent writes or flushes should
/// have no effect on the returned [`FileSlice`] object.
/// have no effect on the returned `FileSlice` object.
///
/// You should only use this to read files create with [`Directory::open_write()`].
/// You should only use this to read files create with [Directory::open_write].
fn open_read(&self, path: &Path) -> Result<FileSlice, OpenReadError> {
let file_handle = self.get_file_handle(path)?;
Ok(FileSlice::new(file_handle))
@@ -128,28 +128,27 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
/// Removes a file
///
/// Removing a file will not affect an eventual
/// existing [`FileSlice`] pointing to it.
/// existing FileSlice pointing to it.
///
/// Removing a nonexistent file, returns a
/// [`DeleteError::FileDoesNotExist`].
/// Removing a nonexistent file, yields a
/// `DeleteError::DoesNotExist`.
fn delete(&self, path: &Path) -> Result<(), DeleteError>;
/// Returns true if and only if the file exists
fn exists(&self, path: &Path) -> Result<bool, OpenReadError>;
/// Opens a writer for the *virtual file* associated with
/// a [`Path`].
/// a Path.
///
/// Right after this call, for the span of the execution of the program
/// the file should be created and any subsequent call to
/// [`Directory::open_read()`] for the same path should return
/// a [`FileSlice`].
/// the file should be created and any subsequent call to `open_read` for the
/// same path should return a `FileSlice`.
///
/// However, depending on the directory implementation,
/// it might be required to call [`Directory::sync_directory()`] to ensure
/// it might be required to call `sync_directory` to ensure
/// that the file is durably created.
/// (The semantics here are the same when dealing with
/// a POSIX filesystem.)
/// a posix filesystem.)
///
/// Write operations may be aggressively buffered.
/// The client of this trait is responsible for calling flush
@@ -158,19 +157,19 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
///
/// Flush operation should also be persistent.
///
/// The user shall not rely on [`Drop`] triggering `flush`.
/// Note that [`RamDirectory`][crate::directory::RamDirectory] will
/// panic! if `flush` was not called.
/// The user shall not rely on `Drop` triggering `flush`.
/// Note that `RamDirectory` will panic! if `flush`
/// was not called.
///
/// The file may not previously exist.
fn open_write(&self, path: &Path) -> Result<WritePtr, OpenWriteError>;
/// Reads the full content file that has been written using
/// [`Directory::atomic_write()`].
/// atomic_write.
///
/// This should only be used for small files.
///
/// You should only use this to read files create with [`Directory::atomic_write()`].
/// You should only use this to read files create with [Directory::atomic_write].
fn atomic_read(&self, path: &Path) -> Result<Vec<u8>, OpenReadError>;
/// Atomically replace the content of a file with data.
@@ -187,9 +186,9 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
/// effectively stored durably.
fn sync_directory(&self) -> io::Result<()>;
/// Acquire a lock in the directory given in the [`Lock`].
/// Acquire a lock in the given directory.
///
/// The method is blocking or not depending on the [`Lock`] object.
/// The method is blocking or not depending on the `Lock` object.
fn acquire_lock(&self, lock: &Lock) -> Result<DirectoryLock, LockError> {
let mut box_directory = self.box_clone();
let mut retry_policy = retry_policy(lock.is_blocking);
@@ -211,15 +210,15 @@ pub trait Directory: DirectoryClone + fmt::Debug + Send + Sync + 'static {
}
/// Registers a callback that will be called whenever a change on the `meta.json`
/// using the [`Directory::atomic_write()`] API is detected.
/// using the `atomic_write` API is detected.
///
/// The behavior when using `.watch()` on a file using [`Directory::open_write()`] is, on the
/// other hand, undefined.
/// The behavior when using `.watch()` on a file using [Directory::open_write] is, on the other
/// hand, undefined.
///
/// The file will be watched for the lifetime of the returned `WatchHandle`. The caller is
/// required to keep it.
/// It does not override previous callbacks. When the file is modified, all callback that are
/// registered (and whose [`WatchHandle`] is still alive) are triggered.
/// registered (and whose `WatchHandle` is still alive) are triggered.
///
/// Internally, tantivy only uses this API to detect new commits to implement the
/// `OnCommit` `ReloadPolicy`. Not implementing watch in a `Directory` only prevents the

View File

@@ -4,14 +4,12 @@ use once_cell::sync::Lazy;
/// A directory lock.
///
/// A lock is associated with a specific path.
///
/// The lock will be passed to [`Directory::acquire_lock`](crate::Directory::acquire_lock).
///
/// A lock is associated to a specific path and some
/// [`LockParams`](./enum.LockParams.html).
/// Tantivy itself uses only two locks but client application
/// can use the directory facility to define their own locks.
/// - [`INDEX_WRITER_LOCK`]
/// - [`META_LOCK`]
/// - [INDEX_WRITER_LOCK]
/// - [META_LOCK]
///
/// Check out these locks documentation for more information.
#[derive(Debug)]
@@ -20,21 +18,19 @@ pub struct Lock {
/// Depending on the platform, the lock might rely on the creation
/// and deletion of this filepath.
pub filepath: PathBuf,
/// `is_blocking` describes whether acquiring the lock is meant
/// `lock_params` describes whether acquiring the lock is meant
/// to be a blocking operation or a non-blocking.
///
/// Acquiring a blocking lock blocks until the lock is
/// available.
///
/// Acquiring a non-blocking lock returns rapidly, either successfully
/// Acquiring a blocking lock returns rapidly, either successfully
/// or with an error signifying that someone is already holding
/// the lock.
pub is_blocking: bool,
}
/// Only one process should be able to write tantivy's index at a time.
/// This lock file, when present, is in charge of preventing other processes to open an
/// `IndexWriter`.
/// This lock file, when present, is in charge of preventing other processes to open an IndexWriter.
///
/// If the process is killed and this file remains, it is safe to remove it manually.
///

View File

@@ -4,9 +4,7 @@ use std::{fmt, io};
use crate::Version;
/// Error while trying to acquire a directory [lock](crate::directory::Lock).
///
/// This is returned from [`Directory::acquire_lock`](crate::Directory::acquire_lock).
/// Error while trying to acquire a directory lock.
#[derive(Debug, Clone, Error)]
pub enum LockError {
/// Failed to acquired a lock as it is already held by another

View File

@@ -27,7 +27,7 @@ pub(crate) fn make_io_err(msg: String) -> io::Error {
io::Error::new(io::ErrorKind::Other, msg)
}
/// Returns `None` iff the file exists, can be read, but is empty (and hence
/// Returns None iff the file exists, can be read, but is empty (and hence
/// cannot be mmapped)
fn open_mmap(full_path: &Path) -> result::Result<Option<Mmap>, OpenReadError> {
let file = File::open(full_path).map_err(|io_err| {
@@ -56,10 +56,10 @@ fn open_mmap(full_path: &Path) -> result::Result<Option<Mmap>, OpenReadError> {
#[derive(Default, Clone, Debug, Serialize, Deserialize)]
pub struct CacheCounters {
/// Number of time the cache prevents to call `mmap`
// Number of time the cache prevents to call `mmap`
pub hit: usize,
/// Number of time tantivy had to call `mmap`
/// as no entry was in the cache.
// Number of time tantivy had to call `mmap`
// as no entry was in the cache.
pub miss: usize,
}
@@ -472,8 +472,6 @@ mod tests {
// There are more tests in directory/mod.rs
// The following tests are specific to the MmapDirectory
use std::time::Duration;
use common::HasLen;
use super::*;
@@ -612,14 +610,7 @@ mod tests {
mmap_directory.get_cache_info().mmapped.len()
);
}
// This test failed on CI. The last Mmap is dropped from the merging thread so there might
// be a race condition indeed.
for _ in 0..10 {
if mmap_directory.get_cache_info().mmapped.is_empty() {
return Ok(());
}
std::thread::sleep(Duration::from_millis(200));
}
panic!("The cache still contains information. One of the Mmap has not been dropped.");
assert!(mmap_directory.get_cache_info().mmapped.is_empty());
Ok(())
}
}

View File

@@ -15,7 +15,7 @@ use crate::directory::{
WatchHandle, WritePtr,
};
/// Writer associated with the [`RamDirectory`].
/// Writer associated with the `RamDirectory`
///
/// The Writer just writes a buffer.
struct VecWriter {
@@ -136,32 +136,18 @@ impl RamDirectory {
Self::default()
}
/// Deep clones the directory.
///
/// Ulterior writes on one of the copy
/// will not affect the other copy.
pub fn deep_clone(&self) -> RamDirectory {
let inner_clone = InnerDirectory {
fs: self.fs.read().unwrap().fs.clone(),
watch_router: Default::default(),
};
RamDirectory {
fs: Arc::new(RwLock::new(inner_clone)),
}
}
/// Returns the sum of the size of the different files
/// in the [`RamDirectory`].
/// in the RamDirectory.
pub fn total_mem_usage(&self) -> usize {
self.fs.read().unwrap().total_mem_usage()
}
/// Write a copy of all of the files saved in the [`RamDirectory`] in the target [`Directory`].
/// Write a copy of all of the files saved in the RamDirectory in the target `Directory`.
///
/// Files are all written using the [`Directory::open_write()`] meaning, even if they were
/// written using the [`Directory::atomic_write()`] api.
/// Files are all written using the `Directory::write` meaning, even if they were
/// written using the `atomic_write` api.
///
/// If an error is encountered, files may be persisted partially.
/// If an error is encounterred, files may be persisted partially.
pub fn persist(&self, dest: &dyn Directory) -> crate::Result<()> {
let wlock = self.fs.write().unwrap();
for (path, file) in wlock.fs.iter() {
@@ -270,23 +256,4 @@ mod tests {
assert_eq!(directory_copy.atomic_read(path_atomic).unwrap(), msg_atomic);
assert_eq!(directory_copy.atomic_read(path_seq).unwrap(), msg_seq);
}
#[test]
fn test_ram_directory_deep_clone() {
let dir = RamDirectory::default();
let test = Path::new("test");
let test2 = Path::new("test2");
dir.atomic_write(test, b"firstwrite").unwrap();
let dir_clone = dir.deep_clone();
assert_eq!(
dir_clone.atomic_read(test).unwrap(),
dir.atomic_read(test).unwrap()
);
dir.atomic_write(test, b"original").unwrap();
dir_clone.atomic_write(test, b"clone").unwrap();
dir_clone.atomic_write(test2, b"clone2").unwrap();
assert_eq!(dir.atomic_read(test).unwrap(), b"original");
assert_eq!(&dir_clone.atomic_read(test).unwrap(), b"clone");
assert_eq!(&dir_clone.atomic_read(test2).unwrap(), b"clone2");
}
}

View File

@@ -3,10 +3,10 @@ use std::borrow::{Borrow, BorrowMut};
use crate::fastfield::AliveBitSet;
use crate::DocId;
/// Sentinel value returned when a [`DocSet`] has been entirely consumed.
/// Sentinel value returned when a DocSet has been entirely consumed.
///
/// This is not `u32::MAX` as one would have expected, due to the lack of SSE2 instructions
/// to compare `[u32; 4]`.
/// This is not u32::MAX as one would have expected, due to the lack of SSE2 instructions
/// to compare [u32; 4].
pub const TERMINATED: DocId = i32::MAX as u32;
/// Represents an iterable set of sorted doc ids.
@@ -20,21 +20,21 @@ pub trait DocSet: Send {
/// assert_eq!(doc, docset.doc());
/// ```
///
/// If we reached the end of the `DocSet`, [`TERMINATED`] should be returned.
/// If we reached the end of the DocSet, TERMINATED should be returned.
///
/// Calling `.advance()` on a terminated `DocSet` should be supported, and [`TERMINATED`] should
/// Calling `.advance()` on a terminated DocSet should be supported, and TERMINATED should
/// be returned.
fn advance(&mut self) -> DocId;
/// Advances the `DocSet` forward until reaching the target, or going to the
/// lowest [`DocId`] greater than the target.
/// Advances the DocSet forward until reaching the target, or going to the
/// lowest DocId greater than the target.
///
/// If the end of the `DocSet` is reached, [`TERMINATED`] is returned.
/// If the end of the DocSet is reached, TERMINATED is returned.
///
/// Calling `.seek(target)` on a terminated `DocSet` is legal. Implementation
/// of `DocSet` should support it.
/// Calling `.seek(target)` on a terminated DocSet is legal. Implementation
/// of DocSet should support it.
///
/// Calling `seek(TERMINATED)` is also legal and is the normal way to consume a `DocSet`.
/// Calling `seek(TERMINATED)` is also legal and is the normal way to consume a DocSet.
fn seek(&mut self, target: DocId) -> DocId {
let mut doc = self.doc();
debug_assert!(doc <= target);
@@ -73,9 +73,9 @@ pub trait DocSet: Send {
}
/// Returns the current document
/// Right after creating a new `DocSet`, the docset points to the first document.
/// Right after creating a new DocSet, the docset points to the first document.
///
/// If the `DocSet` is empty, `.doc()` should return [`TERMINATED`].
/// If the DocSet is empty, .doc() should return `TERMINATED`.
fn doc(&self) -> DocId;
/// Returns a best-effort hint of the

View File

@@ -1,9 +1,7 @@
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::directory::{FileSlice, OwnedBytes};
use crate::fastfield::MultiValueLength;
use crate::fastfield::{DynamicFastFieldReader, MultiValueLength};
use crate::DocId;
/// Reader for byte array fast fields
@@ -18,13 +16,13 @@ use crate::DocId;
/// and the start index for the next document, and keeping the bytes in between.
#[derive(Clone)]
pub struct BytesFastFieldReader {
idx_reader: Arc<dyn Column<u64>>,
idx_reader: DynamicFastFieldReader<u64>,
values: OwnedBytes,
}
impl BytesFastFieldReader {
pub(crate) fn open(
idx_reader: Arc<dyn Column<u64>>,
idx_reader: DynamicFastFieldReader<u64>,
values_file: FileSlice,
) -> crate::Result<BytesFastFieldReader> {
let values = values_file.read_bytes()?;

View File

@@ -1,9 +1,6 @@
use std::io::{self, Write};
use fastfield_codecs::VecColumn;
use std::io;
use crate::fastfield::serializer::CompositeFastFieldSerializer;
use crate::fastfield::MultivalueStartIndex;
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::schema::{Document, Field, Value};
use crate::DocId;
@@ -13,17 +10,15 @@ use crate::DocId;
/// This `BytesFastFieldWriter` is only useful for advanced users.
/// The normal way to get your associated bytes in your index
/// is to
/// - declare your field with fast set to
/// [`Cardinality::SingleValue`](crate::schema::Cardinality::SingleValue)
/// - declare your field with fast set to `Cardinality::SingleValue`
/// in your schema
/// - add your document simply by calling `.add_document(...)` with associating bytes to the field.
///
/// The `BytesFastFieldWriter` can be acquired from the
/// fast field writer by calling
/// [`.get_bytes_writer_mut(...)`](crate::fastfield::FastFieldsWriter::get_bytes_writer_mut).
/// [`.get_bytes_writer(...)`](./struct.FastFieldsWriter.html#method.get_bytes_writer).
///
/// Once acquired, writing is done by calling
/// [`.add_document_val(&[u8])`](BytesFastFieldWriter::add_document_val)
/// Once acquired, writing is done by calling `.add_document_val(&[u8])`
/// once per document, even if there are no bytes associated to it.
pub struct BytesFastFieldWriter {
field: Field,
@@ -109,27 +104,22 @@ impl BytesFastFieldWriter {
/// Serializes the fast field values by pushing them to the `FastFieldSerializer`.
pub fn serialize(
mut self,
&self,
serializer: &mut CompositeFastFieldSerializer,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
// writing the offset index
{
self.doc_index.push(self.vals.len() as u64);
let col = VecColumn::from(&self.doc_index[..]);
if let Some(doc_id_map) = doc_id_map {
let multi_value_start_index = MultivalueStartIndex::new(&col, doc_id_map);
serializer.create_auto_detect_u64_fast_field_with_idx(
self.field,
multi_value_start_index,
0,
)?;
} else {
serializer.create_auto_detect_u64_fast_field_with_idx(self.field, col, 0)?;
}
let mut doc_index_serializer =
serializer.new_u64_fast_field_with_idx(self.field, 0, self.vals.len() as u64, 0)?;
let mut offset = 0;
for vals in self.get_ordered_values(doc_id_map) {
doc_index_serializer.add_val(offset)?;
offset += vals.len() as u64;
}
doc_index_serializer.add_val(self.vals.len() as u64)?;
doc_index_serializer.close_field()?;
// writing the values themselves
let mut value_serializer = serializer.new_bytes_fast_field(self.field);
let mut value_serializer = serializer.new_bytes_fast_field_with_idx(self.field, 1);
// the else could be removed, but this is faster (difference not benchmarked)
if let Some(doc_id_map) = doc_id_map {
for vals in self.get_ordered_values(Some(doc_id_map)) {

361
src/fastfield/gcd.rs Normal file
View File

@@ -0,0 +1,361 @@
use std::io::{self, Write};
use std::num::NonZeroU64;
use common::BinarySerializable;
use fastdivide::DividerU64;
use fastfield_codecs::{Column, FastFieldCodec};
use ownedbytes::OwnedBytes;
pub const GCD_DEFAULT: u64 = 1;
/// Wrapper for accessing a fastfield.
///
/// Holds the data and the codec to the read the data.
#[derive(Clone)]
pub struct GCDReader<CodecReader: Column> {
gcd_params: GCDParams,
reader: CodecReader,
}
#[derive(Debug, Clone, Copy)]
struct GCDParams {
gcd: u64,
min_value: u64,
num_vals: u64,
}
impl GCDParams {
pub fn eval(&self, val: u64) -> u64 {
self.min_value + self.gcd * val
}
}
impl BinarySerializable for GCDParams {
fn serialize<W: Write>(&self, writer: &mut W) -> io::Result<()> {
self.gcd.serialize(writer)?;
self.min_value.serialize(writer)?;
self.num_vals.serialize(writer)?;
Ok(())
}
fn deserialize<R: io::Read>(reader: &mut R) -> io::Result<Self> {
let gcd: u64 = u64::deserialize(reader)?;
let min_value: u64 = u64::deserialize(reader)?;
let num_vals: u64 = u64::deserialize(reader)?;
Ok(Self {
gcd,
min_value,
num_vals,
})
}
}
pub fn open_gcd_from_bytes<WrappedCodec: FastFieldCodec>(
bytes: OwnedBytes,
) -> io::Result<GCDReader<WrappedCodec::Reader>> {
let footer_offset = bytes.len() - 24;
let (body, mut footer) = bytes.split(footer_offset);
let gcd_params = GCDParams::deserialize(&mut footer)?;
let reader: WrappedCodec::Reader = WrappedCodec::open_from_bytes(body)?;
Ok(GCDReader { gcd_params, reader })
}
impl<C: Column + Clone> Column for GCDReader<C> {
#[inline]
fn get_val(&self, doc: u64) -> u64 {
let val = self.reader.get_val(doc);
self.gcd_params.eval(val)
}
fn min_value(&self) -> u64 {
self.gcd_params.eval(self.reader.min_value())
}
fn max_value(&self) -> u64 {
self.gcd_params.eval(self.reader.max_value())
}
fn num_vals(&self) -> u64 {
self.gcd_params.num_vals
}
}
pub fn write_gcd_header<W: Write>(
field_write: &mut W,
min_value: u64,
gcd: u64,
num_vals: u64,
) -> io::Result<()> {
gcd.serialize(field_write)?;
min_value.serialize(field_write)?;
num_vals.serialize(field_write)?;
Ok(())
}
/// Compute the gcd of two non null numbers.
///
/// It is recommended, but not required, to feed values such that `large >= small`.
fn compute_gcd(mut large: NonZeroU64, mut small: NonZeroU64) -> NonZeroU64 {
loop {
let rem: u64 = large.get() % small;
if let Some(new_small) = NonZeroU64::new(rem) {
(large, small) = (small, new_small);
} else {
return small;
}
}
}
// Find GCD for iterator of numbers
pub fn find_gcd(numbers: impl Iterator<Item = u64>) -> Option<NonZeroU64> {
let mut numbers = numbers.flat_map(NonZeroU64::new);
let mut gcd: NonZeroU64 = numbers.next()?;
if gcd.get() == 1 {
return Some(gcd);
}
let mut gcd_divider = DividerU64::divide_by(gcd.get());
for val in numbers {
let remainder = val.get() - (gcd_divider.divide(val.get())) * gcd.get();
if remainder == 0 {
continue;
}
gcd = compute_gcd(val, gcd);
if gcd.get() == 1 {
return Some(gcd);
}
gcd_divider = DividerU64::divide_by(gcd.get());
}
Some(gcd)
}
#[cfg(test)]
mod tests {
use std::collections::HashMap;
use std::num::NonZeroU64;
use std::path::Path;
use std::time::{Duration, SystemTime};
use common::HasLen;
use fastfield_codecs::Column;
use crate::directory::{CompositeFile, RamDirectory, WritePtr};
use crate::fastfield::gcd::compute_gcd;
use crate::fastfield::serializer::FastFieldCodecEnableCheck;
use crate::fastfield::tests::{FIELD, FIELDI64, SCHEMA, SCHEMAI64};
use crate::fastfield::{
find_gcd, CompositeFastFieldSerializer, DynamicFastFieldReader, FastFieldCodecType,
FastFieldsWriter, ALL_CODECS,
};
use crate::schema::{Cardinality, Schema};
use crate::{DateOptions, DatePrecision, DateTime, Directory};
fn get_index(
docs: &[crate::Document],
schema: &Schema,
codec_enable_checker: FastFieldCodecEnableCheck,
) -> crate::Result<RamDirectory> {
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer =
CompositeFastFieldSerializer::from_write_with_codec(write, codec_enable_checker)
.unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(schema);
for doc in docs {
fast_field_writers.add_document(doc);
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
Ok(directory)
}
fn test_fastfield_gcd_i64_with_codec(
code_type: FastFieldCodecType,
num_vals: usize,
) -> crate::Result<()> {
let path = Path::new("test");
let mut docs = vec![];
for i in 1..=num_vals {
let val = (i as i64 - 5) * 1000i64;
docs.push(doc!(*FIELDI64=>val));
}
let directory = get_index(&docs, &SCHEMAI64, code_type.into())?;
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<i64>::open(file)?;
assert_eq!(fast_field_reader.get_val(0), -4000i64);
assert_eq!(fast_field_reader.get_val(1), -3000i64);
assert_eq!(fast_field_reader.get_val(2), -2000i64);
assert_eq!(fast_field_reader.max_value(), (num_vals as i64 - 5) * 1000);
assert_eq!(fast_field_reader.min_value(), -4000i64);
let file = directory.open_read(path).unwrap();
// Can't apply gcd
let path = Path::new("test");
docs.pop();
docs.push(doc!(*FIELDI64=>2001i64));
let directory = get_index(&docs, &SCHEMAI64, code_type.into())?;
let file2 = directory.open_read(path).unwrap();
assert!(file2.len() > file.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_i64() -> crate::Result<()> {
for &code_type in ALL_CODECS {
test_fastfield_gcd_i64_with_codec(code_type, 5500)?;
}
Ok(())
}
fn test_fastfield_gcd_u64_with_codec(
code_type: FastFieldCodecType,
num_vals: usize,
) -> crate::Result<()> {
let path = Path::new("test");
let mut docs = vec![];
for i in 1..=num_vals {
let val = i as u64 * 1000u64;
docs.push(doc!(*FIELD=>val));
}
let directory = get_index(&docs, &SCHEMA, code_type.into())?;
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(file)?;
assert_eq!(fast_field_reader.get_val(0), 1000u64);
assert_eq!(fast_field_reader.get_val(1), 2000u64);
assert_eq!(fast_field_reader.get_val(2), 3000u64);
assert_eq!(fast_field_reader.max_value(), num_vals as u64 * 1000);
assert_eq!(fast_field_reader.min_value(), 1000u64);
let file = directory.open_read(path).unwrap();
// Can't apply gcd
let path = Path::new("test");
docs.pop();
docs.push(doc!(*FIELDI64=>2001u64));
let directory = get_index(&docs, &SCHEMA, code_type.into())?;
let file2 = directory.open_read(path).unwrap();
assert!(file2.len() > file.len());
Ok(())
}
#[test]
fn test_fastfield_gcd_u64() -> crate::Result<()> {
for &code_type in ALL_CODECS {
test_fastfield_gcd_u64_with_codec(code_type, 5500)?;
}
Ok(())
}
#[test]
pub fn test_fastfield2() {
let test_fastfield = DynamicFastFieldReader::<u64>::from(vec![100, 200, 300]);
assert_eq!(test_fastfield.get_val(0), 100);
assert_eq!(test_fastfield.get_val(1), 200);
assert_eq!(test_fastfield.get_val(2), 300);
}
#[test]
pub fn test_gcd_date() -> crate::Result<()> {
let size_prec_sec =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Seconds)?;
let size_prec_micro =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Microseconds)?;
assert!(size_prec_sec < size_prec_micro);
let size_prec_sec =
test_gcd_date_with_codec(FastFieldCodecType::Linear, DatePrecision::Seconds)?;
let size_prec_micro =
test_gcd_date_with_codec(FastFieldCodecType::Linear, DatePrecision::Microseconds)?;
assert!(size_prec_sec < size_prec_micro);
Ok(())
}
fn test_gcd_date_with_codec(
codec_type: FastFieldCodecType,
precision: DatePrecision,
) -> crate::Result<usize> {
let time1 = DateTime::from_timestamp_micros(
SystemTime::now()
.duration_since(SystemTime::UNIX_EPOCH)
.unwrap()
.as_secs() as i64,
);
let time2 = DateTime::from_timestamp_micros(
SystemTime::now()
.checked_sub(Duration::from_micros(4111))
.unwrap()
.duration_since(SystemTime::UNIX_EPOCH)
.unwrap()
.as_secs() as i64,
);
let time3 = DateTime::from_timestamp_micros(
SystemTime::now()
.checked_sub(Duration::from_millis(2000))
.unwrap()
.duration_since(SystemTime::UNIX_EPOCH)
.unwrap()
.as_secs() as i64,
);
let mut schema_builder = Schema::builder();
let date_options = DateOptions::default()
.set_fast(Cardinality::SingleValue)
.set_precision(precision);
let field = schema_builder.add_date_field("field", date_options);
let schema = schema_builder.build();
let docs = vec![doc!(field=>time1), doc!(field=>time2), doc!(field=>time3)];
let directory = get_index(&docs, &schema, codec_type.into())?;
let path = Path::new("test");
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let len = file.len();
let test_fastfield = DynamicFastFieldReader::<DateTime>::open(file)?;
assert_eq!(test_fastfield.get_val(0), time1.truncate(precision));
assert_eq!(test_fastfield.get_val(1), time2.truncate(precision));
assert_eq!(test_fastfield.get_val(2), time3.truncate(precision));
Ok(len)
}
#[test]
fn test_compute_gcd() {
let test_compute_gcd_aux = |large, small, expected| {
let large = NonZeroU64::new(large).unwrap();
let small = NonZeroU64::new(small).unwrap();
let expected = NonZeroU64::new(expected).unwrap();
assert_eq!(compute_gcd(small, large), expected);
assert_eq!(compute_gcd(large, small), expected);
};
test_compute_gcd_aux(1, 4, 1);
test_compute_gcd_aux(2, 4, 2);
test_compute_gcd_aux(10, 25, 5);
test_compute_gcd_aux(25, 25, 25);
}
#[test]
fn find_gcd_test() {
assert_eq!(find_gcd([0].into_iter()), None);
assert_eq!(find_gcd([0, 10].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([10, 0].into_iter()), NonZeroU64::new(10));
assert_eq!(find_gcd([].into_iter()), None);
assert_eq!(find_gcd([15, 30, 5, 10].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([15, 16, 10].into_iter()), NonZeroU64::new(1));
assert_eq!(find_gcd([0, 5, 5, 5].into_iter()), NonZeroU64::new(5));
assert_eq!(find_gcd([0, 0].into_iter()), None);
}
}

View File

@@ -20,30 +20,39 @@
//!
//! Read access performance is comparable to that of an array lookup.
use fastfield_codecs::MonotonicallyMappableToU64;
use fastfield_codecs::FastFieldCodecType;
pub use self::alive_bitset::{intersect_alive_bitsets, write_alive_bitset, AliveBitSet};
pub use self::bytes::{BytesFastFieldReader, BytesFastFieldWriter};
pub use self::error::{FastFieldNotAvailableError, Result};
pub use self::facet_reader::FacetReader;
pub(crate) use self::multivalued::MultivalueStartIndex;
pub(crate) use self::gcd::{find_gcd, GCDReader, GCD_DEFAULT};
pub use self::multivalued::{MultiValuedFastFieldReader, MultiValuedFastFieldWriter};
pub use self::reader::DynamicFastFieldReader;
pub use self::readers::FastFieldReaders;
pub(crate) use self::readers::{type_and_cardinality, FastType};
pub use self::serializer::{Column, CompositeFastFieldSerializer};
pub use self::serializer::{Column, CompositeFastFieldSerializer, FastFieldStats};
pub use self::writer::{FastFieldsWriter, IntFastFieldWriter};
use crate::schema::{Type, Value};
use crate::schema::{Cardinality, FieldType, Type, Value};
use crate::{DateTime, DocId};
mod alive_bitset;
mod bytes;
mod error;
mod facet_reader;
mod gcd;
mod multivalued;
mod reader;
mod readers;
mod serializer;
mod writer;
pub(crate) const ALL_CODECS: &[FastFieldCodecType; 3] = &[
FastFieldCodecType::Bitpacked,
FastFieldCodecType::Linear,
FastFieldCodecType::BlockwiseLinear,
];
/// Trait for `BytesFastFieldReader` and `MultiValuedFastFieldReader` to return the length of data
/// for a doc_id
pub trait MultiValueLength {
@@ -55,64 +64,169 @@ pub trait MultiValueLength {
/// Trait for types that are allowed for fast fields:
/// (u64, i64 and f64, bool, DateTime).
pub trait FastValue:
MonotonicallyMappableToU64 + Copy + Send + Sync + PartialOrd + 'static
{
/// Returns the `schema::Type` for this FastValue.
fn to_type() -> Type;
pub trait FastValue: Clone + Copy + Send + Sync + PartialOrd + 'static {
/// Converts a value from u64
///
/// Internally all fast field values are encoded as u64.
/// **Note: To be used for converting encoded Term, Posting values.**
fn from_u64(val: u64) -> Self;
/// Converts a value to u64.
///
/// Internally all fast field values are encoded as u64.
fn to_u64(&self) -> u64;
/// Returns the fast field cardinality that can be extracted from the given
/// `FieldType`.
///
/// If the type is not a fast field, `None` is returned.
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality>;
/// Cast value to `u64`.
/// The value is just reinterpreted in memory.
fn as_u64(&self) -> u64;
/// Build a default value. This default value is never used, so the value does not
/// really matter.
fn make_zero() -> Self {
Self::from_u64(0u64)
Self::from_u64(0i64.to_u64())
}
/// Returns the `schema::Type` for this FastValue.
fn to_type() -> Type;
}
impl FastValue for u64 {
fn from_u64(val: u64) -> Self {
val
}
fn to_u64(&self) -> u64 {
*self
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::U64(ref integer_options) => integer_options.get_fastfield_cardinality(),
FieldType::Facet(_) => Some(Cardinality::MultiValues),
_ => None,
}
}
fn as_u64(&self) -> u64 {
*self
}
fn to_type() -> Type {
Type::U64
}
}
impl FastValue for i64 {
fn from_u64(val: u64) -> Self {
common::u64_to_i64(val)
}
fn to_u64(&self) -> u64 {
common::i64_to_u64(*self)
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::I64(ref integer_options) => integer_options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
*self as u64
}
fn to_type() -> Type {
Type::I64
}
}
impl FastValue for f64 {
fn from_u64(val: u64) -> Self {
common::u64_to_f64(val)
}
fn to_u64(&self) -> u64 {
common::f64_to_u64(*self)
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::F64(ref integer_options) => integer_options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
self.to_bits()
}
fn to_type() -> Type {
Type::F64
}
}
impl FastValue for bool {
fn from_u64(val: u64) -> Self {
val != 0u64
}
fn to_u64(&self) -> u64 {
match self {
false => 0,
true => 1,
}
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::Bool(ref integer_options) => integer_options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
*self as u64
}
fn to_type() -> Type {
Type::Bool
}
}
impl MonotonicallyMappableToU64 for DateTime {
fn to_u64(self) -> u64 {
self.timestamp_micros.to_u64()
}
fn from_u64(val: u64) -> Self {
let timestamp_micros = i64::from_u64(val);
DateTime { timestamp_micros }
}
}
impl FastValue for DateTime {
/// Converts a timestamp microseconds into DateTime.
///
/// **Note the timestamps is expected to be in microseconds.**
fn from_u64(timestamp_micros_u64: u64) -> Self {
let timestamp_micros = i64::from_u64(timestamp_micros_u64);
Self::from_timestamp_micros(timestamp_micros)
}
fn to_u64(&self) -> u64 {
common::i64_to_u64(self.into_timestamp_micros())
}
fn fast_field_cardinality(field_type: &FieldType) -> Option<Cardinality> {
match *field_type {
FieldType::Date(ref options) => options.get_fastfield_cardinality(),
_ => None,
}
}
fn as_u64(&self) -> u64 {
self.into_timestamp_micros().as_u64()
}
fn to_type() -> Type {
Type::Date
}
fn make_zero() -> Self {
DateTime {
timestamp_micros: 0,
}
}
}
fn value_to_u64(value: &Value) -> u64 {
@@ -152,19 +266,17 @@ mod tests {
use std::collections::HashMap;
use std::ops::Range;
use std::path::Path;
use std::sync::Arc;
use common::HasLen;
use fastfield_codecs::{open, FastFieldCodecType};
use once_cell::sync::Lazy;
use rand::prelude::SliceRandom;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use rand::SeedableRng;
use super::*;
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::merge_policy::NoMergePolicy;
use crate::schema::{Cardinality, Document, Field, Schema, SchemaBuilder, FAST, STRING, TEXT};
use crate::schema::{Document, Field, Schema, FAST, STRING, TEXT};
use crate::time::OffsetDateTime;
use crate::{DateOptions, DatePrecision, Index, SegmentId, SegmentReader};
@@ -173,11 +285,19 @@ mod tests {
schema_builder.add_u64_field("field", FAST);
schema_builder.build()
});
pub static SCHEMAI64: Lazy<Schema> = Lazy::new(|| {
let mut schema_builder = Schema::builder();
schema_builder.add_i64_field("field", FAST);
schema_builder.build()
});
pub static FIELD: Lazy<Field> = Lazy::new(|| SCHEMA.get_field("field").unwrap());
pub static FIELDI64: Lazy<Field> = Lazy::new(|| SCHEMAI64.get_field("field").unwrap());
#[test]
pub fn test_fastfield() {
let test_fastfield = fastfield_codecs::serialize_and_load(&[100u64, 200u64, 300u64][..]);
let test_fastfield = DynamicFastFieldReader::<u64>::from(vec![100, 200, 300]);
assert_eq!(test_fastfield.get_val(0u64), 100);
assert_eq!(test_fastfield.get_val(1u64), 200);
assert_eq!(test_fastfield.get_val(2u64), 300);
@@ -206,10 +326,10 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 25);
assert_eq!(file.len(), 45);
let composite_file = CompositeFile::open(&file)?;
let fast_field_bytes = composite_file.open_read(*FIELD).unwrap().read_bytes()?;
let fast_field_reader = open::<u64>(fast_field_bytes)?;
let file = composite_file.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(file)?;
assert_eq!(fast_field_reader.get_val(0), 13u64);
assert_eq!(fast_field_reader.get_val(1), 14u64);
assert_eq!(fast_field_reader.get_val(2), 2u64);
@@ -237,14 +357,11 @@ mod tests {
serializer.close()?;
}
let file = directory.open_read(path)?;
assert_eq!(file.len(), 53);
assert_eq!(file.len(), 70);
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
assert_eq!(fast_field_reader.get_val(0), 4u64);
assert_eq!(fast_field_reader.get_val(1), 14_082_001u64);
assert_eq!(fast_field_reader.get_val(2), 3_052u64);
@@ -276,14 +393,11 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 26);
assert_eq!(file.len(), 43);
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
for doc in 0..10_000 {
assert_eq!(fast_field_reader.get_val(doc), 100_000u64);
}
@@ -311,14 +425,11 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 80040);
assert_eq!(file.len(), 80051);
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
assert_eq!(fast_field_reader.get_val(0), 0u64);
for doc in 1..10_001 {
assert_eq!(
@@ -353,15 +464,13 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 40_usize);
// assert_eq!(file.len(), 17710 as usize); //bitpacked size
// assert_eq!(file.len(), 10175_usize); // linear interpol size
assert_eq!(file.len(), 75_usize); // linear interpol size after calc improvement
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite
.open_read(i64_field)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<i64>(data)?;
let data = fast_fields_composite.open_read(i64_field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<i64>::open(data)?;
assert_eq!(fast_field_reader.min_value(), -100i64);
assert_eq!(fast_field_reader.max_value(), 9_999i64);
@@ -400,11 +509,8 @@ mod tests {
let file = directory.open_read(path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data = fast_fields_composite
.open_read(i64_field)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<i64>(data)?;
let data = fast_fields_composite.open_read(i64_field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<i64>::open(data)?;
assert_eq!(fast_field_reader.get_val(0), 0i64);
}
Ok(())
@@ -441,11 +547,8 @@ mod tests {
let file = directory.open_read(path)?;
{
let fast_fields_composite = CompositeFile::open(&file)?;
let data = fast_fields_composite
.open_read(*FIELD)
.unwrap()
.read_bytes()?;
let fast_field_reader = open::<u64>(data)?;
let data = fast_fields_composite.open_read(*FIELD).unwrap();
let fast_field_reader = DynamicFastFieldReader::<u64>::open(data)?;
for a in 0..n {
assert_eq!(fast_field_reader.get_val(a as u64), permutation[a as usize]);
@@ -504,7 +607,7 @@ mod tests {
let mut all = vec![];
for doc in docs {
let mut out: Vec<u64> = vec![];
let mut out = vec![];
ff.get_vals(doc, &mut out);
all.extend(out);
}
@@ -701,6 +804,7 @@ mod tests {
#[test]
fn test_datefastfield() -> crate::Result<()> {
use crate::fastfield::FastValue;
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field(
"date",
@@ -761,8 +865,7 @@ mod tests {
#[test]
pub fn test_fastfield_bool() {
let test_fastfield: Arc<dyn Column<bool>> =
fastfield_codecs::serialize_and_load::<bool>(&[true, false, true, false]);
let test_fastfield = DynamicFastFieldReader::<bool>::from(vec![true, false, true, false]);
assert_eq!(test_fastfield.get_val(0), true);
assert_eq!(test_fastfield.get_val(1), false);
assert_eq!(test_fastfield.get_val(2), true);
@@ -793,10 +896,10 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 24);
assert_eq!(file.len(), 44);
let composite_file = CompositeFile::open(&file)?;
let data = composite_file.open_read(field).unwrap().read_bytes()?;
let fast_field_reader = open::<bool>(data)?;
let file = composite_file.open_read(field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<bool>::open(file)?;
assert_eq!(fast_field_reader.get_val(0), true);
assert_eq!(fast_field_reader.get_val(1), false);
assert_eq!(fast_field_reader.get_val(2), true);
@@ -829,10 +932,10 @@ mod tests {
serializer.close().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 36);
assert_eq!(file.len(), 56);
let composite_file = CompositeFile::open(&file)?;
let data = composite_file.open_read(field).unwrap().read_bytes()?;
let fast_field_reader = open::<bool>(data)?;
let file = composite_file.open_read(field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<bool>::open(file)?;
for i in 0..25 {
assert_eq!(fast_field_reader.get_val(i * 2), true);
assert_eq!(fast_field_reader.get_val(i * 2 + 1), false);
@@ -847,95 +950,132 @@ mod tests {
let directory: RamDirectory = RamDirectory::create();
let mut schema_builder = Schema::builder();
let field = schema_builder.add_bool_field("field_bool", FAST);
schema_builder.add_bool_field("field_bool", FAST);
let schema = schema_builder.build();
let field = schema.get_field("field_bool").unwrap();
{
let write: WritePtr = directory.open_write(path).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write)?;
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
let doc = Document::default();
fast_field_writers.add_document(&doc);
fast_field_writers.serialize(&mut serializer, &HashMap::new(), None)?;
serializer.close()?;
}
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
assert_eq!(file.len(), 23);
let data = composite_file.open_read(field).unwrap().read_bytes()?;
let fast_field_reader = open::<bool>(data)?;
assert_eq!(fast_field_reader.get_val(0), false);
Ok(())
}
fn get_index(
docs: &[crate::Document],
schema: &Schema,
codec_types: &[FastFieldCodecType],
) -> crate::Result<RamDirectory> {
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer =
CompositeFastFieldSerializer::from_write_with_codec(write, codec_types).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(schema);
for doc in docs {
fast_field_writers.add_document(doc);
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
Ok(directory)
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 43);
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(field).unwrap();
let fast_field_reader = DynamicFastFieldReader::<bool>::open(file)?;
assert_eq!(fast_field_reader.get_val(0), false);
#[test]
pub fn test_gcd_date() -> crate::Result<()> {
let size_prec_sec =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Seconds)?;
assert_eq!(size_prec_sec, 28 + (1_000 * 13) / 8); // 13 bits per val = ceil(log_2(number of seconds in 2hours);
let size_prec_micro =
test_gcd_date_with_codec(FastFieldCodecType::Bitpacked, DatePrecision::Microseconds)?;
assert_eq!(size_prec_micro, 26 + (1_000 * 33) / 8); // 33 bits per val = ceil(log_2(number of microsecsseconds in 2hours);
Ok(())
}
}
fn test_gcd_date_with_codec(
codec_type: FastFieldCodecType,
precision: DatePrecision,
) -> crate::Result<usize> {
let mut rng = StdRng::seed_from_u64(2u64);
const T0: i64 = 1_662_345_825_012_529i64;
const ONE_HOUR_IN_MICROSECS: i64 = 3_600 * 1_000_000;
let times: Vec<DateTime> = std::iter::repeat_with(|| {
// +- One hour.
let t = T0 + rng.gen_range(-ONE_HOUR_IN_MICROSECS..ONE_HOUR_IN_MICROSECS);
DateTime::from_timestamp_micros(t)
})
.take(1_000)
.collect();
let date_options = DateOptions::default()
.set_fast(Cardinality::SingleValue)
.set_precision(precision);
let mut schema_builder = SchemaBuilder::default();
let field = schema_builder.add_date_field("field", date_options);
let schema = schema_builder.build();
#[cfg(all(test, feature = "unstable"))]
mod bench {
use fastfield_codecs::Column;
use test::{self, Bencher};
let docs: Vec<Document> = times.iter().map(|time| doc!(field=>*time)).collect();
use super::tests::generate_permutation;
use super::*;
use crate::fastfield::tests::generate_permutation_gcd;
let directory = get_index(&docs[..], &schema, &[codec_type])?;
let path = Path::new("test");
let file = directory.open_read(path).unwrap();
let composite_file = CompositeFile::open(&file)?;
let file = composite_file.open_read(*FIELD).unwrap();
let len = file.len();
let test_fastfield = open::<DateTime>(file.read_bytes()?)?;
#[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
});
}
for (i, time) in times.iter().enumerate() {
assert_eq!(test_fastfield.get_val(i as u64), time.truncate(precision));
}
Ok(len)
#[bench]
fn bench_intfastfield_jumpy_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column = DynamicFastFieldReader::from(permutation);
b.iter(|| {
let mut a = 0u64;
for _ in 0..n {
a = column.get_val(a as u64);
}
a
});
}
#[bench]
fn bench_intfastfield_stride7_vec(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
b.iter(|| {
let mut a = 0u64;
for i in (0..n / 7).map(|val| val * 7) {
a += permutation[i as usize];
}
a
});
}
#[bench]
fn bench_intfastfield_stride7_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column = DynamicFastFieldReader::from(permutation);
b.iter(|| {
let mut a = 0u64;
for i in (0..n / 7).map(|val| val * 7) {
a += column.get_val(i as u64);
}
a
});
}
#[bench]
fn bench_intfastfield_scan_all_fflookup(b: &mut Bencher) {
let permutation = generate_permutation();
let n = permutation.len();
let column = DynamicFastFieldReader::from(permutation);
b.iter(|| {
let mut a = 0u64;
for i in 0u64..n as u64 {
a += column.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 = DynamicFastFieldReader::from(permutation);
b.iter(|| {
let mut a = 0u64;
for i in 0..n as u64 {
a += column.get_val(i);
}
a
});
}
#[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

@@ -3,7 +3,6 @@ mod writer;
pub use self::reader::MultiValuedFastFieldReader;
pub use self::writer::MultiValuedFastFieldWriter;
pub(crate) use self::writer::MultivalueStartIndex;
#[cfg(test)]
mod tests {
@@ -342,13 +341,11 @@ mod tests {
}
proptest! {
#![proptest_config(proptest::prelude::ProptestConfig::with_cases(5))]
#[test]
fn test_multivalued_proptest(ops in proptest::collection::vec(operation_strategy(), 1..10)) {
assert!(test_multivalued_no_panic(&ops[..]).is_ok());
}
}
#[test]
fn test_multivalued_proptest_gcd() {
use IndexingOp::*;
@@ -387,219 +384,3 @@ mod tests {
Ok(())
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use std::collections::HashMap;
use std::path::Path;
use test::{self, Bencher};
use super::*;
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::fastfield::{CompositeFastFieldSerializer, FastFieldsWriter};
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::schema::{Cardinality, NumericOptions, Schema};
use crate::Document;
fn bench_multi_value_ff_merge_opt(
num_docs: usize,
segments_every_n_docs: usize,
merge_policy: impl crate::indexer::MergePolicy + 'static,
) {
let mut builder = crate::schema::SchemaBuilder::new();
let fast_multi =
crate::schema::NumericOptions::default().set_fast(Cardinality::MultiValues);
let multi_field = builder.add_f64_field("f64s", fast_multi);
let index = crate::Index::create_in_ram(builder.build());
let mut writer = index.writer_for_tests().unwrap();
writer.set_merge_policy(Box::new(merge_policy));
for i in 0..num_docs {
let mut doc = crate::Document::new();
doc.add_f64(multi_field, 0.24);
doc.add_f64(multi_field, 0.27);
doc.add_f64(multi_field, 0.37);
if i % 3 == 0 {
doc.add_f64(multi_field, 0.44);
}
writer.add_document(doc).unwrap();
if i % segments_every_n_docs == 0 {
writer.commit().unwrap();
}
}
{
writer.wait_merging_threads().unwrap();
let mut writer = index.writer_for_tests().unwrap();
let segment_ids = index.searchable_segment_ids().unwrap();
writer.merge(&segment_ids).wait().unwrap();
}
// If a merging thread fails, we should end up with more
// than one segment here
assert_eq!(1, index.searchable_segments().unwrap().len());
}
#[bench]
fn bench_multi_value_ff_merge_many_segments(b: &mut Bencher) {
let num_docs = 100_000;
b.iter(|| {
bench_multi_value_ff_merge_opt(num_docs, 1_000, crate::indexer::NoMergePolicy);
});
}
#[bench]
fn bench_multi_value_ff_merge_many_segments_log_merge(b: &mut Bencher) {
let num_docs = 100_000;
b.iter(|| {
let merge_policy = crate::indexer::LogMergePolicy::default();
bench_multi_value_ff_merge_opt(num_docs, 1_000, merge_policy);
});
}
#[bench]
fn bench_multi_value_ff_merge_few_segments(b: &mut Bencher) {
let num_docs = 100_000;
b.iter(|| {
bench_multi_value_ff_merge_opt(num_docs, 33_000, crate::indexer::NoMergePolicy);
});
}
fn multi_values(num_docs: usize, vals_per_doc: usize) -> Vec<Vec<u64>> {
let mut vals = vec![];
for _i in 0..num_docs {
let mut block = vec![];
for j in 0..vals_per_doc {
block.push(j as u64);
}
vals.push(block);
}
vals
}
#[bench]
fn bench_multi_value_fflookup(b: &mut Bencher) {
let num_docs = 100_000;
let path = Path::new("test");
let directory: RamDirectory = RamDirectory::create();
let field = {
let options = NumericOptions::default().set_fast(Cardinality::MultiValues);
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", options);
let schema = schema_builder.build();
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for block in &multi_values(num_docs, 3) {
let mut doc = Document::new();
for val in block {
doc.add_u64(field, *val);
}
fast_field_writers.add_document(&doc);
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
field
};
let file = directory.open_read(&path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data_idx = fast_fields_composite
.open_read_with_idx(field, 0)
.unwrap()
.read_bytes()
.unwrap();
let idx_reader = fastfield_codecs::open(data_idx).unwrap();
let data_vals = fast_fields_composite
.open_read_with_idx(field, 1)
.unwrap()
.read_bytes()
.unwrap();
let vals_reader = fastfield_codecs::open(data_vals).unwrap();
let fast_field_reader = MultiValuedFastFieldReader::open(idx_reader, vals_reader);
b.iter(|| {
let mut sum = 0u64;
let mut data = Vec::with_capacity(10);
for i in 0u32..num_docs as u32 {
fast_field_reader.get_vals(i, &mut data);
sum += data.iter().sum::<u64>();
}
sum
});
}
}
#[bench]
fn bench_multi_value_ff_creation(b: &mut Bencher) {
// 3 million ff entries
let num_docs = 1_000_000;
let multi_values = multi_values(num_docs, 3);
b.iter(|| {
let directory: RamDirectory = RamDirectory::create();
let options = NumericOptions::default().set_fast(Cardinality::MultiValues);
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", options);
let schema = schema_builder.build();
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for block in &multi_values {
let mut doc = Document::new();
for val in block {
doc.add_u64(field, *val);
}
fast_field_writers.add_document(&doc);
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
});
}
#[bench]
fn bench_multi_value_ff_creation_with_sorting(b: &mut Bencher) {
// 3 million ff entries
let num_docs = 1_000_000;
let multi_values = multi_values(num_docs, 3);
let doc_id_mapping =
DocIdMapping::from_new_id_to_old_id((0..1_000_000).collect::<Vec<_>>());
b.iter(|| {
let directory: RamDirectory = RamDirectory::create();
let options = NumericOptions::default().set_fast(Cardinality::MultiValues);
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", options);
let schema = schema_builder.build();
let write: WritePtr = directory.open_write(Path::new("test")).unwrap();
let mut serializer = CompositeFastFieldSerializer::from_write(write).unwrap();
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
for block in &multi_values {
let mut doc = Document::new();
for val in block {
doc.add_u64(field, *val);
}
fast_field_writers.add_document(&doc);
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), Some(&doc_id_mapping))
.unwrap();
serializer.close().unwrap();
});
}
}

View File

@@ -1,9 +1,8 @@
use std::ops::Range;
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::fastfield::{FastValue, MultiValueLength};
use crate::fastfield::{DynamicFastFieldReader, FastValue, MultiValueLength};
use crate::DocId;
/// Reader for a multivalued `u64` fast field.
@@ -15,14 +14,14 @@ use crate::DocId;
/// The `idx_reader` associated, for each document, the index of its first value.
#[derive(Clone)]
pub struct MultiValuedFastFieldReader<Item: FastValue> {
idx_reader: Arc<dyn Column<u64>>,
vals_reader: Arc<dyn Column<Item>>,
idx_reader: DynamicFastFieldReader<u64>,
vals_reader: DynamicFastFieldReader<Item>,
}
impl<Item: FastValue> MultiValuedFastFieldReader<Item> {
pub(crate) fn open(
idx_reader: Arc<dyn Column<u64>>,
vals_reader: Arc<dyn Column<Item>>,
idx_reader: DynamicFastFieldReader<u64>,
vals_reader: DynamicFastFieldReader<Item>,
) -> MultiValuedFastFieldReader<Item> {
MultiValuedFastFieldReader {
idx_reader,

View File

@@ -1,11 +1,10 @@
use std::io;
use std::sync::Mutex;
use fastfield_codecs::{Column, MonotonicallyMappableToU64, VecColumn};
use fnv::FnvHashMap;
use measure_time::{debug_time, trace_time};
use tantivy_bitpacker::minmax;
use crate::fastfield::{value_to_u64, CompositeFastFieldSerializer, FastFieldType};
use crate::fastfield::serializer::BitpackedSerializerLegacy;
use crate::fastfield::{value_to_u64, CompositeFastFieldSerializer, FastFieldType, FastValue};
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::postings::UnorderedTermId;
use crate::schema::{Document, Field, Value};
@@ -18,15 +17,17 @@ use crate::{DatePrecision, DocId};
/// This `Writer` is only useful for advanced users.
/// The normal way to get your multivalued int in your index
/// is to
/// - declare your field with fast set to
/// [`Cardinality::MultiValues`](crate::schema::Cardinality::MultiValues) in your schema
/// - declare your field with fast set to `Cardinality::MultiValues`
/// in your schema
/// - add your document simply by calling `.add_document(...)`.
///
/// The `MultiValuedFastFieldWriter` can be acquired from the fastfield writer, by calling
/// [`FastFieldWriter::get_multivalue_writer_mut()`](crate::fastfield::FastFieldsWriter::get_multivalue_writer_mut).
/// The `MultiValuedFastFieldWriter` can be acquired from the
/// fastfield writer, by calling
/// [`.get_multivalue_writer_mut(...)`](./struct.FastFieldsWriter.html#method.
/// get_multivalue_writer_mut).
///
/// Once acquired, writing is done by calling
/// [`.add_document(&Document)`](MultiValuedFastFieldWriter::add_document) once per value.
/// [`.add_document_vals(&[u64])`](MultiValuedFastFieldWriter::add_document_vals) once per document.
///
/// The serializer makes it possible to remap all of the values
/// that were pushed to the writer using a mapping.
@@ -100,6 +101,16 @@ impl MultiValuedFastFieldWriter {
}
}
/// Register all of the values associated to a document.
///
/// The method returns the `DocId` of the document that was
/// just written.
pub fn add_document_vals(&mut self, vals: &[UnorderedTermId]) -> DocId {
let doc = self.doc_index.len() as DocId;
self.next_doc();
self.vals.extend_from_slice(vals);
doc
}
/// Returns an iterator over values per doc_id in ascending doc_id order.
///
/// Normally the order is simply iterating self.doc_id_index.
@@ -139,230 +150,73 @@ impl MultiValuedFastFieldWriter {
/// `tantivy` builds a mapping to convert this `UnorderedTermId` into
/// term ordinals.
pub fn serialize(
mut self,
&self,
serializer: &mut CompositeFastFieldSerializer,
term_mapping_opt: Option<&FnvHashMap<UnorderedTermId, TermOrdinal>>,
mapping_opt: Option<&FnvHashMap<UnorderedTermId, TermOrdinal>>,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
{
self.doc_index.push(self.vals.len() as u64);
let col = VecColumn::from(&self.doc_index[..]);
// writing the offset index
let mut doc_index_serializer =
serializer.new_u64_fast_field_with_idx(self.field, 0, self.vals.len() as u64, 0)?;
trace_time!(
"segment-serialize-multi-fast-field-idx, num_vals {}, field_id {:?}",
col.num_vals(),
self.field()
);
if let Some(doc_id_map) = doc_id_map {
let multi_value_start_index = MultivalueStartIndex::new(&col, doc_id_map);
serializer.create_auto_detect_u64_fast_field_with_idx(
self.field,
multi_value_start_index,
0,
)?;
} else {
serializer.create_auto_detect_u64_fast_field_with_idx(self.field, col, 0)?;
let mut offset = 0;
for vals in self.get_ordered_values(doc_id_map) {
doc_index_serializer.add_val(offset)?;
offset += vals.len() as u64;
}
doc_index_serializer.add_val(self.vals.len() as u64)?;
doc_index_serializer.close_field()?;
}
{
trace_time!(
"segment-serialize-multi-fast-field-values, num_vals {}, field_id {:?}",
self.vals.len(),
self.field()
);
// writing the values themselves.
let mut value_serializer: BitpackedSerializerLegacy<'_, _>;
if let Some(mapping) = mapping_opt {
value_serializer = serializer.new_u64_fast_field_with_idx(
self.field,
0u64,
mapping.len() as u64,
1,
)?;
// Writing the values themselves.
// TODO FIXME: Use less memory.
let mut values: Vec<u64> = Vec::new();
if let Some(term_mapping) = term_mapping_opt {
if self.fast_field_type.is_facet() {
let mut doc_vals: Vec<u64> = Vec::with_capacity(100);
for vals in self.get_ordered_values(doc_id_map) {
// In the case of facets, we want a vec of facet ord that is sorted.
doc_vals.clear();
let remapped_vals = vals
.iter()
.map(|val| *term_mapping.get(val).expect("Missing term ordinal"));
.map(|val| *mapping.get(val).expect("Missing term ordinal"));
doc_vals.extend(remapped_vals);
doc_vals.sort_unstable();
for &val in &doc_vals {
values.push(val);
value_serializer.add_val(val)?;
}
}
} else {
for vals in self.get_ordered_values(doc_id_map) {
let remapped_vals = vals
.iter()
.map(|val| *term_mapping.get(val).expect("Missing term ordinal"));
.map(|val| *mapping.get(val).expect("Missing term ordinal"));
for val in remapped_vals {
values.push(val);
value_serializer.add_val(val)?;
}
}
}
} else {
let val_min_max = minmax(self.vals.iter().cloned());
let (val_min, val_max) = val_min_max.unwrap_or((0u64, 0u64));
value_serializer =
serializer.new_u64_fast_field_with_idx(self.field, val_min, val_max, 1)?;
for vals in self.get_ordered_values(doc_id_map) {
// sort values in case of remapped doc_ids?
for &val in vals {
values.push(val);
value_serializer.add_val(val)?;
}
}
}
let col = VecColumn::from(&values[..]);
serializer.create_auto_detect_u64_fast_field_with_idx(self.field, col, 1)?;
value_serializer.close_field()?;
}
Ok(())
}
}
pub(crate) struct MultivalueStartIndex<'a, C: Column> {
column: &'a C,
doc_id_map: &'a DocIdMapping,
min_max_opt: Mutex<Option<(u64, u64)>>,
random_seeker: Mutex<MultivalueStartIndexRandomSeeker<'a, C>>,
}
struct MultivalueStartIndexRandomSeeker<'a, C: Column> {
seek_head: MultivalueStartIndexIter<'a, C>,
seek_next_id: u64,
}
impl<'a, C: Column> MultivalueStartIndexRandomSeeker<'a, C> {
fn new(column: &'a C, doc_id_map: &'a DocIdMapping) -> Self {
Self {
seek_head: MultivalueStartIndexIter {
column,
doc_id_map,
new_doc_id: 0,
offset: 0u64,
},
seek_next_id: 0u64,
}
}
}
impl<'a, C: Column> MultivalueStartIndex<'a, C> {
pub fn new(column: &'a C, doc_id_map: &'a DocIdMapping) -> Self {
assert_eq!(column.num_vals(), doc_id_map.num_old_doc_ids() as u64 + 1);
MultivalueStartIndex {
column,
doc_id_map,
min_max_opt: Mutex::default(),
random_seeker: Mutex::new(MultivalueStartIndexRandomSeeker::new(column, doc_id_map)),
}
}
fn minmax(&self) -> (u64, u64) {
if let Some((min, max)) = *self.min_max_opt.lock().unwrap() {
return (min, max);
}
let (min, max) = tantivy_bitpacker::minmax(self.iter()).unwrap_or((0u64, 0u64));
*self.min_max_opt.lock().unwrap() = Some((min, max));
(min, max)
}
}
impl<'a, C: Column> Column for MultivalueStartIndex<'a, C> {
fn get_val(&self, idx: u64) -> u64 {
let mut random_seeker_lock = self.random_seeker.lock().unwrap();
if random_seeker_lock.seek_next_id > idx {
*random_seeker_lock =
MultivalueStartIndexRandomSeeker::new(self.column, self.doc_id_map);
}
let to_skip = idx - random_seeker_lock.seek_next_id;
random_seeker_lock.seek_next_id = idx + 1;
random_seeker_lock.seek_head.nth(to_skip as usize).unwrap()
}
fn min_value(&self) -> u64 {
self.minmax().0
}
fn max_value(&self) -> u64 {
self.minmax().1
}
fn num_vals(&self) -> u64 {
(self.doc_id_map.num_new_doc_ids() + 1) as u64
}
fn iter<'b>(&'b self) -> Box<dyn Iterator<Item = u64> + 'b> {
Box::new(MultivalueStartIndexIter::new(self.column, self.doc_id_map))
}
}
struct MultivalueStartIndexIter<'a, C: Column> {
pub column: &'a C,
pub doc_id_map: &'a DocIdMapping,
pub new_doc_id: usize,
pub offset: u64,
}
impl<'a, C: Column> MultivalueStartIndexIter<'a, C> {
fn new(column: &'a C, doc_id_map: &'a DocIdMapping) -> Self {
Self {
column,
doc_id_map,
new_doc_id: 0,
offset: 0,
}
}
}
impl<'a, C: Column> Iterator for MultivalueStartIndexIter<'a, C> {
type Item = u64;
fn next(&mut self) -> Option<Self::Item> {
if self.new_doc_id > self.doc_id_map.num_new_doc_ids() {
return None;
}
let new_doc_id = self.new_doc_id;
self.new_doc_id += 1;
let start_offset = self.offset;
if new_doc_id < self.doc_id_map.num_new_doc_ids() {
let old_doc = self.doc_id_map.get_old_doc_id(new_doc_id as u32) as u64;
let num_vals_for_doc = self.column.get_val(old_doc + 1) - self.column.get_val(old_doc);
self.offset += num_vals_for_doc;
}
Some(start_offset)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_multivalue_start_index() {
let doc_id_mapping = DocIdMapping::from_new_id_to_old_id(vec![4, 1, 2]);
assert_eq!(doc_id_mapping.num_old_doc_ids(), 5);
let col = VecColumn::from(&[0u64, 3, 5, 10, 12, 16][..]);
let multivalue_start_index = MultivalueStartIndex::new(
&col, // 3, 2, 5, 2, 4
&doc_id_mapping,
);
assert_eq!(multivalue_start_index.num_vals(), 4);
assert_eq!(
multivalue_start_index.iter().collect::<Vec<u64>>(),
vec![0, 4, 6, 11]
); // 4, 2, 5
}
#[test]
fn test_multivalue_get_vals() {
let doc_id_mapping =
DocIdMapping::from_new_id_to_old_id(vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]);
assert_eq!(doc_id_mapping.num_old_doc_ids(), 10);
let col = VecColumn::from(&[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55][..]);
let multivalue_start_index = MultivalueStartIndex::new(&col, &doc_id_mapping);
assert_eq!(
multivalue_start_index.iter().collect::<Vec<u64>>(),
vec![0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55]
);
assert_eq!(multivalue_start_index.num_vals(), 11);
assert_eq!(multivalue_start_index.get_val(3), 2);
assert_eq!(multivalue_start_index.get_val(5), 5);
assert_eq!(multivalue_start_index.get_val(8), 21);
assert_eq!(multivalue_start_index.get_val(4), 3);
assert_eq!(multivalue_start_index.get_val(0), 0);
assert_eq!(multivalue_start_index.get_val(10), 55);
}
}

278
src/fastfield/reader.rs Normal file
View File

@@ -0,0 +1,278 @@
use std::collections::HashMap;
use std::marker::PhantomData;
use std::path::Path;
use common::BinarySerializable;
use fastfield_codecs::bitpacked::{BitpackedCodec, BitpackedReader};
use fastfield_codecs::blockwise_linear::{BlockwiseLinearCodec, BlockwiseLinearReader};
use fastfield_codecs::linear::{LinearCodec, LinearReader};
use fastfield_codecs::{Column, FastFieldCodec, FastFieldCodecType};
use super::gcd::open_gcd_from_bytes;
use super::FastValue;
use crate::directory::{CompositeFile, Directory, FileSlice, OwnedBytes, RamDirectory, WritePtr};
use crate::error::DataCorruption;
use crate::fastfield::{CompositeFastFieldSerializer, FastFieldsWriter, GCDReader};
use crate::schema::{Schema, FAST};
#[derive(Clone)]
/// DynamicFastFieldReader wraps different readers to access
/// the various encoded fastfield data
pub enum DynamicFastFieldReader<Item: FastValue> {
/// Bitpacked compressed fastfield data.
Bitpacked(FastFieldReaderCodecWrapper<Item, BitpackedReader>),
/// Linear interpolated values + bitpacked
Linear(FastFieldReaderCodecWrapper<Item, LinearReader>),
/// Blockwise linear interpolated values + bitpacked
BlockwiseLinear(FastFieldReaderCodecWrapper<Item, BlockwiseLinearReader>),
/// GCD and Bitpacked compressed fastfield data.
BitpackedGCD(FastFieldReaderCodecWrapper<Item, GCDReader<BitpackedReader>>),
/// GCD and Linear interpolated values + bitpacked
LinearGCD(FastFieldReaderCodecWrapper<Item, GCDReader<LinearReader>>),
/// GCD and Blockwise linear interpolated values + bitpacked
BlockwiseLinearGCD(FastFieldReaderCodecWrapper<Item, GCDReader<BlockwiseLinearReader>>),
}
impl<Item: FastValue> DynamicFastFieldReader<Item> {
/// Returns correct the reader wrapped in the `DynamicFastFieldReader` enum for the data.
pub fn open_from_id(
mut bytes: OwnedBytes,
codec_type: FastFieldCodecType,
) -> crate::Result<DynamicFastFieldReader<Item>> {
let reader = match codec_type {
FastFieldCodecType::Bitpacked => {
DynamicFastFieldReader::Bitpacked(BitpackedCodec::open_from_bytes(bytes)?.into())
}
FastFieldCodecType::Linear => {
DynamicFastFieldReader::Linear(LinearCodec::open_from_bytes(bytes)?.into())
}
FastFieldCodecType::BlockwiseLinear => DynamicFastFieldReader::BlockwiseLinear(
BlockwiseLinearCodec::open_from_bytes(bytes)?.into(),
),
FastFieldCodecType::Gcd => {
let codec_type = FastFieldCodecType::deserialize(&mut bytes)?;
match codec_type {
FastFieldCodecType::Bitpacked => DynamicFastFieldReader::BitpackedGCD(
open_gcd_from_bytes::<BitpackedCodec>(bytes)?.into(),
),
FastFieldCodecType::Linear => DynamicFastFieldReader::LinearGCD(
open_gcd_from_bytes::<LinearCodec>(bytes)?.into(),
),
FastFieldCodecType::BlockwiseLinear => {
DynamicFastFieldReader::BlockwiseLinearGCD(
open_gcd_from_bytes::<BlockwiseLinearCodec>(bytes)?.into(),
)
}
FastFieldCodecType::Gcd => {
return Err(DataCorruption::comment_only(
"Gcd codec wrapped into another gcd codec. This combination is not \
allowed.",
)
.into())
}
}
}
};
Ok(reader)
}
/// Returns correct the reader wrapped in the `DynamicFastFieldReader` enum for the data.
pub fn open(file: FileSlice) -> crate::Result<DynamicFastFieldReader<Item>> {
let mut bytes = file.read_bytes()?;
let codec_type = FastFieldCodecType::deserialize(&mut bytes)?;
Self::open_from_id(bytes, codec_type)
}
}
impl<Item: FastValue> Column<Item> for DynamicFastFieldReader<Item> {
#[inline]
fn get_val(&self, idx: u64) -> Item {
match self {
Self::Bitpacked(reader) => reader.get_val(idx),
Self::Linear(reader) => reader.get_val(idx),
Self::BlockwiseLinear(reader) => reader.get_val(idx),
Self::BitpackedGCD(reader) => reader.get_val(idx),
Self::LinearGCD(reader) => reader.get_val(idx),
Self::BlockwiseLinearGCD(reader) => reader.get_val(idx),
}
}
#[inline]
fn get_range(&self, start: u64, output: &mut [Item]) {
match self {
Self::Bitpacked(reader) => reader.get_range(start, output),
Self::Linear(reader) => reader.get_range(start, output),
Self::BlockwiseLinear(reader) => reader.get_range(start, output),
Self::BitpackedGCD(reader) => reader.get_range(start, output),
Self::LinearGCD(reader) => reader.get_range(start, output),
Self::BlockwiseLinearGCD(reader) => reader.get_range(start, output),
}
}
fn min_value(&self) -> Item {
match self {
Self::Bitpacked(reader) => reader.min_value(),
Self::Linear(reader) => reader.min_value(),
Self::BlockwiseLinear(reader) => reader.min_value(),
Self::BitpackedGCD(reader) => reader.min_value(),
Self::LinearGCD(reader) => reader.min_value(),
Self::BlockwiseLinearGCD(reader) => reader.min_value(),
}
}
fn max_value(&self) -> Item {
match self {
Self::Bitpacked(reader) => reader.max_value(),
Self::Linear(reader) => reader.max_value(),
Self::BlockwiseLinear(reader) => reader.max_value(),
Self::BitpackedGCD(reader) => reader.max_value(),
Self::LinearGCD(reader) => reader.max_value(),
Self::BlockwiseLinearGCD(reader) => reader.max_value(),
}
}
fn num_vals(&self) -> u64 {
match self {
Self::Bitpacked(reader) => reader.num_vals(),
Self::Linear(reader) => reader.num_vals(),
Self::BlockwiseLinear(reader) => reader.num_vals(),
Self::BitpackedGCD(reader) => reader.num_vals(),
Self::LinearGCD(reader) => reader.num_vals(),
Self::BlockwiseLinearGCD(reader) => reader.num_vals(),
}
}
}
/// Wrapper for accessing a fastfield.
///
/// Holds the data and the codec to the read the data.
#[derive(Clone)]
pub struct FastFieldReaderCodecWrapper<Item: FastValue, CodecReader> {
reader: CodecReader,
_phantom: PhantomData<Item>,
}
impl<Item: FastValue, CodecReader> From<CodecReader>
for FastFieldReaderCodecWrapper<Item, CodecReader>
{
fn from(reader: CodecReader) -> Self {
FastFieldReaderCodecWrapper {
reader,
_phantom: PhantomData,
}
}
}
impl<Item: FastValue, D: Column> FastFieldReaderCodecWrapper<Item, D> {
#[inline]
pub(crate) fn get_u64(&self, idx: u64) -> Item {
let data = self.reader.get_val(idx);
Item::from_u64(data)
}
/// Internally `multivalued` also use SingleValue Fast fields.
/// It works as follows... A first column contains the list of start index
/// for each document, a second column contains the actual values.
///
/// The values associated to a given doc, are then
/// `second_column[first_column.get(doc)..first_column.get(doc+1)]`.
///
/// Which means single value fast field reader can be indexed internally with
/// something different from a `DocId`. For this use case, we want to use `u64`
/// values.
///
/// See `get_range` for an actual documentation about this method.
pub(crate) fn get_range_u64(&self, start: u64, output: &mut [Item]) {
for (i, out) in output.iter_mut().enumerate() {
*out = self.get_u64(start + (i as u64));
}
}
}
impl<Item: FastValue, C: Column + Clone> Column<Item> for FastFieldReaderCodecWrapper<Item, C> {
/// Return the value associated to the given document.
///
/// This accessor should return as fast as possible.
///
/// # Panics
///
/// May panic if `doc` is greater than the segment
// `maxdoc`.
fn get_val(&self, idx: u64) -> Item {
self.get_u64(idx)
}
/// Fills an output buffer with the fast field values
/// associated with the `DocId` going from
/// `start` to `start + output.len()`.
///
/// Regardless of the type of `Item`, this method works
/// - transmuting the output array
/// - extracting the `Item`s as if they were `u64`
/// - possibly converting the `u64` value to the right type.
///
/// # Panics
///
/// May panic if `start + output.len()` is greater than
/// the segment's `maxdoc`.
fn get_range(&self, start: u64, output: &mut [Item]) {
self.get_range_u64(start, output);
}
/// Returns the minimum value for this fast field.
///
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value.
fn min_value(&self) -> Item {
Item::from_u64(self.reader.min_value())
}
/// Returns the maximum value for this fast field.
///
/// The max value does not take in account of possible
/// deleted document, and should be considered as an upper bound
/// of the actual maximum value.
fn max_value(&self) -> Item {
Item::from_u64(self.reader.max_value())
}
fn num_vals(&self) -> u64 {
self.reader.num_vals()
}
}
impl<Item: FastValue> From<Vec<Item>> for DynamicFastFieldReader<Item> {
fn from(vals: Vec<Item>) -> DynamicFastFieldReader<Item> {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_u64_field("field", FAST);
let schema = schema_builder.build();
let path = Path::new("__dummy__");
let directory: RamDirectory = RamDirectory::create();
{
let write: WritePtr = directory
.open_write(path)
.expect("With a RamDirectory, this should never fail.");
let mut serializer = CompositeFastFieldSerializer::from_write(write)
.expect("With a RamDirectory, this should never fail.");
let mut fast_field_writers = FastFieldsWriter::from_schema(&schema);
{
let fast_field_writer = fast_field_writers
.get_field_writer_mut(field)
.expect("With a RamDirectory, this should never fail.");
for val in vals {
fast_field_writer.add_val(val.to_u64());
}
}
fast_field_writers
.serialize(&mut serializer, &HashMap::new(), None)
.unwrap();
serializer.close().unwrap();
}
let file = directory.open_read(path).expect("Failed to open the file");
let composite_file = CompositeFile::open(&file).expect("Failed to read the composite file");
let field_file = composite_file
.open_read(field)
.expect("File component not found");
DynamicFastFieldReader::open(field_file).unwrap()
}
}

View File

@@ -1,7 +1,4 @@
use std::sync::Arc;
use fastfield_codecs::{open, Column};
use super::reader::DynamicFastFieldReader;
use crate::directory::{CompositeFile, FileSlice};
use crate::fastfield::{
BytesFastFieldReader, FastFieldNotAvailableError, FastValue, MultiValuedFastFieldReader,
@@ -112,17 +109,14 @@ impl FastFieldReaders {
&self,
field: Field,
index: usize,
) -> crate::Result<Arc<dyn Column<TFastValue>>> {
) -> crate::Result<DynamicFastFieldReader<TFastValue>> {
let fast_field_slice = self.fast_field_data(field, index)?;
let bytes = fast_field_slice.read_bytes()?;
let column = fastfield_codecs::open(bytes)?;
Ok(column)
DynamicFastFieldReader::open(fast_field_slice)
}
pub(crate) fn typed_fast_field_reader<TFastValue: FastValue>(
&self,
field: Field,
) -> crate::Result<Arc<dyn Column<TFastValue>>> {
) -> crate::Result<DynamicFastFieldReader<TFastValue>> {
self.typed_fast_field_reader_with_idx(field, 0)
}
@@ -138,7 +132,7 @@ impl FastFieldReaders {
/// Returns the `u64` fast field reader reader associated to `field`.
///
/// If `field` is not a u64 fast field, this method returns an Error.
pub fn u64(&self, field: Field) -> crate::Result<Arc<dyn Column<u64>>> {
pub fn u64(&self, field: Field) -> crate::Result<DynamicFastFieldReader<u64>> {
self.check_type(field, FastType::U64, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
@@ -148,14 +142,14 @@ impl FastFieldReaders {
///
/// If not, the fastfield reader will returns the u64-value associated to the original
/// FastValue.
pub fn u64_lenient(&self, field: Field) -> crate::Result<Arc<dyn Column<u64>>> {
pub fn u64_lenient(&self, field: Field) -> crate::Result<DynamicFastFieldReader<u64>> {
self.typed_fast_field_reader(field)
}
/// Returns the `i64` fast field reader reader associated to `field`.
///
/// If `field` is not a i64 fast field, this method returns an Error.
pub fn i64(&self, field: Field) -> crate::Result<Arc<dyn Column<i64>>> {
pub fn i64(&self, field: Field) -> crate::Result<DynamicFastFieldReader<i64>> {
self.check_type(field, FastType::I64, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
@@ -163,7 +157,7 @@ impl FastFieldReaders {
/// Returns the `date` fast field reader reader associated to `field`.
///
/// If `field` is not a date fast field, this method returns an Error.
pub fn date(&self, field: Field) -> crate::Result<Arc<dyn Column<DateTime>>> {
pub fn date(&self, field: Field) -> crate::Result<DynamicFastFieldReader<DateTime>> {
self.check_type(field, FastType::Date, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
@@ -171,7 +165,7 @@ impl FastFieldReaders {
/// Returns the `f64` fast field reader reader associated to `field`.
///
/// If `field` is not a f64 fast field, this method returns an Error.
pub fn f64(&self, field: Field) -> crate::Result<Arc<dyn Column<f64>>> {
pub fn f64(&self, field: Field) -> crate::Result<DynamicFastFieldReader<f64>> {
self.check_type(field, FastType::F64, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
@@ -179,7 +173,7 @@ impl FastFieldReaders {
/// Returns the `bool` fast field reader reader associated to `field`.
///
/// If `field` is not a bool fast field, this method returns an Error.
pub fn bool(&self, field: Field) -> crate::Result<Arc<dyn Column<bool>>> {
pub fn bool(&self, field: Field) -> crate::Result<DynamicFastFieldReader<bool>> {
self.check_type(field, FastType::Bool, Cardinality::SingleValue)?;
self.typed_fast_field_reader(field)
}
@@ -247,8 +241,7 @@ impl FastFieldReaders {
)));
}
let fast_field_idx_file = self.fast_field_data(field, 0)?;
let fast_field_idx_bytes = fast_field_idx_file.read_bytes()?;
let idx_reader = open(fast_field_idx_bytes)?;
let idx_reader = DynamicFastFieldReader::open(fast_field_idx_file)?;
let data = self.fast_field_data(field, 1)?;
BytesFastFieldReader::open(idx_reader, data)
} else {

View File

@@ -1,9 +1,17 @@
use std::io::{self, Write};
use std::num::NonZeroU64;
pub use fastfield_codecs::Column;
use fastfield_codecs::{FastFieldCodecType, MonotonicallyMappableToU64, ALL_CODEC_TYPES};
use common::{BinarySerializable, CountingWriter};
use fastdivide::DividerU64;
pub use fastfield_codecs::bitpacked::{BitpackedCodec, BitpackedSerializerLegacy};
use fastfield_codecs::blockwise_linear::BlockwiseLinearCodec;
use fastfield_codecs::linear::LinearCodec;
use fastfield_codecs::FastFieldCodecType;
pub use fastfield_codecs::{Column, FastFieldCodec, FastFieldStats};
use super::{find_gcd, ALL_CODECS, GCD_DEFAULT};
use crate::directory::{CompositeWrite, WritePtr};
use crate::fastfield::gcd::write_gcd_header;
use crate::schema::Field;
/// `CompositeFastFieldSerializer` is in charge of serializing
@@ -15,68 +23,272 @@ use crate::schema::Field;
/// the serializer.
/// The serializer expects to receive the following calls.
///
/// * `create_auto_detect_u64_fast_field(...)`
/// * `create_auto_detect_u64_fast_field(...)`
/// * `new_u64_fast_field(...)`
/// * `add_val(...)`
/// * `add_val(...)`
/// * `add_val(...)`
/// * ...
/// * `let bytes_fastfield = new_bytes_fast_field(...)`
/// * `bytes_fastfield.write_all(...)`
/// * `bytes_fastfield.write_all(...)`
/// * `bytes_fastfield.flush()`
/// * `close_field()`
/// * `new_u64_fast_field(...)`
/// * `add_val(...)`
/// * ...
/// * `close_field()`
/// * `close()`
pub struct CompositeFastFieldSerializer {
composite_write: CompositeWrite<WritePtr>,
codec_types: Vec<FastFieldCodecType>,
codec_enable_checker: FastFieldCodecEnableCheck,
}
#[derive(Debug, Clone)]
pub struct FastFieldCodecEnableCheck {
enabled_codecs: Vec<FastFieldCodecType>,
}
impl FastFieldCodecEnableCheck {
fn allow_all() -> Self {
FastFieldCodecEnableCheck {
enabled_codecs: ALL_CODECS.to_vec(),
}
}
fn is_enabled(&self, code_type: FastFieldCodecType) -> bool {
self.enabled_codecs.contains(&code_type)
}
}
impl From<FastFieldCodecType> for FastFieldCodecEnableCheck {
fn from(code_type: FastFieldCodecType) -> Self {
FastFieldCodecEnableCheck {
enabled_codecs: vec![code_type],
}
}
}
// use this, when this is merged and stabilized explicit_generic_args_with_impl_trait
// https://github.com/rust-lang/rust/pull/86176
fn codec_estimation<C: FastFieldCodec>(
fastfield_accessor: &impl Column,
estimations: &mut Vec<(f32, FastFieldCodecType)>,
) {
if let Some(ratio) = C::estimate(fastfield_accessor) {
estimations.push((ratio, C::CODEC_TYPE));
}
}
impl CompositeFastFieldSerializer {
/// New fast field serializer with all codec types
/// Constructor
pub fn from_write(write: WritePtr) -> io::Result<CompositeFastFieldSerializer> {
Self::from_write_with_codec(write, &ALL_CODEC_TYPES)
Self::from_write_with_codec(write, FastFieldCodecEnableCheck::allow_all())
}
/// New fast field serializer with allowed codec types
/// Constructor
pub fn from_write_with_codec(
write: WritePtr,
codec_types: &[FastFieldCodecType],
codec_enable_checker: FastFieldCodecEnableCheck,
) -> io::Result<CompositeFastFieldSerializer> {
// just making room for the pointer to header.
let composite_write = CompositeWrite::wrap(write);
Ok(CompositeFastFieldSerializer {
composite_write,
codec_types: codec_types.to_vec(),
codec_enable_checker,
})
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field<T: MonotonicallyMappableToU64>(
pub fn create_auto_detect_u64_fast_field(
&mut self,
field: Field,
fastfield_accessor: impl Column<T>,
fastfield_accessor: impl Column,
) -> io::Result<()> {
self.create_auto_detect_u64_fast_field_with_idx(field, fastfield_accessor, 0)
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field_with_idx<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
fastfield_accessor: impl Column<T>,
idx: usize,
pub fn write_header<W: Write>(
field_write: &mut W,
codec_type: FastFieldCodecType,
) -> io::Result<()> {
let field_write = self.composite_write.for_field_with_idx(field, idx);
fastfield_codecs::serialize(fastfield_accessor, field_write, &self.codec_types)?;
codec_type.to_code().serialize(field_write)?;
Ok(())
}
/// Start serializing a new [u8] fast field. Use the returned writer to write data into the
/// bytes field. To associate the bytes with documents a seperate index must be created on
/// index 0. See bytes/writer.rs::serialize for an example.
///
/// The bytes will be stored as is, no compression will be applied.
pub fn new_bytes_fast_field(&mut self, field: Field) -> impl Write + '_ {
self.composite_write.for_field_with_idx(field, 1)
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field_with_idx(
&mut self,
field: Field,
fastfield_accessor: impl Column,
idx: usize,
) -> io::Result<()> {
let min_value = fastfield_accessor.min_value();
let field_write = self.composite_write.for_field_with_idx(field, idx);
let gcd = find_gcd(fastfield_accessor.iter().map(|val| val - min_value))
.map(NonZeroU64::get)
.unwrap_or(GCD_DEFAULT);
if gcd == 1 {
return Self::create_auto_detect_u64_fast_field_with_idx_gcd(
self.codec_enable_checker.clone(),
field,
field_write,
fastfield_accessor,
);
}
Self::write_header(field_write, FastFieldCodecType::Gcd)?;
struct GCDWrappedFFAccess<T: Column> {
fastfield_accessor: T,
base_value: u64,
max_value: u64,
num_vals: u64,
gcd: DividerU64,
}
impl<T: Column> Column for GCDWrappedFFAccess<T> {
fn get_val(&self, position: u64) -> u64 {
self.gcd
.divide(self.fastfield_accessor.get_val(position) - self.base_value)
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(
self.fastfield_accessor
.iter()
.map(|val| self.gcd.divide(val - self.base_value)),
)
}
fn min_value(&self) -> u64 {
0
}
fn max_value(&self) -> u64 {
self.max_value
}
fn num_vals(&self) -> u64 {
self.num_vals
}
}
let num_vals = fastfield_accessor.num_vals();
let base_value = fastfield_accessor.min_value();
let max_value = (fastfield_accessor.max_value() - fastfield_accessor.min_value()) / gcd;
let fastfield_accessor = GCDWrappedFFAccess {
fastfield_accessor,
base_value,
max_value,
num_vals,
gcd: DividerU64::divide_by(gcd),
};
Self::create_auto_detect_u64_fast_field_with_idx_gcd(
self.codec_enable_checker.clone(),
field,
field_write,
fastfield_accessor,
)?;
write_gcd_header(field_write, base_value, gcd, num_vals)?;
Ok(())
}
/// Serialize data into a new u64 fast field. The best compression codec will be chosen
/// automatically.
pub fn create_auto_detect_u64_fast_field_with_idx_gcd<W: Write>(
codec_enable_checker: FastFieldCodecEnableCheck,
field: Field,
field_write: &mut CountingWriter<W>,
fastfield_accessor: impl Column,
) -> io::Result<()> {
let mut estimations = vec![];
if codec_enable_checker.is_enabled(FastFieldCodecType::Bitpacked) {
codec_estimation::<BitpackedCodec>(&fastfield_accessor, &mut estimations);
}
if codec_enable_checker.is_enabled(FastFieldCodecType::Linear) {
codec_estimation::<LinearCodec>(&fastfield_accessor, &mut estimations);
}
if codec_enable_checker.is_enabled(FastFieldCodecType::BlockwiseLinear) {
codec_estimation::<BlockwiseLinearCodec>(&fastfield_accessor, &mut estimations);
}
if let Some(broken_estimation) = estimations.iter().find(|estimation| estimation.0.is_nan())
{
warn!(
"broken estimation for fast field codec {:?}",
broken_estimation.1
);
}
// removing nan values for codecs with broken calculations, and max values which disables
// codecs
estimations.retain(|estimation| !estimation.0.is_nan() && estimation.0 != f32::MAX);
estimations.sort_by(|a, b| a.0.partial_cmp(&b.0).unwrap());
let (_ratio, codec_type) = estimations[0];
debug!("choosing fast field codec {codec_type:?} for field_id {field:?}"); // todo print actual field name
Self::write_header(field_write, codec_type)?;
match codec_type {
FastFieldCodecType::Bitpacked => {
BitpackedCodec::serialize(field_write, &fastfield_accessor)?;
}
FastFieldCodecType::Linear => {
LinearCodec::serialize(field_write, &fastfield_accessor)?;
}
FastFieldCodecType::BlockwiseLinear => {
BlockwiseLinearCodec::serialize(field_write, &fastfield_accessor)?;
}
FastFieldCodecType::Gcd => {
return Err(io::Error::new(
io::ErrorKind::InvalidData,
"GCD codec not supported.",
));
}
}
field_write.flush()?;
Ok(())
}
/// Start serializing a new u64 fast field
pub fn serialize_into(
&mut self,
field: Field,
min_value: u64,
max_value: u64,
) -> io::Result<BitpackedSerializerLegacy<'_, CountingWriter<WritePtr>>> {
self.new_u64_fast_field_with_idx(field, min_value, max_value, 0)
}
/// Start serializing a new u64 fast field
pub fn new_u64_fast_field(
&mut self,
field: Field,
min_value: u64,
max_value: u64,
) -> io::Result<BitpackedSerializerLegacy<'_, CountingWriter<WritePtr>>> {
self.new_u64_fast_field_with_idx(field, min_value, max_value, 0)
}
/// Start serializing a new u64 fast field
pub fn new_u64_fast_field_with_idx(
&mut self,
field: Field,
min_value: u64,
max_value: u64,
idx: usize,
) -> io::Result<BitpackedSerializerLegacy<'_, CountingWriter<WritePtr>>> {
let field_write = self.composite_write.for_field_with_idx(field, idx);
// Prepend codec id to field data for compatibility with DynamicFastFieldReader.
FastFieldCodecType::Bitpacked.serialize(field_write)?;
BitpackedSerializerLegacy::open(field_write, min_value, max_value)
}
/// Start serializing a new [u8] fast field
pub fn new_bytes_fast_field_with_idx(
&mut self,
field: Field,
idx: usize,
) -> FastBytesFieldSerializer<'_, CountingWriter<WritePtr>> {
let field_write = self.composite_write.for_field_with_idx(field, idx);
FastBytesFieldSerializer { write: field_write }
}
/// Closes the serializer
@@ -86,3 +298,17 @@ impl CompositeFastFieldSerializer {
self.composite_write.close()
}
}
pub struct FastBytesFieldSerializer<'a, W: Write> {
write: &'a mut W,
}
impl<'a, W: Write> FastBytesFieldSerializer<'a, W> {
pub fn write_all(&mut self, vals: &[u8]) -> io::Result<()> {
self.write.write_all(vals)
}
pub fn flush(&mut self) -> io::Result<()> {
self.write.flush()
}
}

View File

@@ -2,13 +2,13 @@ use std::collections::HashMap;
use std::io;
use common;
use fastfield_codecs::{Column, MonotonicallyMappableToU64};
use fastfield_codecs::Column;
use fnv::FnvHashMap;
use measure_time::{debug_time, trace_time};
use tantivy_bitpacker::BlockedBitpacker;
use super::multivalued::MultiValuedFastFieldWriter;
use super::FastFieldType;
use super::serializer::FastFieldStats;
use super::{FastFieldType, FastValue};
use crate::fastfield::{BytesFastFieldWriter, CompositeFastFieldSerializer};
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::postings::UnorderedTermId;
@@ -169,7 +169,7 @@ impl FastFieldsWriter {
/// Returns the fast field multi-value writer for the given field.
///
/// Returns `None` if the field does not exist, or is not
/// Returns None if the field does not exist, or is not
/// configured as a multivalued fastfield in the schema.
pub fn get_multivalue_writer_mut(
&mut self,
@@ -183,7 +183,7 @@ impl FastFieldsWriter {
/// Returns the bytes fast field writer for the given field.
///
/// Returns `None` if the field does not exist, or is not
/// Returns None if the field does not exist, or is not
/// configured as a bytes fastfield in the schema.
pub fn get_bytes_writer_mut(&mut self, field: Field) -> Option<&mut BytesFastFieldWriter> {
// TODO optimize
@@ -211,13 +211,12 @@ impl FastFieldsWriter {
/// Serializes all of the `FastFieldWriter`s by pushing them in
/// order to the fast field serializer.
pub fn serialize(
self,
&self,
serializer: &mut CompositeFastFieldSerializer,
mapping: &HashMap<Field, FnvHashMap<UnorderedTermId, TermOrdinal>>,
doc_id_map: Option<&DocIdMapping>,
) -> io::Result<()> {
debug_time!("segment-serialize-all-fast-fields",);
for field_writer in self.term_id_writers {
for field_writer in &self.term_id_writers {
let field = field_writer.field();
field_writer.serialize(serializer, mapping.get(&field), doc_id_map)?;
}
@@ -225,11 +224,11 @@ impl FastFieldsWriter {
field_writer.serialize(serializer, doc_id_map)?;
}
for field_writer in self.multi_values_writers {
for field_writer in &self.multi_values_writers {
let field = field_writer.field();
field_writer.serialize(serializer, mapping.get(&field), doc_id_map)?;
}
for field_writer in self.bytes_value_writers {
for field_writer in &self.bytes_value_writers {
field_writer.serialize(serializer, doc_id_map)?;
}
Ok(())
@@ -361,18 +360,17 @@ impl IntFastFieldWriter {
(self.val_min, self.val_max)
};
let fastfield_accessor = WriterFastFieldAccessProvider {
doc_id_map,
vals: &self.vals,
let stats = FastFieldStats {
min_value: min,
max_value: max,
num_vals: self.val_count as u64,
};
trace_time!(
"segment-serialize-single-value-field, field_id {:?}",
self.field()
);
let fastfield_accessor = WriterFastFieldAccessProvider {
doc_id_map,
vals: &self.vals,
stats,
};
serializer.create_auto_detect_u64_fast_field(self.field, fastfield_accessor)?;
@@ -384,11 +382,8 @@ impl IntFastFieldWriter {
struct WriterFastFieldAccessProvider<'map, 'bitp> {
doc_id_map: Option<&'map DocIdMapping>,
vals: &'bitp BlockedBitpacker,
min_value: u64,
max_value: u64,
num_vals: u64,
stats: FastFieldStats,
}
impl<'map, 'bitp> Column for WriterFastFieldAccessProvider<'map, 'bitp> {
/// Return the value associated to the given doc.
///
@@ -422,14 +417,14 @@ impl<'map, 'bitp> Column for WriterFastFieldAccessProvider<'map, 'bitp> {
}
fn min_value(&self) -> u64 {
self.min_value
self.stats.min_value
}
fn max_value(&self) -> u64 {
self.max_value
self.stats.max_value
}
fn num_vals(&self) -> u64 {
self.num_vals
self.stats.num_vals
}
}

View File

@@ -178,7 +178,7 @@ pub struct DeleteCursor {
impl DeleteCursor {
/// Skips operations and position it so that
/// - either all of the delete operation currently in the queue are consume and the next get
/// will return `None`.
/// will return None.
/// - the next get will return the first operation with an
/// `opstamp >= target_opstamp`.
pub fn skip_to(&mut self, target_opstamp: Opstamp) {
@@ -246,27 +246,18 @@ impl DeleteCursor {
mod tests {
use super::{DeleteOperation, DeleteQueue};
use crate::query::{Explanation, Scorer, Weight};
use crate::{DocId, Score, SegmentReader};
struct DummyWeight;
impl Weight for DummyWeight {
fn scorer(&self, _reader: &SegmentReader, _boost: Score) -> crate::Result<Box<dyn Scorer>> {
Err(crate::TantivyError::InternalError("dummy impl".to_owned()))
}
fn explain(&self, _reader: &SegmentReader, _doc: DocId) -> crate::Result<Explanation> {
Err(crate::TantivyError::InternalError("dummy impl".to_owned()))
}
}
use crate::schema::{Field, Term};
#[test]
fn test_deletequeue() {
let delete_queue = DeleteQueue::new();
let make_op = |i: usize| DeleteOperation {
opstamp: i as u64,
target: Box::new(DummyWeight),
let make_op = |i: usize| {
let field = Field::from_field_id(1u32);
DeleteOperation {
opstamp: i as u64,
term: Term::from_field_u64(field, i as u64),
}
};
delete_queue.push(make_op(1));

View File

@@ -91,12 +91,6 @@ impl DocIdMapping {
.map(|old_doc| els[*old_doc as usize])
.collect()
}
pub fn num_new_doc_ids(&self) -> usize {
self.new_doc_id_to_old.len()
}
pub fn num_old_doc_ids(&self) -> usize {
self.old_doc_id_to_new.len()
}
}
pub(crate) fn expect_field_id_for_sort_field(
@@ -149,6 +143,8 @@ pub(crate) fn get_doc_id_mapping_from_field(
#[cfg(test)]
mod tests_indexsorting {
use fastfield_codecs::Column;
use crate::collector::TopDocs;
use crate::indexer::doc_id_mapping::DocIdMapping;
use crate::query::QueryParser;

View File

@@ -11,6 +11,7 @@ use super::segment_updater::SegmentUpdater;
use super::{AddBatch, AddBatchReceiver, AddBatchSender, PreparedCommit};
use crate::core::{Index, Segment, SegmentComponent, SegmentId, SegmentMeta, SegmentReader};
use crate::directory::{DirectoryLock, GarbageCollectionResult, TerminatingWrite};
use crate::docset::{DocSet, TERMINATED};
use crate::error::TantivyError;
use crate::fastfield::write_alive_bitset;
use crate::indexer::delete_queue::{DeleteCursor, DeleteQueue};
@@ -19,9 +20,8 @@ use crate::indexer::index_writer_status::IndexWriterStatus;
use crate::indexer::operation::DeleteOperation;
use crate::indexer::stamper::Stamper;
use crate::indexer::{MergePolicy, SegmentEntry, SegmentWriter};
use crate::query::{Query, TermQuery};
use crate::schema::{Document, IndexRecordOption, Term};
use crate::{FutureResult, IndexReader, Opstamp};
use crate::{FutureResult, Opstamp};
// Size of the margin for the `memory_arena`. A segment is closed when the remaining memory
// in the `memory_arena` goes below MARGIN_IN_BYTES.
@@ -31,7 +31,7 @@ pub const MARGIN_IN_BYTES: usize = 1_000_000;
pub const MEMORY_ARENA_NUM_BYTES_MIN: usize = ((MARGIN_IN_BYTES as u32) * 3u32) as usize;
pub const MEMORY_ARENA_NUM_BYTES_MAX: usize = u32::MAX as usize - MARGIN_IN_BYTES;
// We impose the number of index writer threads to be at most this.
// We impose the number of index writer thread to be at most this.
pub const MAX_NUM_THREAD: usize = 8;
// Add document will block if the number of docs waiting in the queue to be indexed
@@ -40,7 +40,7 @@ const PIPELINE_MAX_SIZE_IN_DOCS: usize = 10_000;
fn error_in_index_worker_thread(context: &str) -> TantivyError {
TantivyError::ErrorInThread(format!(
"{}. A worker thread encountered an error (io::Error most likely) or panicked.",
"{}. A worker thread encounterred an error (io::Error most likely) or panicked.",
context
))
}
@@ -49,7 +49,7 @@ fn error_in_index_worker_thread(context: &str) -> TantivyError {
///
/// It manages a small number of indexing thread, as well as a shared
/// indexing queue.
/// Each indexing thread builds its own independent [`Segment`], via
/// Each indexing thread builds its own independent `Segment`, via
/// a `SegmentWriter` object.
pub struct IndexWriter {
// the lock is just used to bind the
@@ -57,7 +57,6 @@ pub struct IndexWriter {
_directory_lock: Option<DirectoryLock>,
index: Index,
index_reader: IndexReader,
memory_arena_in_bytes_per_thread: usize,
@@ -93,14 +92,19 @@ fn compute_deleted_bitset(
// A delete operation should only affect
// document that were inserted before it.
delete_op
.target
.for_each(segment_reader, &mut |doc_matching_delete_query, _| {
if doc_opstamps.is_deleted(doc_matching_delete_query, delete_op.opstamp) {
alive_bitset.remove(doc_matching_delete_query);
let inverted_index = segment_reader.inverted_index(delete_op.term.field())?;
if let Some(mut docset) =
inverted_index.read_postings(&delete_op.term, IndexRecordOption::Basic)?
{
let mut doc_matching_deleted_term = docset.doc();
while doc_matching_deleted_term != TERMINATED {
if doc_opstamps.is_deleted(doc_matching_deleted_term, delete_op.opstamp) {
alive_bitset.remove(doc_matching_deleted_term);
might_have_changed = true;
}
})?;
doc_matching_deleted_term = docset.advance();
}
}
delete_cursor.advance();
}
Ok(might_have_changed)
@@ -298,7 +302,6 @@ impl IndexWriter {
memory_arena_in_bytes_per_thread,
index: index.clone(),
index_reader: index.reader()?,
index_writer_status: IndexWriterStatus::from(document_receiver),
operation_sender: document_sender,
@@ -382,8 +385,8 @@ impl IndexWriter {
.operation_receiver()
.ok_or_else(|| {
crate::TantivyError::ErrorInThread(
"The index writer was killed. It can happen if an indexing worker encountered \
an Io error for instance."
"The index writer was killed. It can happen if an indexing worker \
encounterred an Io error for instance."
.to_string(),
)
})
@@ -507,12 +510,10 @@ impl IndexWriter {
Ok(self.committed_opstamp)
}
/// Merges a given list of segments.
///
/// If all segments are empty no new segment will be created.
/// Merges a given list of segments
///
/// `segment_ids` is required to be non-empty.
pub fn merge(&mut self, segment_ids: &[SegmentId]) -> FutureResult<Option<SegmentMeta>> {
pub fn merge(&mut self, segment_ids: &[SegmentId]) -> FutureResult<SegmentMeta> {
let merge_operation = self.segment_updater.make_merge_operation(segment_ids);
let segment_updater = self.segment_updater.clone();
segment_updater.start_merge(merge_operation)
@@ -592,14 +593,14 @@ impl IndexWriter {
/// * `.commit()`: to accept this commit
/// * `.abort()`: to cancel this commit.
///
/// In the current implementation, [`PreparedCommit`] borrows
/// the [`IndexWriter`] mutably so we are guaranteed that no new
/// In the current implementation, `PreparedCommit` borrows
/// the `IndexWriter` mutably so we are guaranteed that no new
/// document can be added as long as it is committed or is
/// dropped.
///
/// It is also possible to add a payload to the `commit`
/// using this API.
/// See [`PreparedCommit::set_payload()`].
/// See [`PreparedCommit::set_payload()`](PreparedCommit.html)
pub fn prepare_commit(&mut self) -> crate::Result<PreparedCommit> {
// Here, because we join all of the worker threads,
// all of the segment update for this commit have been
@@ -663,33 +664,10 @@ impl IndexWriter {
/// Like adds, the deletion itself will be visible
/// only after calling `commit()`.
pub fn delete_term(&self, term: Term) -> Opstamp {
let query = TermQuery::new(term, IndexRecordOption::Basic);
// For backward compatibility, if Term is invalid for the index, do nothing but return an
// Opstamp
self.delete_query(Box::new(query))
.unwrap_or_else(|_| self.stamper.stamp())
}
/// Delete all documents matching a given query.
/// Returns an `Err` if the query can't be executed.
///
/// Delete operation only affects documents that
/// were added in previous commits, and documents
/// that were added previously in the same commit.
///
/// Like adds, the deletion itself will be visible
/// only after calling `commit()`.
#[doc(hidden)]
pub fn delete_query(&self, query: Box<dyn Query>) -> crate::Result<Opstamp> {
let weight = query.weight(&self.index_reader.searcher(), false)?;
let opstamp = self.stamper.stamp();
let delete_operation = DeleteOperation {
opstamp,
target: weight,
};
let delete_operation = DeleteOperation { opstamp, term };
self.delete_queue.push(delete_operation);
Ok(opstamp)
opstamp
}
/// Returns the opstamp of the last successful commit.
@@ -758,17 +736,10 @@ impl IndexWriter {
let (batch_opstamp, stamps) = self.get_batch_opstamps(count);
let mut adds = AddBatch::default();
for (user_op, opstamp) in user_operations_it.zip(stamps) {
match user_op {
UserOperation::Delete(term) => {
let query = TermQuery::new(term, IndexRecordOption::Basic);
let weight = query.weight(&self.index_reader.searcher(), false)?;
let delete_operation = DeleteOperation {
opstamp,
target: weight,
};
let delete_operation = DeleteOperation { opstamp, term };
self.delete_queue.push(delete_operation);
}
UserOperation::Add(document) => {
@@ -804,6 +775,7 @@ impl Drop for IndexWriter {
mod tests {
use std::collections::{HashMap, HashSet};
use fastfield_codecs::Column;
use proptest::prelude::*;
use proptest::prop_oneof;
use proptest::strategy::Strategy;
@@ -813,7 +785,7 @@ mod tests {
use crate::directory::error::LockError;
use crate::error::*;
use crate::indexer::NoMergePolicy;
use crate::query::{BooleanQuery, Occur, Query, QueryParser, TermQuery};
use crate::query::{QueryParser, TermQuery};
use crate::schema::{
self, Cardinality, Facet, FacetOptions, IndexRecordOption, NumericOptions,
TextFieldIndexing, TextOptions, FAST, INDEXED, STORED, STRING, TEXT,
@@ -1040,92 +1012,6 @@ mod tests {
Ok(())
}
#[test]
fn test_merge_on_empty_segments_single_segment() -> crate::Result<()> {
let mut schema_builder = schema::Schema::builder();
let text_field = schema_builder.add_text_field("text", schema::TEXT);
let index = Index::create_in_ram(schema_builder.build());
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()?;
let num_docs_containing = |s: &str| {
let term_a = Term::from_field_text(text_field, s);
reader.searcher().doc_freq(&term_a).unwrap()
};
// writing the segment
let mut index_writer = index.writer(12_000_000).unwrap();
index_writer.add_document(doc!(text_field=>"a"))?;
index_writer.commit()?;
// this should create 1 segment
let segments = index.searchable_segment_ids().unwrap();
assert_eq!(segments.len(), 1);
reader.reload().unwrap();
assert_eq!(num_docs_containing("a"), 1);
index_writer.delete_term(Term::from_field_text(text_field, "a"));
index_writer.commit()?;
reader.reload().unwrap();
assert_eq!(num_docs_containing("a"), 0);
index_writer.merge(&segments);
index_writer.wait_merging_threads().unwrap();
let segments = index.searchable_segment_ids().unwrap();
assert_eq!(segments.len(), 0);
Ok(())
}
#[test]
fn test_merge_on_empty_segments() -> crate::Result<()> {
let mut schema_builder = schema::Schema::builder();
let text_field = schema_builder.add_text_field("text", schema::TEXT);
let index = Index::create_in_ram(schema_builder.build());
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()?;
let num_docs_containing = |s: &str| {
let term_a = Term::from_field_text(text_field, s);
reader.searcher().doc_freq(&term_a).unwrap()
};
// writing the segment
let mut index_writer = index.writer(12_000_000).unwrap();
index_writer.add_document(doc!(text_field=>"a"))?;
index_writer.commit()?;
index_writer.add_document(doc!(text_field=>"a"))?;
index_writer.commit()?;
index_writer.add_document(doc!(text_field=>"a"))?;
index_writer.commit()?;
index_writer.add_document(doc!(text_field=>"a"))?;
index_writer.commit()?;
// this should create 4 segments
let segments = index.searchable_segment_ids().unwrap();
assert_eq!(segments.len(), 4);
reader.reload().unwrap();
assert_eq!(num_docs_containing("a"), 4);
index_writer.delete_term(Term::from_field_text(text_field, "a"));
index_writer.commit()?;
reader.reload().unwrap();
assert_eq!(num_docs_containing("a"), 0);
index_writer.merge(&segments);
index_writer.wait_merging_threads().unwrap();
let segments = index.searchable_segment_ids().unwrap();
assert_eq!(segments.len(), 0);
Ok(())
}
#[test]
fn test_with_merges() -> crate::Result<()> {
let mut schema_builder = schema::Schema::builder();
@@ -1445,72 +1331,10 @@ mod tests {
Ok(())
}
#[test]
fn test_delete_query_with_sort_by_field() -> crate::Result<()> {
let mut schema_builder = schema::Schema::builder();
let id_field =
schema_builder.add_u64_field("id", schema::INDEXED | schema::STORED | schema::FAST);
let schema = schema_builder.build();
let settings = IndexSettings {
sort_by_field: Some(IndexSortByField {
field: "id".to_string(),
order: Order::Desc,
}),
..Default::default()
};
let index = Index::builder()
.schema(schema)
.settings(settings)
.create_in_ram()?;
let index_reader = index.reader()?;
let mut index_writer = index.writer_for_tests()?;
// create and delete docs in same commit
for id in 0u64..5u64 {
index_writer.add_document(doc!(id_field => id))?;
}
for id in 1u64..4u64 {
let term = Term::from_field_u64(id_field, id);
let not_term = Term::from_field_u64(id_field, 2);
let term = Box::new(TermQuery::new(term, Default::default()));
let not_term = Box::new(TermQuery::new(not_term, Default::default()));
let query: BooleanQuery = vec![
(Occur::Must, term as Box<dyn Query>),
(Occur::MustNot, not_term as Box<dyn Query>),
]
.into();
index_writer.delete_query(Box::new(query))?;
}
for id in 5u64..10u64 {
index_writer.add_document(doc!(id_field => id))?;
}
index_writer.commit()?;
index_reader.reload()?;
let searcher = index_reader.searcher();
assert_eq!(searcher.segment_readers().len(), 1);
let segment_reader = searcher.segment_reader(0);
assert_eq!(segment_reader.num_docs(), 8);
assert_eq!(segment_reader.max_doc(), 10);
let fast_field_reader = segment_reader.fast_fields().u64(id_field)?;
let in_order_alive_ids: Vec<u64> = segment_reader
.doc_ids_alive()
.map(|doc| fast_field_reader.get_val(doc as u64))
.collect();
assert_eq!(&in_order_alive_ids[..], &[9, 8, 7, 6, 5, 4, 2, 0]);
Ok(())
}
#[derive(Debug, Clone, Copy)]
enum IndexingOp {
AddDoc { id: u64 },
DeleteDoc { id: u64 },
DeleteDocQuery { id: u64 },
Commit,
Merge,
}
@@ -1518,7 +1342,6 @@ mod tests {
fn balanced_operation_strategy() -> impl Strategy<Value = IndexingOp> {
prop_oneof![
(0u64..20u64).prop_map(|id| IndexingOp::DeleteDoc { id }),
(0u64..20u64).prop_map(|id| IndexingOp::DeleteDocQuery { id }),
(0u64..20u64).prop_map(|id| IndexingOp::AddDoc { id }),
(0u64..1u64).prop_map(|_| IndexingOp::Commit),
(0u64..1u64).prop_map(|_| IndexingOp::Merge),
@@ -1527,8 +1350,7 @@ mod tests {
fn adding_operation_strategy() -> impl Strategy<Value = IndexingOp> {
prop_oneof![
5 => (0u64..100u64).prop_map(|id| IndexingOp::DeleteDoc { id }),
5 => (0u64..100u64).prop_map(|id| IndexingOp::DeleteDocQuery { id }),
10 => (0u64..100u64).prop_map(|id| IndexingOp::DeleteDoc { id }),
50 => (0u64..100u64).prop_map(|id| IndexingOp::AddDoc { id }),
2 => (0u64..1u64).prop_map(|_| IndexingOp::Commit),
1 => (0u64..1u64).prop_map(|_| IndexingOp::Merge),
@@ -1548,10 +1370,6 @@ mod tests {
existing_ids.remove(&id);
deleted_ids.insert(id);
}
IndexingOp::DeleteDocQuery { id } => {
existing_ids.remove(&id);
deleted_ids.insert(id);
}
_ => {}
}
}
@@ -1634,11 +1452,6 @@ mod tests {
IndexingOp::DeleteDoc { id } => {
index_writer.delete_term(Term::from_field_u64(id_field, id));
}
IndexingOp::DeleteDocQuery { id } => {
let term = Term::from_field_u64(id_field, id);
let query = TermQuery::new(term, Default::default());
index_writer.delete_query(Box::new(query))?;
}
IndexingOp::Commit => {
index_writer.commit()?;
}
@@ -1717,7 +1530,6 @@ mod tests {
// multivalue fast field tests
for segment_reader in searcher.segment_readers().iter() {
let id_reader = segment_reader.fast_fields().u64(id_field).unwrap();
let ff_reader = segment_reader.fast_fields().u64s(multi_numbers).unwrap();
let bool_ff_reader = segment_reader.fast_fields().bools(multi_bools).unwrap();
for doc in segment_reader.doc_ids_alive() {
@@ -1725,7 +1537,6 @@ mod tests {
ff_reader.get_vals(doc, &mut vals);
assert_eq!(vals.len(), 2);
assert_eq!(vals[0], vals[1]);
assert_eq!(id_reader.get_val(doc as u64), vals[0]);
let mut bool_vals = vec![];
bool_ff_reader.get_vals(doc, &mut bool_vals);

View File

@@ -15,7 +15,7 @@ impl IndexWriterStatus {
}
/// Returns a copy of the operation receiver.
/// If the index writer was killed, returns `None`.
/// If the index writer was killed, returns None.
pub fn operation_receiver(&self) -> Option<AddBatchReceiver> {
let rlock = self
.inner

View File

@@ -1,4 +1,3 @@
use fastfield_codecs::MonotonicallyMappableToU64;
use fnv::FnvHashMap;
use murmurhash32::murmurhash2;

View File

@@ -1,21 +1,19 @@
use std::cmp;
use std::collections::HashMap;
use std::io::Write;
use std::sync::Arc;
use fastfield_codecs::VecColumn;
use itertools::Itertools;
use measure_time::{debug_time, trace_time};
use measure_time::debug_time;
use crate::core::{Segment, SegmentReader};
use crate::docset::{DocSet, TERMINATED};
use crate::error::DataCorruption;
use crate::fastfield::{
AliveBitSet, Column, CompositeFastFieldSerializer, MultiValueLength, MultiValuedFastFieldReader,
AliveBitSet, Column, CompositeFastFieldSerializer, DynamicFastFieldReader, FastFieldStats,
MultiValueLength, MultiValuedFastFieldReader,
};
use crate::fieldnorm::{FieldNormReader, FieldNormReaders, FieldNormsSerializer, FieldNormsWriter};
use crate::indexer::doc_id_mapping::{expect_field_id_for_sort_field, SegmentDocIdMapping};
use crate::indexer::sorted_doc_id_column::SortedDocIdColumn;
use crate::indexer::sorted_doc_id_multivalue_column::SortedDocIdMultiValueColumn;
use crate::indexer::SegmentSerializer;
use crate::postings::{InvertedIndexSerializer, Postings, SegmentPostings};
use crate::schema::{Cardinality, Field, FieldType, Schema};
@@ -88,6 +86,28 @@ pub struct IndexMerger {
max_doc: u32,
}
fn compute_min_max_val(
u64_reader: &impl Column<u64>,
segment_reader: &SegmentReader,
) -> Option<(u64, u64)> {
if segment_reader.max_doc() == 0 {
return None;
}
if segment_reader.alive_bitset().is_none() {
// no deleted documents,
// we can use the previous min_val, max_val.
return Some((u64_reader.min_value(), u64_reader.max_value()));
}
// some deleted documents,
// we need to recompute the max / min
segment_reader
.doc_ids_alive()
.map(|doc_id| u64_reader.get_val(doc_id as u64))
.minmax()
.into_option()
}
struct TermOrdinalMapping {
per_segment_new_term_ordinals: Vec<Vec<TermOrdinal>>,
}
@@ -109,6 +129,14 @@ impl TermOrdinalMapping {
fn get_segment(&self, segment_ord: usize) -> &[TermOrdinal] {
&(self.per_segment_new_term_ordinals[segment_ord])[..]
}
fn max_term_ord(&self) -> TermOrdinal {
self.per_segment_new_term_ordinals
.iter()
.flat_map(|term_ordinals| term_ordinals.iter().max().cloned())
.max()
.unwrap_or_default()
}
}
struct DeltaComputer {
@@ -171,7 +199,6 @@ impl IndexMerger {
readers.push(reader);
}
}
let max_doc = readers.iter().map(|reader| reader.num_docs()).sum();
if let Some(sort_by_field) = index_settings.sort_by_field.as_ref() {
readers = Self::sort_readers_by_min_sort_field(readers, sort_by_field)?;
@@ -250,11 +277,7 @@ impl IndexMerger {
mut term_ord_mappings: HashMap<Field, TermOrdinalMapping>,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
debug_time!(
"merge-all-fast-fields, num_segments {}, num docs new segment {}",
self.readers.len(),
doc_id_mapping.len()
);
debug_time!("write-fast-fields");
for (field, field_entry) in self.schema.fields() {
let field_type = field_entry.field_type();
@@ -314,14 +337,82 @@ impl IndexMerger {
fast_field_serializer: &mut CompositeFastFieldSerializer,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
let fast_field_accessor = SortedDocIdColumn::new(&self.readers, doc_id_mapping, field);
trace_time!(
"merge-single-fast-field, num_vals {}, num_segments {}, field_id {:?}",
fast_field_accessor.num_vals(),
self.readers.len(),
field
);
fast_field_serializer.create_auto_detect_u64_fast_field(field, fast_field_accessor)?;
let (min_value, max_value) = self
.readers
.iter()
.filter_map(|reader| {
let u64_reader: DynamicFastFieldReader<u64> =
reader.fast_fields().typed_fast_field_reader(field).expect(
"Failed to find a reader for single fast field. This is a tantivy bug and \
it should never happen.",
);
compute_min_max_val(&u64_reader, reader)
})
.reduce(|a, b| (a.0.min(b.0), a.1.max(b.1)))
.expect("Unexpected error, empty readers in IndexMerger");
let fast_field_readers = self
.readers
.iter()
.map(|reader| {
let u64_reader: DynamicFastFieldReader<u64> =
reader.fast_fields().typed_fast_field_reader(field).expect(
"Failed to find a reader for single fast field. This is a tantivy bug and \
it should never happen.",
);
u64_reader
})
.collect::<Vec<_>>();
let stats = FastFieldStats {
min_value,
max_value,
num_vals: doc_id_mapping.len() as u64,
};
#[derive(Clone)]
struct SortedDocIdFieldAccessProvider<'a> {
doc_id_mapping: &'a SegmentDocIdMapping,
fast_field_readers: &'a Vec<DynamicFastFieldReader<u64>>,
stats: FastFieldStats,
}
impl<'a> Column for SortedDocIdFieldAccessProvider<'a> {
fn get_val(&self, doc: u64) -> u64 {
let DocAddress {
doc_id,
segment_ord,
} = self.doc_id_mapping.get_old_doc_addr(doc as u32);
self.fast_field_readers[segment_ord as usize].get_val(doc_id as u64)
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(
self.doc_id_mapping
.iter_old_doc_addrs()
.map(|old_doc_addr| {
let fast_field_reader =
&self.fast_field_readers[old_doc_addr.segment_ord as usize];
fast_field_reader.get_val(old_doc_addr.doc_id as u64)
}),
)
}
fn min_value(&self) -> u64 {
self.stats.min_value
}
fn max_value(&self) -> u64 {
self.stats.max_value
}
fn num_vals(&self) -> u64 {
self.stats.num_vals
}
}
let fastfield_accessor = SortedDocIdFieldAccessProvider {
doc_id_mapping,
fast_field_readers: &fast_field_readers,
stats,
};
fast_field_serializer.create_auto_detect_u64_fast_field(field, fastfield_accessor)?;
Ok(())
}
@@ -352,7 +443,7 @@ impl IndexMerger {
pub(crate) fn get_sort_field_accessor(
reader: &SegmentReader,
sort_by_field: &IndexSortByField,
) -> crate::Result<Arc<dyn Column>> {
) -> crate::Result<impl Column> {
let field_id = expect_field_id_for_sort_field(reader.schema(), sort_by_field)?; // for now expect fastfield, but not strictly required
let value_accessor = reader.fast_fields().u64_lenient(field_id)?;
Ok(value_accessor)
@@ -361,7 +452,7 @@ impl IndexMerger {
pub(crate) fn get_reader_with_sort_field_accessor(
&self,
sort_by_field: &IndexSortByField,
) -> crate::Result<Vec<(SegmentOrdinal, Arc<dyn Column>)>> {
) -> crate::Result<Vec<(SegmentOrdinal, impl Column)>> {
let reader_ordinal_and_field_accessors = self
.readers
.iter()
@@ -439,6 +530,31 @@ impl IndexMerger {
doc_id_mapping: &SegmentDocIdMapping,
reader_and_field_accessors: &[(&SegmentReader, T)],
) -> crate::Result<Vec<u64>> {
let mut total_num_vals = 0u64;
// In the first pass, we compute the total number of vals.
//
// This is required by the bitpacker, as it needs to know
// what should be the bit length use for bitpacking.
let mut num_docs = 0;
for (reader, u64s_reader) in reader_and_field_accessors.iter() {
if let Some(alive_bitset) = reader.alive_bitset() {
num_docs += alive_bitset.num_alive_docs() as u64;
for doc in reader.doc_ids_alive() {
let num_vals = u64s_reader.get_len(doc) as u64;
total_num_vals += num_vals;
}
} else {
num_docs += reader.max_doc() as u64;
total_num_vals += u64s_reader.get_total_len();
}
}
let stats = FastFieldStats {
max_value: total_num_vals,
// The fastfield offset index contains (num_docs + 1) values.
num_vals: num_docs + 1,
min_value: 0,
};
// We can now create our `idx` serializer, and in a second pass,
// can effectively push the different indexes.
@@ -456,7 +572,35 @@ impl IndexMerger {
}
offsets.push(offset);
let fastfield_accessor = VecColumn::from(&offsets[..]);
#[derive(Clone)]
struct FieldIndexAccessProvider<'a> {
offsets: &'a [u64],
stats: FastFieldStats,
}
impl<'a> Column for FieldIndexAccessProvider<'a> {
fn get_val(&self, doc: u64) -> u64 {
self.offsets[doc as usize]
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(self.offsets.iter().cloned())
}
fn min_value(&self) -> u64 {
self.stats.min_value
}
fn max_value(&self) -> u64 {
self.stats.max_value
}
fn num_vals(&self) -> u64 {
self.stats.num_vals
}
}
let fastfield_accessor = FieldIndexAccessProvider {
offsets: &offsets,
stats,
};
fast_field_serializer.create_auto_detect_u64_fast_field(field, fastfield_accessor)?;
Ok(offsets)
@@ -468,19 +612,13 @@ impl IndexMerger {
fast_field_serializer: &mut CompositeFastFieldSerializer,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<Vec<u64>> {
trace_time!(
"merge-multi-fast-field-idx, num_segments {}, field_id {:?}",
self.readers.len(),
field
);
let reader_ordinal_and_field_accessors = self
.readers
.iter()
.map(|reader| {
let u64s_reader: MultiValuedFastFieldReader<u64> = reader
.fast_fields()
.typed_fast_field_multi_reader::<u64>(field)
.typed_fast_field_multi_reader(field)
.expect(
"Failed to find index for multivalued field. This is a bug in tantivy, \
please report.",
@@ -504,7 +642,7 @@ impl IndexMerger {
fast_field_serializer: &mut CompositeFastFieldSerializer,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
trace_time!("write-term-id-fast-field");
debug_time!("write-term-id-fast-field");
// Multifastfield consists of 2 fastfields.
// The first serves as an index into the second one and is strictly increasing.
@@ -526,23 +664,25 @@ impl IndexMerger {
.collect::<Vec<_>>();
// We can now write the actual fast field values.
// In the case of hierarchical facets, they are actually term ordinals.
let max_term_ord = term_ordinal_mappings.max_term_ord();
{
let mut vals = Vec::new();
let mut buffer = Vec::new();
let mut serialize_vals =
fast_field_serializer.new_u64_fast_field_with_idx(field, 0u64, max_term_ord, 1)?;
let mut vals = Vec::with_capacity(100);
for old_doc_addr in doc_id_mapping.iter_old_doc_addrs() {
let term_ordinal_mapping: &[TermOrdinal] =
term_ordinal_mappings.get_segment(old_doc_addr.segment_ord as usize);
let ff_reader = &fast_field_reader[old_doc_addr.segment_ord as usize];
ff_reader.get_vals(old_doc_addr.doc_id, &mut buffer);
for &prev_term_ord in &buffer {
ff_reader.get_vals(old_doc_addr.doc_id, &mut vals);
for &prev_term_ord in &vals {
let new_term_ord = term_ordinal_mapping[prev_term_ord as usize];
vals.push(new_term_ord);
serialize_vals.add_val(new_term_ord)?;
}
}
let col = VecColumn::from(&vals[..]);
fast_field_serializer.create_auto_detect_u64_fast_field_with_idx(field, col, 1)?;
serialize_vals.close_field()?;
}
Ok(())
}
@@ -585,15 +725,115 @@ impl IndexMerger {
let offsets =
self.write_multi_value_fast_field_idx(field, fast_field_serializer, doc_id_mapping)?;
let fastfield_accessor =
SortedDocIdMultiValueColumn::new(&self.readers, doc_id_mapping, &offsets, field);
trace_time!(
"merge-multi-fast-field-values, num_vals {}, num_segments {}, field_id {:?}",
fastfield_accessor.num_vals(),
self.readers.len(),
field
);
let mut min_value = u64::MAX;
let mut max_value = u64::MIN;
let mut num_vals = 0;
let mut vals = Vec::with_capacity(100);
let mut ff_readers = Vec::new();
// Our values are bitpacked and we need to know what should be
// our bitwidth and our minimum value before serializing any values.
//
// Computing those is non-trivial if some documents are deleted.
// We go through a complete first pass to compute the minimum and the
// maximum value and initialize our Serializer.
for reader in &self.readers {
let ff_reader: MultiValuedFastFieldReader<u64> = reader
.fast_fields()
.typed_fast_field_multi_reader(field)
.expect(
"Failed to find multivalued fast field reader. This is a bug in tantivy. \
Please report.",
);
for doc in reader.doc_ids_alive() {
ff_reader.get_vals(doc, &mut vals);
for &val in &vals {
min_value = cmp::min(val, min_value);
max_value = cmp::max(val, max_value);
}
num_vals += vals.len();
}
ff_readers.push(ff_reader);
// TODO optimize when no deletes
}
if min_value > max_value {
min_value = 0;
max_value = 0;
}
// We can now initialize our serializer, and push it the different values
let stats = FastFieldStats {
max_value,
num_vals: num_vals as u64,
min_value,
};
struct SortedDocIdMultiValueAccessProvider<'a> {
doc_id_mapping: &'a SegmentDocIdMapping,
fast_field_readers: &'a Vec<MultiValuedFastFieldReader<u64>>,
offsets: Vec<u64>,
stats: FastFieldStats,
}
impl<'a> Column for SortedDocIdMultiValueAccessProvider<'a> {
fn get_val(&self, pos: u64) -> u64 {
// use the offsets index to find the doc_id which will contain the position.
// the offsets are strictly increasing so we can do a simple search on it.
let new_doc_id: DocId =
self.offsets
.iter()
.position(|&offset| offset > pos)
.expect("pos is out of bounds") as DocId
- 1u32;
// now we need to find the position of `pos` in the multivalued bucket
let num_pos_covered_until_now = self.offsets[new_doc_id as usize];
let pos_in_values = pos - num_pos_covered_until_now;
let old_doc_addr = self.doc_id_mapping.get_old_doc_addr(new_doc_id);
let num_vals = self.fast_field_readers[old_doc_addr.segment_ord as usize]
.get_len(old_doc_addr.doc_id);
assert!(num_vals >= pos_in_values);
let mut vals = Vec::new();
self.fast_field_readers[old_doc_addr.segment_ord as usize]
.get_vals(old_doc_addr.doc_id, &mut vals);
vals[pos_in_values as usize]
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(
self.doc_id_mapping
.iter_old_doc_addrs()
.flat_map(|old_doc_addr| {
let ff_reader =
&self.fast_field_readers[old_doc_addr.segment_ord as usize];
let mut vals = Vec::new();
ff_reader.get_vals(old_doc_addr.doc_id, &mut vals);
vals.into_iter()
}),
)
}
fn min_value(&self) -> u64 {
self.stats.min_value
}
fn max_value(&self) -> u64 {
self.stats.max_value
}
fn num_vals(&self) -> u64 {
self.stats.num_vals
}
}
let fastfield_accessor = SortedDocIdMultiValueAccessProvider {
doc_id_mapping,
fast_field_readers: &ff_readers,
offsets,
stats,
};
fast_field_serializer.create_auto_detect_u64_fast_field_with_idx(
field,
fastfield_accessor,
@@ -627,7 +867,7 @@ impl IndexMerger {
doc_id_mapping,
&reader_and_field_accessors,
)?;
let mut serialize_vals = fast_field_serializer.new_bytes_fast_field(field);
let mut serialize_vals = fast_field_serializer.new_bytes_fast_field_with_idx(field, 1);
for old_doc_addr in doc_id_mapping.iter_old_doc_addrs() {
let bytes_reader = &reader_and_field_accessors[old_doc_addr.segment_ord as usize].1;
@@ -647,7 +887,7 @@ impl IndexMerger {
fieldnorm_reader: Option<FieldNormReader>,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<Option<TermOrdinalMapping>> {
debug_time!("write-postings-for-field {:?}", indexed_field);
debug_time!("write-postings-for-field");
let mut positions_buffer: Vec<u32> = Vec::with_capacity(1_000);
let mut delta_computer = DeltaComputer::new();
@@ -850,7 +1090,7 @@ impl IndexMerger {
debug!("write-storable-field");
if !doc_id_mapping.is_trivial() {
debug!("non-trivial-doc-id-mapping (index is sorted)");
debug!("non-trivial-doc-id-mapping");
let store_readers: Vec<_> = self
.readers
@@ -878,7 +1118,7 @@ impl IndexMerger {
}
}
} else {
debug!("trivial-doc-id-mapping (index is not sorted)");
debug!("trivial-doc-id-mapping");
for reader in &self.readers {
let store_reader = reader.get_store_reader(1)?;
if reader.has_deletes()
@@ -959,6 +1199,7 @@ impl IndexMerger {
#[cfg(test)]
mod tests {
use byteorder::{BigEndian, ReadBytesExt};
use fastfield_codecs::Column;
use schema::FAST;
use crate::collector::tests::{

View File

@@ -1,5 +1,7 @@
#[cfg(test)]
mod tests {
use fastfield_codecs::Column;
use crate::collector::TopDocs;
use crate::core::Index;
use crate::fastfield::{AliveBitSet, MultiValuedFastFieldReader};
@@ -478,12 +480,11 @@ mod tests {
#[cfg(all(test, feature = "unstable"))]
mod bench_sorted_index_merge {
use std::sync::Arc;
use fastfield_codecs::Column;
use test::{self, Bencher};
use crate::core::Index;
use crate::fastfield::DynamicFastFieldReader;
use crate::indexer::merger::IndexMerger;
use crate::schema::{Cardinality, NumericOptions, Schema};
use crate::{IndexSettings, IndexSortByField, IndexWriter, Order};
@@ -535,7 +536,7 @@ mod bench_sorted_index_merge {
b.iter(|| {
let sorted_doc_ids = doc_id_mapping.iter_old_doc_addrs().map(|doc_addr| {
let reader = &merger.readers[doc_addr.segment_ord as usize];
let u64_reader: Arc<dyn Column<u64>> =
let u64_reader: DynamicFastFieldReader<u64> =
reader.fast_fields().typed_fast_field_reader(field).expect(
"Failed to find a reader for single fast field. This is a tantivy bug and \
it should never happen.",

View File

@@ -19,8 +19,6 @@ mod segment_register;
pub mod segment_serializer;
pub mod segment_updater;
mod segment_writer;
mod sorted_doc_id_column;
mod sorted_doc_id_multivalue_column;
mod stamper;
use crossbeam_channel as channel;

View File

@@ -1,11 +1,20 @@
use crate::query::Weight;
use crate::schema::{Document, Term};
use crate::Opstamp;
/// Timestamped Delete operation.
#[derive(Clone, Eq, PartialEq, Debug)]
pub struct DeleteOperation {
pub opstamp: Opstamp,
pub target: Box<dyn Weight>,
pub term: Term,
}
impl Default for DeleteOperation {
fn default() -> Self {
DeleteOperation {
opstamp: 0u64,
term: Term::new(),
}
}
}
/// Timestamped Add operation.

View File

@@ -173,7 +173,6 @@ impl SegmentManager {
.to_string();
return Err(TantivyError::InvalidArgument(error_msg));
}
Ok(segment_entries)
}
@@ -187,7 +186,7 @@ impl SegmentManager {
pub(crate) fn end_merge(
&self,
before_merge_segment_ids: &[SegmentId],
after_merge_segment_entry: Option<SegmentEntry>,
after_merge_segment_entry: SegmentEntry,
) -> crate::Result<SegmentsStatus> {
let mut registers_lock = self.write();
let segments_status = registers_lock
@@ -208,9 +207,7 @@ impl SegmentManager {
for segment_id in before_merge_segment_ids {
target_register.remove_segment(segment_id);
}
if let Some(entry) = after_merge_segment_entry {
target_register.add_segment_entry(entry);
}
target_register.add_segment_entry(after_merge_segment_entry);
Ok(segments_status)
}

View File

@@ -38,16 +38,11 @@ impl SegmentSerializer {
let fieldnorms_serializer = FieldNormsSerializer::from_write(fieldnorms_write)?;
let postings_serializer = InvertedIndexSerializer::open(&mut segment)?;
let settings = segment.index().settings();
let store_writer = StoreWriter::new(
store_write,
settings.docstore_compression,
settings.docstore_blocksize,
settings.docstore_compress_dedicated_thread,
)?;
let compressor = segment.index().settings().docstore_compression;
let blocksize = segment.index().settings().docstore_blocksize;
Ok(SegmentSerializer {
segment,
store_writer,
store_writer: StoreWriter::new(store_write, compressor, blocksize)?,
fast_field_serializer,
fieldnorms_serializer: Some(fieldnorms_serializer),
postings_serializer,

View File

@@ -91,15 +91,7 @@ fn merge(
index: &Index,
mut segment_entries: Vec<SegmentEntry>,
target_opstamp: Opstamp,
) -> crate::Result<Option<SegmentEntry>> {
let num_docs = segment_entries
.iter()
.map(|segment| segment.meta().num_docs() as u64)
.sum::<u64>();
if num_docs == 0 {
return Ok(None);
}
) -> crate::Result<SegmentEntry> {
// first we need to apply deletes to our segment.
let merged_segment = index.new_segment();
@@ -128,7 +120,7 @@ fn merge(
let merged_segment_id = merged_segment.id();
let segment_meta = index.new_segment_meta(merged_segment_id, num_docs);
Ok(Some(SegmentEntry::new(segment_meta, delete_cursor, None)))
Ok(SegmentEntry::new(segment_meta, delete_cursor, None))
}
/// Advanced: Merges a list of segments from different indices in a new index.
@@ -483,10 +475,7 @@ impl SegmentUpdater {
// suggested and the moment when it ended up being executed.)
//
// `segment_ids` is required to be non-empty.
pub fn start_merge(
&self,
merge_operation: MergeOperation,
) -> FutureResult<Option<SegmentMeta>> {
pub fn start_merge(&self, merge_operation: MergeOperation) -> FutureResult<SegmentMeta> {
assert!(
!merge_operation.segment_ids().is_empty(),
"Segment_ids cannot be empty."
@@ -523,8 +512,9 @@ impl SegmentUpdater {
merge_operation.target_opstamp(),
) {
Ok(after_merge_segment_entry) => {
let res = segment_updater.end_merge(merge_operation, after_merge_segment_entry);
let _send_result = merging_future_send.send(res);
let segment_meta_res =
segment_updater.end_merge(merge_operation, after_merge_segment_entry);
let _send_result = merging_future_send.send(segment_meta_res);
}
Err(merge_error) => {
warn!(
@@ -532,10 +522,8 @@ impl SegmentUpdater {
merge_operation.segment_ids().to_vec(),
merge_error
);
if cfg!(test) {
panic!("{:?}", merge_error);
}
let _send_result = merging_future_send.send(Err(merge_error));
assert!(!cfg!(test), "Merge failed.");
}
}
});
@@ -585,42 +573,35 @@ impl SegmentUpdater {
fn end_merge(
&self,
merge_operation: MergeOperation,
mut after_merge_segment_entry: Option<SegmentEntry>,
) -> crate::Result<Option<SegmentMeta>> {
mut after_merge_segment_entry: SegmentEntry,
) -> crate::Result<SegmentMeta> {
let segment_updater = self.clone();
let after_merge_segment_meta = after_merge_segment_entry
.as_ref()
.map(|after_merge_segment_entry| after_merge_segment_entry.meta().clone());
let after_merge_segment_meta = after_merge_segment_entry.meta().clone();
self.schedule_task(move || {
info!(
"End merge {:?}",
after_merge_segment_entry.as_ref().map(|entry| entry.meta())
);
info!("End merge {:?}", after_merge_segment_entry.meta());
{
if let Some(after_merge_segment_entry) = after_merge_segment_entry.as_mut() {
let mut delete_cursor = after_merge_segment_entry.delete_cursor().clone();
if let Some(delete_operation) = delete_cursor.get() {
let committed_opstamp = segment_updater.load_meta().opstamp;
if delete_operation.opstamp < committed_opstamp {
let index = &segment_updater.index;
let segment = index.segment(after_merge_segment_entry.meta().clone());
if let Err(advance_deletes_err) = advance_deletes(
segment,
after_merge_segment_entry,
committed_opstamp,
) {
error!(
"Merge of {:?} was cancelled (advancing deletes failed): {:?}",
merge_operation.segment_ids(),
advance_deletes_err
);
assert!(!cfg!(test), "Merge failed.");
let mut delete_cursor = after_merge_segment_entry.delete_cursor().clone();
if let Some(delete_operation) = delete_cursor.get() {
let committed_opstamp = segment_updater.load_meta().opstamp;
if delete_operation.opstamp < committed_opstamp {
let index = &segment_updater.index;
let segment = index.segment(after_merge_segment_entry.meta().clone());
if let Err(advance_deletes_err) = advance_deletes(
segment,
&mut after_merge_segment_entry,
committed_opstamp,
) {
error!(
"Merge of {:?} was cancelled (advancing deletes failed): {:?}",
merge_operation.segment_ids(),
advance_deletes_err
);
assert!(!cfg!(test), "Merge failed.");
// ... cancel merge
// `merge_operations` are tracked. As it is dropped, the
// the segment_ids will be available again for merge.
return Err(advance_deletes_err);
}
// ... cancel merge
// `merge_operations` are tracked. As it is dropped, the
// the segment_ids will be available again for merge.
return Err(advance_deletes_err);
}
}
}

View File

@@ -1,9 +1,7 @@
use fastfield_codecs::MonotonicallyMappableToU64;
use super::doc_id_mapping::{get_doc_id_mapping_from_field, DocIdMapping};
use super::operation::AddOperation;
use crate::core::Segment;
use crate::fastfield::FastFieldsWriter;
use crate::fastfield::{FastFieldsWriter, FastValue as _};
use crate::fieldnorm::{FieldNormReaders, FieldNormsWriter};
use crate::indexer::json_term_writer::index_json_values;
use crate::indexer::segment_serializer::SegmentSerializer;
@@ -138,7 +136,7 @@ impl SegmentWriter {
remap_and_write(
&self.per_field_postings_writers,
self.ctx,
self.fast_field_writers,
&self.fast_field_writers,
&self.fieldnorms_writer,
&self.schema,
self.segment_serializer,
@@ -345,7 +343,7 @@ impl SegmentWriter {
fn remap_and_write(
per_field_postings_writers: &PerFieldPostingsWriter,
ctx: IndexingContext,
fast_field_writers: FastFieldsWriter,
fast_field_writers: &FastFieldsWriter,
fieldnorms_writer: &FieldNormsWriter,
schema: &Schema,
mut serializer: SegmentSerializer,
@@ -380,14 +378,12 @@ fn remap_and_write(
let store_write = serializer
.segment_mut()
.open_write(SegmentComponent::Store)?;
let settings = serializer.segment().index().settings();
let store_writer = StoreWriter::new(
store_write,
settings.docstore_compression,
settings.docstore_blocksize,
settings.docstore_compress_dedicated_thread,
)?;
let old_store_writer = std::mem::replace(&mut serializer.store_writer, store_writer);
let compressor = serializer.segment().index().settings().docstore_compression;
let block_size = serializer.segment().index().settings().docstore_blocksize;
let old_store_writer = std::mem::replace(
&mut serializer.store_writer,
StoreWriter::new(store_write, compressor, block_size)?,
);
old_store_writer.close()?;
let store_read = StoreReader::open(
serializer

View File

@@ -1,112 +0,0 @@
use std::sync::Arc;
use fastfield_codecs::Column;
use itertools::Itertools;
use crate::indexer::doc_id_mapping::SegmentDocIdMapping;
use crate::schema::Field;
use crate::{DocAddress, SegmentReader};
pub(crate) struct SortedDocIdColumn<'a> {
doc_id_mapping: &'a SegmentDocIdMapping,
fast_field_readers: Vec<Arc<dyn Column<u64>>>,
min_value: u64,
max_value: u64,
num_vals: u64,
}
fn compute_min_max_val(
u64_reader: &dyn Column<u64>,
segment_reader: &SegmentReader,
) -> Option<(u64, u64)> {
if segment_reader.max_doc() == 0 {
return None;
}
if segment_reader.alive_bitset().is_none() {
// no deleted documents,
// we can use the previous min_val, max_val.
return Some((u64_reader.min_value(), u64_reader.max_value()));
}
// some deleted documents,
// we need to recompute the max / min
segment_reader
.doc_ids_alive()
.map(|doc_id| u64_reader.get_val(doc_id as u64))
.minmax()
.into_option()
}
impl<'a> SortedDocIdColumn<'a> {
pub(crate) fn new(
readers: &'a [SegmentReader],
doc_id_mapping: &'a SegmentDocIdMapping,
field: Field,
) -> Self {
let (min_value, max_value) = readers
.iter()
.filter_map(|reader| {
let u64_reader: Arc<dyn Column<u64>> =
reader.fast_fields().typed_fast_field_reader(field).expect(
"Failed to find a reader for single fast field. This is a tantivy bug and \
it should never happen.",
);
compute_min_max_val(&*u64_reader, reader)
})
.reduce(|a, b| (a.0.min(b.0), a.1.max(b.1)))
.expect("Unexpected error, empty readers in IndexMerger");
let fast_field_readers = readers
.iter()
.map(|reader| {
let u64_reader: Arc<dyn Column<u64>> =
reader.fast_fields().typed_fast_field_reader(field).expect(
"Failed to find a reader for single fast field. This is a tantivy bug and \
it should never happen.",
);
u64_reader
})
.collect::<Vec<_>>();
SortedDocIdColumn {
doc_id_mapping,
fast_field_readers,
min_value,
max_value,
num_vals: doc_id_mapping.len() as u64,
}
}
}
impl<'a> Column for SortedDocIdColumn<'a> {
fn get_val(&self, doc: u64) -> u64 {
let DocAddress {
doc_id,
segment_ord,
} = self.doc_id_mapping.get_old_doc_addr(doc as u32);
self.fast_field_readers[segment_ord as usize].get_val(doc_id as u64)
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(
self.doc_id_mapping
.iter_old_doc_addrs()
.map(|old_doc_addr| {
let fast_field_reader =
&self.fast_field_readers[old_doc_addr.segment_ord as usize];
fast_field_reader.get_val(old_doc_addr.doc_id as u64)
}),
)
}
fn min_value(&self) -> u64 {
self.min_value
}
fn max_value(&self) -> u64 {
self.max_value
}
fn num_vals(&self) -> u64 {
self.num_vals
}
}

View File

@@ -1,121 +0,0 @@
use std::cmp;
use fastfield_codecs::Column;
use crate::fastfield::{MultiValueLength, MultiValuedFastFieldReader};
use crate::indexer::doc_id_mapping::SegmentDocIdMapping;
use crate::schema::Field;
use crate::{DocId, SegmentReader};
// We can now initialize our serializer, and push it the different values
pub(crate) struct SortedDocIdMultiValueColumn<'a> {
doc_id_mapping: &'a SegmentDocIdMapping,
fast_field_readers: Vec<MultiValuedFastFieldReader<u64>>,
offsets: &'a [u64],
min_value: u64,
max_value: u64,
num_vals: u64,
}
impl<'a> SortedDocIdMultiValueColumn<'a> {
pub(crate) fn new(
readers: &'a [SegmentReader],
doc_id_mapping: &'a SegmentDocIdMapping,
offsets: &'a [u64],
field: Field,
) -> Self {
// Our values are bitpacked and we need to know what should be
// our bitwidth and our minimum value before serializing any values.
//
// Computing those is non-trivial if some documents are deleted.
// We go through a complete first pass to compute the minimum and the
// maximum value and initialize our Serializer.
let mut num_vals = 0;
let mut min_value = u64::MAX;
let mut max_value = u64::MIN;
let mut vals = Vec::new();
let mut fast_field_readers = Vec::with_capacity(readers.len());
for reader in readers {
let ff_reader: MultiValuedFastFieldReader<u64> = reader
.fast_fields()
.typed_fast_field_multi_reader::<u64>(field)
.expect(
"Failed to find multivalued fast field reader. This is a bug in tantivy. \
Please report.",
);
for doc in reader.doc_ids_alive() {
ff_reader.get_vals(doc, &mut vals);
for &val in &vals {
min_value = cmp::min(val, min_value);
max_value = cmp::max(val, max_value);
}
num_vals += vals.len();
}
fast_field_readers.push(ff_reader);
// TODO optimize when no deletes
}
if min_value > max_value {
min_value = 0;
max_value = 0;
}
SortedDocIdMultiValueColumn {
doc_id_mapping,
fast_field_readers,
offsets,
min_value,
max_value,
num_vals: num_vals as u64,
}
}
}
impl<'a> Column for SortedDocIdMultiValueColumn<'a> {
fn get_val(&self, pos: u64) -> u64 {
// use the offsets index to find the doc_id which will contain the position.
// the offsets are strictly increasing so we can do a simple search on it.
let new_doc_id: DocId = self
.offsets
.iter()
.position(|&offset| offset > pos)
.expect("pos is out of bounds") as DocId
- 1u32;
// now we need to find the position of `pos` in the multivalued bucket
let num_pos_covered_until_now = self.offsets[new_doc_id as usize];
let pos_in_values = pos - num_pos_covered_until_now;
let old_doc_addr = self.doc_id_mapping.get_old_doc_addr(new_doc_id);
let num_vals =
self.fast_field_readers[old_doc_addr.segment_ord as usize].get_len(old_doc_addr.doc_id);
assert!(num_vals >= pos_in_values);
let mut vals = Vec::new();
self.fast_field_readers[old_doc_addr.segment_ord as usize]
.get_vals(old_doc_addr.doc_id, &mut vals);
vals[pos_in_values as usize]
}
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(
self.doc_id_mapping
.iter_old_doc_addrs()
.flat_map(|old_doc_addr| {
let ff_reader = &self.fast_field_readers[old_doc_addr.segment_ord as usize];
let mut vals = Vec::new();
ff_reader.get_vals(old_doc_addr.doc_id, &mut vals);
vals.into_iter()
}),
)
}
fn min_value(&self) -> u64 {
self.min_value
}
fn max_value(&self) -> u64 {
self.max_value
}
fn num_vals(&self) -> u64 {
self.num_vals
}
}

View File

@@ -421,6 +421,7 @@ pub struct DocAddress {
#[cfg(test)]
pub mod tests {
use common::{BinarySerializable, FixedSize};
use fastfield_codecs::Column;
use rand::distributions::{Bernoulli, Uniform};
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};

View File

@@ -1,18 +1,18 @@
//! Tantivy can (if instructed to do so in the schema) store the term positions in a given field.
//! This position is expressed as token ordinal. For instance,
//! In "The beauty and the beast", the term "the" appears in position 0 and position 3.
//! In "The beauty and the beast", the term "the" appears in position 0 and position 4.
//! This information is useful to run phrase queries.
//!
//! The [position](crate::SegmentComponent::Positions) file contains all of the
//! The [position](../enum.SegmentComponent.html#variant.Positions) file contains all of the
//! bitpacked positions delta, for all terms of a given field, one term after the other.
//!
//! Each term is encoded independently.
//! Like for posting lists, tantivy relies on simd bitpacking to encode the positions delta in
//! blocks of 128 deltas. Because we rarely have a multiple of 128, the final block encodes
//! the remaining values with variable int encoding.
//! Like for positing lists, tantivy relies on simd bitpacking to encode the positions delta in
//! blocks of 128 deltas. Because we rarely have a multiple of 128, a final block may encode the
//! remaining values variable byte encoding.
//!
//! In order to make reading possible, the term delta positions first encode the number of
//! bitpacked blocks, then the bitwidth for each block, then the actual bitpacked blocks and finally
//! In order to make reading possible, the term delta positions first encodes the number of
//! bitpacked blocks, then the bitwidth for each blocks, then the actual bitpacked block and finally
//! the final variable int encoded block.
//!
//! Contrary to postings list, the reader does not have access on the number of positions that is

View File

@@ -12,7 +12,7 @@ use crate::postings::compression::COMPRESSION_BLOCK_SIZE;
/// ```
///
/// the `start` argument is just used to hint that the response is
/// greater than beyond `start`. The implementation may or may not use
/// greater than beyond `start`. the implementation may or may not use
/// it for optimization.
///
/// # Assumption

View File

@@ -222,7 +222,7 @@ pub mod tests {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let index = Index::create_in_ram(schema.clone());
let segment = index.new_segment();
{

View File

@@ -12,7 +12,7 @@ use crate::{DocId, DocSet, Score, TERMINATED};
///
/// We always have `before_pivot_len` < `pivot_len`.
///
/// `None` is returned if we establish that no document can exceed the threshold.
/// None is returned if we establish that no document can exceed the threshold.
fn find_pivot_doc(
term_scorers: &[TermScorerWithMaxScore],
threshold: Score,

View File

@@ -72,7 +72,7 @@ impl PhraseQuery {
self.slop = value;
}
/// The [`Field`] this `PhraseQuery` is targeting.
/// The `Field` this `PhraseQuery` is targeting.
pub fn field(&self) -> Field {
self.field
}
@@ -85,10 +85,10 @@ impl PhraseQuery {
.collect::<Vec<Term>>()
}
/// Returns the [`PhraseWeight`] for the given phrase query given a specific `searcher`.
/// Returns the `PhraseWeight` for the given phrase query given a specific `searcher`.
///
/// This function is the same as [`Query::weight()`] except it returns
/// a specialized type [`PhraseWeight`] instead of a Boxed trait.
/// This function is the same as `.weight(...)` except it returns
/// a specialized type `PhraseWeight` instead of a Boxed trait.
pub(crate) fn phrase_weight(
&self,
searcher: &Searcher,
@@ -121,7 +121,7 @@ impl PhraseQuery {
impl Query for PhraseQuery {
/// Create the weight associated to a query.
///
/// See [`Weight`].
/// See [`Weight`](./trait.Weight.html).
fn weight(&self, searcher: &Searcher, scoring_enabled: bool) -> crate::Result<Box<dyn Weight>> {
let phrase_weight = self.phrase_weight(searcher, scoring_enabled)?;
Ok(Box::new(phrase_weight))

View File

@@ -15,39 +15,38 @@ use crate::{DocAddress, Term};
/// - a set of documents
/// - a way to score these documents
///
/// When performing a [search](Searcher::search), these documents will then
/// be pushed to a [`Collector`](crate::collector::Collector),
/// When performing a [search](Searcher::search), these documents will then
/// be pushed to a [Collector](../collector/trait.Collector.html),
/// which will in turn be in charge of deciding what to do with them.
///
/// Concretely, this scored docset is represented by the
/// [`Scorer`] trait.
/// [`Scorer`](./trait.Scorer.html) trait.
///
/// Because our index is actually split into segments, the
/// query does not actually directly creates [`DocSet`](crate::DocSet) object.
/// Instead, the query creates a [`Weight`] object for a given searcher.
/// query does not actually directly creates `DocSet` object.
/// Instead, the query creates a [`Weight`](./trait.Weight.html)
/// object for a given searcher.
///
/// The weight object, in turn, makes it possible to create
/// a scorer for a specific [`SegmentReader`].
/// a scorer for a specific [`SegmentReader`](../struct.SegmentReader.html).
///
/// So to sum it up :
/// - a `Query` is a recipe to define a set of documents as well the way to score them.
/// - a [`Weight`] is this recipe tied to a specific [`Searcher`]. It may for instance
/// - a `Query` is recipe to define a set of documents as well the way to score them.
/// - a `Weight` is this recipe tied to a specific `Searcher`. It may for instance
/// hold statistics about the different term of the query. It is created by the query.
/// - a [`Scorer`] is a cursor over the set of matching documents, for a specific
/// [`SegmentReader`]. It is created by the [`Weight`].
/// - a `Scorer` is a cursor over the set of matching documents, for a specific
/// [`SegmentReader`](../struct.SegmentReader.html). It is created by the
/// [`Weight`](./trait.Weight.html).
///
/// When implementing a new type of `Query`, it is normal to implement a
/// dedicated `Query`, [`Weight`] and [`Scorer`].
///
/// [`Scorer`]: crate::query::Scorer
/// [`SegmentReader`]: crate::SegmentReader
/// dedicated `Query`, `Weight` and `Scorer`.
pub trait Query: QueryClone + Send + Sync + downcast_rs::Downcast + fmt::Debug {
/// Create the weight associated to a query.
///
/// If scoring is not required, setting `scoring_enabled` to `false`
/// can increase performances.
///
/// See [`Weight`].
/// See [`Weight`](./trait.Weight.html).
fn weight(&self, searcher: &Searcher, scoring_enabled: bool) -> crate::Result<Box<dyn Weight>>;
/// Returns an `Explanation` for the score of the document.

View File

@@ -113,8 +113,8 @@ fn trim_ast(logical_ast: LogicalAst) -> Option<LogicalAst> {
/// The language covered by the current parser is extremely simple.
///
/// * simple terms: "e.g.: `Barack Obama` are simply tokenized using tantivy's
/// [`SimpleTokenizer`](crate::tokenizer::SimpleTokenizer), hence becoming `["barack", "obama"]`.
/// The terms are then searched within the default terms of the query parser.
/// [`SimpleTokenizer`](../tokenizer/struct.SimpleTokenizer.html), hence becoming `["barack",
/// "obama"]`. The terms are then searched within the default terms of the query parser.
///
/// e.g. If `body` and `title` are default fields, our example terms are
/// `["title:barack", "body:barack", "title:obama", "body:obama"]`.
@@ -166,8 +166,8 @@ fn trim_ast(logical_ast: LogicalAst) -> Option<LogicalAst> {
/// devops. Negative boosts are not allowed.
///
/// It is also possible to define a boost for a some specific field, at the query parser level.
/// (See [`set_field_boost(...)`](QueryParser::set_field_boost)). Typically you may want to boost a
/// title field.
/// (See [`set_boost(...)`](#method.set_field_boost) ). Typically you may want to boost a title
/// field.
///
/// Phrase terms support the `~` slop operator which allows to set the phrase's matching
/// distance in words. `"big wolf"~1` will return documents containing the phrase `"big bad wolf"`.

View File

@@ -7,7 +7,7 @@ use crate::Score;
/// Scored set of documents matching a query within a specific segment.
///
/// See [`Query`](crate::query::Query).
/// See [`Query`](./trait.Query.html).
pub trait Scorer: downcast_rs::Downcast + DocSet + 'static {
/// Returns the score.
///

View File

@@ -19,7 +19,7 @@ pub(crate) fn for_each_scorer<TScorer: Scorer + ?Sized>(
/// Calls `callback` with all of the `(doc, score)` for which score
/// is exceeding a given threshold.
///
/// This method is useful for the [`TopDocs`](crate::collector::TopDocs) collector.
/// This method is useful for the TopDocs collector.
/// For all docsets, the blanket implementation has the benefit
/// of prefiltering (doc, score) pairs, avoiding the
/// virtual dispatch cost.
@@ -41,22 +41,22 @@ pub(crate) fn for_each_pruning_scorer<TScorer: Scorer + ?Sized>(
}
}
/// A Weight is the specialization of a `Query`
/// A Weight is the specialization of a Query
/// for a given set of segments.
///
/// See [`Query`](crate::query::Query).
/// See [`Query`](./trait.Query.html).
pub trait Weight: Send + Sync + 'static {
/// Returns the scorer for the given segment.
///
/// `boost` is a multiplier to apply to the score.
///
/// See [`Query`](crate::query::Query).
/// See [`Query`](./trait.Query.html).
fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>>;
/// Returns an [`Explanation`] for the given document.
/// Returns an `Explanation` for the given document.
fn explain(&self, reader: &SegmentReader, doc: DocId) -> crate::Result<Explanation>;
/// Returns the number documents within the given [`SegmentReader`].
/// Returns the number documents within the given `SegmentReader`.
fn count(&self, reader: &SegmentReader) -> crate::Result<u32> {
let mut scorer = self.scorer(reader, 1.0)?;
if let Some(alive_bitset) = reader.alive_bitset() {
@@ -81,7 +81,7 @@ pub trait Weight: Send + Sync + 'static {
/// Calls `callback` with all of the `(doc, score)` for which score
/// is exceeding a given threshold.
///
/// This method is useful for the [`TopDocs`](crate::collector::TopDocs) collector.
/// This method is useful for the TopDocs collector.
/// For all docsets, the blanket implementation has the benefit
/// of prefiltering (doc, score) pairs, avoiding the
/// virtual dispatch cost.

View File

@@ -23,7 +23,7 @@ pub enum ReloadPolicy {
/// The index is entirely reloaded manually.
/// All updates of the index should be manual.
///
/// No change is reflected automatically. You are required to call [`IndexReader::reload()`]
/// No change is reflected automatically. You are required to call `IndexReader::reload()`
/// manually.
Manual,
/// The index is reloaded within milliseconds after a new commit is available.
@@ -31,11 +31,11 @@ pub enum ReloadPolicy {
OnCommit, // TODO add NEAR_REAL_TIME(target_ms)
}
/// [`IndexReader`] builder
/// [IndexReader] builder
///
/// It makes it possible to configure:
/// - [`ReloadPolicy`] defining when new index versions are detected
/// - [`Warmer`] implementations
/// - [ReloadPolicy] defining when new index versions are detected
/// - [Warmer] implementations
/// - number of warming threads, for parallelizing warming work
/// - The cache size of the underlying doc store readers.
#[derive(Clone)]
@@ -108,7 +108,7 @@ impl IndexReaderBuilder {
/// Sets the reload_policy.
///
/// See [`ReloadPolicy`] for more details.
/// See [`ReloadPolicy`](./enum.ReloadPolicy.html) for more details.
#[must_use]
pub fn reload_policy(mut self, reload_policy: ReloadPolicy) -> IndexReaderBuilder {
self.reload_policy = reload_policy;
@@ -124,7 +124,7 @@ impl IndexReaderBuilder {
self
}
/// Set the [`Warmer`]s that are invoked when reloading searchable segments.
/// Set the [Warmer]s that are invoked when reloading searchable segments.
#[must_use]
pub fn warmers(mut self, warmers: Vec<Weak<dyn Warmer>>) -> IndexReaderBuilder {
self.warmers = warmers;
@@ -133,8 +133,8 @@ impl IndexReaderBuilder {
/// Sets the number of warming threads.
///
/// This allows parallelizing warming work when there are multiple [`Warmer`] registered with
/// the [`IndexReader`].
/// This allows parallelizing warming work when there are multiple [Warmer] registered with the
/// [IndexReader].
#[must_use]
pub fn num_warming_threads(mut self, num_warming_threads: usize) -> IndexReaderBuilder {
self.num_warming_threads = num_warming_threads;
@@ -186,7 +186,7 @@ impl InnerIndexReader {
searcher_generation_inventory,
})
}
/// Opens the freshest segments [`SegmentReader`].
/// Opens the freshest segments `SegmentReader`.
///
/// This function acquires a lot to prevent GC from removing files
/// as we are opening our index.
@@ -264,7 +264,7 @@ impl InnerIndexReader {
/// you instances of `Searcher` for the last loaded version.
///
/// `Clone` does not clone the different pool of searcher. `IndexReader`
/// just wraps an `Arc`.
/// just wraps and `Arc`.
#[derive(Clone)]
pub struct IndexReader {
inner: Arc<InnerIndexReader>,
@@ -280,7 +280,7 @@ impl IndexReader {
/// Update searchers so that they reflect the state of the last
/// `.commit()`.
///
/// If you set up the [`ReloadPolicy::OnCommit`] (which is the default)
/// If you set up the `OnCommit` `ReloadPolicy` (which is the default)
/// every commit should be rapidly reflected on your `IndexReader` and you should
/// not need to call `reload()` at all.
///

View File

@@ -10,12 +10,12 @@ pub const GC_INTERVAL: Duration = Duration::from_secs(1);
/// `Warmer` can be used to maintain segment-level state e.g. caches.
///
/// They must be registered with the [`IndexReaderBuilder`](super::IndexReaderBuilder).
/// They must be registered with the [super::IndexReaderBuilder].
pub trait Warmer: Sync + Send {
/// Perform any warming work using the provided [`Searcher`].
/// Perform any warming work using the provided [Searcher].
fn warm(&self, searcher: &Searcher) -> crate::Result<()>;
/// Discards internal state for any [`SearcherGeneration`] not provided.
/// Discards internal state for any [SearcherGeneration] not provided.
fn garbage_collect(&self, live_generations: &[&SearcherGeneration]);
}
@@ -38,11 +38,11 @@ impl WarmingState {
}))))
}
/// Start tracking a new generation of [`Searcher`], and [`Warmer::warm`] it if there are active
/// Start tracking a new generation of [Searcher], and [Warmer::warm] it if there are active
/// warmers.
///
/// A background GC thread for [`Warmer::garbage_collect`] calls is uniquely created if there
/// are active warmers.
/// A background GC thread for [Warmer::garbage_collect] calls is uniquely created if there are
/// active warmers.
pub fn warm_new_searcher_generation(&self, searcher: &Searcher) -> crate::Result<()> {
self.0
.lock()
@@ -90,7 +90,7 @@ impl WarmingStateInner {
Ok(())
}
/// Attempt to upgrade the weak `Warmer` references, pruning those which cannot be upgraded.
/// Attempt to upgrade the weak Warmer references, pruning those which cannot be upgraded.
/// Return the strong references.
fn pruned_warmers(&mut self) -> Vec<Arc<dyn Warmer>> {
let strong_warmers = self
@@ -102,7 +102,7 @@ impl WarmingStateInner {
strong_warmers
}
/// [`Warmer::garbage_collect`] active warmers if some searcher generation is observed to have
/// [Warmer::garbage_collect] active warmers if some searcher generation is observed to have
/// been dropped.
fn gc_maybe(&mut self) -> bool {
let live_generations = self.searcher_generation_inventory.list();
@@ -144,8 +144,8 @@ impl WarmingStateInner {
Ok(true)
}
/// Every [`GC_INTERVAL`] attempt to GC, with panics caught and logged using
/// [`std::panic::catch_unwind`].
/// Every [GC_INTERVAL] attempt to GC, with panics caught and logged using
/// [std::panic::catch_unwind].
fn gc_loop(inner: Weak<Mutex<WarmingStateInner>>) {
for _ in crossbeam_channel::tick(GC_INTERVAL) {
if let Some(inner) = inner.upgrade() {

View File

@@ -115,7 +115,7 @@ impl DateOptions {
/// Returns the cardinality of the fastfield.
///
/// If the field has not been declared as a fastfield, then
/// the method returns `None`.
/// the method returns None.
pub fn get_fastfield_cardinality(&self) -> Option<Cardinality> {
self.fast
}

View File

@@ -103,7 +103,7 @@ impl Type {
}
/// Interprets a 1byte code as a type.
/// Returns `None` if the code is invalid.
/// Returns None if the code is invalid.
pub fn from_code(code: u8) -> Option<Self> {
match code {
b's' => Some(Type::Str),

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