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4 Commits

Author SHA1 Message Date
Paul Masurel
8828b6d310 Support for columnar 2022-12-21 12:21:30 +09:00
Paul Masurel
2b89bf9050 Support for NotNaN in fast fields 2022-12-21 12:20:48 +09:00
Paul Masurel
3580198447 Minor refactoring 2022-12-21 12:18:33 +09:00
Paul Masurel
d96a716d20 Refactoring to prepare for the addition of dynamic fast field 2022-12-21 12:16:00 +09:00
118 changed files with 2083 additions and 4359 deletions

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@@ -15,7 +15,7 @@ rust-version = "1.62"
[dependencies]
oneshot = "0.1.5"
base64 = "0.21.0"
base64 = "0.20.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
once_cell = "1.10.0"
@@ -36,6 +36,7 @@ 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"
stable_deref_trait = "1.2.0"
rust-stemmers = "1.2.0"
downcast-rs = "1.2.0"
bitpacking = { version = "0.8.4", default-features = false, features = ["bitpacker4x"] }
@@ -48,7 +49,7 @@ murmurhash32 = "0.2.0"
time = { version = "0.3.10", features = ["serde-well-known"] }
smallvec = "1.8.0"
rayon = "1.5.2"
lru = "0.9.0"
lru = "0.7.5"
fastdivide = "0.4.0"
itertools = "0.10.3"
measure_time = "0.8.2"
@@ -61,7 +62,7 @@ tantivy-query-grammar = { version= "0.19.0", path="./query-grammar" }
tantivy-bitpacker = { version= "0.3", path="./bitpacker" }
common = { version= "0.5", path = "./common/", package = "tantivy-common" }
fastfield_codecs = { version= "0.3", path="./fastfield_codecs", default-features = false }
tokenizer-api = { version="0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
ownedbytes = { version= "0.5", path="./ownedbytes" }
[target.'cfg(windows)'.dependencies]
winapi = "0.3.9"
@@ -107,7 +108,7 @@ unstable = [] # useful for benches.
quickwit = ["sstable"]
[workspace]
members = ["query-grammar", "bitpacker", "common", "fastfield_codecs", "ownedbytes", "stacker", "sstable", "columnar", "tokenizer-api"]
members = ["query-grammar", "bitpacker", "common", "fastfield_codecs", "ownedbytes", "stacker", "sstable", "columnar"]
# Following the "fail" crate best practises, we isolate
# tests that define specific behavior in fail check points

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@@ -29,7 +29,7 @@ Your mileage WILL vary depending on the nature of queries and their load.
# Features
- Full-text search
- Configurable tokenizer (stemming available for 17 Latin languages) with third party support for Chinese ([tantivy-jieba](https://crates.io/crates/tantivy-jieba) and [cang-jie](https://crates.io/crates/cang-jie)), Japanese ([lindera](https://github.com/lindera-morphology/lindera-tantivy), [Vaporetto](https://crates.io/crates/vaporetto_tantivy), and [tantivy-tokenizer-tiny-segmenter](https://crates.io/crates/tantivy-tokenizer-tiny-segmenter)) and Korean ([lindera](https://github.com/lindera-morphology/lindera-tantivy) + [lindera-ko-dic-builder](https://github.com/lindera-morphology/lindera-ko-dic-builder))
- Configurable tokenizer (stemming available for 17 Latin languages with third party support for Chinese ([tantivy-jieba](https://crates.io/crates/tantivy-jieba) and [cang-jie](https://crates.io/crates/cang-jie)), Japanese ([lindera](https://github.com/lindera-morphology/lindera-tantivy), [Vaporetto](https://crates.io/crates/vaporetto_tantivy), and [tantivy-tokenizer-tiny-segmenter](https://crates.io/crates/tantivy-tokenizer-tiny-segmenter)) and Korean ([lindera](https://github.com/lindera-morphology/lindera-tantivy) + [lindera-ko-dic-builder](https://github.com/lindera-morphology/lindera-ko-dic-builder))
- Fast (check out the :racehorse: :sparkles: [benchmark](https://tantivy-search.github.io/bench/) :sparkles: :racehorse:)
- Tiny startup time (<10ms), perfect for command-line tools
- BM25 scoring (the same as Lucene)
@@ -42,12 +42,12 @@ Your mileage WILL vary depending on the nature of queries and their load.
- Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene)
- `&[u8]` fast fields
- Text, i64, u64, f64, dates, and hierarchical facet fields
- Compressed document store (LZ4, Zstd, None, Brotli, Snap)
- LZ4 compressed document store
- Range queries
- Faceted search
- Configurable indexing (optional term frequency and position indexing)
- JSON Field
- Aggregation Collector: histogram, range buckets, average, and stats metrics
- Aggregation Collector: range buckets, average, and stats metrics
- LogMergePolicy with deletes
- Searcher Warmer API
- Cheesy logo with a horse
@@ -81,10 +81,6 @@ There are many ways to support this project.
We use the GitHub Pull Request workflow: reference a GitHub ticket and/or include a comprehensive commit message when opening a PR.
## Tokenizer
When implementing a tokenizer for tantivy depend on the `tantivy-tokenizer-api` crate.
## Minimum supported Rust version
Tantivy currently requires at least Rust 1.62 or later to compile.

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@@ -91,15 +91,17 @@ impl BitUnpacker {
return 0u64;
}
let addr_in_bits = idx * self.num_bits as u32;
let addr = (addr_in_bits >> 3) as usize;
let addr = addr_in_bits >> 3;
let bit_shift = addr_in_bits & 7;
debug_assert!(
addr + 8 <= data.len(),
addr + 8 <= data.len() as u32,
"The fast field field should have been padded with 7 bytes."
);
let bytes: [u8; 8] = (&data[addr..addr + 8]).try_into().unwrap();
let bytes: [u8; 8] = (&data[(addr as usize)..(addr as usize) + 8])
.try_into()
.unwrap();
let val_unshifted_unmasked: u64 = u64::from_le_bytes(bytes);
let val_shifted = val_unshifted_unmasked >> bit_shift;
let val_shifted: u64 = val_unshifted_unmasked >> bit_shift;
val_shifted & self.mask
}
}

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@@ -1,8 +1,6 @@
mod bitpacker;
mod blocked_bitpacker;
use std::cmp::Ordering;
pub use crate::bitpacker::{BitPacker, BitUnpacker};
pub use crate::blocked_bitpacker::BlockedBitpacker;
@@ -39,104 +37,44 @@ pub fn compute_num_bits(n: u64) -> u8 {
}
}
/// Computes the (min, max) of an iterator of `PartialOrd` values.
///
/// For values implementing `Ord` (in a way consistent to their `PartialOrd` impl),
/// this function behaves as expected.
///
/// For values with partial ordering, the behavior is non-trivial and may
/// depends on the order of the values.
/// For floats however, it simply returns the same results as if NaN were
/// skipped.
pub fn minmax<I, T>(mut vals: I) -> Option<(T, T)>
where
I: Iterator<Item = T>,
T: Copy + PartialOrd,
T: Copy + Ord,
{
let first_el = vals.find(|val| {
// We use this to make sure we skip all NaN values when
// working with a float type.
val.partial_cmp(val) == Some(Ordering::Equal)
})?;
let mut min_so_far: T = first_el;
let mut max_so_far: T = first_el;
for val in vals {
if val.partial_cmp(&min_so_far) == Some(Ordering::Less) {
min_so_far = val;
}
if val.partial_cmp(&max_so_far) == Some(Ordering::Greater) {
max_so_far = val;
}
if let Some(first_el) = vals.next() {
return Some(vals.fold((first_el, first_el), |(min_val, max_val), el| {
(min_val.min(el), max_val.max(el))
}));
}
Some((min_so_far, max_so_far))
None
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_compute_num_bits() {
assert_eq!(compute_num_bits(1), 1u8);
assert_eq!(compute_num_bits(0), 0u8);
assert_eq!(compute_num_bits(2), 2u8);
assert_eq!(compute_num_bits(3), 2u8);
assert_eq!(compute_num_bits(4), 3u8);
assert_eq!(compute_num_bits(255), 8u8);
assert_eq!(compute_num_bits(256), 9u8);
assert_eq!(compute_num_bits(5_000_000_000), 33u8);
}
#[test]
fn test_minmax_empty() {
let vals: Vec<u32> = vec![];
assert_eq!(minmax(vals.into_iter()), None);
}
#[test]
fn test_minmax_one() {
assert_eq!(minmax(vec![1].into_iter()), Some((1, 1)));
}
#[test]
fn test_minmax_two() {
assert_eq!(minmax(vec![1, 2].into_iter()), Some((1, 2)));
assert_eq!(minmax(vec![2, 1].into_iter()), Some((1, 2)));
}
#[test]
fn test_minmax_nan() {
assert_eq!(
minmax(vec![f64::NAN, 1f64, 2f64].into_iter()),
Some((1f64, 2f64))
);
assert_eq!(
minmax(vec![2f64, f64::NAN, 1f64].into_iter()),
Some((1f64, 2f64))
);
assert_eq!(
minmax(vec![2f64, 1f64, f64::NAN].into_iter()),
Some((1f64, 2f64))
);
}
#[test]
fn test_minmax_inf() {
assert_eq!(
minmax(vec![f64::INFINITY, 1f64, 2f64].into_iter()),
Some((1f64, f64::INFINITY))
);
assert_eq!(
minmax(vec![-f64::INFINITY, 1f64, 2f64].into_iter()),
Some((-f64::INFINITY, 2f64))
);
assert_eq!(
minmax(vec![2f64, f64::INFINITY, 1f64].into_iter()),
Some((1f64, f64::INFINITY))
);
assert_eq!(
minmax(vec![2f64, 1f64, -f64::INFINITY].into_iter()),
Some((-f64::INFINITY, 2f64))
);
}
#[test]
fn test_compute_num_bits() {
assert_eq!(compute_num_bits(1), 1u8);
assert_eq!(compute_num_bits(0), 0u8);
assert_eq!(compute_num_bits(2), 2u8);
assert_eq!(compute_num_bits(3), 2u8);
assert_eq!(compute_num_bits(4), 3u8);
assert_eq!(compute_num_bits(255), 8u8);
assert_eq!(compute_num_bits(256), 9u8);
assert_eq!(compute_num_bits(5_000_000_000), 33u8);
}
#[test]
fn test_minmax_empty() {
let vals: Vec<u32> = vec![];
assert_eq!(minmax(vals.into_iter()), None);
}
#[test]
fn test_minmax_one() {
assert_eq!(minmax(vec![1].into_iter()), Some((1, 1)));
}
#[test]
fn test_minmax_two() {
assert_eq!(minmax(vec![1, 2].into_iter()), Some((1, 2)));
assert_eq!(minmax(vec![2, 1].into_iter()), Some((1, 2)));
}

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@@ -2,17 +2,25 @@
name = "tantivy-columnar"
version = "0.1.0"
edition = "2021"
license = "MIT"
[dependencies]
stacker = { path = "../stacker", package="tantivy-stacker"}
serde_json = "1"
thiserror = "1"
fnv = "1"
tantivy-fst = "0.4.0"
sstable = { path = "../sstable", package = "tantivy-sstable" }
common = { path = "../common", package = "tantivy-common" }
fastfield_codecs = { path = "../fastfield_codecs"}
ordered-float = "3.4"
itertools = "0.10"
[features]
# default = ["quickwit"]
# quickwit = ["common/quickwit"]
[dev-dependencies]
proptest = "1"

View File

@@ -2,6 +2,7 @@
This crate describes columnar format used in tantivy.
## Goals
This format is special in the following way.
@@ -14,50 +15,15 @@ we need to be able to load columns rapidly.
and different cardinality `(required, optional, multivalued)`.
- columns, once loaded, offer cheap random access.
# Coercion rules
# Format
Users can create a columnar by inserting rows to a `ColumnarWriter`,
and serializing it into a `Write` object.
Nothing prevents a user from recording values with different type to the same `column_name`.
A quickwit/tantivy style sstable associated
`(column names, column_cardinality, column_type) to range of bytes.
In that case, `tantivy-columnar`'s behavior is as follows:
- JsonValues are grouped into 3 types (String, Number, bool).
Values that corresponds to different groups are mapped to different columns. For instance, String values are treated independently
from Number or boolean values. `tantivy-columnar` will simply emit several columns associated to a given column_name.
- Only one column for a given json value type is emitted. If number values with different number types are recorded (e.g. u64, i64, f64),
`tantivy-columnar` will pick the first type that can represents the set of appended value, with the following prioriy order (`i64`, `u64`, `f64`).
`i64` is picked over `u64` as it is likely to yield less change of types. Most use cases strictly requiring `u64` show the
restriction on 50% of the values (e.g. a 64-bit hash). On the other hand, a lot of use cases can show rare negative value.
# Columnar format
This columnar format may have more than one column (with different types) associated to the same `column_name` (see [Coercion rules](#coercion-rules) above).
The `(column_name, columne_type)` couple however uniquely identifies a column.
That couple is serialized as a column `column_key`. The format of that key is:
The format of the key is:
`[column_name][ZERO_BYTE][column_type_header: u8]`
```
COLUMNAR:=
[COLUMNAR_DATA]
[COLUMNAR_KEY_TO_DATA_INDEX]
[COLUMNAR_FOOTER];
# Columns are sorted by their column key.
COLUMNAR_DATA:=
[COLUMN_DATA]+;
COLUMNAR_FOOTER := [RANGE_SSTABLE_BYTES_LEN: 8 bytes little endian]
```
The columnar file starts by the actual column data, concatenated one after the other,
sorted by column key.
A sstable associates
`(column name, column_cardinality, column_type) to range of bytes.
Column name may not contain the zero byte `\0`.
Column name may not contain the zero byte.
Listing all columns associated to `column_name` can therefore
be done by listing all keys prefixed by

View File

@@ -1,154 +1,107 @@
use crate::utils::{place_bits, select_bits};
use crate::value::NumericalType;
use crate::InvalidData;
/// Enum describing the number of values that can exist per document
/// (or per row if you will).
///
/// The cardinality must fit on 2 bits.
#[derive(Clone, Copy, Hash, Default, Debug, PartialEq, Eq, PartialOrd, Ord)]
#[repr(u8)]
pub enum Cardinality {
/// All documents contain exactly one value.
/// Required is the default for auto-detecting the Cardinality, since it is the most strict.
#[default]
Required = 0,
/// All documents contain at most one value.
Optional = 1,
/// All documents may contain any number of values.
Multivalued = 2,
}
impl Cardinality {
pub(crate) fn to_code(self) -> u8 {
self as u8
}
pub(crate) fn try_from_code(code: u8) -> Result<Cardinality, InvalidData> {
match code {
0 => Ok(Cardinality::Required),
1 => Ok(Cardinality::Optional),
2 => Ok(Cardinality::Multivalued),
_ => Err(InvalidData),
}
}
}
/// The column type represents the column type and can fit on 6-bits.
///
/// - bits[0..3]: Column category type.
/// - bits[3..6]: Numerical type if necessary.
#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy)]
pub enum ColumnType {
Bytes,
Numerical(NumericalType),
Bool,
}
impl ColumnType {
/// Encoded over 6 bits.
pub(crate) fn to_code(self) -> u8 {
let column_type_category;
let numerical_type_code: u8;
match self {
ColumnType::Bytes => {
column_type_category = ColumnTypeCategory::Str;
numerical_type_code = 0u8;
}
ColumnType::Numerical(numerical_type) => {
column_type_category = ColumnTypeCategory::Numerical;
numerical_type_code = numerical_type.to_code();
}
ColumnType::Bool => {
column_type_category = ColumnTypeCategory::Bool;
numerical_type_code = 0u8;
}
}
place_bits::<0, 3>(column_type_category.to_code()) | place_bits::<3, 6>(numerical_type_code)
}
pub(crate) fn try_from_code(code: u8) -> Result<ColumnType, InvalidData> {
if select_bits::<6, 8>(code) != 0u8 {
return Err(InvalidData);
}
let column_type_category_code = select_bits::<0, 3>(code);
let numerical_type_code = select_bits::<3, 6>(code);
let column_type_category = ColumnTypeCategory::try_from_code(column_type_category_code)?;
match column_type_category {
ColumnTypeCategory::Bool => {
if numerical_type_code != 0u8 {
return Err(InvalidData);
}
Ok(ColumnType::Bool)
}
ColumnTypeCategory::Str => {
if numerical_type_code != 0u8 {
return Err(InvalidData);
}
Ok(ColumnType::Bytes)
}
ColumnTypeCategory::Numerical => {
let numerical_type = NumericalType::try_from_code(numerical_type_code)?;
Ok(ColumnType::Numerical(numerical_type))
}
}
}
}
/// Column types are grouped into different categories that
/// corresponds to the different types of `JsonValue` types.
///
/// The columnar writer will apply coercion rules to make sure that
/// at most one column exist per `ColumnTypeCategory`.
///
/// See also [README.md].
#[derive(Copy, Clone, Ord, PartialOrd, Eq, PartialEq, Debug)]
#[repr(u8)]
pub(crate) enum ColumnTypeCategory {
Bool = 0u8,
Str = 1u8,
Numerical = 2u8,
}
impl ColumnTypeCategory {
pub fn to_code(self) -> u8 {
self as u8
}
pub fn try_from_code(code: u8) -> Result<Self, InvalidData> {
pub fn try_from_code(code: u8) -> Option<Cardinality> {
match code {
0u8 => Ok(Self::Bool),
1u8 => Ok(Self::Str),
2u8 => Ok(Self::Numerical),
_ => Err(InvalidData),
0 => Some(Cardinality::Required),
1 => Some(Cardinality::Optional),
2 => Some(Cardinality::Multivalued),
_ => None,
}
}
}
#[derive(Hash, Eq, PartialEq, Debug, Clone, Copy)]
pub enum ColumnType {
Bytes,
Numerical(NumericalType),
}
impl ColumnType {
pub fn to_code(self) -> u8 {
match self {
ColumnType::Bytes => 0u8,
ColumnType::Numerical(numerical_type) => 1u8 | (numerical_type.to_code() << 1),
}
}
pub fn try_from_code(code: u8) -> Option<ColumnType> {
if code == 0u8 {
return Some(ColumnType::Bytes);
}
if code & 1u8 == 0u8 {
return None;
}
let numerical_type = NumericalType::try_from_code(code >> 1)?;
Some(ColumnType::Numerical(numerical_type))
}
}
/// Represents the type and cardinality of a column.
/// This is encoded over one-byte and added to a column key in the
/// columnar sstable.
///
/// - [0..6] bits: encodes the column type
/// - [6..8] bits: encodes the cardinality
/// Cardinality is encoded as the first two highest two bits.
/// The low 6 bits encode the column type.
#[derive(Eq, Hash, PartialEq, Debug, Copy, Clone)]
pub struct ColumnTypeAndCardinality {
pub typ: ColumnType,
pub cardinality: Cardinality,
pub typ: ColumnType,
}
#[inline]
const fn compute_mask(num_bits: u8) -> u8 {
if num_bits == 8 {
u8::MAX
} else {
(1u8 << num_bits) - 1
}
}
#[inline]
fn select_bits<const START: u8, const END: u8>(code: u8) -> u8 {
assert!(START <= END);
assert!(END <= 8);
let num_bits: u8 = END - START;
let mask: u8 = compute_mask(num_bits);
(code >> START) & mask
}
#[inline]
fn place_bits<const START: u8, const END: u8>(code: u8) -> u8 {
assert!(START <= END);
assert!(END <= 8);
let num_bits: u8 = END - START;
let mask: u8 = compute_mask(num_bits);
assert!(code <= mask);
code << START
}
impl ColumnTypeAndCardinality {
pub fn to_code(self) -> u8 {
place_bits::<0, 6>(self.typ.to_code()) | place_bits::<6, 8>(self.cardinality.to_code())
place_bits::<6, 8>(self.cardinality.to_code()) | place_bits::<0, 6>(self.typ.to_code())
}
pub fn try_from_code(code: u8) -> Result<ColumnTypeAndCardinality, InvalidData> {
pub fn try_from_code(code: u8) -> Option<ColumnTypeAndCardinality> {
let typ_code = select_bits::<0, 6>(code);
let cardinality_code = select_bits::<6, 8>(code);
let cardinality = Cardinality::try_from_code(cardinality_code)?;
let typ = ColumnType::try_from_code(typ_code)?;
assert_eq!(typ.to_code(), typ_code);
Ok(ColumnTypeAndCardinality { cardinality, typ })
Some(ColumnTypeAndCardinality { cardinality, typ })
}
}
@@ -163,15 +116,14 @@ mod tests {
fn test_column_type_header_to_code() {
let mut column_type_header_set: HashSet<ColumnTypeAndCardinality> = HashSet::new();
for code in u8::MIN..=u8::MAX {
if let Ok(column_type_header) = ColumnTypeAndCardinality::try_from_code(code) {
if let Some(column_type_header) = ColumnTypeAndCardinality::try_from_code(code) {
assert_eq!(column_type_header.to_code(), code);
assert!(column_type_header_set.insert(column_type_header));
}
}
assert_eq!(
column_type_header_set.len(),
3 /* cardinality */ *
(1 + 1 + 3) // column_types (str, bool, numerical x 3)
3 /* cardinality */ * (1 + 3) // column_types
);
}
@@ -179,19 +131,20 @@ mod tests {
fn test_column_type_to_code() {
let mut column_type_set: HashSet<ColumnType> = HashSet::new();
for code in u8::MIN..=u8::MAX {
if let Ok(column_type) = ColumnType::try_from_code(code) {
if let Some(column_type) = ColumnType::try_from_code(code) {
assert_eq!(column_type.to_code(), code);
assert!(column_type_set.insert(column_type));
}
}
assert_eq!(column_type_set.len(), 2 + 3);
assert_eq!(column_type_set.len(), 1 + 3);
}
#[test]
fn test_cardinality_to_code() {
let mut num_cardinality = 0;
for code in u8::MIN..=u8::MAX {
if let Ok(cardinality) = Cardinality::try_from_code(code) {
let cardinality_opt = Cardinality::try_from_code(code);
if let Some(cardinality) = cardinality_opt {
assert_eq!(cardinality.to_code(), code);
num_cardinality += 1;
}

View File

@@ -1,27 +1,16 @@
use std::io;
use fnv::FnvHashMap;
use sstable::SSTable;
pub(crate) struct TermIdMapping {
unordered_to_ord: Vec<OrderedId>,
}
impl TermIdMapping {
pub fn to_ord(&self, unordered: UnorderedId) -> OrderedId {
self.unordered_to_ord[unordered.0 as usize]
fn fst_err_into_io_err(fst_err: tantivy_fst::Error) -> io::Error {
match fst_err {
tantivy_fst::Error::Fst(fst_err) => {
io::Error::new(io::ErrorKind::Other, format!("FST Error: {:?}", fst_err))
}
tantivy_fst::Error::Io(io_err) => io_err,
}
}
/// When we add values, we cannot know their ordered id yet.
/// For this reason, we temporarily assign them a `UnorderedId`
/// that will be mapped to an `OrderedId` upon serialization.
#[derive(Clone, Copy, Debug, Hash, PartialEq, Eq)]
pub struct UnorderedId(pub u32);
#[derive(Clone, Copy, Hash, PartialEq, Eq, Debug)]
pub struct OrderedId(pub u32);
/// `DictionaryBuilder` for dictionary encoding.
///
/// It stores the different terms encounterred and assigns them a temporary value
@@ -30,10 +19,20 @@ pub struct OrderedId(pub u32);
/// Upon serialization, we will sort the ids and hence build a `UnorderedId -> Term ordinal`
/// mapping.
#[derive(Default)]
pub(crate) struct DictionaryBuilder {
pub struct DictionaryBuilder {
dict: FnvHashMap<Vec<u8>, UnorderedId>,
}
pub struct IdMapping {
unordered_to_ord: Vec<OrderedId>,
}
impl IdMapping {
pub fn to_ord(&self, unordered: UnorderedId) -> OrderedId {
self.unordered_to_ord[unordered.0 as usize]
}
}
impl DictionaryBuilder {
/// Get or allocate an unordered id.
/// (This ID is simply an auto-incremented id.)
@@ -48,37 +47,32 @@ impl DictionaryBuilder {
/// Serialize the dictionary into an fst, and returns the
/// `UnorderedId -> TermOrdinal` map.
pub fn serialize<'a, W: io::Write + 'a>(&self, wrt: &mut W) -> io::Result<TermIdMapping> {
let mut terms: Vec<(&[u8], UnorderedId)> =
self.dict.iter().map(|(k, v)| (k.as_slice(), *v)).collect();
terms.sort_unstable_by_key(|(key, _)| *key);
// TODO Remove the allocation.
let mut unordered_to_ord: Vec<OrderedId> = vec![OrderedId(0u32); terms.len()];
let mut sstable_builder = sstable::VoidSSTable::writer(wrt);
for (ord, (key, unordered_id)) in terms.into_iter().enumerate() {
let ordered_id = OrderedId(ord as u32);
sstable_builder.insert(key, &())?;
unordered_to_ord[unordered_id.0 as usize] = ordered_id;
}
sstable_builder.finish()?;
Ok(TermIdMapping { unordered_to_ord })
pub fn serialize<'a, W: io::Write + 'a>(&self, wrt: &mut W) -> io::Result<IdMapping> {
serialize_inner(&self.dict, wrt).map_err(fst_err_into_io_err)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_dictionary_builder() {
let mut dictionary_builder = DictionaryBuilder::default();
let hello_uid = dictionary_builder.get_or_allocate_id(b"hello");
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy");
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax");
let mut buffer = Vec::new();
let id_mapping = dictionary_builder.serialize(&mut buffer).unwrap();
assert_eq!(id_mapping.to_ord(hello_uid), OrderedId(1));
assert_eq!(id_mapping.to_ord(happy_uid), OrderedId(0));
assert_eq!(id_mapping.to_ord(tax_uid), OrderedId(2));
/// Helper function just there for error conversion.
fn serialize_inner<'a, W: io::Write + 'a>(
dict: &FnvHashMap<Vec<u8>, UnorderedId>,
wrt: &mut W,
) -> tantivy_fst::Result<IdMapping> {
let mut terms: Vec<(&[u8], UnorderedId)> =
dict.iter().map(|(k, v)| (k.as_slice(), *v)).collect();
terms.sort_unstable_by_key(|(key, _)| *key);
let mut unordered_to_ord: Vec<OrderedId> = vec![OrderedId(0u32); terms.len()];
let mut fst_builder = tantivy_fst::MapBuilder::new(wrt)?;
for (ord, (key, unordered_id)) in terms.into_iter().enumerate() {
let ordered_id = OrderedId(ord as u32);
fst_builder.insert(key, ord as u64)?;
unordered_to_ord[unordered_id.0 as usize] = ordered_id;
}
fst_builder.finish()?;
Ok(IdMapping { unordered_to_ord })
}
#[derive(Clone, Copy, Debug)]
pub struct UnorderedId(pub u32);
#[derive(Clone, Copy)]
pub struct OrderedId(pub u32);

View File

@@ -1,77 +1,57 @@
// 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/>.
mod column_type_header;
mod dictionary;
mod reader;
pub(crate) mod utils;
mod serializer;
mod value;
mod writer;
pub use column_type_header::Cardinality;
pub use reader::ColumnarReader;
pub use value::{NumericalType, NumericalValue};
pub use serializer::ColumnarSerializer;
pub use writer::ColumnarWriter;
pub type DocId = u32;
#[derive(Copy, Clone, Debug)]
pub struct InvalidData;
#[cfg(test)]
mod tests {
use std::ops::Range;
use common::file_slice::FileSlice;
use crate::column_type_header::{ColumnType, ColumnTypeAndCardinality};
use crate::column_type_header::ColumnTypeAndCardinality;
use crate::reader::ColumnarReader;
use crate::serializer::ColumnarSerializer;
use crate::value::NumericalValue;
use crate::{Cardinality, ColumnarWriter};
use crate::ColumnarWriter;
#[test]
fn test_dataframe_writer_bytes() {
fn test_dataframe_writer() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_str(1u32, "my_string", "hello");
dataframe_writer.record_str(3u32, "my_string", "helloeee");
dataframe_writer.record_numerical(1u32, b"srical.value", NumericalValue::U64(1u64));
dataframe_writer.record_numerical(2u32, b"srical.value", NumericalValue::U64(2u64));
dataframe_writer.record_numerical(4u32, b"srical.value", NumericalValue::I64(2i64));
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let columnar_fileslice = FileSlice::from(buffer);
let columnar = ColumnarReader::open(columnar_fileslice).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<(ColumnTypeAndCardinality, Range<u64>)> =
columnar.read_columns("my_string").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].1, 0..158);
}
#[test]
fn test_dataframe_writer_bool() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_bool(1u32, "bool.value", false);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let columnar_fileslice = FileSlice::from(buffer);
let columnar = ColumnarReader::open(columnar_fileslice).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<(ColumnTypeAndCardinality, Range<u64>)> =
columnar.read_columns("bool.value").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(
cols[0].0,
ColumnTypeAndCardinality {
cardinality: Cardinality::Optional,
typ: ColumnType::Bool
}
);
assert_eq!(cols[0].1, 0..21);
}
#[test]
fn test_dataframe_writer_numerical() {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_numerical(1u32, "srical.value", NumericalValue::U64(12u64));
dataframe_writer.record_numerical(2u32, "srical.value", NumericalValue::U64(13u64));
dataframe_writer.record_numerical(4u32, "srical.value", NumericalValue::U64(15u64));
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
let serializer = ColumnarSerializer::new(&mut buffer);
dataframe_writer.serialize(5, serializer).unwrap();
let columnar_fileslice = FileSlice::from(buffer);
let columnar = ColumnarReader::open(columnar_fileslice).unwrap();
assert_eq!(columnar.num_columns(), 1);

View File

@@ -3,29 +3,25 @@ use std::{io, mem};
use common::file_slice::FileSlice;
use common::BinarySerializable;
use sstable::{Dictionary, RangeSSTable};
use sstable::{Dictionary, SSTableRange};
use crate::column_type_header::ColumnTypeAndCardinality;
fn io_invalid_data(msg: String) -> io::Error {
io::Error::new(io::ErrorKind::InvalidData, msg)
io::Error::new(io::ErrorKind::InvalidData, msg) // format!("Invalid key found.
// {key_bytes:?}")));
}
/// The ColumnarReader makes it possible to access a set of columns
/// associated to field names.
pub struct ColumnarReader {
column_dictionary: Dictionary<RangeSSTable>,
column_dictionary: Dictionary<SSTableRange>,
column_data: FileSlice,
}
impl ColumnarReader {
/// Opens a new Columnar file.
pub fn open<F>(file_slice: F) -> io::Result<ColumnarReader>
where FileSlice: From<F> {
Self::open_inner(file_slice.into())
pub fn num_columns(&self) -> usize {
self.column_dictionary.num_terms()
}
fn open_inner(file_slice: FileSlice) -> io::Result<ColumnarReader> {
pub fn open(file_slice: FileSlice) -> io::Result<ColumnarReader> {
let (file_slice_without_sstable_len, sstable_len_bytes) =
file_slice.split_from_end(mem::size_of::<u64>());
let mut sstable_len_bytes = sstable_len_bytes.read_bytes()?;
@@ -39,50 +35,13 @@ impl ColumnarReader {
})
}
// TODO fix ugly API
pub fn list_columns(
&self,
) -> io::Result<Vec<(String, ColumnTypeAndCardinality, Range<u64>, u64)>> {
let mut stream = self.column_dictionary.stream()?;
let mut results = Vec::new();
while stream.advance() {
let key_bytes: &[u8] = stream.key();
let column_code: u8 = key_bytes.last().cloned().unwrap();
let column_type_and_cardinality = ColumnTypeAndCardinality::try_from_code(column_code)
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
let range = stream.value().clone();
let column_name = String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 1]);
let range_len = range.end - range.start;
results.push((
column_name.to_string(),
column_type_and_cardinality,
range,
range_len,
));
}
Ok(results)
}
/// Get all columns for the given column name.
///
/// There can be more than one column associated to a given column name, provided they have
/// different types.
// TODO fix ugly API
pub fn read_columns(
&self,
column_name: &str,
field_name: &str,
) -> io::Result<Vec<(ColumnTypeAndCardinality, Range<u64>)>> {
// Each column is a associated to a given `column_key`,
// that starts by `column_name\0column_header`.
//
// Listing the columns associated to the given column name is therefore equivalent to
// listing `column_key` with the prefix `column_name\0`.
//
// This is in turn equivalent to searching for the range
// `[column_name,\0`..column_name\1)`.
let mut start_key = column_name.to_string();
let mut start_key = field_name.to_string();
start_key.push('\0');
let mut end_key = column_name.to_string();
let mut end_key = field_name.to_string();
end_key.push(1u8 as char);
let mut stream = self
.column_dictionary
@@ -93,18 +52,15 @@ impl ColumnarReader {
let mut results = Vec::new();
while stream.advance() {
let key_bytes: &[u8] = stream.key();
assert!(key_bytes.starts_with(start_key.as_bytes()));
if !key_bytes.starts_with(start_key.as_bytes()) {
return Err(io_invalid_data(format!("Invalid key found. {key_bytes:?}")));
}
let column_code: u8 = key_bytes.last().cloned().unwrap();
let column_type_and_cardinality = ColumnTypeAndCardinality::try_from_code(column_code)
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
.ok_or_else(|| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
let range = stream.value().clone();
results.push((column_type_and_cardinality, range));
}
Ok(results)
}
/// Return the number of columns in the columnar.
pub fn num_columns(&self) -> usize {
self.column_dictionary.num_terms()
}
}

View File

@@ -0,0 +1,39 @@
use std::io;
use std::io::Write;
use std::ops::Range;
use common::CountingWriter;
use sstable::value::RangeWriter;
use sstable::SSTableRange;
pub struct ColumnarSerializer<W: io::Write> {
wrt: CountingWriter<W>,
sstable_range: sstable::Writer<Vec<u8>, RangeWriter>,
}
impl<W: io::Write> ColumnarSerializer<W> {
pub fn new(wrt: W) -> ColumnarSerializer<W> {
let sstable_range: sstable::Writer<Vec<u8>, RangeWriter> =
sstable::Dictionary::<SSTableRange>::builder(Vec::with_capacity(100_000)).unwrap();
ColumnarSerializer {
wrt: CountingWriter::wrap(wrt),
sstable_range,
}
}
pub fn record_column_offsets(&mut self, key: &[u8], byte_range: Range<u64>) -> io::Result<()> {
self.sstable_range.insert(key, &byte_range)
}
pub fn wrt(&mut self) -> &mut CountingWriter<W> {
&mut self.wrt
}
pub fn finalize(mut self) -> io::Result<()> {
let sstable_bytes: Vec<u8> = self.sstable_range.finish()?;
let sstable_num_bytes: u64 = sstable_bytes.len() as u64;
self.wrt.write_all(&sstable_bytes)?;
self.wrt.write_all(&sstable_num_bytes.to_le_bytes()[..])?;
Ok(())
}
}

View File

@@ -1,76 +0,0 @@
const fn compute_mask(num_bits: u8) -> u8 {
if num_bits == 8 {
u8::MAX
} else {
(1u8 << num_bits) - 1
}
}
#[inline(always)]
#[must_use]
pub(crate) fn select_bits<const START: u8, const END: u8>(code: u8) -> u8 {
assert!(START <= END);
assert!(END <= 8);
let num_bits: u8 = END - START;
let mask: u8 = compute_mask(num_bits);
(code >> START) & mask
}
#[inline(always)]
#[must_use]
pub(crate) fn place_bits<const START: u8, const END: u8>(code: u8) -> u8 {
assert!(START <= END);
assert!(END <= 8);
let num_bits: u8 = END - START;
let mask: u8 = compute_mask(num_bits);
assert!(code <= mask);
code << START
}
/// Pop-front one bytes from a slice of bytes.
#[inline(always)]
pub fn pop_first_byte(bytes: &mut &[u8]) -> Option<u8> {
if bytes.is_empty() {
return None;
}
let first_byte = bytes[0];
*bytes = &bytes[1..];
Some(first_byte)
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_select_bits() {
assert_eq!(255u8, select_bits::<0, 8>(255u8));
assert_eq!(0u8, select_bits::<0, 0>(255u8));
assert_eq!(8u8, select_bits::<0, 4>(8u8));
assert_eq!(4u8, select_bits::<1, 4>(8u8));
assert_eq!(0u8, select_bits::<1, 3>(8u8));
}
#[test]
fn test_place_bits() {
assert_eq!(255u8, place_bits::<0, 8>(255u8));
assert_eq!(4u8, place_bits::<2, 3>(1u8));
assert_eq!(0u8, place_bits::<2, 2>(0u8));
}
#[test]
#[should_panic]
fn test_place_bits_overflows() {
let _ = place_bits::<1, 4>(8u8);
}
#[test]
fn test_pop_first_byte() {
let mut cursor: &[u8] = &b"abcd"[..];
assert_eq!(pop_first_byte(&mut cursor), Some(b'a'));
assert_eq!(pop_first_byte(&mut cursor), Some(b'b'));
assert_eq!(pop_first_byte(&mut cursor), Some(b'c'));
assert_eq!(pop_first_byte(&mut cursor), Some(b'd'));
assert_eq!(pop_first_byte(&mut cursor), None);
}
}

View File

@@ -1,10 +1,10 @@
use crate::InvalidData;
use ordered_float::NotNan;
#[derive(Copy, Clone, Debug, PartialEq)]
pub enum NumericalValue {
I64(i64),
U64(u64),
F64(f64),
F64(NotNan<f64>),
}
impl From<u64> for NumericalValue {
@@ -19,8 +19,8 @@ impl From<i64> for NumericalValue {
}
}
impl From<f64> for NumericalValue {
fn from(val: f64) -> Self {
impl From<NotNan<f64>> for NumericalValue {
fn from(val: NotNan<f64>) -> Self {
NumericalValue::F64(val)
}
}
@@ -51,12 +51,12 @@ impl NumericalType {
self as u8
}
pub fn try_from_code(code: u8) -> Result<NumericalType, InvalidData> {
pub fn try_from_code(code: u8) -> Option<NumericalType> {
match code {
0 => Ok(NumericalType::I64),
1 => Ok(NumericalType::U64),
2 => Ok(NumericalType::F64),
_ => Err(InvalidData),
0 => Some(NumericalType::I64),
1 => Some(NumericalType::U64),
2 => Some(NumericalType::F64),
_ => None,
}
}
}
@@ -64,7 +64,6 @@ impl NumericalType {
/// We voluntarily avoid using `Into` here to keep this
/// implementation quirk as private as possible.
///
/// # Panics
/// This coercion trait actually panics if it is used
/// to convert a loose types to a stricter type.
///
@@ -96,11 +95,11 @@ impl Coerce for u64 {
}
}
impl Coerce for f64 {
impl Coerce for NotNan<f64> {
fn coerce(value: NumericalValue) -> Self {
match value {
NumericalValue::I64(val) => val as f64,
NumericalValue::U64(val) => val as f64,
NumericalValue::I64(val) => unsafe { NotNan::new_unchecked(val as f64) },
NumericalValue::U64(val) => unsafe { NotNan::new_unchecked(val as f64) },
NumericalValue::F64(val) => val,
}
}
@@ -114,7 +113,7 @@ mod tests {
fn test_numerical_type_code() {
let mut num_numerical_type = 0;
for code in u8::MIN..=u8::MAX {
if let Ok(numerical_type) = NumericalType::try_from_code(code) {
if let Some(numerical_type) = NumericalType::try_from_code(code) {
assert_eq!(numerical_type.to_code(), code);
num_numerical_type += 1;
}

View File

@@ -1,239 +1,231 @@
use std::fmt;
use std::num::NonZeroU8;
use ordered_float::NotNan;
use thiserror::Error;
use crate::dictionary::UnorderedId;
use crate::utils::{place_bits, pop_first_byte, select_bits};
use crate::value::NumericalValue;
use crate::{DocId, InvalidData, NumericalType};
use crate::DocId;
/// When we build a columnar dataframe, we first just group
/// all mutations per column, and appends them in append-only buffer
/// in the stacker.
///
/// These ColumnOperation<T> are therefore serialize/deserialized
/// in memory.
/// all mutations per column, and append them in append-only object.
///
/// We represents all of these operations as `ColumnOperation`.
#[derive(Eq, PartialEq, Debug, Clone, Copy)]
pub(super) enum ColumnOperation<T> {
pub(crate) enum ColumnOperation<T> {
NewDoc(DocId),
Value(T),
}
#[derive(Copy, Clone, Eq, PartialEq, Debug)]
struct ColumnOperationMetadata {
op_type: ColumnOperationType,
len: u8,
}
impl ColumnOperationMetadata {
fn to_code(self) -> u8 {
place_bits::<0, 4>(self.len) | place_bits::<4, 8>(self.op_type.to_code())
}
fn try_from_code(code: u8) -> Result<Self, InvalidData> {
let len = select_bits::<0, 4>(code);
let typ_code = select_bits::<4, 8>(code);
let column_type = ColumnOperationType::try_from_code(typ_code)?;
Ok(ColumnOperationMetadata {
op_type: column_type,
len,
})
}
}
#[derive(Copy, Clone, Eq, PartialEq, Debug)]
#[repr(u8)]
enum ColumnOperationType {
NewDoc = 0u8,
AddValue = 1u8,
}
impl ColumnOperationType {
pub fn to_code(self) -> u8 {
self as u8
}
pub fn try_from_code(code: u8) -> Result<Self, InvalidData> {
match code {
0 => Ok(Self::NewDoc),
1 => Ok(Self::AddValue),
_ => Err(InvalidData),
}
}
}
impl<V: SymbolValue> ColumnOperation<V> {
pub(super) fn serialize(self) -> impl AsRef<[u8]> {
let mut minibuf = MiniBuffer::default();
let column_op_metadata = match self {
ColumnOperation::NewDoc(new_doc) => {
let symbol_len = new_doc.serialize(&mut minibuf.bytes[1..]);
ColumnOperationMetadata {
op_type: ColumnOperationType::NewDoc,
len: symbol_len,
}
}
ColumnOperation::Value(val) => {
let symbol_len = val.serialize(&mut minibuf.bytes[1..]);
ColumnOperationMetadata {
op_type: ColumnOperationType::AddValue,
len: symbol_len,
}
}
};
minibuf.bytes[0] = column_op_metadata.to_code();
// +1 for the metadata
minibuf.len = 1 + column_op_metadata.len;
minibuf
}
/// Deserialize a colummn operation.
/// Returns None if the buffer is empty.
///
/// Panics if the payload is invalid:
/// this deserialize method is meant to target in memory.
pub(super) fn deserialize(bytes: &mut &[u8]) -> Option<Self> {
let column_op_metadata_byte = pop_first_byte(bytes)?;
let column_op_metadata = ColumnOperationMetadata::try_from_code(column_op_metadata_byte)
.expect("Invalid op metadata byte");
let symbol_bytes: &[u8];
(symbol_bytes, *bytes) = bytes.split_at(column_op_metadata.len as usize);
match column_op_metadata.op_type {
ColumnOperationType::NewDoc => {
let new_doc = u32::deserialize(symbol_bytes);
Some(ColumnOperation::NewDoc(new_doc))
}
ColumnOperationType::AddValue => {
let value = V::deserialize(symbol_bytes);
Some(ColumnOperation::Value(value))
}
}
}
}
impl<T> From<T> for ColumnOperation<T> {
fn from(value: T) -> Self {
ColumnOperation::Value(value)
}
}
// Serialization trait very local to the writer.
// As we write fast fields, we accumulate them in "in memory".
// In order to limit memory usage, and in order
// to benefit from the stacker, we do this by serialization our data
// as "Symbols".
#[allow(clippy::from_over_into)]
pub(super) trait SymbolValue: Clone + Copy {
// Serializes the symbol into the given buffer.
// Returns the number of bytes written into the buffer.
/// # Panics
/// May not exceed 9bytes
fn serialize(self, buffer: &mut [u8]) -> u8;
// Panics if invalid
fn deserialize(bytes: &[u8]) -> Self;
pub(crate) trait SymbolValue: Into<MiniBuffer> + Clone + Copy + fmt::Debug {
fn deserialize(header: NonZeroU8, bytes: &mut &[u8]) -> Result<Self, ParseError>;
}
impl SymbolValue for bool {
fn serialize(self, buffer: &mut [u8]) -> u8 {
buffer[0] = u8::from(self);
1u8
}
pub(crate) struct MiniBuffer {
pub bytes: [u8; 9],
pub len: usize,
}
fn deserialize(bytes: &[u8]) -> Self {
bytes[0] == 1u8
impl MiniBuffer {
pub fn as_slice(&self) -> &[u8] {
&self.bytes[..self.len]
}
}
#[derive(Default)]
struct MiniBuffer {
pub bytes: [u8; 10],
pub len: u8,
}
impl AsRef<[u8]> for MiniBuffer {
fn as_ref(&self) -> &[u8] {
&self.bytes[..self.len as usize]
}
fn compute_header_byte(typ: SymbolType, len: usize) -> u8 {
assert!(len <= 9);
(len << 4) as u8 | typ as u8
}
impl SymbolValue for NumericalValue {
fn deserialize(mut bytes: &[u8]) -> Self {
let type_code = pop_first_byte(&mut bytes).unwrap();
let symbol_type = NumericalType::try_from_code(type_code).unwrap();
let mut octet: [u8; 8] = [0u8; 8];
octet[..bytes.len()].copy_from_slice(bytes);
match symbol_type {
NumericalType::U64 => {
fn deserialize(header_byte: NonZeroU8, bytes: &mut &[u8]) -> Result<Self, ParseError> {
let (typ, len) = parse_header_byte(header_byte)?;
let value_bytes: &[u8];
(value_bytes, *bytes) = bytes.split_at(len);
let symbol: NumericalValue = match typ {
SymbolType::U64 => {
let mut octet: [u8; 8] = [0u8; 8];
octet[..value_bytes.len()].copy_from_slice(value_bytes);
let val: u64 = u64::from_le_bytes(octet);
NumericalValue::U64(val)
}
NumericalType::I64 => {
SymbolType::I64 => {
let mut octet: [u8; 8] = [0u8; 8];
octet[..value_bytes.len()].copy_from_slice(value_bytes);
let encoded: u64 = u64::from_le_bytes(octet);
let val: i64 = decode_zig_zag(encoded);
NumericalValue::I64(val)
}
NumericalType::F64 => {
debug_assert_eq!(bytes.len(), 8);
let val: f64 = f64::from_le_bytes(octet);
NumericalValue::F64(val)
SymbolType::Float => {
let octet: [u8; 8] =
value_bytes.try_into().map_err(|_| ParseError::InvalidLen {
typ: SymbolType::Float,
len,
})?;
let val_possibly_nan = f64::from_le_bytes(octet);
let val_not_nan = NotNan::new(val_possibly_nan)
.map_err(|_| ParseError::NaN)?;
NumericalValue::F64(val_not_nan)
}
}
};
Ok(symbol)
}
}
/// F64: Serialize with a fixed size of 9 bytes
/// U64: Serialize without leading zeroes
/// I64: ZigZag encoded and serialize without leading zeroes
fn serialize(self, output: &mut [u8]) -> u8 {
#[allow(clippy::from_over_into)]
impl Into<MiniBuffer> for NumericalValue {
fn into(self) -> MiniBuffer {
let mut bytes = [0u8; 9];
match self {
NumericalValue::F64(val) => {
output[0] = NumericalType::F64 as u8;
output[1..9].copy_from_slice(&val.to_le_bytes());
9u8
let len = 8;
let header_byte = compute_header_byte(SymbolType::Float, len);
bytes[0] = header_byte;
bytes[1..].copy_from_slice(&val.to_le_bytes());
MiniBuffer {
bytes,
len: len + 1,
}
}
NumericalValue::U64(val) => {
let len = compute_num_bytes_for_u64(val) as u8;
output[0] = NumericalType::U64 as u8;
output[1..9].copy_from_slice(&val.to_le_bytes());
len + 1u8
let len = compute_num_bytes_for_u64(val);
let header_byte = compute_header_byte(SymbolType::U64, len);
bytes[0] = header_byte;
bytes[1..].copy_from_slice(&val.to_le_bytes());
MiniBuffer {
bytes,
len: len + 1,
}
}
NumericalValue::I64(val) => {
let zig_zag_encoded = encode_zig_zag(val);
let len = compute_num_bytes_for_u64(zig_zag_encoded) as u8;
output[0] = NumericalType::I64 as u8;
output[1..9].copy_from_slice(&zig_zag_encoded.to_le_bytes());
len + 1u8
let encoded = encode_zig_zag(val);
let len = compute_num_bytes_for_u64(encoded);
let header_byte = compute_header_byte(SymbolType::I64, len);
bytes[0] = header_byte;
bytes[1..].copy_from_slice(&encoded.to_le_bytes());
MiniBuffer {
bytes,
len: len + 1,
}
}
}
}
}
impl SymbolValue for u32 {
fn serialize(self, output: &mut [u8]) -> u8 {
let len = compute_num_bytes_for_u64(self as u64);
output[0..4].copy_from_slice(&self.to_le_bytes());
len as u8
}
fn deserialize(bytes: &[u8]) -> Self {
let mut quartet: [u8; 4] = [0u8; 4];
quartet[..bytes.len()].copy_from_slice(bytes);
u32::from_le_bytes(quartet)
#[allow(clippy::from_over_into)]
impl Into<MiniBuffer> for UnorderedId {
fn into(self) -> MiniBuffer {
let mut bytes = [0u8; 9];
let val = self.0 as u64;
let len = compute_num_bytes_for_u64(val) + 1;
bytes[0] = len as u8;
bytes[1..].copy_from_slice(&val.to_le_bytes());
MiniBuffer { bytes, len }
}
}
impl SymbolValue for UnorderedId {
fn serialize(self, output: &mut [u8]) -> u8 {
self.0.serialize(output)
}
fn deserialize(bytes: &[u8]) -> Self {
UnorderedId(u32::deserialize(bytes))
fn deserialize(header: NonZeroU8, bytes: &mut &[u8]) -> Result<UnorderedId, ParseError> {
let len = header.get() as usize;
let symbol_bytes: &[u8];
(symbol_bytes, *bytes) = bytes.split_at(len);
let mut value_bytes = [0u8; 4];
value_bytes[..len - 1].copy_from_slice(&symbol_bytes[1..]);
let value = u32::from_le_bytes(value_bytes);
Ok(UnorderedId(value))
}
}
const HEADER_MASK: u8 = (1u8 << 4) - 1u8;
fn compute_num_bytes_for_u64(val: u64) -> usize {
let msb = (64u32 - val.leading_zeros()) as usize;
(msb + 7) / 8
}
fn parse_header_byte(byte: NonZeroU8) -> Result<(SymbolType, usize), ParseError> {
let len = (byte.get() as usize) >> 4;
let typ_code = byte.get() & HEADER_MASK;
let typ = SymbolType::try_from(typ_code)?;
Ok((typ, len))
}
#[derive(Error, Debug)]
pub enum ParseError {
#[error("Type byte unknown `{0}`")]
UnknownType(u8),
#[error("Invalid len for type `{len}` for type `{typ:?}`.")]
InvalidLen { typ: SymbolType, len: usize },
#[error("Missing bytes.")]
MissingBytes,
#[error("Not a number value.")]
NaN,
}
impl<V: SymbolValue> ColumnOperation<V> {
pub fn serialize(self) -> MiniBuffer {
match self {
ColumnOperation::NewDoc(doc) => {
let mut minibuf: [u8; 9] = [0u8; 9];
minibuf[0] = 0u8;
minibuf[1..5].copy_from_slice(&doc.to_le_bytes());
MiniBuffer {
bytes: minibuf,
len: 5,
}
}
ColumnOperation::Value(val) => val.into(),
}
}
pub fn deserialize(bytes: &mut &[u8]) -> Result<Self, ParseError> {
if bytes.is_empty() {
return Err(ParseError::MissingBytes);
}
let header_byte = bytes[0];
*bytes = &bytes[1..];
if let Some(header_byte) = NonZeroU8::new(header_byte) {
let value = V::deserialize(header_byte, bytes)?;
Ok(ColumnOperation::Value(value))
} else {
let doc_bytes: &[u8];
(doc_bytes, *bytes) = bytes.split_at(4);
let doc: u32 =
u32::from_le_bytes(doc_bytes.try_into().map_err(|_| ParseError::MissingBytes)?);
Ok(ColumnOperation::NewDoc(doc))
}
}
}
#[derive(Copy, Clone, Debug, Eq, PartialEq)]
#[repr(u8)]
pub enum SymbolType {
U64 = 1u8,
I64 = 2u8,
Float = 3u8,
}
impl TryFrom<u8> for SymbolType {
type Error = ParseError;
fn try_from(byte: u8) -> Result<Self, ParseError> {
match byte {
1u8 => Ok(SymbolType::U64),
2u8 => Ok(SymbolType::I64),
3u8 => Ok(SymbolType::Float),
_ => Err(ParseError::UnknownType(byte)),
}
}
}
fn encode_zig_zag(n: i64) -> u64 {
((n << 1) ^ (n >> 63)) as u64
}
@@ -244,7 +236,7 @@ fn decode_zig_zag(n: u64) -> i64 {
#[cfg(test)]
mod tests {
use super::*;
use super::{SymbolType, *};
#[track_caller]
fn test_zig_zag_aux(val: i64) {
@@ -276,28 +268,31 @@ mod tests {
}
}
#[track_caller]
fn ser_deser_header_byte_aux(symbol_type: SymbolType, len: usize) {
let header_byte = compute_header_byte(symbol_type, len);
let (serdeser_numerical_type, serdeser_len) =
parse_header_byte(NonZeroU8::new(header_byte).unwrap()).unwrap();
assert_eq!(symbol_type, serdeser_numerical_type);
assert_eq!(len, serdeser_len);
}
#[test]
fn test_column_op_metadata_byte_serialization() {
for len in 0..=15 {
for op_type in [ColumnOperationType::AddValue, ColumnOperationType::NewDoc] {
let column_op_metadata = ColumnOperationMetadata { op_type, len };
let column_op_metadata_code = column_op_metadata.to_code();
let serdeser_metadata =
ColumnOperationMetadata::try_from_code(column_op_metadata_code).unwrap();
assert_eq!(column_op_metadata, serdeser_metadata);
}
fn test_header_byte_serialization() {
for len in 1..9 {
ser_deser_header_byte_aux(SymbolType::Float, len);
ser_deser_header_byte_aux(SymbolType::I64, len);
ser_deser_header_byte_aux(SymbolType::U64, len);
}
}
#[track_caller]
fn ser_deser_symbol(column_op: ColumnOperation<NumericalValue>) {
let buf = column_op.serialize();
let mut buffer = buf.as_ref().to_vec();
buffer.extend_from_slice(b"234234");
let mut bytes = &buffer[..];
fn ser_deser_symbol(symbol: ColumnOperation<NumericalValue>) {
let buf = symbol.serialize();
let mut bytes = &buf.bytes[..];
let serdeser_symbol = ColumnOperation::deserialize(&mut bytes).unwrap();
assert_eq!(bytes.len() + buf.as_ref().len() as usize, buffer.len());
assert_eq!(column_op, serdeser_symbol);
assert_eq!(bytes.len() + buf.len, buf.bytes.len());
assert_eq!(symbol, serdeser_symbol);
}
#[test]
@@ -323,24 +318,4 @@ mod tests {
ser_deser_symbol(ColumnOperation::Value(NumericalValue::U64(u64::MIN)));
ser_deser_symbol(ColumnOperation::Value(NumericalValue::U64(u64::MAX)));
}
fn test_column_operation_unordered_aux(val: u32, expected_len: usize) {
let column_op = ColumnOperation::Value(UnorderedId(val));
let minibuf = column_op.serialize();
assert_eq!(minibuf.as_ref().len() as usize, expected_len);
let mut buf = minibuf.as_ref().to_vec();
buf.extend_from_slice(&[2, 2, 2, 2, 2, 2]);
let mut cursor = &buf[..];
let column_op_serdeser: ColumnOperation<UnorderedId> =
ColumnOperation::deserialize(&mut cursor).unwrap();
assert_eq!(column_op_serdeser, ColumnOperation::Value(UnorderedId(val)));
assert_eq!(cursor.len() + expected_len, buf.len());
}
#[test]
fn test_column_operation_unordered() {
test_column_operation_unordered_aux(300u32, 3);
test_column_operation_unordered_aux(1u32, 2);
test_column_operation_unordered_aux(0u32, 1);
}
}

View File

@@ -1,265 +0,0 @@
use std::cmp::Ordering;
use stacker::{ExpUnrolledLinkedList, MemoryArena};
use crate::dictionary::{DictionaryBuilder, UnorderedId};
use crate::writer::column_operation::{ColumnOperation, SymbolValue};
use crate::{Cardinality, DocId, NumericalType, NumericalValue};
#[derive(Copy, Clone, Debug, Eq, PartialEq)]
#[repr(u8)]
enum DocumentStep {
Same = 0,
Next = 1,
Skipped = 2,
}
#[inline(always)]
fn delta_with_last_doc(last_doc_opt: Option<u32>, doc: u32) -> DocumentStep {
let expected_next_doc = last_doc_opt.map(|last_doc| last_doc + 1).unwrap_or(0u32);
match doc.cmp(&expected_next_doc) {
Ordering::Less => DocumentStep::Same,
Ordering::Equal => DocumentStep::Next,
Ordering::Greater => DocumentStep::Skipped,
}
}
#[derive(Copy, Clone, Default)]
pub struct ColumnWriter {
// Detected cardinality of the column so far.
cardinality: Cardinality,
// Last document inserted.
// None if no doc has been added yet.
last_doc_opt: Option<u32>,
// Buffer containing the serialized values.
values: ExpUnrolledLinkedList,
}
impl ColumnWriter {
/// Returns an iterator over the Symbol that have been recorded
/// for the given column.
pub(super) fn operation_iterator<'a, V: SymbolValue>(
&self,
arena: &MemoryArena,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<V>> + 'a {
buffer.clear();
self.values.read_to_end(arena, buffer);
let mut cursor: &[u8] = &buffer[..];
std::iter::from_fn(move || ColumnOperation::deserialize(&mut cursor))
}
/// Records a change of the document being recorded.
///
/// This function will also update the cardinality of the column
/// if necessary.
pub(super) fn record<S: SymbolValue>(&mut self, doc: DocId, value: S, arena: &mut MemoryArena) {
// Difference between `doc` and the last doc.
match delta_with_last_doc(self.last_doc_opt, doc) {
DocumentStep::Same => {
// This is the last encounterred document.
self.cardinality = Cardinality::Multivalued;
}
DocumentStep::Next => {
self.last_doc_opt = Some(doc);
self.write_symbol::<S>(ColumnOperation::NewDoc(doc), arena);
}
DocumentStep::Skipped => {
self.cardinality = self.cardinality.max(Cardinality::Optional);
self.last_doc_opt = Some(doc);
self.write_symbol::<S>(ColumnOperation::NewDoc(doc), arena);
}
}
self.write_symbol(ColumnOperation::Value(value), arena);
}
// Get the cardinality.
// The overall number of docs in the column is necessary to
// deal with the case where the all docs contain 1 value, except some documents
// at the end of the column.
pub(crate) fn get_cardinality(&self, num_docs: DocId) -> Cardinality {
match delta_with_last_doc(self.last_doc_opt, num_docs) {
DocumentStep::Same | DocumentStep::Next => self.cardinality,
DocumentStep::Skipped => self.cardinality.max(Cardinality::Optional),
}
}
/// Appends a new symbol to the `ColumnWriter`.
fn write_symbol<V: SymbolValue>(
&mut self,
column_operation: ColumnOperation<V>,
arena: &mut MemoryArena,
) {
self.values
.writer(arena)
.extend_from_slice(column_operation.serialize().as_ref());
}
}
#[derive(Clone, Copy, Default)]
pub(crate) struct NumericalColumnWriter {
compatible_numerical_types: CompatibleNumericalTypes,
column_writer: ColumnWriter,
}
/// State used to store what types are still acceptable
/// after having seen a set of numerical values.
#[derive(Clone, Copy)]
struct CompatibleNumericalTypes {
all_values_within_i64_range: bool,
all_values_within_u64_range: bool,
// f64 is always acceptable.
}
impl Default for CompatibleNumericalTypes {
fn default() -> CompatibleNumericalTypes {
CompatibleNumericalTypes {
all_values_within_i64_range: true,
all_values_within_u64_range: true,
}
}
}
impl CompatibleNumericalTypes {
fn accept_value(&mut self, numerical_value: NumericalValue) {
match numerical_value {
NumericalValue::I64(val_i64) => {
let value_within_u64_range = val_i64 >= 0i64;
self.all_values_within_u64_range &= value_within_u64_range;
}
NumericalValue::U64(val_u64) => {
let value_within_i64_range = val_u64 < i64::MAX as u64;
self.all_values_within_i64_range &= value_within_i64_range;
}
NumericalValue::F64(_) => {
self.all_values_within_i64_range = false;
self.all_values_within_u64_range = false;
}
}
}
pub fn to_numerical_type(self) -> NumericalType {
if self.all_values_within_i64_range {
NumericalType::I64
} else if self.all_values_within_u64_range {
NumericalType::U64
} else {
NumericalType::F64
}
}
}
impl NumericalColumnWriter {
pub fn column_type_and_cardinality(&self, num_docs: DocId) -> (NumericalType, Cardinality) {
let numerical_type = self.compatible_numerical_types.to_numerical_type();
let cardinality = self.column_writer.get_cardinality(num_docs);
(numerical_type, cardinality)
}
pub fn record_numerical_value(
&mut self,
doc: DocId,
value: NumericalValue,
arena: &mut MemoryArena,
) {
self.compatible_numerical_types.accept_value(value);
self.column_writer.record(doc, value, arena);
}
pub(super) fn operation_iterator<'a>(
self,
arena: &MemoryArena,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<NumericalValue>> + 'a {
self.column_writer.operation_iterator(arena, buffer)
}
}
#[derive(Copy, Clone, Default)]
pub(crate) struct StrColumnWriter {
pub(crate) dictionary_id: u32,
pub(crate) column_writer: ColumnWriter,
}
impl StrColumnWriter {
pub(crate) fn with_dictionary_id(dictionary_id: u32) -> StrColumnWriter {
StrColumnWriter {
dictionary_id,
column_writer: Default::default(),
}
}
pub(crate) fn record_bytes(
&mut self,
doc: DocId,
bytes: &[u8],
dictionaries: &mut [DictionaryBuilder],
arena: &mut MemoryArena,
) {
let unordered_id = dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes);
self.column_writer.record(doc, unordered_id, arena);
}
pub(super) fn operation_iterator<'a>(
&self,
arena: &MemoryArena,
byte_buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<UnorderedId>> + 'a {
self.column_writer.operation_iterator(arena, byte_buffer)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_delta_with_last_doc() {
assert_eq!(delta_with_last_doc(None, 0u32), DocumentStep::Next);
assert_eq!(delta_with_last_doc(None, 1u32), DocumentStep::Skipped);
assert_eq!(delta_with_last_doc(None, 2u32), DocumentStep::Skipped);
assert_eq!(delta_with_last_doc(Some(0u32), 0u32), DocumentStep::Same);
assert_eq!(delta_with_last_doc(Some(1u32), 1u32), DocumentStep::Same);
assert_eq!(delta_with_last_doc(Some(1u32), 2u32), DocumentStep::Next);
assert_eq!(delta_with_last_doc(Some(1u32), 3u32), DocumentStep::Skipped);
assert_eq!(delta_with_last_doc(Some(1u32), 4u32), DocumentStep::Skipped);
}
#[track_caller]
fn test_column_writer_coercion_iter_aux(
values: impl Iterator<Item = NumericalValue>,
expected_numerical_type: NumericalType,
) {
let mut compatible_numerical_types = CompatibleNumericalTypes::default();
for value in values {
compatible_numerical_types.accept_value(value);
}
assert_eq!(
compatible_numerical_types.to_numerical_type(),
expected_numerical_type
);
}
#[track_caller]
fn test_column_writer_coercion_aux(
values: &[NumericalValue],
expected_numerical_type: NumericalType,
) {
test_column_writer_coercion_iter_aux(values.iter().copied(), expected_numerical_type);
test_column_writer_coercion_iter_aux(values.iter().rev().copied(), expected_numerical_type);
}
#[test]
fn test_column_writer_coercion() {
test_column_writer_coercion_aux(&[], NumericalType::I64);
test_column_writer_coercion_aux(&[1i64.into()], NumericalType::I64);
test_column_writer_coercion_aux(&[1u64.into()], NumericalType::I64);
// We don't detect exact integer at the moment. We could!
test_column_writer_coercion_aux(&[1f64.into()], NumericalType::F64);
test_column_writer_coercion_aux(&[u64::MAX.into()], NumericalType::U64);
test_column_writer_coercion_aux(&[(i64::MAX as u64).into()], NumericalType::U64);
test_column_writer_coercion_aux(&[(1u64 << 63).into()], NumericalType::U64);
test_column_writer_coercion_aux(&[1i64.into(), 1u64.into()], NumericalType::I64);
test_column_writer_coercion_aux(&[u64::MAX.into(), (-1i64).into()], NumericalType::F64);
}
}

View File

@@ -1,51 +1,196 @@
mod column_operation;
mod column_writers;
mod serializer;
mod value_index;
use std::io;
use std::io::{self, Write};
use column_operation::ColumnOperation;
use common::CountingWriter;
use fastfield_codecs::serialize::ValueIndexInfo;
use fastfield_codecs::{Column, MonotonicallyMappableToU64, VecColumn};
use serializer::ColumnarSerializer;
use stacker::{Addr, ArenaHashMap, MemoryArena};
use ordered_float::NotNan;
use stacker::{Addr, ArenaHashMap, ExpUnrolledLinkedList, MemoryArena};
use crate::column_type_header::{ColumnType, ColumnTypeAndCardinality, ColumnTypeCategory};
use crate::dictionary::{DictionaryBuilder, TermIdMapping, UnorderedId};
use crate::column_type_header::{ColumnType, ColumnTypeAndCardinality};
use crate::dictionary::{DictionaryBuilder, IdMapping, UnorderedId};
use crate::value::{Coerce, NumericalType, NumericalValue};
use crate::writer::column_writers::{ColumnWriter, NumericalColumnWriter, StrColumnWriter};
use crate::writer::column_operation::SymbolValue;
use crate::writer::value_index::{IndexBuilder, SpareIndexBuilders};
use crate::{Cardinality, DocId};
use crate::{Cardinality, ColumnarSerializer, DocId};
/// This is a set of buffers that are used to temporarily write the values into before passing them
/// to the fast field codecs.
#[derive(Default)]
struct SpareBuffers {
value_index_builders: SpareIndexBuilders,
i64_values: Vec<i64>,
u64_values: Vec<u64>,
f64_values: Vec<f64>,
bool_values: Vec<bool>,
#[derive(Copy, Clone, Default)]
struct ColumnWriter {
// Detected cardinality of the column so far.
cardinality: Cardinality,
// Last document inserted.
// None if no doc has been added yet.
last_doc_opt: Option<u32>,
// Buffer containing the serialized values.
values: ExpUnrolledLinkedList,
}
#[derive(Clone, Copy, Default)]
pub struct NumericalColumnWriter {
compatible_numerical_types: CompatibleNumericalTypes,
column_writer: ColumnWriter,
}
#[derive(Clone, Copy)]
struct CompatibleNumericalTypes {
all_values_within_i64_range: bool,
all_values_within_u64_range: bool,
}
impl Default for CompatibleNumericalTypes {
fn default() -> CompatibleNumericalTypes {
CompatibleNumericalTypes {
all_values_within_i64_range: true,
all_values_within_u64_range: true,
}
}
}
impl CompatibleNumericalTypes {
pub fn accept_value(&mut self, numerical_value: NumericalValue) {
match numerical_value {
NumericalValue::I64(val_i64) => {
let value_within_u64_range = val_i64 >= 0i64;
self.all_values_within_u64_range &= value_within_u64_range;
}
NumericalValue::U64(val_u64) => {
let value_within_i64_range = val_u64 < i64::MAX as u64;
self.all_values_within_i64_range &= value_within_i64_range;
}
NumericalValue::F64(_) => {
self.all_values_within_i64_range = false;
self.all_values_within_u64_range = false;
}
}
}
pub fn to_numerical_type(self) -> NumericalType {
if self.all_values_within_i64_range {
NumericalType::I64
} else if self.all_values_within_u64_range {
NumericalType::U64
} else {
NumericalType::F64
}
}
}
impl NumericalColumnWriter {
pub fn record_numerical_value(
&mut self,
doc: DocId,
value: NumericalValue,
arena: &mut MemoryArena,
) {
self.compatible_numerical_types.accept_value(value);
self.column_writer.record(doc, value, arena);
}
}
impl ColumnWriter {
fn symbol_iterator<'a, V: SymbolValue>(
&self,
arena: &MemoryArena,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<V>> + 'a {
buffer.clear();
self.values.read_to_end(arena, buffer);
let mut cursor: &[u8] = &buffer[..];
std::iter::from_fn(move || {
if cursor.is_empty() {
return None;
}
let symbol = ColumnOperation::deserialize(&mut cursor)
.expect("Failed to deserialize symbol from in-memory. This should never happen.");
Some(symbol)
})
}
fn delta_with_last_doc(&self, doc: DocId) -> u32 {
self.last_doc_opt
.map(|last_doc| doc - last_doc)
.unwrap_or(doc + 1u32)
}
/// Records a change of the document being recorded.
///
/// This function will also update the cardinality of the column
/// if necessary.
fn record(&mut self, doc: DocId, value: NumericalValue, arena: &mut MemoryArena) {
// Difference between `doc` and the last doc.
match self.delta_with_last_doc(doc) {
0 => {
// This is the last encounterred document.
self.cardinality = Cardinality::Multivalued;
}
1 => {
self.last_doc_opt = Some(doc);
self.write_symbol::<NumericalValue>(ColumnOperation::NewDoc(doc), arena);
}
_ => {
self.cardinality = self.cardinality.max(Cardinality::Optional);
self.last_doc_opt = Some(doc);
self.write_symbol::<NumericalValue>(ColumnOperation::NewDoc(doc), arena);
}
}
self.write_symbol(ColumnOperation::Value(value), arena);
}
// Get the cardinality.
// The overall number of docs in the column is necessary to
// deal with the case where the all docs contain 1 value, except some documents
// at the end of the column.
fn get_cardinality(&self, num_docs: DocId) -> Cardinality {
if self.delta_with_last_doc(num_docs) > 1 {
self.cardinality.max(Cardinality::Optional)
} else {
self.cardinality
}
}
fn write_symbol<V: SymbolValue>(
&mut self,
symbol: ColumnOperation<V>,
arena: &mut MemoryArena,
) {
self.values
.writer(arena)
.extend_from_slice(symbol.serialize().as_slice());
}
}
#[derive(Copy, Clone, Default)]
pub struct BytesColumnWriter {
dictionary_id: u32,
column_writer: ColumnWriter,
}
impl BytesColumnWriter {
pub fn with_dictionary_id(dictionary_id: u32) -> BytesColumnWriter {
BytesColumnWriter {
dictionary_id,
column_writer: Default::default(),
}
}
pub fn record_bytes(
&mut self,
doc: DocId,
bytes: &[u8],
dictionaries: &mut [DictionaryBuilder],
arena: &mut MemoryArena,
) {
let unordered_id = dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes);
let numerical_value = NumericalValue::U64(unordered_id.0 as u64);
self.column_writer.record(doc, numerical_value, arena);
}
}
/// Makes it possible to create a new columnar.
///
/// ```rust
/// use tantivy_columnar::ColumnarWriter;
///
/// let mut columnar_writer = ColumnarWriter::default();
/// columnar_writer.record_str(0u32 /* doc id */, "product_name", "Red backpack");
/// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10u64);
/// columnar_writer.record_str(1u32 /* doc id */, "product_name", "Apple");
/// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10.5f64); //< uh oh we ended up mixing integer and floats.
/// let mut wrt: Vec<u8> = Vec::new();
/// columnar_writer.serialize(2u32, &mut wrt).unwrap();
/// ```
pub struct ColumnarWriter {
numerical_field_hash_map: ArenaHashMap,
bool_field_hash_map: ArenaHashMap,
bytes_field_hash_map: ArenaHashMap,
arena: MemoryArena,
// Dictionaries used to store dictionary-encoded values.
@@ -53,11 +198,19 @@ pub struct ColumnarWriter {
buffers: SpareBuffers,
}
#[derive(Default)]
struct SpareBuffers {
byte_buffer: Vec<u8>,
value_index_builders: SpareIndexBuilders,
i64_values: Vec<i64>,
u64_values: Vec<u64>,
f64_values: Vec<ordered_float::NotNan<f64>>,
}
impl Default for ColumnarWriter {
fn default() -> Self {
ColumnarWriter {
numerical_field_hash_map: ArenaHashMap::new(10_000),
bool_field_hash_map: ArenaHashMap::new(10_000),
bytes_field_hash_map: ArenaHashMap::new(10_000),
dictionaries: Vec::new(),
arena: MemoryArena::default(),
@@ -66,213 +219,186 @@ impl Default for ColumnarWriter {
}
}
#[derive(Copy, Clone, Ord, PartialOrd, Eq, PartialEq, Debug)]
enum BytesOrNumerical {
Bytes,
Numerical,
}
impl ColumnarWriter {
pub fn record_numerical<T: Into<NumericalValue> + Copy>(
&mut self,
doc: DocId,
column_name: &str,
numerical_value: T,
) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
pub fn record_numerical(&mut self, doc: DocId, key: &[u8], numerical_value: NumericalValue) {
let (hash_map, arena) = (&mut self.numerical_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<NumericalColumnWriter>| {
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
column.record_numerical_value(doc, numerical_value.into(), arena);
column
},
);
hash_map.mutate_or_create(key, |column_opt: Option<NumericalColumnWriter>| {
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
column.record_numerical_value(doc, numerical_value, arena);
column
});
}
pub fn record_bool(&mut self, doc: DocId, column_name: &str, val: bool) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
let (hash_map, arena) = (&mut self.bool_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(doc, val, arena);
column
},
);
}
pub fn record_str(&mut self, doc: DocId, column_name: &str, value: &str) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
pub fn record_bytes(&mut self, doc: DocId, key: &[u8], value: &[u8]) {
let (hash_map, arena, dictionaries) = (
&mut self.bytes_field_hash_map,
&mut self.arena,
&mut self.dictionaries,
);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<StrColumnWriter>| {
let mut column: StrColumnWriter = column_opt.unwrap_or_else(|| {
// Each column has its own dictionary
let dictionary_id = dictionaries.len() as u32;
dictionaries.push(DictionaryBuilder::default());
StrColumnWriter::with_dictionary_id(dictionary_id)
});
column.record_bytes(doc, value.as_bytes(), dictionaries, arena);
column
},
);
hash_map.mutate_or_create(key, |column_opt: Option<BytesColumnWriter>| {
let mut column: BytesColumnWriter = column_opt.unwrap_or_else(|| {
let dictionary_id = dictionaries.len() as u32;
dictionaries.push(DictionaryBuilder::default());
BytesColumnWriter::with_dictionary_id(dictionary_id)
});
column.record_bytes(doc, value, dictionaries, arena);
column
});
}
pub fn serialize(&mut self, num_docs: DocId, wrt: &mut dyn io::Write) -> io::Result<()> {
let mut serializer = ColumnarSerializer::new(wrt);
let mut field_columns: Vec<(&[u8], ColumnTypeCategory, Addr)> = self
pub fn serialize<W: io::Write>(
&mut self,
num_docs: DocId,
mut serializer: ColumnarSerializer<W>,
) -> io::Result<()> {
let mut field_columns: Vec<(&[u8], BytesOrNumerical, Addr)> = self
.numerical_field_hash_map
.iter()
.map(|(term, addr, _)| (term, ColumnTypeCategory::Numerical, addr))
.map(|(term, addr, _)| (term, BytesOrNumerical::Numerical, addr))
.collect();
field_columns.extend(
self.bytes_field_hash_map
.iter()
.map(|(term, addr, _)| (term, ColumnTypeCategory::Str, addr)),
.map(|(term, addr, _)| (term, BytesOrNumerical::Bytes, addr)),
);
field_columns.extend(
self.bool_field_hash_map
.iter()
.map(|(term, addr, _)| (term, ColumnTypeCategory::Bool, addr)),
);
field_columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
let mut key_buffer = Vec::new();
field_columns.sort_unstable_by_key(|(key, col_type, _)| (*key, *col_type));
let (arena, buffers, dictionaries) = (&self.arena, &mut self.buffers, &self.dictionaries);
let mut symbol_byte_buffer: Vec<u8> = Vec::new();
for (column_name, bytes_or_numerical, addr) in field_columns {
match bytes_or_numerical {
ColumnTypeCategory::Bool => {
let column_writer: ColumnWriter = self.bool_field_hash_map.read(addr);
let cardinality = column_writer.get_cardinality(num_docs);
let column_type_and_cardinality = ColumnTypeAndCardinality {
cardinality,
typ: ColumnType::Bool,
};
let mut column_serializer =
serializer.serialize_column(column_name, column_type_and_cardinality);
serialize_bool_column(
cardinality,
num_docs,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
buffers,
&mut column_serializer,
)?;
}
ColumnTypeCategory::Str => {
let str_column_writer: StrColumnWriter = self.bytes_field_hash_map.read(addr);
for (key, bytes_or_numerical, addr) in field_columns {
let wrt = serializer.wrt();
let start_offset = wrt.written_bytes();
let column_type_and_cardinality: ColumnTypeAndCardinality =
match bytes_or_numerical {
BytesOrNumerical::Bytes => {
let BytesColumnWriter { dictionary_id, column_writer } =
self.bytes_field_hash_map.read(addr);
let dictionary_builder =
&dictionaries[str_column_writer.dictionary_id as usize];
let cardinality = str_column_writer.column_writer.get_cardinality(num_docs);
let column_type_and_cardinality = ColumnTypeAndCardinality {
cardinality,
typ: ColumnType::Bytes,
};
let mut column_serializer =
serializer.serialize_column(column_name, column_type_and_cardinality);
&dictionaries[dictionary_id as usize];
serialize_bytes_column(
cardinality,
&column_writer,
num_docs,
dictionary_builder,
str_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
arena,
buffers,
&mut column_serializer,
wrt,
)?;
ColumnTypeAndCardinality {
cardinality: column_writer.get_cardinality(num_docs),
typ: ColumnType::Bytes,
}
}
ColumnTypeCategory::Numerical => {
let numerical_column_writer: NumericalColumnWriter =
BytesOrNumerical::Numerical => {
let NumericalColumnWriter { compatible_numerical_types, column_writer } =
self.numerical_field_hash_map.read(addr);
let (numerical_type, cardinality) =
numerical_column_writer.column_type_and_cardinality(num_docs);
let column_type_and_cardinality = ColumnTypeAndCardinality {
cardinality,
typ: ColumnType::Numerical(numerical_type),
};
let mut column_serializer =
serializer.serialize_column(column_name, column_type_and_cardinality);
let cardinality = column_writer.get_cardinality(num_docs);
let numerical_type = compatible_numerical_types.to_numerical_type();
serialize_numerical_column(
cardinality,
num_docs,
numerical_type,
numerical_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
&column_writer,
num_docs,
arena,
buffers,
&mut column_serializer,
wrt,
)?;
ColumnTypeAndCardinality {
cardinality,
typ: ColumnType::Numerical(numerical_type),
}
}
};
let end_offset = wrt.written_bytes();
let key_with_type = prepare_key(key, column_type_and_cardinality, &mut key_buffer);
serializer.record_column_offsets(key_with_type, start_offset..end_offset)?;
}
serializer.finalize()?;
Ok(())
}
}
fn serialize_bytes_column(
cardinality: Cardinality,
/// Returns a key consisting of the concatenation of the key and the column_type_and_cardinality
/// code.
fn prepare_key<'a>(
key: &[u8],
column_type_cardinality: ColumnTypeAndCardinality,
buffer: &'a mut Vec<u8>,
) -> &'a [u8] {
buffer.clear();
buffer.extend_from_slice(key);
buffer.push(0u8);
buffer.push(column_type_cardinality.to_code());
&buffer[..]
}
fn serialize_bytes_column<W: io::Write>(
column_writer: &ColumnWriter,
num_docs: DocId,
dictionary_builder: &DictionaryBuilder,
operation_it: impl Iterator<Item = ColumnOperation<UnorderedId>>,
arena: &MemoryArena,
buffers: &mut SpareBuffers,
wrt: impl io::Write,
wrt: &mut CountingWriter<W>,
) -> io::Result<()> {
let start_offset = wrt.written_bytes();
let id_mapping: IdMapping = dictionary_builder.serialize(wrt)?;
let dictionary_num_bytes: u32 = (wrt.written_bytes() - start_offset) as u32;
let cardinality = column_writer.get_cardinality(num_docs);
let SpareBuffers {
byte_buffer,
value_index_builders,
u64_values,
..
} = buffers;
let mut counting_writer = CountingWriter::wrap(wrt);
let term_id_mapping: TermIdMapping = dictionary_builder.serialize(&mut counting_writer)?;
let dictionary_num_bytes: u32 = counting_writer.written_bytes() as u32;
let mut wrt = counting_writer.finish();
let operation_iterator = operation_it.map(|symbol: ColumnOperation<UnorderedId>| {
// We map unordered ids to ordered ids.
match symbol {
ColumnOperation::Value(unordered_id) => {
let ordered_id = term_id_mapping.to_ord(unordered_id);
ColumnOperation::Value(ordered_id.0 as u64)
let symbol_iterator = column_writer
.symbol_iterator(arena, byte_buffer)
.map(|symbol: ColumnOperation<UnorderedId>| {
// We map unordered ids to ordered ids.
match symbol {
ColumnOperation::Value(unordered_id) => {
let ordered_id = id_mapping.to_ord(unordered_id);
ColumnOperation::Value(ordered_id.0 as u64)
}
ColumnOperation::NewDoc(doc) => ColumnOperation::NewDoc(doc),
}
ColumnOperation::NewDoc(doc) => ColumnOperation::NewDoc(doc),
}
});
});
serialize_column(
operation_iterator,
symbol_iterator,
cardinality,
num_docs,
value_index_builders,
u64_values,
&mut wrt,
wrt,
)?;
wrt.write_all(&dictionary_num_bytes.to_le_bytes()[..])?;
Ok(())
}
fn serialize_numerical_column(
fn serialize_numerical_column<W: io::Write>(
cardinality: Cardinality,
num_docs: DocId,
numerical_type: NumericalType,
op_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
column_writer: &ColumnWriter,
num_docs: DocId,
arena: &MemoryArena,
buffers: &mut SpareBuffers,
wrt: &mut impl io::Write,
wrt: &mut W,
) -> io::Result<()> {
let SpareBuffers {
byte_buffer,
value_index_builders,
u64_values,
i64_values,
f64_values,
..
} = buffers;
let symbol_iterator = column_writer.symbol_iterator(arena, byte_buffer);
match numerical_type {
NumericalType::I64 => {
serialize_column(
coerce_numerical_symbol::<i64>(op_iterator),
coerce_numerical_symbol::<i64>(symbol_iterator),
cardinality,
num_docs,
value_index_builders,
@@ -282,7 +408,7 @@ fn serialize_numerical_column(
}
NumericalType::U64 => {
serialize_column(
coerce_numerical_symbol::<u64>(op_iterator),
coerce_numerical_symbol::<u64>(symbol_iterator),
cardinality,
num_docs,
value_index_builders,
@@ -292,7 +418,7 @@ fn serialize_numerical_column(
}
NumericalType::F64 => {
serialize_column(
coerce_numerical_symbol::<f64>(op_iterator),
coerce_numerical_symbol::<NotNan<f64>>(symbol_iterator),
cardinality,
num_docs,
value_index_builders,
@@ -304,75 +430,52 @@ fn serialize_numerical_column(
Ok(())
}
fn serialize_bool_column(
cardinality: Cardinality,
num_docs: DocId,
column_operations_it: impl Iterator<Item = ColumnOperation<bool>>,
buffers: &mut SpareBuffers,
wrt: &mut impl io::Write,
) -> io::Result<()> {
let SpareBuffers {
value_index_builders,
bool_values,
..
} = buffers;
serialize_column(
column_operations_it,
cardinality,
num_docs,
value_index_builders,
bool_values,
wrt,
)?;
Ok(())
}
fn serialize_column<
T: Copy + Default + std::fmt::Debug + Send + Sync + MonotonicallyMappableToU64 + PartialOrd,
T: Copy + Ord + Default + Send + Sync + MonotonicallyMappableToU64,
W: io::Write,
>(
op_iterator: impl Iterator<Item = ColumnOperation<T>>,
symbol_iterator: impl Iterator<Item = ColumnOperation<T>>,
cardinality: Cardinality,
num_docs: DocId,
value_index_builders: &mut SpareIndexBuilders,
values: &mut Vec<T>,
mut wrt: impl io::Write,
wrt: &mut W,
) -> io::Result<()>
where
for<'a> VecColumn<'a, T>: Column<T>,
{
values.clear();
match cardinality {
Cardinality::Required => {
consume_operation_iterator(
op_iterator,
consume_symbol_iterator(
symbol_iterator,
value_index_builders.borrow_required_index_builder(),
values,
);
fastfield_codecs::serialize(
VecColumn::from(&values[..]),
&mut wrt,
wrt,
&fastfield_codecs::ALL_CODEC_TYPES[..],
)?;
}
Cardinality::Optional => {
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
consume_operation_iterator(op_iterator, optional_index_builder, values);
consume_symbol_iterator(symbol_iterator, optional_index_builder, values);
let optional_index = optional_index_builder.finish(num_docs);
fastfield_codecs::serialize::serialize_new(
ValueIndexInfo::SingleValue(Box::new(optional_index)),
VecColumn::from(&values[..]),
&mut wrt,
wrt,
&fastfield_codecs::ALL_CODEC_TYPES[..],
)?;
}
Cardinality::Multivalued => {
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
consume_symbol_iterator(symbol_iterator, multivalued_index_builder, values);
let multivalued_index = multivalued_index_builder.finish(num_docs);
fastfield_codecs::serialize::serialize_new(
ValueIndexInfo::MultiValue(Box::new(multivalued_index)),
VecColumn::from(&values[..]),
&mut wrt,
wrt,
&fastfield_codecs::ALL_CODEC_TYPES[..],
)?;
}
@@ -381,10 +484,10 @@ where
}
fn coerce_numerical_symbol<T>(
operation_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
symbol_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
) -> impl Iterator<Item = ColumnOperation<T>>
where T: Coerce {
operation_iterator.map(|symbol| match symbol {
symbol_iterator.map(|symbol| match symbol {
ColumnOperation::NewDoc(doc) => ColumnOperation::NewDoc(doc),
ColumnOperation::Value(numerical_value) => {
ColumnOperation::Value(Coerce::coerce(numerical_value))
@@ -392,12 +495,12 @@ where T: Coerce {
})
}
fn consume_operation_iterator<T: std::fmt::Debug, TIndexBuilder: IndexBuilder>(
operation_iterator: impl Iterator<Item = ColumnOperation<T>>,
fn consume_symbol_iterator<T, TIndexBuilder: IndexBuilder>(
symbol_iterator: impl Iterator<Item = ColumnOperation<T>>,
index_builder: &mut TIndexBuilder,
values: &mut Vec<T>,
) {
for symbol in operation_iterator {
for symbol in symbol_iterator {
match symbol {
ColumnOperation::NewDoc(doc) => {
index_builder.record_doc(doc);
@@ -412,24 +515,42 @@ fn consume_operation_iterator<T: std::fmt::Debug, TIndexBuilder: IndexBuilder>(
#[cfg(test)]
mod tests {
use column_operation::ColumnOperation;
use ordered_float::NotNan;
use stacker::MemoryArena;
use super::*;
use crate::value::NumericalValue;
use super::prepare_key;
use crate::column_type_header::{ColumnType, ColumnTypeAndCardinality};
use crate::value::{NumericalType, NumericalValue};
use crate::writer::column_operation::ColumnOperation;
use crate::writer::CompatibleNumericalTypes;
use crate::Cardinality;
#[test]
fn test_prepare_key_bytes() {
let mut buffer: Vec<u8> = b"somegarbage".to_vec();
let column_type_and_cardinality = ColumnTypeAndCardinality {
typ: ColumnType::Bytes,
cardinality: Cardinality::Optional,
};
let prepared_key = prepare_key(b"root\0child", column_type_and_cardinality, &mut buffer);
assert_eq!(prepared_key.len(), 12);
assert_eq!(&prepared_key[..10], b"root\0child");
assert_eq!(prepared_key[10], 0u8);
assert_eq!(prepared_key[11], column_type_and_cardinality.to_code());
}
#[test]
fn test_column_writer_required_simple() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(0u32, NumericalValue::from(14i64), &mut arena);
column_writer.record(1u32, NumericalValue::from(15i64), &mut arena);
column_writer.record(2u32, NumericalValue::from(-16i64), &mut arena);
column_writer.record(0u32, 14i64.into(), &mut arena);
column_writer.record(1u32, 15i64.into(), &mut arena);
column_writer.record(2u32, (-16i64).into(), &mut arena);
assert_eq!(column_writer.get_cardinality(3), Cardinality::Required);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.symbol_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 6);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -453,12 +574,12 @@ mod tests {
fn test_column_writer_optional_cardinality_missing_first() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(1u32, NumericalValue::from(15i64), &mut arena);
column_writer.record(2u32, NumericalValue::from(-16i64), &mut arena);
column_writer.record(1u32, 15i64.into(), &mut arena);
column_writer.record(2u32, (-16i64).into(), &mut arena);
assert_eq!(column_writer.get_cardinality(3), Cardinality::Optional);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.symbol_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 4);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
@@ -477,11 +598,11 @@ mod tests {
fn test_column_writer_optional_cardinality_missing_last() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(0u32, NumericalValue::from(15i64), &mut arena);
column_writer.record(0u32, 15i64.into(), &mut arena);
assert_eq!(column_writer.get_cardinality(2), Cardinality::Optional);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.symbol_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 2);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -495,12 +616,12 @@ mod tests {
fn test_column_writer_multivalued() {
let mut arena = MemoryArena::default();
let mut column_writer = super::ColumnWriter::default();
column_writer.record(0u32, NumericalValue::from(16i64), &mut arena);
column_writer.record(0u32, NumericalValue::from(17i64), &mut arena);
column_writer.record(0u32, 16i64.into(), &mut arena);
column_writer.record(0u32, 17i64.into(), &mut arena);
assert_eq!(column_writer.get_cardinality(1), Cardinality::Multivalued);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&mut arena, &mut buffer)
.symbol_iterator(&mut arena, &mut buffer)
.collect();
assert_eq!(symbols.len(), 3);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -513,4 +634,42 @@ mod tests {
ColumnOperation::Value(NumericalValue::I64(17i64))
));
}
#[track_caller]
fn test_column_writer_coercion_iter_aux(
values: impl Iterator<Item = NumericalValue>,
expected_numerical_type: NumericalType,
) {
let mut compatible_numerical_types = CompatibleNumericalTypes::default();
for value in values {
compatible_numerical_types.accept_value(value);
}
assert_eq!(
compatible_numerical_types.to_numerical_type(),
expected_numerical_type
);
}
#[track_caller]
fn test_column_writer_coercion_aux(
values: &[NumericalValue],
expected_numerical_type: NumericalType,
) {
test_column_writer_coercion_iter_aux(values.iter().copied(), expected_numerical_type);
test_column_writer_coercion_iter_aux(values.iter().rev().copied(), expected_numerical_type);
}
#[test]
fn test_column_writer_coercion() {
test_column_writer_coercion_aux(&[], NumericalType::I64);
test_column_writer_coercion_aux(&[1i64.into()], NumericalType::I64);
test_column_writer_coercion_aux(&[1u64.into()], NumericalType::I64);
// We don't detect exact integer at the moment. We could!
test_column_writer_coercion_aux(&[NotNan::new(1f64).unwrap().into()], NumericalType::F64);
test_column_writer_coercion_aux(&[u64::MAX.into()], NumericalType::U64);
test_column_writer_coercion_aux(&[(i64::MAX as u64).into()], NumericalType::U64);
test_column_writer_coercion_aux(&[(1u64 << 63).into()], NumericalType::U64);
test_column_writer_coercion_aux(&[1i64.into(), 1u64.into()], NumericalType::I64);
test_column_writer_coercion_aux(&[u64::MAX.into(), (-1i64).into()], NumericalType::F64);
}
}

View File

@@ -1,116 +0,0 @@
use std::io;
use std::io::Write;
use common::CountingWriter;
use sstable::value::RangeValueWriter;
use sstable::RangeSSTable;
use crate::column_type_header::ColumnTypeAndCardinality;
pub struct ColumnarSerializer<W: io::Write> {
wrt: CountingWriter<W>,
sstable_range: sstable::Writer<Vec<u8>, RangeValueWriter>,
prepare_key_buffer: Vec<u8>,
}
/// Returns a key consisting of the concatenation of the key and the column_type_and_cardinality
/// code.
fn prepare_key(
key: &[u8],
column_type_cardinality: ColumnTypeAndCardinality,
buffer: &mut Vec<u8>,
) {
buffer.clear();
buffer.extend_from_slice(key);
buffer.push(0u8);
buffer.push(column_type_cardinality.to_code());
}
impl<W: io::Write> ColumnarSerializer<W> {
pub(crate) fn new(wrt: W) -> ColumnarSerializer<W> {
let sstable_range: sstable::Writer<Vec<u8>, RangeValueWriter> =
sstable::Dictionary::<RangeSSTable>::builder(Vec::with_capacity(100_000)).unwrap();
ColumnarSerializer {
wrt: CountingWriter::wrap(wrt),
sstable_range,
prepare_key_buffer: Vec::new(),
}
}
pub fn serialize_column<'a>(
&'a mut self,
column_name: &[u8],
column_type_cardinality: ColumnTypeAndCardinality,
) -> impl io::Write + 'a {
let start_offset = self.wrt.written_bytes();
prepare_key(
column_name,
column_type_cardinality,
&mut self.prepare_key_buffer,
);
ColumnSerializer {
columnar_serializer: self,
start_offset,
}
}
pub(crate) fn finalize(mut self) -> io::Result<()> {
let sstable_bytes: Vec<u8> = self.sstable_range.finish()?;
let sstable_num_bytes: u64 = sstable_bytes.len() as u64;
self.wrt.write_all(&sstable_bytes)?;
self.wrt.write_all(&sstable_num_bytes.to_le_bytes()[..])?;
Ok(())
}
}
struct ColumnSerializer<'a, W: io::Write> {
columnar_serializer: &'a mut ColumnarSerializer<W>,
start_offset: u64,
}
impl<'a, W: io::Write> Drop for ColumnSerializer<'a, W> {
fn drop(&mut self) {
let end_offset: u64 = self.columnar_serializer.wrt.written_bytes();
let byte_range = self.start_offset..end_offset;
self.columnar_serializer.sstable_range.insert_cannot_fail(
&self.columnar_serializer.prepare_key_buffer[..],
&byte_range,
);
self.columnar_serializer.prepare_key_buffer.clear();
}
}
impl<'a, W: io::Write> io::Write for ColumnSerializer<'a, W> {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
self.columnar_serializer.wrt.write(buf)
}
fn flush(&mut self) -> io::Result<()> {
self.columnar_serializer.wrt.flush()
}
fn write_all(&mut self, buf: &[u8]) -> io::Result<()> {
self.columnar_serializer.wrt.write_all(buf)
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::column_type_header::ColumnType;
use crate::Cardinality;
#[test]
fn test_prepare_key_bytes() {
let mut buffer: Vec<u8> = b"somegarbage".to_vec();
let column_type_and_cardinality = ColumnTypeAndCardinality {
typ: ColumnType::Bytes,
cardinality: Cardinality::Optional,
};
prepare_key(b"root\0child", column_type_and_cardinality, &mut buffer);
assert_eq!(buffer.len(), 12);
assert_eq!(&buffer[..10], b"root\0child");
assert_eq!(buffer[10], 0u8);
assert_eq!(buffer[11], column_type_and_cardinality.to_code());
}
}

View File

@@ -5,7 +5,7 @@ use crate::DocId;
/// The `IndexBuilder` interprets a sequence of
/// calls of the form:
/// (record_doc,record_value+)*
/// and can then serialize the results into an index to associate docids with their value[s].
/// and can then serialize the results into an index.
///
/// It has different implementation depending on whether the
/// cardinality is required, optional, or multivalued.
@@ -30,7 +30,6 @@ pub struct OptionalIndexBuilder {
}
struct SingleValueArrayIndex<'a> {
// DocIds with a value. DocIds are strictly increasing
docs: &'a [DocId],
num_docs: DocId,
}
@@ -84,8 +83,7 @@ impl IndexBuilder for OptionalIndexBuilder {
#[derive(Default)]
pub struct MultivaluedIndexBuilder {
// TODO should we switch to `start_offset`?
// contains the num values so far for each `DocId`.
end_offsets: Vec<DocId>,
end_values: Vec<DocId>,
total_num_vals_seen: u32,
}
@@ -113,22 +111,22 @@ impl<'a> MultiValueIndexInfo for MultivaluedValueArrayIndex<'a> {
impl MultivaluedIndexBuilder {
pub fn finish(&mut self, num_docs: DocId) -> impl MultiValueIndexInfo + '_ {
self.end_offsets
self.end_values
.resize(num_docs as usize, self.total_num_vals_seen);
MultivaluedValueArrayIndex {
end_offsets: &self.end_offsets[..],
end_offsets: &self.end_values[..],
}
}
fn reset(&mut self) {
self.end_offsets.clear();
self.end_values.clear();
self.total_num_vals_seen = 0;
}
}
impl IndexBuilder for MultivaluedIndexBuilder {
fn record_doc(&mut self, doc: DocId) {
self.end_offsets
self.end_values
.resize(doc as usize, self.total_num_vals_seen);
}

View File

@@ -24,11 +24,8 @@ pub trait FileHandle: 'static + Send + Sync + HasLen + fmt::Debug {
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes>;
#[doc(hidden)]
async fn read_bytes_async(&self, _byte_range: Range<usize>) -> io::Result<OwnedBytes> {
Err(io::Error::new(
io::ErrorKind::Unsupported,
"Async read is not supported.",
))
async fn read_bytes_async(&self, byte_range: Range<usize>) -> io::Result<OwnedBytes> {
self.read_bytes(byte_range)
}
}
@@ -39,6 +36,7 @@ impl FileHandle for &'static [u8] {
Ok(OwnedBytes::new(bytes))
}
#[cfg(feature = "quickwit")]
async fn read_bytes_async(&self, byte_range: Range<usize>) -> io::Result<OwnedBytes> {
Ok(self.read_bytes(byte_range)?)
}
@@ -67,16 +65,7 @@ impl fmt::Debug for FileSlice {
}
}
/// Takes a range, a `RangeBounds` object, and returns
/// a `Range` that corresponds to the relative application of the
/// `RangeBounds` object to the original `Range`.
///
/// For instance, combine_ranges(`[2..11)`, `[5..7]`) returns `[7..10]`
/// as it reads, what is the sub-range that starts at the 5 element of
/// `[2..11)` and ends at the 9th element included.
///
/// This function panics, if the result would suggest something outside
/// of the bounds of the original range.
#[inline]
fn combine_ranges<R: RangeBounds<usize>>(orig_range: Range<usize>, rel_range: R) -> Range<usize> {
let start: usize = orig_range.start
+ match rel_range.start_bound().cloned() {
@@ -224,6 +213,7 @@ impl FileHandle for FileSlice {
self.read_bytes_slice(range)
}
#[cfg(feature = "quickwit")]
async fn read_bytes_async(&self, byte_range: Range<usize>) -> io::Result<OwnedBytes> {
self.read_bytes_slice_async(byte_range).await
}
@@ -241,15 +231,16 @@ impl FileHandle for OwnedBytes {
Ok(self.slice(range))
}
#[cfg(feature = "quickwit")]
async fn read_bytes_async(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
self.read_bytes(range)
let bytes = self.read_bytes(range)?;
Ok(bytes)
}
}
#[cfg(test)]
mod tests {
use std::io;
use std::ops::Bound;
use std::sync::Arc;
use super::{FileHandle, FileSlice};
@@ -332,11 +323,6 @@ mod tests {
assert_eq!(combine_ranges(1..3, 1..), 2..3);
assert_eq!(combine_ranges(1..4, ..2), 1..3);
assert_eq!(combine_ranges(3..10, 2..5), 5..8);
assert_eq!(combine_ranges(2..11, 5..=7), 7..10);
assert_eq!(
combine_ranges(2..11, (Bound::Excluded(5), Bound::Unbounded)),
8..11
);
}
#[test]

View File

@@ -1,166 +0,0 @@
use std::cell::RefCell;
use std::iter::Peekable;
use std::rc::Rc;
pub trait GroupByIteratorExtended: Iterator {
/// Return an `Iterator` that groups iterator elements. Consecutive elements that map to the
/// same key are assigned to the same group.
///
/// The returned Iterator item is `(K, impl Iterator)`, where Iterator are the items of the
/// group.
///
/// ```
/// use tantivy_common::GroupByIteratorExtended;
///
/// // group data into blocks of larger than zero or not.
/// let data: Vec<i32> = vec![1, 3, -2, -2, 1, 0, 1, 2];
/// // groups: |---->|------>|--------->|
///
/// let mut data_grouped = Vec::new();
/// // Note: group is an iterator
/// for (key, group) in data.into_iter().group_by(|val| *val >= 0) {
/// data_grouped.push((key, group.collect()));
/// }
/// assert_eq!(data_grouped, vec![(true, vec![1, 3]), (false, vec![-2, -2]), (true, vec![1, 0, 1, 2])]);
/// ```
fn group_by<K, F>(self, key: F) -> GroupByIterator<Self, F, K>
where
Self: Sized,
F: FnMut(&Self::Item) -> K,
K: PartialEq + Copy,
Self::Item: Copy,
{
GroupByIterator::new(self, key)
}
}
impl<I: Iterator> GroupByIteratorExtended for I {}
pub struct GroupByIterator<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
{
// I really would like to avoid the Rc<RefCell>, but the Iterator is shared between
// `GroupByIterator` and `GroupIter`. In practice they are used consecutive and
// `GroupByIter` is finished before calling next on `GroupByIterator`. I'm not sure there
// is a solution with lifetimes for that, because we would need to enforce it in the usage
// somehow.
//
// One potential solution would be to replace the iterator approach with something similar.
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
}
struct GroupByShared<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
{
iter: Peekable<I>,
group_by_fn: F,
}
impl<I, F, K> GroupByIterator<I, F, K>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
K: Copy,
{
fn new(inner: I, group_by_fn: F) -> Self {
let inner = GroupByShared {
iter: inner.peekable(),
group_by_fn,
};
Self {
inner: Rc::new(RefCell::new(inner)),
}
}
}
impl<I, F, K> Iterator for GroupByIterator<I, F, K>
where
I: Iterator,
I::Item: Copy,
F: FnMut(&I::Item) -> K,
K: Copy,
{
type Item = (K, GroupIterator<I, F, K>);
fn next(&mut self) -> Option<Self::Item> {
let mut inner = self.inner.borrow_mut();
let value = *inner.iter.peek()?;
let key = (inner.group_by_fn)(&value);
let inner = self.inner.clone();
let group_iter = GroupIterator {
inner,
group_key: key,
};
Some((key, group_iter))
}
}
pub struct GroupIterator<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
{
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
group_key: K,
}
impl<I, F, K: PartialEq + Copy> Iterator for GroupIterator<I, F, K>
where
I: Iterator,
I::Item: Copy,
F: FnMut(&I::Item) -> K,
{
type Item = I::Item;
fn next(&mut self) -> Option<Self::Item> {
let mut inner = self.inner.borrow_mut();
// peek if next value is in group
let peek_val = *inner.iter.peek()?;
if (inner.group_by_fn)(&peek_val) == self.group_key {
inner.iter.next()
} else {
None
}
}
}
#[cfg(test)]
mod tests {
use super::*;
fn group_by_collect<I: Iterator<Item = u32>>(iter: I) -> Vec<(I::Item, Vec<I::Item>)> {
iter.group_by(|val| val / 10)
.map(|(el, iter)| (el, iter.collect::<Vec<_>>()))
.collect::<Vec<_>>()
}
#[test]
fn group_by_two_groups() {
let vals = vec![1u32, 4, 15];
let grouped_vals = group_by_collect(vals.into_iter());
assert_eq!(grouped_vals, vec![(0, vec![1, 4]), (1, vec![15])]);
}
#[test]
fn group_by_test_empty() {
let vals = vec![];
let grouped_vals = group_by_collect(vals.into_iter());
assert_eq!(grouped_vals, vec![]);
}
#[test]
fn group_by_three_groups() {
let vals = vec![1u32, 4, 15, 1];
let grouped_vals = group_by_collect(vals.into_iter());
assert_eq!(
grouped_vals,
vec![(0, vec![1, 4]), (1, vec![15]), (0, vec![1])]
);
}
}

View File

@@ -6,13 +6,11 @@ pub use byteorder::LittleEndian as Endianness;
mod bitset;
pub mod file_slice;
mod group_by;
mod serialize;
mod vint;
mod writer;
pub use bitset::*;
pub use group_by::GroupByIteratorExtended;
pub use ownedbytes::{OwnedBytes, StableDeref};
pub use ownedbytes::OwnedBytes;
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
pub use vint::{
deserialize_vint_u128, read_u32_vint, read_u32_vint_no_advance, serialize_vint_u128,

View File

@@ -1,17 +1,15 @@
// # Faceted Search
// # Basic Example
//
// This example covers the faceted search functionalities of
// This example covers the basic functionalities of
// tantivy.
//
// We will :
// - define a text field "name" in our schema
// - define a facet field "classification" in our schema
// - create an index in memory
// - index few documents with respective facets in our index
// - search and count the number of documents that the classifications start the facet "/Felidae"
// - Search the facet "/Felidae/Pantherinae" and count the number of documents that the
// classifications include the facet.
//
// - define our schema
// = create an index in a directory
// - index few documents in our index
// - search for the best document matchings "sea whale"
// - retrieve the best document original content.
// ---
// Importing tantivy...
use tantivy::collector::FacetCollector;
@@ -23,7 +21,7 @@ fn main() -> tantivy::Result<()> {
// Let's create a temporary directory for the sake of this example
let mut schema_builder = Schema::builder();
let name = schema_builder.add_text_field("name", TEXT | STORED);
let name = schema_builder.add_text_field("felin_name", TEXT | STORED);
// this is our faceted field: its scientific classification
let classification = schema_builder.add_facet_field("classification", FacetOptions::default());

View File

@@ -14,12 +14,14 @@ repository = "https://github.com/quickwit-oss/tantivy"
[dependencies]
common = { version = "0.5", path = "../common/", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.3", path = "../bitpacker/" }
prettytable-rs = {version="0.10.0", optional= true}
ownedbytes = { version = "0.5", 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", optional=true}
ordered-float = "3.4"
[dev-dependencies]
more-asserts = "0.3.0"

View File

@@ -4,11 +4,11 @@ extern crate test;
#[cfg(test)]
mod tests {
use std::ops::RangeInclusive;
use std::iter;
use std::sync::Arc;
use common::OwnedBytes;
use fastfield_codecs::*;
use ownedbytes::OwnedBytes;
use rand::prelude::*;
use test::Bencher;
@@ -71,24 +71,27 @@ mod tests {
});
}
const FIFTY_PERCENT_RANGE: RangeInclusive<u64> = 1..=50;
const SINGLE_ITEM: u64 = 90;
const SINGLE_ITEM_RANGE: RangeInclusive<u64> = 90..=90;
const ONE_PERCENT_ITEM_RANGE: RangeInclusive<u64> = 49..=49;
fn get_data_50percent_item() -> Vec<u128> {
let mut rng = StdRng::from_seed([1u8; 32]);
fn get_exp_data() -> Vec<u64> {
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.gen_range(1..=100);
data.push(val);
for i in 0..100 {
let num = i * i;
data.extend(iter::repeat(i as u64).take(num));
}
data.push(SINGLE_ITEM);
data.shuffle(&mut StdRng::from_seed([1u8; 32]));
data.shuffle(&mut rng);
let data = data.iter().map(|el| *el as u128).collect::<Vec<_>>();
// lengt = 328350
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 get_u128_column_random() -> Arc<dyn Column<u128>> {
let permutation = generate_random();
let permutation = permutation.iter().map(|el| *el as u128).collect::<Vec<_>>();
@@ -103,82 +106,15 @@ mod tests {
open_u128::<u128>(out).unwrap()
}
// U64 RANGE START
#[bench]
fn bench_intfastfield_getrange_u64_50percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn Column<u64>> = serialize_and_load(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
FIFTY_PERCENT_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_1percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn Column<u64>> = serialize_and_load(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
ONE_PERCENT_ITEM_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_single_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn Column<u64>> = serialize_and_load(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
SINGLE_ITEM_RANGE,
0..data.len() as u32,
&mut positions,
);
positions
});
}
#[bench]
fn bench_intfastfield_getrange_u64_hit_all(b: &mut Bencher) {
let data = get_data_50percent_item();
let data = data.iter().map(|el| *el as u64).collect::<Vec<_>>();
let column: Arc<dyn Column<u64>> = serialize_and_load(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(0..=u64::MAX, 0..data.len() as u32, &mut positions);
positions
});
}
// U64 RANGE END
// U128 RANGE START
#[bench]
fn bench_intfastfield_getrange_u128_50percent_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let (major_item, _minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
*FIFTY_PERCENT_RANGE.start() as u128..=*FIFTY_PERCENT_RANGE.end() as u128,
major_item..=major_item,
0..data.len() as u32,
&mut positions,
);
@@ -188,13 +124,13 @@ mod tests {
#[bench]
fn bench_intfastfield_getrange_u128_single_hit(b: &mut Bencher) {
let data = get_data_50percent_item();
let (_major_item, minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
let mut positions = Vec::new();
column.get_docids_for_value_range(
*SINGLE_ITEM_RANGE.start() as u128..=*SINGLE_ITEM_RANGE.end() as u128,
minor_item..=minor_item,
0..data.len() as u32,
&mut positions,
);
@@ -204,7 +140,7 @@ mod tests {
#[bench]
fn bench_intfastfield_getrange_u128_hit_all(b: &mut Bencher) {
let data = get_data_50percent_item();
let (_major_item, _minor_item, data) = get_data_50percent_item();
let column = get_u128_column_from_data(&data);
b.iter(|| {
@@ -213,7 +149,6 @@ mod tests {
positions
});
}
// U128 RANGE END
#[bench]
fn bench_intfastfield_scan_all_fflookup_u128(b: &mut Bencher) {

View File

@@ -1,6 +1,6 @@
use std::io::{self, Write};
use common::OwnedBytes;
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::serialize::NormalizedHeader;

View File

@@ -1,7 +1,8 @@
use std::sync::Arc;
use std::{io, iter};
use common::{BinarySerializable, CountingWriter, DeserializeFrom, OwnedBytes};
use common::{BinarySerializable, CountingWriter, DeserializeFrom};
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::line::Line;
@@ -46,7 +47,7 @@ impl FastFieldCodec for BlockwiseLinearCodec {
type Reader = BlockwiseLinearReader;
fn open_from_bytes(
bytes: common::OwnedBytes,
bytes: ownedbytes::OwnedBytes,
normalized_header: NormalizedHeader,
) -> io::Result<Self::Reader> {
let footer_len: u32 = (&bytes[bytes.len() - 4..]).deserialize()?;
@@ -170,18 +171,15 @@ impl Column for BlockwiseLinearReader {
interpoled_val.wrapping_add(bitpacked_diff)
}
#[inline(always)]
fn min_value(&self) -> u64 {
// The BlockwiseLinearReader assumes a normalized vector.
0u64
}
#[inline(always)]
fn max_value(&self) -> u64 {
self.normalized_header.max_value
}
#[inline(always)]
fn num_vals(&self) -> u32 {
self.normalized_header.num_vals
}

View File

@@ -1,4 +1,3 @@
use std::fmt::{self, Debug};
use std::marker::PhantomData;
use std::ops::{Range, RangeInclusive};
@@ -7,7 +6,7 @@ use tantivy_bitpacker::minmax;
use crate::monotonic_mapping::StrictlyMonotonicFn;
/// `Column` provides columnar access on a field.
pub trait Column<T: PartialOrd + Debug = u64>: Send + Sync {
pub trait Column<T: PartialOrd = u64>: Send + Sync {
/// Return the value associated with the given idx.
///
/// This accessor should return as fast as possible.
@@ -35,10 +34,6 @@ pub trait Column<T: PartialOrd + Debug = u64>: Send + Sync {
/// Get the positions of values which are in the provided value range.
///
/// Note that position == docid for single value fast fields
///
/// # Truncation
/// `DateTime` has a truncation setting. This function should get passed the truncated values
/// to avoid unexpected results.
#[inline]
fn get_docids_for_value_range(
&self,
@@ -88,7 +83,7 @@ pub struct VecColumn<'a, T = u64> {
max_value: T,
}
impl<'a, C: Column<T>, T: Copy + PartialOrd + fmt::Debug> Column<T> for &'a C {
impl<'a, C: Column<T>, T: Copy + PartialOrd> Column<T> for &'a C {
fn get_val(&self, idx: u32) -> T {
(*self).get_val(idx)
}
@@ -114,7 +109,7 @@ impl<'a, C: Column<T>, T: Copy + PartialOrd + fmt::Debug> Column<T> for &'a C {
}
}
impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> Column<T> for VecColumn<'a, T> {
impl<'a, T: Copy + PartialOrd + Send + Sync> Column<T> for VecColumn<'a, T> {
fn get_val(&self, position: u32) -> T {
self.values[position as usize]
}
@@ -140,9 +135,8 @@ impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> Column<T> for VecColumn<'a,
}
}
impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
where
V: AsRef<[T]> + ?Sized,
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();
@@ -183,8 +177,8 @@ pub fn monotonic_map_column<C, T, Input, Output>(
where
C: Column<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Sync + Copy + Debug,
Output: PartialOrd + Send + Sync + Copy + Debug,
Input: PartialOrd + Send + Sync + Clone,
Output: PartialOrd + Send + Sync + Clone,
{
MonotonicMappingColumn {
from_column,
@@ -197,8 +191,8 @@ impl<C, T, Input, Output> Column<Output> for MonotonicMappingColumn<C, T, Input>
where
C: Column<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Sync + Copy + Debug,
Output: PartialOrd + Send + Sync + Copy + Debug,
Input: PartialOrd + Send + Sync + Clone,
Output: PartialOrd + Send + Sync + Clone,
{
#[inline]
fn get_val(&self, idx: u32) -> Output {
@@ -234,15 +228,12 @@ where
doc_id_range: Range<u32>,
positions: &mut Vec<u32>,
) {
if range.start() > &self.max_value() || range.end() < &self.min_value() {
return;
}
let range = self.monotonic_mapping.inverse_coerce(range);
if range.start() > range.end() {
return;
}
self.from_column
.get_docids_for_value_range(range, doc_id_range, positions)
self.from_column.get_docids_for_value_range(
self.monotonic_mapping.inverse(range.start().clone())
..=self.monotonic_mapping.inverse(range.end().clone()),
doc_id_range,
positions,
)
}
// We voluntarily do not implement get_range as it yields a regression,
@@ -253,8 +244,7 @@ where
pub struct IterColumn<T>(T);
impl<T> From<T> for IterColumn<T>
where
T: Iterator + Clone + ExactSizeIterator,
where T: Iterator + Clone + ExactSizeIterator
{
fn from(iter: T) -> Self {
IterColumn(iter)
@@ -264,7 +254,7 @@ where
impl<T> Column<T::Item> for IterColumn<T>
where
T: Iterator + Clone + ExactSizeIterator + Send + Sync,
T::Item: PartialOrd + fmt::Debug,
T::Item: PartialOrd,
{
fn get_val(&self, idx: u32) -> T::Item {
self.0.clone().nth(idx as usize).unwrap()

View File

@@ -17,7 +17,8 @@ use std::{
ops::{Range, RangeInclusive},
};
use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt, VIntU128};
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;
@@ -453,8 +454,6 @@ impl CompactSpaceDecompressor {
#[cfg(test)]
mod tests {
use std::fmt;
use super::*;
use crate::format_version::read_format_version;
use crate::null_index_footer::read_null_index_footer;
@@ -708,7 +707,7 @@ mod tests {
);
}
fn get_positions_for_value_range_helper<C: Column<T> + ?Sized, T: PartialOrd + fmt::Debug>(
fn get_positions_for_value_range_helper<C: Column<T> + ?Sized, T: PartialOrd>(
column: &C,
value_range: RangeInclusive<T>,
doc_id_range: Range<u32>,

View File

@@ -1,6 +1,7 @@
use std::io;
use common::{BinarySerializable, OwnedBytes};
use common::BinarySerializable;
use ownedbytes::OwnedBytes;
const MAGIC_NUMBER: u16 = 4335u16;
const FASTFIELD_FORMAT_VERSION: u8 = 1;

View File

@@ -45,7 +45,7 @@ mod tests {
use std::io;
use std::num::NonZeroU64;
use common::OwnedBytes;
use ownedbytes::OwnedBytes;
use crate::gcd::{compute_gcd, find_gcd};
use crate::{FastFieldCodecType, VecColumn};

View File

@@ -14,11 +14,11 @@ extern crate more_asserts;
#[cfg(all(test, feature = "unstable"))]
extern crate test;
use std::io;
use std::io::Write;
use std::sync::Arc;
use std::{fmt, io};
use common::{BinarySerializable, OwnedBytes};
use common::BinarySerializable;
use compact_space::CompactSpaceDecompressor;
use format_version::read_format_version;
use monotonic_mapping::{
@@ -26,6 +26,7 @@ use monotonic_mapping::{
StrictlyMonotonicMappingToInternalBaseval, StrictlyMonotonicMappingToInternalGCDBaseval,
};
use null_index_footer::read_null_index_footer;
use ownedbytes::OwnedBytes;
use serialize::{Header, U128Header};
mod bitpacked;
@@ -44,6 +45,8 @@ mod column;
mod gcd;
pub mod serialize;
pub use ordered_float;
use self::bitpacked::BitpackedCodec;
use self::blockwise_linear::BlockwiseLinearCodec;
pub use self::column::{monotonic_map_column, Column, IterColumn, VecColumn};
@@ -133,7 +136,7 @@ impl U128FastFieldCodecType {
}
/// Returns the correct codec reader wrapped in the `Arc` for the data.
pub fn open_u128<Item: MonotonicallyMappableToU128 + fmt::Debug>(
pub fn open_u128<Item: MonotonicallyMappableToU128>(
bytes: OwnedBytes,
) -> io::Result<Arc<dyn Column<Item>>> {
let (bytes, _format_version) = read_format_version(bytes)?;
@@ -147,9 +150,7 @@ pub fn open_u128<Item: MonotonicallyMappableToU128 + fmt::Debug>(
}
/// Returns the correct codec reader wrapped in the `Arc` for the data.
pub fn open<T: MonotonicallyMappableToU64 + fmt::Debug>(
bytes: OwnedBytes,
) -> io::Result<Arc<dyn Column<T>>> {
pub fn open<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::Result<Arc<dyn Column<T>>> {
let (bytes, _format_version) = read_format_version(bytes)?;
let (mut bytes, _null_index_footer) = read_null_index_footer(bytes)?;
let header = Header::deserialize(&mut bytes)?;
@@ -162,7 +163,7 @@ pub fn open<T: MonotonicallyMappableToU64 + fmt::Debug>(
}
}
fn open_specific_codec<C: FastFieldCodec, Item: MonotonicallyMappableToU64 + fmt::Debug>(
fn open_specific_codec<C: FastFieldCodec, Item: MonotonicallyMappableToU64>(
bytes: OwnedBytes,
header: &Header,
) -> io::Result<Arc<dyn Column<Item>>> {
@@ -323,9 +324,6 @@ mod tests {
pub fn get_codec_test_datasets() -> Vec<(Vec<u64>, &'static str)> {
let mut data_and_names = vec![];
let data = vec![10];
data_and_names.push((data, "minimal test"));
let data = (10..=10_000_u64).collect::<Vec<_>>();
data_and_names.push((data, "simple monotonically increasing"));
@@ -333,9 +331,6 @@ mod tests {
vec![5, 6, 7, 8, 9, 10, 99, 100],
"offset in linear interpol",
));
data_and_names.push((vec![3, 18446744073709551613, 5], "docid range regression"));
data_and_names.push((vec![5, 50, 3, 13, 1, 1000, 35], "rand small"));
data_and_names.push((vec![10], "single value"));
@@ -443,7 +438,7 @@ mod tests {
mod bench {
use std::sync::Arc;
use common::OwnedBytes;
use ownedbytes::OwnedBytes;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::{self, Bencher};

View File

@@ -1,6 +1,7 @@
use std::io::{self, Write};
use common::{BinarySerializable, OwnedBytes};
use common::BinarySerializable;
use ownedbytes::OwnedBytes;
use tantivy_bitpacker::{compute_num_bits, BitPacker, BitUnpacker};
use crate::line::Line;
@@ -24,13 +25,13 @@ impl Column for LinearReader {
interpoled_val.wrapping_add(bitpacked_diff)
}
#[inline(always)]
#[inline]
fn min_value(&self) -> u64 {
// The LinearReader assumes a normalized vector.
0u64
}
#[inline(always)]
#[inline]
fn max_value(&self) -> u64 {
self.header.max_value
}

View File

@@ -6,10 +6,10 @@ use std::io::BufRead;
use std::net::{IpAddr, Ipv6Addr};
use std::str::FromStr;
use common::OwnedBytes;
use fastfield_codecs::{open_u128, serialize_u128, Column, FastFieldCodecType, VecColumn};
use itertools::Itertools;
use measure_time::print_time;
use ownedbytes::OwnedBytes;
use prettytable::{Cell, Row, Table};
fn print_set_stats(ip_addrs: &[u128]) {

View File

@@ -1,16 +1,13 @@
use std::fmt;
use std::marker::PhantomData;
use std::ops::RangeInclusive;
use fastdivide::DividerU64;
use ordered_float::NotNan;
use crate::MonotonicallyMappableToU128;
/// Monotonic maps a value to u64 value space.
/// Monotonic mapping enables `PartialOrd` on u64 space without conversion to original space.
pub trait MonotonicallyMappableToU64:
'static + PartialOrd + Copy + Send + Sync + fmt::Debug
{
pub trait MonotonicallyMappableToU64: 'static + PartialOrd + Copy + Send + Sync {
/// Converts a value to u64.
///
/// Internally all fast field values are encoded as u64.
@@ -33,29 +30,11 @@ pub trait MonotonicallyMappableToU64:
/// mapping from their range to their domain. The `inverse` method is required when opening a codec,
/// so a value can be converted back to its original domain (e.g. ip address or f64) from its
/// internal representation.
pub trait StrictlyMonotonicFn<External: Copy, Internal: Copy> {
pub trait StrictlyMonotonicFn<External, Internal> {
/// Strictly monotonically maps the value from External to Internal.
fn mapping(&self, inp: External) -> Internal;
/// Inverse of `mapping`. Maps the value from Internal to External.
fn inverse(&self, out: Internal) -> External;
/// Maps a user provded value from External to Internal.
/// It may be necessary to coerce the value if it is outside the value space.
/// In that case it tries to find the next greater value in the value space.
///
/// Returns a bool to mark if a value was outside the value space and had to be coerced _up_.
/// With that information we can detect if two values in a range both map outside the same value
/// space.
///
/// coerce_up means the next valid upper value in the value space will be chosen if the value
/// has to be coerced.
fn mapping_coerce(&self, inp: RangeInclusive<External>) -> RangeInclusive<Internal> {
self.mapping(*inp.start())..=self.mapping(*inp.end())
}
/// Inverse of `mapping_coerce`.
fn inverse_coerce(&self, out: RangeInclusive<Internal>) -> RangeInclusive<External> {
self.inverse(*out.start())..=self.inverse(*out.end())
}
}
/// Inverts a strictly monotonic mapping from `StrictlyMonotonicFn<A, B>` to
@@ -76,29 +55,15 @@ impl<T> From<T> for StrictlyMonotonicMappingInverter<T> {
}
impl<From, To, T> StrictlyMonotonicFn<To, From> for StrictlyMonotonicMappingInverter<T>
where
T: StrictlyMonotonicFn<From, To>,
From: Copy,
To: Copy,
where T: StrictlyMonotonicFn<From, To>
{
#[inline(always)]
fn mapping(&self, val: To) -> From {
self.orig_mapping.inverse(val)
}
#[inline(always)]
fn inverse(&self, val: From) -> To {
self.orig_mapping.mapping(val)
}
#[inline]
fn mapping_coerce(&self, inp: RangeInclusive<To>) -> RangeInclusive<From> {
self.orig_mapping.inverse_coerce(inp)
}
#[inline]
fn inverse_coerce(&self, out: RangeInclusive<From>) -> RangeInclusive<To> {
self.orig_mapping.mapping_coerce(out)
}
}
/// Applies the strictly monotonic mapping from `T` without any additional changes.
@@ -118,12 +83,10 @@ impl<External: MonotonicallyMappableToU128, T: MonotonicallyMappableToU128>
StrictlyMonotonicFn<External, u128> for StrictlyMonotonicMappingToInternal<T>
where T: MonotonicallyMappableToU128
{
#[inline(always)]
fn mapping(&self, inp: External) -> u128 {
External::to_u128(inp)
}
#[inline(always)]
fn inverse(&self, out: u128) -> External {
External::from_u128(out)
}
@@ -133,12 +96,10 @@ impl<External: MonotonicallyMappableToU64, T: MonotonicallyMappableToU64>
StrictlyMonotonicFn<External, u64> for StrictlyMonotonicMappingToInternal<T>
where T: MonotonicallyMappableToU64
{
#[inline(always)]
fn mapping(&self, inp: External) -> u64 {
External::to_u64(inp)
}
#[inline(always)]
fn inverse(&self, out: u64) -> External {
External::from_u64(out)
}
@@ -166,41 +127,14 @@ impl StrictlyMonotonicMappingToInternalGCDBaseval {
impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
for StrictlyMonotonicMappingToInternalGCDBaseval
{
#[inline(always)]
fn mapping(&self, inp: External) -> u64 {
self.gcd_divider
.divide(External::to_u64(inp) - self.min_value)
}
#[inline(always)]
fn inverse(&self, out: u64) -> External {
External::from_u64(self.min_value + out * self.gcd)
}
#[inline]
#[allow(clippy::reversed_empty_ranges)]
fn mapping_coerce(&self, inp: RangeInclusive<External>) -> RangeInclusive<u64> {
let end = External::to_u64(*inp.end());
if end < self.min_value || inp.end() < inp.start() {
return 1..=0;
}
let map_coerce = |mut inp, coerce_up| {
let inp_lower_bound = self.inverse(0);
if inp < inp_lower_bound {
inp = inp_lower_bound;
}
let val = External::to_u64(inp);
let need_coercion = coerce_up && (val - self.min_value) % self.gcd != 0;
let mut mapped_val = self.mapping(inp);
if need_coercion {
mapped_val += 1;
}
mapped_val
};
let start = map_coerce(*inp.start(), true);
let end = map_coerce(*inp.end(), false);
start..=end
}
}
/// Strictly monotonic mapping with a base value.
@@ -208,7 +142,6 @@ pub(crate) struct StrictlyMonotonicMappingToInternalBaseval {
min_value: u64,
}
impl StrictlyMonotonicMappingToInternalBaseval {
#[inline(always)]
pub(crate) fn new(min_value: u64) -> Self {
Self { min_value }
}
@@ -217,35 +150,20 @@ impl StrictlyMonotonicMappingToInternalBaseval {
impl<External: MonotonicallyMappableToU64> StrictlyMonotonicFn<External, u64>
for StrictlyMonotonicMappingToInternalBaseval
{
#[inline]
#[allow(clippy::reversed_empty_ranges)]
fn mapping_coerce(&self, inp: RangeInclusive<External>) -> RangeInclusive<u64> {
if External::to_u64(*inp.end()) < self.min_value {
return 1..=0;
}
let start = self.mapping(External::to_u64(*inp.start()).max(self.min_value));
let end = self.mapping(External::to_u64(*inp.end()));
start..=end
}
#[inline(always)]
fn mapping(&self, val: External) -> u64 {
External::to_u64(val) - self.min_value
}
#[inline(always)]
fn inverse(&self, val: u64) -> External {
External::from_u64(self.min_value + val)
}
}
impl MonotonicallyMappableToU64 for u64 {
#[inline(always)]
fn to_u64(self) -> u64 {
self
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
val
}
@@ -278,22 +196,51 @@ impl MonotonicallyMappableToU64 for bool {
// TODO remove me.
// Tantivy should refuse NaN values and work with NotNaN internally.
impl MonotonicallyMappableToU64 for f64 {
#[inline(always)]
fn to_u64(self) -> u64 {
common::f64_to_u64(self)
}
#[inline(always)]
fn from_u64(val: u64) -> Self {
common::u64_to_f64(val)
}
}
impl MonotonicallyMappableToU64 for ordered_float::NotNan<f64> {
fn to_u64(self) -> u64 {
common::f64_to_u64(self.into_inner())
}
fn from_u64(val: u64) -> Self {
NotNan::new(common::u64_to_f64(val)).expect("Invalid NotNaN f64 value.")
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_from_u64_pos_inf() {
let inf_as_u64 = common::f64_to_u64(f64::INFINITY);
let inf_back_to_f64 = NotNan::from_u64(inf_as_u64);
assert_eq!(inf_back_to_f64, NotNan::new(f64::INFINITY).unwrap());
}
#[test]
fn test_from_u64_neg_inf() {
let inf_as_u64 = common::f64_to_u64(-f64::INFINITY);
let inf_back_to_f64 = NotNan::from_u64(inf_as_u64);
assert_eq!(inf_back_to_f64, NotNan::new(-f64::INFINITY).unwrap());
}
#[test]
#[should_panic(expected = "Invalid NotNaN")]
fn test_from_u64_nan_panics() {
let nan_as_u64 = common::f64_to_u64(f64::NAN);
NotNan::from_u64(nan_as_u64);
}
#[test]
fn strictly_monotonic_test() {
// identity mapping
@@ -311,7 +258,7 @@ mod tests {
test_round_trip::<_, _, u64>(&mapping, 100u64);
}
fn test_round_trip<T: StrictlyMonotonicFn<K, L>, K: std::fmt::Debug + Eq + Copy, L: Copy>(
fn test_round_trip<T: StrictlyMonotonicFn<K, L>, K: std::fmt::Debug + Eq + Copy, L>(
mapping: &T,
test_val: K,
) {

View File

@@ -1,11 +1,8 @@
use std::fmt;
use std::net::Ipv6Addr;
/// Montonic maps a value to u128 value space
/// Monotonic mapping enables `PartialOrd` on u128 space without conversion to original space.
pub trait MonotonicallyMappableToU128:
'static + PartialOrd + Copy + Send + Sync + fmt::Debug
{
pub trait MonotonicallyMappableToU128: 'static + PartialOrd + Copy + Send + Sync {
/// Converts a value to u128.
///
/// Internally all fast field values are encoded as u64.

View File

@@ -1,8 +1,9 @@
use std::convert::TryInto;
use std::io::{self, Write};
use common::{BinarySerializable, OwnedBytes};
use common::BinarySerializable;
use itertools::Itertools;
use ownedbytes::OwnedBytes;
use super::{get_bit_at, set_bit_at};
@@ -31,16 +32,15 @@ const BLOCK_BITVEC_SIZE: usize = 8;
const BLOCK_OFFSET_SIZE: usize = 4;
const SERIALIZED_BLOCK_SIZE: usize = BLOCK_BITVEC_SIZE + BLOCK_OFFSET_SIZE;
/// Interpreting the bitvec as a list of 64 bits from the low weight to the
/// high weight.
///
/// This function returns the number of bits set to 1 within
/// `[0..pos_in_vec)`.
#[inline]
fn count_ones(bitvec: u64, pos_in_bitvec: u32) -> u32 {
let mask = (1u64 << pos_in_bitvec) - 1;
let masked_bitvec = bitvec & mask;
masked_bitvec.count_ones()
if pos_in_bitvec == 63 {
bitvec.count_ones()
} else {
let mask = (1u64 << (pos_in_bitvec + 1)) - 1;
let masked_bitvec = bitvec & mask;
masked_bitvec.count_ones()
}
}
#[derive(Clone, Copy)]
@@ -67,7 +67,9 @@ impl DenseCodec {
pub fn exists(&self, idx: u32) -> bool {
let block_pos = idx / ELEMENTS_PER_BLOCK;
let bitvec = self.dense_index_block(block_pos).bitvec;
let pos_in_bitvec = idx % ELEMENTS_PER_BLOCK;
get_bit_at(bitvec, pos_in_bitvec)
}
#[inline]
@@ -89,7 +91,8 @@ impl DenseCodec {
let pos_in_block_bit_vec = idx % ELEMENTS_PER_BLOCK;
let ones_in_block = count_ones(index_block.bitvec, pos_in_block_bit_vec);
if get_bit_at(index_block.bitvec, pos_in_block_bit_vec) {
Some(index_block.offset + ones_in_block)
// -1 is ok, since idx does exist, so there's at least one
Some(index_block.offset + ones_in_block - 1)
} else {
None
}
@@ -317,10 +320,9 @@ mod tests {
set_bit_at(&mut block, 0);
set_bit_at(&mut block, 2);
assert_eq!(count_ones(block, 0), 0);
assert_eq!(count_ones(block, 0), 1);
assert_eq!(count_ones(block, 1), 1);
assert_eq!(count_ones(block, 2), 1);
assert_eq!(count_ones(block, 3), 2);
assert_eq!(count_ones(block, 2), 2);
}
}
@@ -346,16 +348,11 @@ mod bench {
codec
}
fn random_range_iterator(
start: u32,
end: u32,
avg_step_size: u32,
avg_deviation: u32,
) -> impl Iterator<Item = u32> {
fn random_range_iterator(start: u32, end: u32, step_size: u32) -> impl Iterator<Item = u32> {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
current += rng.gen_range(1..step_size + 1);
if current >= end {
None
} else {
@@ -364,17 +361,10 @@ mod bench {
})
}
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
let ratio = percent as f32 / 100.0;
let step_size = (1f32 / ratio) as u32;
let deviation = step_size - 1;
random_range_iterator(0, num_values, step_size, deviation)
}
fn walk_over_data(codec: &DenseCodec, avg_step_size: u32) -> Option<u32> {
fn walk_over_data(codec: &DenseCodec, max_step_size: u32) -> Option<u32> {
walk_over_data_from_positions(
codec,
random_range_iterator(0, TOTAL_NUM_VALUES, avg_step_size, 0),
random_range_iterator(0, TOTAL_NUM_VALUES, max_step_size),
)
}
@@ -390,105 +380,69 @@ mod bench {
}
#[bench]
fn bench_translate_orig_to_codec_1percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 1000));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_1percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_10percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_90percent_filled(bench: &mut Bencher) {
fn bench_dense_codec_translate_orig_to_codec_90percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_10percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_50percent_filled_1percent_hit(bench: &mut Bencher) {
fn bench_dense_codec_translate_orig_to_codec_50percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.5f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_90percent_filled_1percent_hit(bench: &mut Bencher) {
fn bench_dense_codec_translate_orig_to_codec_full_scan_10percent(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_dense_codec_translate_orig_to_codec_full_scan_90percent(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_dense_codec_translate_orig_to_codec_10percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_0comma005percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
let num_non_nulls = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(n_percent_step_iterator(0.005, num_non_nulls))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_10percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
let num_non_nulls = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(n_percent_step_iterator(10.0, num_non_nulls))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_full_scan(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
fn bench_dense_codec_translate_codec_to_orig_90percent_filled_random_stride_big_step(
bench: &mut Bencher,
) {
let codec = gen_bools(0.9f64);
let num_vals = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(0..num_vals)
.translate_codec_idx_to_original_idx(random_range_iterator(0, num_vals, 50_000))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_0comma005percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.90f64);
let num_non_nulls = codec.num_non_nulls();
fn bench_dense_codec_translate_codec_to_orig_90percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.9f64);
let num_vals = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(n_percent_step_iterator(0.005, num_non_nulls))
.translate_codec_idx_to_original_idx(random_range_iterator(0, num_vals, 100))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_full_scan(bench: &mut Bencher) {
fn bench_dense_codec_translate_codec_to_orig_90percent_filled_full_scan(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
let num_vals = codec.num_non_nulls();
bench.iter(|| {

View File

@@ -1,6 +1,7 @@
use std::io::{self, Write};
use common::{BitSet, GroupByIteratorExtended, OwnedBytes};
use common::BitSet;
use ownedbytes::OwnedBytes;
use super::{serialize_dense_codec, DenseCodec};
@@ -58,7 +59,6 @@ enum SparseCodecBlockVariant {
impl SparseCodecBlockVariant {
/// The number of non-null values that preceeded that block.
#[inline]
fn offset(&self) -> u32 {
match self {
SparseCodecBlockVariant::Empty { offset } => *offset,
@@ -78,22 +78,12 @@ struct DenseBlock {
}
impl DenseBlock {
#[inline]
pub fn exists(&self, idx: u32) -> bool {
self.codec.exists(idx)
}
#[inline]
pub fn translate_to_codec_idx(&self, idx: u32) -> Option<u32> {
self.codec.translate_to_codec_idx(idx)
}
#[inline]
pub fn translate_codec_idx_to_original_idx_iter<'a>(
&'a self,
iter: impl Iterator<Item = u32> + 'a,
) -> impl Iterator<Item = u32> + 'a {
self.codec.translate_codec_idx_to_original_idx(iter)
}
#[inline]
pub fn translate_codec_idx_to_original_idx(&self, idx: u32) -> u32 {
self.codec
.translate_codec_idx_to_original_idx(idx..=idx)
@@ -217,7 +207,6 @@ struct ValueAddr {
}
/// Splits a idx into block index and value in the block
#[inline]
fn value_addr(idx: u32) -> ValueAddr {
/// Static assert number elements per block this method expects
#[allow(clippy::assertions_on_constants)]
@@ -284,7 +273,6 @@ impl SparseCodec {
}
}
#[inline]
fn find_block(&self, dense_idx: u32, mut block_pos: u32) -> u32 {
loop {
let offset = self.blocks[block_pos as usize].offset();
@@ -296,7 +284,6 @@ impl SparseCodec {
}
/// Translate positions from the codec index to the original index.
/// Correctness: Provided values must be in increasing values
///
/// # Panics
///
@@ -305,41 +292,35 @@ impl SparseCodec {
&'a self,
iter: impl Iterator<Item = u32> + 'a,
) -> impl Iterator<Item = u32> + 'a {
// TODO: There's a big potential performance gain, by using iterators per block instead of
// random access for each element in a block
// group_by itertools won't help though, since it requires a temporary local variable
let mut block_pos = 0u32;
iter.group_by(move |codec_idx| {
block_pos = self.find_block(*codec_idx, block_pos);
block_pos
})
.flat_map(move |(block_pos, block_iter)| {
iter.map(move |codec_idx| {
// update block_pos to limit search scope
block_pos = self.find_block(codec_idx, block_pos);
let block_doc_idx_start = block_pos * ELEMENTS_PER_BLOCK;
let block = &self.blocks[block_pos as usize];
let offset = block.offset();
let indexes_in_block_iter = block_iter.map(move |codec_idx| codec_idx - offset);
let idx_in_block = codec_idx - block.offset();
match block {
SparseCodecBlockVariant::Empty { offset: _ } => {
panic!(
"invalid input, cannot translate to original index. associated empty \
block with dense idx. block_pos {}, idx_in_block {:?}",
block_pos,
indexes_in_block_iter.collect::<Vec<_>>()
block with dense idx. block_pos {}, idx_in_block {}",
block_pos, idx_in_block
)
}
SparseCodecBlockVariant::Dense(dense) => {
Box::new(dense.translate_codec_idx_to_original_idx_iter(indexes_in_block_iter))
as Box<dyn Iterator<Item = u32>>
dense.translate_codec_idx_to_original_idx(idx_in_block) + block_doc_idx_start
}
SparseCodecBlockVariant::Sparse(block) => {
Box::new(indexes_in_block_iter.map(move |idx_in_block| {
block.value_at_idx(&self.data, idx_in_block as u16) as u32
}))
block.value_at_idx(&self.data, idx_in_block as u16) as u32 + block_doc_idx_start
}
}
.map(move |idx| idx + block_doc_idx_start)
})
}
}
#[inline]
fn is_sparse(num_elem_in_block: u32) -> bool {
num_elem_in_block < DENSE_BLOCK_THRESHOLD
}
@@ -614,16 +595,11 @@ mod bench {
codec
}
fn random_range_iterator(
start: u32,
end: u32,
avg_step_size: u32,
avg_deviation: u32,
) -> impl Iterator<Item = u32> {
fn random_range_iterator(start: u32, end: u32, step_size: u32) -> impl Iterator<Item = u32> {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
current += rng.gen_range(1..step_size + 1);
if current >= end {
None
} else {
@@ -632,17 +608,10 @@ mod bench {
})
}
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
let ratio = percent as f32 / 100.0;
let step_size = (1f32 / ratio) as u32;
let deviation = step_size - 1;
random_range_iterator(0, num_values, step_size, deviation)
}
fn walk_over_data(codec: &SparseCodec, avg_step_size: u32) -> Option<u32> {
fn walk_over_data(codec: &SparseCodec, max_step_size: u32) -> Option<u32> {
walk_over_data_from_positions(
codec,
random_range_iterator(0, TOTAL_NUM_VALUES, avg_step_size, 0),
random_range_iterator(0, TOTAL_NUM_VALUES, max_step_size),
)
}
@@ -658,83 +627,83 @@ mod bench {
}
#[bench]
fn bench_translate_orig_to_codec_1percent_filled_10percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_orig_to_codec_1percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_10percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_orig_to_codec_5percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_5percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.05f64);
bench.iter(|| walk_over_data(&codec, 1000));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_1percent_filled(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_10percent_filled(bench: &mut Bencher) {
fn bench_sparse_codec_translate_orig_to_codec_full_scan_10percent(bench: &mut Bencher) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_full_scan_90percent_filled(bench: &mut Bencher) {
fn bench_sparse_codec_translate_orig_to_codec_full_scan_90percent(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_translate_orig_to_codec_10percent_filled_1percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_orig_to_codec_full_scan_1percent(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
bench.iter(|| walk_over_data_from_positions(&codec, 0..TOTAL_NUM_VALUES));
}
#[bench]
fn bench_sparse_codec_translate_orig_to_codec_10percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.1f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_50percent_filled_1percent_hit(bench: &mut Bencher) {
let codec = gen_bools(0.5f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_orig_to_codec_90percent_filled_1percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_orig_to_codec_90percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.9f64);
bench.iter(|| walk_over_data(&codec, 100));
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_0comma005percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_codec_to_orig_1percent_filled_random_stride_big_step(
bench: &mut Bencher,
) {
let codec = gen_bools(0.01f64);
let num_non_nulls = codec.num_non_nulls();
let num_vals = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(n_percent_step_iterator(0.005, num_non_nulls))
.translate_codec_idx_to_original_idx(random_range_iterator(0, num_vals, 50_000))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_10percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_codec_to_orig_1percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.01f64);
let num_non_nulls = codec.num_non_nulls();
let num_vals = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(n_percent_step_iterator(10.0, num_non_nulls))
.translate_codec_idx_to_original_idx(random_range_iterator(0, num_vals, 100))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_1percent_filled_full_scan(bench: &mut Bencher) {
fn bench_sparse_codec_translate_codec_to_orig_1percent_filled_full_scan(bench: &mut Bencher) {
let codec = gen_bools(0.01f64);
let num_vals = codec.num_non_nulls();
bench.iter(|| {
@@ -745,18 +714,33 @@ mod bench {
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_0comma005percent_hit(bench: &mut Bencher) {
fn bench_sparse_codec_translate_codec_to_orig_90percent_filled_random_stride_big_step(
bench: &mut Bencher,
) {
let codec = gen_bools(0.90f64);
let num_non_nulls = codec.num_non_nulls();
let num_vals = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(n_percent_step_iterator(0.005, num_non_nulls))
.translate_codec_idx_to_original_idx(random_range_iterator(0, num_vals, 50_000))
.last()
});
}
#[bench]
fn bench_translate_codec_to_orig_90percent_filled_full_scan(bench: &mut Bencher) {
fn bench_sparse_codec_translate_codec_to_orig_90percent_filled_random_stride(
bench: &mut Bencher,
) {
let codec = gen_bools(0.9f64);
let num_vals = codec.num_non_nulls();
bench.iter(|| {
codec
.translate_codec_idx_to_original_idx(random_range_iterator(0, num_vals, 100))
.last()
});
}
#[bench]
fn bench_sparse_codec_translate_codec_to_orig_90percent_filled_full_scan(bench: &mut Bencher) {
let codec = gen_bools(0.9f64);
let num_vals = codec.num_non_nulls();
bench.iter(|| {

View File

@@ -1,7 +1,8 @@
use std::io::{self, Write};
use std::ops::Range;
use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt};
use common::{BinarySerializable, CountingWriter, VInt};
use ownedbytes::OwnedBytes;
#[derive(Debug, Clone, Copy, Eq, PartialEq)]
pub(crate) enum FastFieldCardinality {

View File

@@ -1,28 +1,10 @@
// 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 std::{fmt, io};
use common::{BinarySerializable, OwnedBytes, VInt};
use common::{BinarySerializable, VInt};
use log::warn;
use ownedbytes::OwnedBytes;
use crate::bitpacked::BitpackedCodec;
use crate::blockwise_linear::BlockwiseLinearCodec;
@@ -167,7 +149,7 @@ impl BinarySerializable for Header {
/// Return estimated compression for given codec in the value range [0.0..1.0], where 1.0 means no
/// compression.
pub fn estimate<T: MonotonicallyMappableToU64 + fmt::Debug>(
pub fn estimate<T: MonotonicallyMappableToU64>(
typed_column: impl Column<T>,
codec_type: FastFieldCodecType,
) -> Option<f32> {
@@ -202,7 +184,6 @@ pub enum ValueIndexInfo<'a> {
SingleValue(Box<dyn SingleValueIndexInfo + 'a>),
}
// TODO Remove me
impl Default for ValueIndexInfo<'static> {
fn default() -> Self {
struct Dummy {}
@@ -276,7 +257,7 @@ pub fn serialize_u128_new<F: Fn() -> I, I: Iterator<Item = u128>>(
}
/// Serializes the column with the codec with the best estimate on the data.
pub fn serialize<T: MonotonicallyMappableToU64 + fmt::Debug>(
pub fn serialize<T: MonotonicallyMappableToU64>(
typed_column: impl Column<T>,
output: &mut impl io::Write,
codecs: &[FastFieldCodecType],
@@ -285,7 +266,7 @@ pub fn serialize<T: MonotonicallyMappableToU64 + fmt::Debug>(
}
/// Serializes the column with the codec with the best estimate on the data.
pub fn serialize_new<T: MonotonicallyMappableToU64 + fmt::Debug>(
pub fn serialize_new<T: MonotonicallyMappableToU64>(
value_index: ValueIndexInfo,
typed_column: impl Column<T>,
output: &mut impl io::Write,
@@ -366,7 +347,7 @@ fn serialize_given_codec(
}
/// Helper function to serialize a column (autodetect from all codecs) and then open it
pub fn serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default + fmt::Debug>(
pub fn serialize_and_load<T: MonotonicallyMappableToU64 + Ord + Default>(
column: &[T],
) -> Arc<dyn Column<T>> {
let mut buffer = Vec::new();

View File

@@ -1208,7 +1208,7 @@ mod tests {
text_field_many_terms => many_terms_data.choose(&mut rng).unwrap().to_string(),
text_field_few_terms => few_terms_data.choose(&mut rng).unwrap().to_string(),
score_field => val as u64,
score_field_f64 => val,
score_field_f64 => val as f64,
score_field_i64 => val as i64,
))?;
}
@@ -1250,7 +1250,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&term_query, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&term_query, &collector).unwrap().into();
agg_res
});
}
@@ -1278,7 +1281,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&term_query, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&term_query, &collector).unwrap().into();
agg_res
});
}
@@ -1306,7 +1312,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&term_query, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&term_query, &collector).unwrap().into();
agg_res
});
}
@@ -1342,7 +1351,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&term_query, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&term_query, &collector).unwrap().into();
agg_res
});
}
@@ -1368,7 +1380,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req, None, index.schema());
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&AllQuery, &collector).unwrap().into();
agg_res
});
}
@@ -1394,7 +1409,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req, None, index.schema());
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&AllQuery, &collector).unwrap().into();
agg_res
});
}
@@ -1428,7 +1446,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&AllQuery, &collector).unwrap().into();
agg_res
});
}
@@ -1460,7 +1481,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&AllQuery, &collector).unwrap().into();
agg_res
});
}
@@ -1496,7 +1520,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&AllQuery, &collector).unwrap().into();
agg_res
});
}
@@ -1523,7 +1550,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&AllQuery, &collector).unwrap().into();
agg_res
});
}
@@ -1567,7 +1597,7 @@ mod tests {
],
..Default::default()
}),
sub_aggregation: sub_agg_req_1,
sub_aggregation: sub_agg_req_1.clone(),
}),
),
]
@@ -1577,7 +1607,10 @@ mod tests {
let collector = AggregationCollector::from_aggs(agg_req_1, None, index.schema());
let searcher = reader.searcher();
searcher.search(&term_query, &collector).unwrap()
let agg_res: AggregationResults =
searcher.search(&term_query, &collector).unwrap().into();
agg_res
});
}
}

View File

@@ -198,10 +198,11 @@ impl Searcher {
collector: &C,
executor: &Executor,
) -> crate::Result<C::Fruit> {
let enabled_scoring = if collector.requires_scoring() {
EnableScoring::enabled_from_searcher(self)
let scoring_enabled = collector.requires_scoring();
let enabled_scoring = if scoring_enabled {
EnableScoring::Enabled(self)
} else {
EnableScoring::disabled_from_searcher(self)
EnableScoring::Disabled(self.schema())
};
let weight = query.weight(enabled_scoring)?;
let segment_readers = self.segment_readers();

View File

@@ -32,7 +32,7 @@ impl LockError {
/// Error that may occur when opening a directory
#[derive(Debug, Clone, Error)]
pub enum OpenDirectoryError {
/// The underlying directory does not exist.
/// The underlying directory does not exists.
#[error("Directory does not exist: '{0}'.")]
DoesNotExist(PathBuf),
/// The path exists but is not a directory.
@@ -151,8 +151,8 @@ impl fmt::Debug for Incompatibility {
/// Error that may occur when accessing a file read
#[derive(Debug, Clone, Error)]
pub enum OpenReadError {
/// The file does not exist.
#[error("Files does not exist: {0:?}")]
/// The file does not exists.
#[error("Files does not exists: {0:?}")]
FileDoesNotExist(PathBuf),
/// Any kind of io::Error.
#[error(
@@ -181,8 +181,8 @@ impl OpenReadError {
/// Error that may occur when trying to delete a file
#[derive(Debug, Clone, Error)]
pub enum DeleteError {
/// The file does not exist.
#[error("File does not exist: '{0}'.")]
/// The file does not exists.
#[error("File does not exists: '{0}'.")]
FileDoesNotExist(PathBuf),
/// Any kind of IO error that happens when
/// interacting with the underlying IO device.

View File

@@ -6,10 +6,10 @@ use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock, Weak};
use std::{fmt, result};
use common::StableDeref;
use fs2::FileExt;
use memmap2::Mmap;
use serde::{Deserialize, Serialize};
use stable_deref_trait::StableDeref;
use tempfile::TempDir;
use crate::core::META_FILEPATH;

View File

@@ -20,7 +20,8 @@ use std::io::BufWriter;
use std::path::PathBuf;
pub use common::file_slice::{FileHandle, FileSlice};
pub use common::{AntiCallToken, OwnedBytes, TerminatingWrite};
pub use common::{AntiCallToken, TerminatingWrite};
pub use ownedbytes::OwnedBytes;
pub(crate) use self::composite_file::{CompositeFile, CompositeWrite};
pub use self::directory::{Directory, DirectoryClone, DirectoryLock};

View File

@@ -232,7 +232,7 @@ impl Directory for RamDirectory {
let path_buf = PathBuf::from(path);
self.fs.write().unwrap().write(path_buf, data);
if path == *META_FILEPATH {
drop(self.fs.write().unwrap().watch_router.broadcast());
let _ = self.fs.write().unwrap().watch_router.broadcast();
}
Ok(())
}

View File

@@ -168,7 +168,7 @@ mod tests {
watch_event_router.broadcast().wait().unwrap();
assert_eq!(2, counter.load(Ordering::SeqCst));
mem::drop(handle_a);
drop(watch_event_router.broadcast());
let _ = watch_event_router.broadcast();
watch_event_router.broadcast().wait().unwrap();
assert_eq!(2, counter.load(Ordering::SeqCst));
}

View File

@@ -1,7 +1,8 @@
use std::io;
use std::io::Write;
use common::{intersect_bitsets, BitSet, OwnedBytes, ReadOnlyBitSet};
use common::{intersect_bitsets, BitSet, ReadOnlyBitSet};
use ownedbytes::OwnedBytes;
use crate::space_usage::ByteCount;
use crate::DocId;
@@ -175,7 +176,7 @@ mod bench {
fn get_alive() -> Vec<u32> {
let mut data = (0..1_000_000_u32).collect::<Vec<u32>>();
for _ in 0..1_000_000 / 8 {
for _ in 0..(1_000_000) * 1 / 8 {
remove_rand(&mut data);
}
data

View File

@@ -96,7 +96,7 @@ mod tests {
let term = Term::from_field_bytes(field, b"lucene".as_ref());
let term_query = TermQuery::new(term, IndexRecordOption::Basic);
let term_weight_err =
term_query.specialized_weight(EnableScoring::disabled_from_schema(searcher.schema()));
term_query.specialized_weight(EnableScoring::Disabled(searcher.schema()));
assert!(matches!(
term_weight_err,
Err(crate::TantivyError::SchemaError(_))

View File

@@ -12,15 +12,13 @@
//!
//!
//! Fields have to be declared as `FAST` in the schema.
//! Currently supported fields are: u64, i64, f64, bytes, ip and text.
//! Currently supported fields are: u64, i64, f64, bytes and text.
//!
//! Fast fields are stored in with [different codecs](fastfield_codecs). The best codec is detected
//! automatically, when serializing.
//!
//! Read access performance is comparable to that of an array lookup.
use std::net::Ipv6Addr;
use fastfield_codecs::MonotonicallyMappableToU64;
pub use self::alive_bitset::{intersect_alive_bitsets, write_alive_bitset, AliveBitSet};
@@ -30,7 +28,7 @@ pub use self::facet_reader::FacetReader;
pub(crate) use self::multivalued::{get_fastfield_codecs_for_multivalue, MultivalueStartIndex};
pub use self::multivalued::{
MultiValueIndex, MultiValueU128FastFieldWriter, MultiValuedFastFieldReader,
MultiValuedFastFieldWriter,
MultiValuedFastFieldWriter, MultiValuedU128FastFieldReader,
};
pub(crate) use self::readers::type_and_cardinality;
pub use self::readers::FastFieldReaders;
@@ -49,33 +47,6 @@ mod readers;
mod serializer;
mod writer;
/// Trait for types that provide a zero value.
///
/// The resulting value is never used, just as placeholder, e.g. for `vec.resize()`.
pub trait MakeZero {
/// Build a default value. This default value is never used, so the value does not
/// really matter.
fn make_zero() -> Self;
}
impl<T: FastValue> MakeZero for T {
fn make_zero() -> Self {
T::from_u64(0)
}
}
impl MakeZero for u128 {
fn make_zero() -> Self {
0
}
}
impl MakeZero for Ipv6Addr {
fn make_zero() -> Self {
Ipv6Addr::from(0u128.to_be_bytes())
}
}
/// Trait for types that are allowed for fast fields:
/// (u64, i64 and f64, bool, DateTime).
pub trait FastValue:
@@ -83,6 +54,12 @@ pub trait FastValue:
{
/// Returns the `schema::Type` for this FastValue.
fn to_type() -> Type;
/// 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)
}
}
impl FastValue for u64 {
@@ -124,6 +101,12 @@ impl FastValue for DateTime {
fn to_type() -> Type {
Type::Date
}
fn make_zero() -> Self {
DateTime {
timestamp_micros: 0,
}
}
}
fn value_to_u64(value: &Value) -> crate::Result<u64> {
@@ -162,7 +145,7 @@ impl FastFieldType {
mod tests {
use std::collections::HashMap;
use std::ops::{Range, RangeInclusive};
use std::ops::Range;
use std::path::Path;
use std::sync::Arc;
@@ -176,9 +159,7 @@ mod tests {
use super::*;
use crate::directory::{CompositeFile, Directory, RamDirectory, WritePtr};
use crate::merge_policy::NoMergePolicy;
use crate::schema::{
Cardinality, Document, Field, Schema, SchemaBuilder, FAST, INDEXED, STRING, TEXT,
};
use crate::schema::{Cardinality, Document, Field, Schema, SchemaBuilder, FAST, STRING, TEXT};
use crate::time::OffsetDateTime;
use crate::{DateOptions, DatePrecision, Index, SegmentId, SegmentReader};
@@ -539,6 +520,11 @@ mod tests {
Ok(())
}
#[test]
fn test_default_date() {
assert_eq!(0, DateTime::make_zero().into_timestamp_secs());
}
fn get_vals_for_docs(ff: &MultiValuedFastFieldReader<u64>, docs: Range<u32>) -> Vec<u64> {
let mut all = vec![];
@@ -983,117 +969,4 @@ mod tests {
}
Ok(len)
}
#[test]
fn test_gcd_bug_regression_1757() {
let mut schema_builder = Schema::builder();
let num_field = schema_builder.add_u64_field("url_norm_hash", FAST | INDEXED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_for_tests().unwrap();
writer
.add_document(doc! {
num_field => 100u64,
})
.unwrap();
writer
.add_document(doc! {
num_field => 200u64,
})
.unwrap();
writer
.add_document(doc! {
num_field => 300u64,
})
.unwrap();
writer.commit().unwrap();
}
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let segment = &searcher.segment_readers()[0];
let field = segment.fast_fields().u64(num_field).unwrap();
let numbers = vec![100, 200, 300];
let test_range = |range: RangeInclusive<u64>| {
let expexted_count = numbers.iter().filter(|num| range.contains(num)).count();
let mut vec = vec![];
field.get_docids_for_value_range(range, 0..u32::MAX, &mut vec);
assert_eq!(vec.len(), expexted_count);
};
test_range(50..=50);
test_range(150..=150);
test_range(350..=350);
test_range(100..=250);
test_range(101..=200);
test_range(101..=199);
test_range(100..=300);
test_range(100..=299);
}
#[test]
fn test_mapping_bug_docids_for_value_range() {
let mut schema_builder = Schema::builder();
let num_field = schema_builder.add_u64_field("url_norm_hash", FAST | INDEXED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
// Values without gcd, but with min_value
let mut writer = index.writer_for_tests().unwrap();
writer
.add_document(doc! {
num_field => 1000u64,
})
.unwrap();
writer
.add_document(doc! {
num_field => 1001u64,
})
.unwrap();
writer
.add_document(doc! {
num_field => 1003u64,
})
.unwrap();
writer.commit().unwrap();
}
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let segment = &searcher.segment_readers()[0];
let field = segment.fast_fields().u64(num_field).unwrap();
let numbers = vec![1000, 1001, 1003];
let test_range = |range: RangeInclusive<u64>| {
let expexted_count = numbers.iter().filter(|num| range.contains(num)).count();
let mut vec = vec![];
field.get_docids_for_value_range(range, 0..u32::MAX, &mut vec);
assert_eq!(vec.len(), expexted_count);
};
let test_range_variant = |start, stop| {
let start_range = start..=stop;
test_range(start_range);
let start_range = start..=(stop - 1);
test_range(start_range);
let start_range = start..=(stop + 1);
test_range(start_range);
let start_range = (start - 1)..=stop;
test_range(start_range);
let start_range = (start - 1)..=(stop - 1);
test_range(start_range);
let start_range = (start - 1)..=(stop + 1);
test_range(start_range);
let start_range = (start + 1)..=stop;
test_range(start_range);
let start_range = (start + 1)..=(stop - 1);
test_range(start_range);
let start_range = (start + 1)..=(stop + 1);
test_range(start_range);
};
test_range_variant(50, 50);
test_range_variant(1000, 1000);
test_range_variant(1000, 1002);
}
}

View File

@@ -80,7 +80,6 @@ impl MultiValueIndex {
///
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
/// match a docid to its value position.
#[allow(clippy::bool_to_int_with_if)]
pub(crate) fn positions_to_docids(&self, doc_id_range: Range<u32>, positions: &mut Vec<u32>) {
if positions.is_empty() {
return;

View File

@@ -5,7 +5,7 @@ mod writer;
use fastfield_codecs::FastFieldCodecType;
pub use index::MultiValueIndex;
pub use self::reader::MultiValuedFastFieldReader;
pub use self::reader::{MultiValuedFastFieldReader, MultiValuedU128FastFieldReader};
pub(crate) use self::writer::MultivalueStartIndex;
pub use self::writer::{MultiValueU128FastFieldWriter, MultiValuedFastFieldWriter};
@@ -525,7 +525,7 @@ mod bench {
serializer.close().unwrap();
field
};
let file = directory.open_read(path).unwrap();
let file = directory.open_read(&path).unwrap();
{
let fast_fields_composite = CompositeFile::open(&file).unwrap();
let data_idx = fast_fields_composite

View File

@@ -1,31 +1,107 @@
use core::fmt;
use std::ops::{Range, RangeInclusive};
use std::sync::Arc;
use fastfield_codecs::Column;
use fastfield_codecs::{Column, MonotonicallyMappableToU128};
use super::MultiValueIndex;
use crate::fastfield::MakeZero;
use crate::fastfield::FastValue;
use crate::DocId;
/// Reader for a multivalued fast field.
/// Reader for a multivalued `u64` fast field.
///
/// The reader is implemented as two fast fields, one u64 fast field for the index and one for the
/// values.
/// The reader is implemented as two `u64` fast field.
///
/// The `vals_reader` will access the concatenated list of all values.
/// The `idx_reader` associates, for each document, the index of its first value.
/// The `vals_reader` will access the concatenated list of all
/// values for all reader.
/// The `idx_reader` associated, for each document, the index of its first value.
/// Stores the start position for each document.
#[derive(Clone)]
pub struct MultiValuedFastFieldReader<T> {
pub struct MultiValuedFastFieldReader<Item: FastValue> {
idx_reader: MultiValueIndex,
vals_reader: Arc<dyn Column<Item>>,
}
impl<Item: FastValue> MultiValuedFastFieldReader<Item> {
pub(crate) fn open(
idx_reader: Arc<dyn Column<u64>>,
vals_reader: Arc<dyn Column<Item>>,
) -> MultiValuedFastFieldReader<Item> {
MultiValuedFastFieldReader {
idx_reader: MultiValueIndex::new(idx_reader),
vals_reader,
}
}
/// Returns the array of values associated with the given `doc`.
#[inline]
fn get_vals_for_range(&self, range: Range<u32>, vals: &mut Vec<Item>) {
let len = (range.end - range.start) as usize;
vals.resize(len, Item::make_zero());
self.vals_reader
.get_range(range.start as u64, &mut vals[..]);
}
/// Returns the array of values associated with the given `doc`.
#[inline]
pub fn get_vals(&self, doc: DocId, vals: &mut Vec<Item>) {
let range = self.idx_reader.range(doc);
self.get_vals_for_range(range, vals);
}
/// returns the multivalue index
pub fn get_index_reader(&self) -> &MultiValueIndex {
&self.idx_reader
}
/// Returns the minimum value for this fast field.
///
/// 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.
pub fn min_value(&self) -> Item {
self.vals_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.
pub fn max_value(&self) -> Item {
self.vals_reader.max_value()
}
/// Returns the number of values associated with the document `DocId`.
#[inline]
pub fn num_vals(&self, doc: DocId) -> u32 {
self.idx_reader.num_vals_for_doc(doc)
}
/// Returns the overall number of values in this field.
#[inline]
pub fn total_num_vals(&self) -> u32 {
self.idx_reader.total_num_vals()
}
}
/// Reader for a multivalued `u128` fast field.
///
/// The reader is implemented as a `u64` fast field for the index and a `u128` fast field.
///
/// The `vals_reader` will access the concatenated list of all
/// values for all reader.
/// The `idx_reader` associated, for each document, the index of its first value.
#[derive(Clone)]
pub struct MultiValuedU128FastFieldReader<T: MonotonicallyMappableToU128> {
idx_reader: MultiValueIndex,
vals_reader: Arc<dyn Column<T>>,
}
impl<T: PartialOrd + MakeZero + Copy + fmt::Debug> MultiValuedFastFieldReader<T> {
impl<T: MonotonicallyMappableToU128> MultiValuedU128FastFieldReader<T> {
pub(crate) fn open(
idx_reader: Arc<dyn Column<u64>>,
vals_reader: Arc<dyn Column<T>>,
) -> MultiValuedFastFieldReader<T> {
) -> MultiValuedU128FastFieldReader<T> {
Self {
idx_reader: MultiValueIndex::new(idx_reader),
vals_reader,
@@ -46,7 +122,7 @@ impl<T: PartialOrd + MakeZero + Copy + fmt::Debug> MultiValuedFastFieldReader<T>
#[inline]
fn get_vals_for_range(&self, range: Range<u32>, vals: &mut Vec<T>) {
let len = (range.end - range.start) as usize;
vals.resize(len, T::make_zero());
vals.resize(len, T::from_u128(0));
self.vals_reader
.get_range(range.start as u64, &mut vals[..]);
}
@@ -123,131 +199,8 @@ impl<T: PartialOrd + MakeZero + Copy + fmt::Debug> MultiValuedFastFieldReader<T>
#[cfg(test)]
mod tests {
use time::{Duration, OffsetDateTime};
use crate::collector::Count;
use crate::core::Index;
use crate::query::RangeQuery;
use crate::schema::{Cardinality, Facet, FacetOptions, NumericOptions, Schema};
use crate::{DateOptions, DatePrecision, DateTime};
#[test]
fn test_multivalued_date_docids_for_value_range_1() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field(
"multi_date_field",
DateOptions::default()
.set_fast(Cardinality::MultiValues)
.set_indexed()
.set_fieldnorm()
.set_precision(DatePrecision::Microseconds)
.set_stored(),
);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_for_tests()?;
let first_time_stamp = OffsetDateTime::now_utc();
index_writer.add_document(doc!(
date_field => DateTime::from_utc(first_time_stamp),
date_field => DateTime::from_utc(first_time_stamp),
))?;
// add another second
let two_secs_ahead = first_time_stamp + Duration::seconds(2);
index_writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
let reader = searcher.segment_reader(0);
let date_ff_reader = reader.fast_fields().dates(date_field).unwrap();
let mut docids = vec![];
date_ff_reader.get_docids_for_value_range(
DateTime::from_utc(first_time_stamp)..=DateTime::from_utc(two_secs_ahead),
0..5,
&mut docids,
);
assert_eq!(docids, vec![0]);
let count_multiples =
|range_query: RangeQuery| searcher.search(&range_query, &Count).unwrap();
assert_eq!(
count_multiples(RangeQuery::new_date(
date_field,
DateTime::from_utc(first_time_stamp)..DateTime::from_utc(two_secs_ahead)
)),
1
);
Ok(())
}
#[test]
fn test_multivalued_date_docids_for_value_range_2() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field(
"multi_date_field",
DateOptions::default()
.set_fast(Cardinality::MultiValues)
// TODO: Test different precision after fixing https://github.com/quickwit-oss/tantivy/issues/1783
.set_precision(DatePrecision::Microseconds)
.set_indexed()
.set_fieldnorm()
.set_stored(),
);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_for_tests()?;
let first_time_stamp = OffsetDateTime::now_utc();
index_writer.add_document(doc!(
date_field => DateTime::from_utc(first_time_stamp),
date_field => DateTime::from_utc(first_time_stamp),
))?;
index_writer.add_document(doc!())?;
// add one second
index_writer.add_document(doc!(
date_field => DateTime::from_utc(first_time_stamp + Duration::seconds(1)),
))?;
// add another second
let two_secs_ahead = first_time_stamp + Duration::seconds(2);
index_writer.add_document(doc!(
date_field => DateTime::from_utc(two_secs_ahead),
date_field => DateTime::from_utc(two_secs_ahead),
date_field => DateTime::from_utc(two_secs_ahead),
))?;
// add three seconds
index_writer.add_document(doc!(
date_field => DateTime::from_utc(first_time_stamp + Duration::seconds(3)),
))?;
index_writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
let reader = searcher.segment_reader(0);
assert_eq!(reader.num_docs(), 5);
let date_ff_reader = reader.fast_fields().dates(date_field).unwrap();
let mut docids = vec![];
date_ff_reader.get_docids_for_value_range(
DateTime::from_utc(first_time_stamp)..=DateTime::from_utc(two_secs_ahead),
0..5,
&mut docids,
);
assert_eq!(docids, vec![0, 2, 3]);
let count_multiples =
|range_query: RangeQuery| searcher.search(&range_query, &Count).unwrap();
assert_eq!(
count_multiples(RangeQuery::new_date(
date_field,
DateTime::from_utc(first_time_stamp)..DateTime::from_utc(two_secs_ahead)
)),
2
);
Ok(())
}
#[test]
fn test_multifastfield_reader() -> crate::Result<()> {

View File

@@ -3,9 +3,11 @@ use std::sync::Arc;
use fastfield_codecs::{open, open_u128, Column};
use super::multivalued::MultiValuedFastFieldReader;
use super::multivalued::MultiValuedU128FastFieldReader;
use crate::directory::{CompositeFile, FileSlice};
use crate::fastfield::{BytesFastFieldReader, FastFieldNotAvailableError, FastValue};
use crate::fastfield::{
BytesFastFieldReader, FastFieldNotAvailableError, FastValue, MultiValuedFastFieldReader,
};
use crate::schema::{Cardinality, Field, FieldType, Schema};
use crate::space_usage::PerFieldSpaceUsage;
use crate::{DateTime, TantivyError};
@@ -159,14 +161,20 @@ impl FastFieldReaders {
/// Returns the `ip` fast field reader reader associated to `field`.
///
/// If `field` is not a u128 fast field, this method returns an Error.
pub fn ip_addrs(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<Ipv6Addr>> {
pub fn ip_addrs(
&self,
field: Field,
) -> crate::Result<MultiValuedU128FastFieldReader<Ipv6Addr>> {
self.check_type(field, FastType::U128, Cardinality::MultiValues)?;
let idx_reader: Arc<dyn Column<u64>> = self.typed_fast_field_reader(field)?;
let bytes = self.fast_field_data(field, 1)?.read_bytes()?;
let vals_reader = open_u128::<Ipv6Addr>(bytes)?;
Ok(MultiValuedFastFieldReader::open(idx_reader, vals_reader))
Ok(MultiValuedU128FastFieldReader::open(
idx_reader,
vals_reader,
))
}
/// Returns the `u128` fast field reader reader associated to `field`.
@@ -181,14 +189,17 @@ impl FastFieldReaders {
/// Returns the `u128` multi-valued fast field reader reader associated to `field`.
///
/// If `field` is not a u128 multi-valued fast field, this method returns an Error.
pub fn u128s(&self, field: Field) -> crate::Result<MultiValuedFastFieldReader<u128>> {
pub fn u128s(&self, field: Field) -> crate::Result<MultiValuedU128FastFieldReader<u128>> {
self.check_type(field, FastType::U128, Cardinality::MultiValues)?;
let idx_reader: Arc<dyn Column<u64>> = self.typed_fast_field_reader(field)?;
let bytes = self.fast_field_data(field, 1)?.read_bytes()?;
let vals_reader = open_u128::<u128>(bytes)?;
Ok(MultiValuedFastFieldReader::open(idx_reader, vals_reader))
Ok(MultiValuedU128FastFieldReader::open(
idx_reader,
vals_reader,
))
}
/// Returns the `u64` fast field reader reader associated with `field`, regardless of whether

View File

@@ -1,4 +1,3 @@
use std::fmt;
use std::io::{self, Write};
pub use fastfield_codecs::Column;
@@ -50,7 +49,7 @@ impl CompositeFastFieldSerializer {
/// 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 + fmt::Debug>(
pub fn create_auto_detect_u64_fast_field<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
fastfield_accessor: impl Column<T>,
@@ -60,9 +59,7 @@ impl CompositeFastFieldSerializer {
/// 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 + fmt::Debug,
>(
pub fn create_auto_detect_u64_fast_field_with_idx<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
fastfield_accessor: impl Column<T>,
@@ -75,9 +72,7 @@ impl CompositeFastFieldSerializer {
/// Serialize data into a new u64 fast field. The best compression codec of the the provided
/// will be chosen.
pub fn create_auto_detect_u64_fast_field_with_idx_and_codecs<
T: MonotonicallyMappableToU64 + fmt::Debug,
>(
pub fn create_auto_detect_u64_fast_field_with_idx_and_codecs<T: MonotonicallyMappableToU64>(
&mut self,
field: Field,
fastfield_accessor: impl Column<T>,

View File

@@ -678,7 +678,7 @@ impl IndexWriter {
/// only after calling `commit()`.
#[doc(hidden)]
pub fn delete_query(&self, query: Box<dyn Query>) -> crate::Result<Opstamp> {
let weight = query.weight(EnableScoring::disabled_from_schema(&self.index.schema()))?;
let weight = query.weight(EnableScoring::Disabled(&self.index.schema()))?;
let opstamp = self.stamper.stamp();
let delete_operation = DeleteOperation {
opstamp,
@@ -759,8 +759,7 @@ impl IndexWriter {
match user_op {
UserOperation::Delete(term) => {
let query = TermQuery::new(term, IndexRecordOption::Basic);
let weight =
query.weight(EnableScoring::disabled_from_schema(&self.index.schema()))?;
let weight = query.weight(EnableScoring::Disabled(&self.index.schema()))?;
let delete_operation = DeleteOperation {
opstamp,
target: weight,

View File

@@ -89,11 +89,11 @@ pub(crate) fn index_json_values<'a>(
Ok(())
}
fn index_json_object(
fn index_json_object<'a>(
doc: DocId,
json_value: &serde_json::Map<String, serde_json::Value>,
text_analyzer: &TextAnalyzer,
json_term_writer: &mut JsonTermWriter,
json_term_writer: &mut JsonTermWriter<'a>,
postings_writer: &mut dyn PostingsWriter,
ctx: &mut IndexingContext,
positions_per_path: &mut IndexingPositionsPerPath,
@@ -113,11 +113,11 @@ fn index_json_object(
}
}
fn index_json_value(
fn index_json_value<'a>(
doc: DocId,
json_value: &serde_json::Value,
text_analyzer: &TextAnalyzer,
json_term_writer: &mut JsonTermWriter,
json_term_writer: &mut JsonTermWriter<'a>,
postings_writer: &mut dyn PostingsWriter,
ctx: &mut IndexingContext,
positions_per_path: &mut IndexingPositionsPerPath,

View File

@@ -13,7 +13,7 @@ use crate::docset::{DocSet, TERMINATED};
use crate::error::DataCorruption;
use crate::fastfield::{
get_fastfield_codecs_for_multivalue, AliveBitSet, Column, CompositeFastFieldSerializer,
MultiValueIndex, MultiValuedFastFieldReader,
MultiValueIndex, MultiValuedFastFieldReader, MultiValuedU128FastFieldReader,
};
use crate::fieldnorm::{FieldNormReader, FieldNormReaders, FieldNormsSerializer, FieldNormsWriter};
use crate::indexer::doc_id_mapping::{expect_field_id_for_sort_field, SegmentDocIdMapping};
@@ -331,18 +331,18 @@ impl IndexMerger {
fast_field_serializer: &mut CompositeFastFieldSerializer,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
let segment_and_ff_readers: Vec<(&SegmentReader, MultiValuedFastFieldReader<u128>)> = self
.readers
.iter()
.map(|segment_reader| {
let ff_reader: MultiValuedFastFieldReader<u128> =
segment_reader.fast_fields().u128s(field).expect(
"Failed to find index for multivalued field. This is a bug in tantivy, \
please report.",
);
(segment_reader, ff_reader)
})
.collect::<Vec<_>>();
let segment_and_ff_readers: Vec<(&SegmentReader, MultiValuedU128FastFieldReader<u128>)> =
self.readers
.iter()
.map(|segment_reader| {
let ff_reader: MultiValuedU128FastFieldReader<u128> =
segment_reader.fast_fields().u128s(field).expect(
"Failed to find index for multivalued field. This is a bug in \
tantivy, please report.",
);
(segment_reader, ff_reader)
})
.collect::<Vec<_>>();
Self::write_1_n_fast_field_idx_generic(
field,

View File

@@ -577,7 +577,7 @@ impl SegmentUpdater {
for merge_operation in merge_candidates {
// If a merge cannot be started this is not a fatal error.
// We do log a warning in `start_merge`.
drop(self.start_merge(merge_operation));
let _ = self.start_merge(merge_operation);
}
}

View File

@@ -20,7 +20,7 @@ mod atomic_impl {
}
pub fn fetch_add(&self, val: u64, order: Ordering) -> u64 {
self.0.fetch_add(val, order)
self.0.fetch_add(val, order) as u64
}
pub fn revert(&self, val: u64, order: Ordering) -> u64 {

View File

@@ -1,14 +1,17 @@
#![doc(html_logo_url = "http://fulmicoton.com/tantivy-logo/tantivy-logo.png")]
#![cfg_attr(all(feature = "unstable", test), feature(test))]
#![cfg_attr(
feature = "cargo-clippy",
allow(
clippy::module_inception,
clippy::needless_range_loop,
clippy::bool_assert_comparison
)
)]
#![doc(test(attr(allow(unused_variables), deny(warnings))))]
#![warn(missing_docs)]
#![allow(
clippy::len_without_is_empty,
clippy::derive_partial_eq_without_eq,
clippy::module_inception,
clippy::needless_range_loop,
clippy::bool_assert_comparison
)]
#![allow(clippy::len_without_is_empty)]
#![allow(clippy::derive_partial_eq_without_eq)]
//! # `tantivy`
//!
@@ -141,7 +144,7 @@ use crate::time::{OffsetDateTime, PrimitiveDateTime, UtcOffset};
/// All constructors and conversions are provided as explicit
/// functions and not by implementing any `From`/`Into` traits
/// to prevent unintended usage.
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord)]
#[derive(Clone, Copy, PartialEq, Eq, PartialOrd, Ord)]
pub struct DateTime {
// Timestamp in microseconds.
pub(crate) timestamp_micros: i64,

View File

@@ -291,7 +291,7 @@ pub mod tests {
const PADDING_VALUE: u32 = 234_234_345u32;
let expected_length = 154;
let mut encoder = BlockEncoder::new();
let input: Vec<u32> = (0u32..123u32).map(|i| 4 + i * 7 / 2).collect();
let input: Vec<u32> = (0u32..123u32).map(|i| 4 + i * 7 / 2).into_iter().collect();
for offset in &[0u32, 1u32, 2u32] {
let encoded_data = encoder.compress_vint_sorted(&input, *offset);
assert!(encoded_data.len() <= expected_length);

View File

@@ -631,7 +631,7 @@ mod bench {
let mut segment_postings = segment_reader
.inverted_index(TERM_A.field())
.unwrap()
.read_postings(&TERM_A, IndexRecordOption::Basic)
.read_postings(&*TERM_A, IndexRecordOption::Basic)
.unwrap()
.unwrap();
while segment_postings.advance() != TERMINATED {}
@@ -647,25 +647,25 @@ mod bench {
let segment_postings_a = segment_reader
.inverted_index(TERM_A.field())
.unwrap()
.read_postings(&TERM_A, IndexRecordOption::Basic)
.read_postings(&*TERM_A, IndexRecordOption::Basic)
.unwrap()
.unwrap();
let segment_postings_b = segment_reader
.inverted_index(TERM_B.field())
.unwrap()
.read_postings(&TERM_B, IndexRecordOption::Basic)
.read_postings(&*TERM_B, IndexRecordOption::Basic)
.unwrap()
.unwrap();
let segment_postings_c = segment_reader
.inverted_index(TERM_C.field())
.unwrap()
.read_postings(&TERM_C, IndexRecordOption::Basic)
.read_postings(&*TERM_C, IndexRecordOption::Basic)
.unwrap()
.unwrap();
let segment_postings_d = segment_reader
.inverted_index(TERM_D.field())
.unwrap()
.read_postings(&TERM_D, IndexRecordOption::Basic)
.read_postings(&*TERM_D, IndexRecordOption::Basic)
.unwrap()
.unwrap();
let mut intersection = Intersection::new(vec![
@@ -687,7 +687,7 @@ mod bench {
let mut segment_postings = segment_reader
.inverted_index(TERM_A.field())
.unwrap()
.read_postings(&TERM_A, IndexRecordOption::Basic)
.read_postings(&*TERM_A, IndexRecordOption::Basic)
.unwrap()
.unwrap();
@@ -705,7 +705,7 @@ mod bench {
let mut segment_postings = segment_reader
.inverted_index(TERM_A.field())
.unwrap()
.read_postings(&TERM_A, IndexRecordOption::Basic)
.read_postings(&*TERM_A, IndexRecordOption::Basic)
.unwrap()
.unwrap();
for doc in &existing_docs {
@@ -746,7 +746,7 @@ mod bench {
let mut segment_postings = segment_reader
.inverted_index(TERM_A.field())
.unwrap()
.read_postings(&TERM_A, IndexRecordOption::Basic)
.read_postings(&*TERM_A, IndexRecordOption::Basic)
.unwrap()
.unwrap();
let mut s = 0u32;

View File

@@ -213,21 +213,21 @@ impl<'a> FieldSerializer<'a> {
fail_point!("FieldSerializer::close_term", |msg: Option<String>| {
Err(io::Error::new(io::ErrorKind::Other, format!("{:?}", msg)))
});
if self.term_open {
self.postings_serializer
.close_term(self.current_term_info.doc_freq)?;
self.current_term_info.postings_range.end =
self.postings_serializer.written_bytes() as usize;
if let Some(positions_serializer) = self.positions_serializer_opt.as_mut() {
positions_serializer.close_term()?;
self.current_term_info.positions_range.end =
positions_serializer.written_bytes() as usize;
}
self.term_dictionary_builder
.insert_value(&self.current_term_info)?;
self.term_open = false;
if !self.term_open {
return Ok(());
}
self.postings_serializer
.close_term(self.current_term_info.doc_freq)?;
self.current_term_info.postings_range.end =
self.postings_serializer.written_bytes() as usize;
if let Some(positions_serializer) = self.positions_serializer_opt.as_mut() {
positions_serializer.close_term()?;
self.current_term_info.positions_range.end =
positions_serializer.written_bytes() as usize;
}
self.term_dictionary_builder
.insert_value(&self.current_term_info)?;
self.term_open = false;
Ok(())
}

View File

@@ -95,7 +95,7 @@ mod tests {
let index = create_test_index()?;
let reader = index.reader()?;
let searcher = reader.searcher();
let weight = AllQuery.weight(EnableScoring::disabled_from_schema(&index.schema()))?;
let weight = AllQuery.weight(EnableScoring::Disabled(&index.schema()))?;
{
let reader = searcher.segment_reader(0);
let mut scorer = weight.scorer(reader, 1.0)?;
@@ -118,7 +118,7 @@ mod tests {
let index = create_test_index()?;
let reader = index.reader()?;
let searcher = reader.searcher();
let weight = AllQuery.weight(EnableScoring::disabled_from_schema(searcher.schema()))?;
let weight = AllQuery.weight(EnableScoring::Disabled(searcher.schema()))?;
let reader = searcher.segment_reader(0);
{
let mut scorer = weight.scorer(reader, 2.0)?;

View File

@@ -146,7 +146,7 @@ impl Query for BooleanQuery {
let sub_weights = self
.subqueries
.iter()
.map(|(occur, subquery)| Ok((*occur, subquery.weight(enable_scoring)?)))
.map(|&(ref occur, ref subquery)| Ok((*occur, subquery.weight(enable_scoring)?)))
.collect::<crate::Result<_>>()?;
Ok(Box::new(BooleanWeight::new(
sub_weights,

View File

@@ -91,7 +91,7 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
boost: Score,
) -> crate::Result<HashMap<Occur, Vec<Box<dyn Scorer>>>> {
let mut per_occur_scorers: HashMap<Occur, Vec<Box<dyn Scorer>>> = HashMap::new();
for (occur, subweight) in &self.weights {
for &(ref occur, ref subweight) in &self.weights {
let sub_scorer: Box<dyn Scorer> = subweight.scorer(reader, boost)?;
per_occur_scorers
.entry(*occur)
@@ -191,7 +191,7 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
}
let mut explanation = Explanation::new("BooleanClause. Sum of ...", scorer.score());
for (occur, subweight) in &self.weights {
for &(ref occur, ref subweight) in &self.weights {
if is_positive_occur(*occur) {
if let Ok(child_explanation) = subweight.explain(reader, doc) {
explanation.add_detail(child_explanation);

View File

@@ -98,7 +98,7 @@ mod tests {
}
{
let query = query_parser.parse_query("+a b")?;
let weight = query.weight(EnableScoring::disabled_from_schema(searcher.schema()))?;
let weight = query.weight(EnableScoring::Disabled(searcher.schema()))?;
let scorer = weight.scorer(searcher.segment_reader(0u32), 1.0)?;
assert!(scorer.is::<TermScorer>());
}

View File

@@ -3,7 +3,7 @@ use tantivy_query_grammar::Occur;
use crate::query::{BooleanWeight, DisjunctionMaxCombiner, EnableScoring, Query, Weight};
use crate::{Score, Term};
/// The disjunction max query returns documents matching one or more wrapped queries,
/// The disjunction max query кeturns documents matching one or more wrapped queries,
/// called query clauses or clauses.
///
/// If a returned document matches multiple query clauses,

View File

@@ -1,5 +1,8 @@
use std::collections::HashMap;
use std::ops::Range;
use levenshtein_automata::{Distance, LevenshteinAutomatonBuilder, DFA};
use once_cell::sync::OnceCell;
use once_cell::sync::Lazy;
use tantivy_fst::Automaton;
use crate::query::{AutomatonWeight, EnableScoring, Query, Weight};
@@ -31,6 +34,22 @@ impl Automaton for DfaWrapper {
}
}
/// A range of Levenshtein distances that we will build DFAs for our terms
/// The computation is exponential, so best keep it to low single digits
const VALID_LEVENSHTEIN_DISTANCE_RANGE: Range<u8> = 0..3;
static LEV_BUILDER: Lazy<HashMap<(u8, bool), LevenshteinAutomatonBuilder>> = Lazy::new(|| {
let mut lev_builder_cache = HashMap::new();
// TODO make population lazy on a `(distance, val)` basis
for distance in VALID_LEVENSHTEIN_DISTANCE_RANGE {
for &transposition in &[false, true] {
let lev_automaton_builder = LevenshteinAutomatonBuilder::new(distance, transposition);
lev_builder_cache.insert((distance, transposition), lev_automaton_builder);
}
}
lev_builder_cache
});
/// A Fuzzy Query matches all of the documents
/// containing a specific term that is within
/// Levenshtein distance
@@ -110,39 +129,30 @@ impl FuzzyTermQuery {
}
fn specialized_weight(&self) -> crate::Result<AutomatonWeight<DfaWrapper>> {
static AUTOMATON_BUILDER: [[OnceCell<LevenshteinAutomatonBuilder>; 2]; 3] = [
[OnceCell::new(), OnceCell::new()],
[OnceCell::new(), OnceCell::new()],
[OnceCell::new(), OnceCell::new()],
];
let automaton_builder = AUTOMATON_BUILDER
.get(self.distance as usize)
.ok_or_else(|| {
InvalidArgument(format!(
"Levenshtein distance of {} is not allowed. Choose a value less than {}",
self.distance,
AUTOMATON_BUILDER.len()
// LEV_BUILDER is a HashMap, whose `get` method returns an Option
match LEV_BUILDER.get(&(self.distance, self.transposition_cost_one)) {
// Unwrap the option and build the Ok(AutomatonWeight)
Some(automaton_builder) => {
let term_text = self.term.as_str().ok_or_else(|| {
crate::TantivyError::InvalidArgument(
"The fuzzy term query requires a string term.".to_string(),
)
})?;
let automaton = if self.prefix {
automaton_builder.build_prefix_dfa(term_text)
} else {
automaton_builder.build_dfa(term_text)
};
Ok(AutomatonWeight::new(
self.term.field(),
DfaWrapper(automaton),
))
})?
.get(self.transposition_cost_one as usize)
.unwrap()
.get_or_init(|| {
LevenshteinAutomatonBuilder::new(self.distance, self.transposition_cost_one)
});
let term_text = self.term.as_str().ok_or_else(|| {
InvalidArgument("The fuzzy term query requires a string term.".to_string())
})?;
let automaton = if self.prefix {
automaton_builder.build_prefix_dfa(term_text)
} else {
automaton_builder.build_dfa(term_text)
};
Ok(AutomatonWeight::new(
self.term.field(),
DfaWrapper(automaton),
))
}
None => Err(InvalidArgument(format!(
"Levenshtein distance of {} is not allowed. Choose a value in the {:?} range",
self.distance, VALID_LEVENSHTEIN_DISTANCE_RANGE
))),
}
}
}

View File

@@ -16,6 +16,7 @@ mod phrase_query;
mod query;
mod query_parser;
mod range_query;
mod range_query_ip_fastfield;
mod regex_query;
mod reqopt_scorer;
mod scorer;

View File

@@ -45,7 +45,7 @@ impl Query for MoreLikeThisQuery {
fn weight(&self, enable_scoring: EnableScoring<'_>) -> crate::Result<Box<dyn Weight>> {
let searcher = match enable_scoring {
EnableScoring::Enabled(searcher) => searcher,
EnableScoring::Disabled { .. } => {
EnableScoring::Disabled(_) => {
let err = "MoreLikeThisQuery requires to enable scoring.".to_string();
return Err(crate::TantivyError::InvalidArgument(err));
}

View File

@@ -80,7 +80,7 @@ pub mod tests {
.collect();
let phrase_query = PhraseQuery::new(terms);
let phrase_weight =
phrase_query.phrase_weight(EnableScoring::disabled_from_schema(searcher.schema()))?;
phrase_query.phrase_weight(EnableScoring::Disabled(searcher.schema()))?;
let mut phrase_scorer = phrase_weight.scorer(searcher.segment_reader(0), 1.0)?;
assert_eq!(phrase_scorer.doc(), 1);
assert_eq!(phrase_scorer.advance(), TERMINATED);
@@ -361,7 +361,7 @@ pub mod tests {
let query_parser = QueryParser::for_index(&index, vec![json_field]);
let phrase_query = query_parser.parse_query(query).unwrap();
let phrase_weight = phrase_query
.weight(EnableScoring::disabled_from_schema(searcher.schema()))
.weight(EnableScoring::Disabled(searcher.schema()))
.unwrap();
let mut phrase_scorer = phrase_weight
.scorer(searcher.segment_reader(0), 1.0f32)

View File

@@ -109,7 +109,7 @@ impl PhraseQuery {
let terms = self.phrase_terms();
let bm25_weight_opt = match enable_scoring {
EnableScoring::Enabled(searcher) => Some(Bm25Weight::for_terms(searcher, &terms)?),
EnableScoring::Disabled { .. } => None,
EnableScoring::Disabled(_) => None,
};
let mut weight = PhraseWeight::new(self.phrase_terms.clone(), bm25_weight_opt);
if self.slop > 0 {

View File

@@ -15,55 +15,24 @@ pub enum EnableScoring<'a> {
Enabled(&'a Searcher),
/// Pass this to disable scoring.
/// This can improve performance.
Disabled {
/// Schema is required.
schema: &'a Schema,
/// Searcher should be provided if available.
searcher_opt: Option<&'a Searcher>,
},
Disabled(&'a Schema),
}
impl<'a> EnableScoring<'a> {
/// Create using [Searcher] with scoring enabled.
pub fn enabled_from_searcher(searcher: &'a Searcher) -> EnableScoring<'a> {
EnableScoring::Enabled(searcher)
}
/// Create using [Searcher] with scoring disabled.
pub fn disabled_from_searcher(searcher: &'a Searcher) -> EnableScoring<'a> {
EnableScoring::Disabled {
schema: searcher.schema(),
searcher_opt: Some(searcher),
}
}
/// Create using [Schema] with scoring disabled.
pub fn disabled_from_schema(schema: &'a Schema) -> EnableScoring<'a> {
Self::Disabled {
schema,
searcher_opt: None,
}
}
/// Returns the searcher if available.
pub fn searcher(&self) -> Option<&Searcher> {
match self {
EnableScoring::Enabled(searcher) => Some(searcher),
EnableScoring::Disabled { searcher_opt, .. } => searcher_opt.to_owned(),
}
}
/// Returns the schema.
pub fn schema(&self) -> &Schema {
match self {
EnableScoring::Enabled(searcher) => searcher.schema(),
EnableScoring::Disabled { schema, .. } => schema,
EnableScoring::Disabled(schema) => schema,
}
}
/// Returns true if the scoring is enabled.
pub fn is_scoring_enabled(&self) -> bool {
matches!(self, EnableScoring::Enabled(..))
match self {
EnableScoring::Enabled(_) => true,
EnableScoring::Disabled(_) => false,
}
}
}
@@ -112,14 +81,14 @@ pub trait Query: QueryClone + Send + Sync + downcast_rs::Downcast + fmt::Debug {
/// Returns an `Explanation` for the score of the document.
fn explain(&self, searcher: &Searcher, doc_address: DocAddress) -> crate::Result<Explanation> {
let weight = self.weight(EnableScoring::enabled_from_searcher(searcher))?;
let weight = self.weight(EnableScoring::Enabled(searcher))?;
let reader = searcher.segment_reader(doc_address.segment_ord);
weight.explain(reader, doc_address.doc_id)
}
/// Returns the number of documents matching the query.
fn count(&self, searcher: &Searcher) -> crate::Result<usize> {
let weight = self.weight(EnableScoring::disabled_from_searcher(searcher))?;
let weight = self.weight(EnableScoring::Disabled(searcher.schema()))?;
let mut result = 0;
for reader in searcher.segment_readers() {
result += weight.count(reader)? as usize;

View File

@@ -54,9 +54,9 @@ impl fmt::Debug for LogicalAst {
if clause.is_empty() {
write!(formatter, "<emptyclause>")?;
} else {
let (occur, subquery) = &clause[0];
let (ref occur, ref subquery) = clause[0];
write!(formatter, "({}{:?}", occur_letter(*occur), subquery)?;
for (occur, subquery) in &clause[1..] {
for &(ref occur, ref subquery) in &clause[1..] {
write!(formatter, " {}{:?}", occur_letter(*occur), subquery)?;
}
formatter.write_str(")")?;

View File

@@ -1,11 +1,9 @@
use std::collections::HashMap;
use std::net::{AddrParseError, IpAddr};
use std::num::{ParseFloatError, ParseIntError};
use std::ops::Bound;
use std::str::{FromStr, ParseBoolError};
use base64::engine::general_purpose::STANDARD as BASE64;
use base64::Engine;
use rustc_hash::FxHashMap;
use tantivy_query_grammar::{UserInputAst, UserInputBound, UserInputLeaf, UserInputLiteral};
use super::logical_ast::*;
@@ -13,10 +11,9 @@ use crate::core::Index;
use crate::indexer::{
convert_to_fast_value_and_get_term, set_string_and_get_terms, JsonTermWriter,
};
use crate::query::range_query::is_type_valid_for_fastfield_range_query;
use crate::query::{
AllQuery, BooleanQuery, BoostQuery, EmptyQuery, FuzzyTermQuery, Occur, PhraseQuery, Query,
RangeQuery, TermQuery, TermSetQuery,
AllQuery, BooleanQuery, BoostQuery, EmptyQuery, Occur, PhraseQuery, Query, RangeQuery,
TermQuery, TermSetQuery,
};
use crate::schema::{
Facet, FacetParseError, Field, FieldType, IndexRecordOption, IntoIpv6Addr, JsonObjectOptions,
@@ -37,7 +34,7 @@ pub enum QueryParserError {
#[error("Unsupported query: {0}")]
UnsupportedQuery(String),
/// The query references a field that is not in the schema
#[error("Field does not exist: '{0}'")]
#[error("Field does not exists: '{0}'")]
FieldDoesNotExist(String),
/// The query contains a term for a `u64` or `i64`-field, but the value
/// is neither.
@@ -163,10 +160,6 @@ fn trim_ast(logical_ast: LogicalAst) -> Option<LogicalAst> {
/// word lexicographically between `a` and `c` (inclusive lower bound, exclusive upper bound).
/// Inclusive bounds are `[]`, exclusive are `{}`.
///
/// * set terms: Using the `IN` operator, a field can be matched against a set of literals, e.g.
/// `title: IN [a b cd]` will match documents where `title` is either `a`, `b` or `cd`, but do so
/// more efficiently than the alternative query `title:a OR title:b OR title:c` does.
///
/// * date values: The query parser supports rfc3339 formatted dates. For example
/// `"2002-10-02T15:00:00.05Z"` or `some_date_field:[2002-10-02T15:00:00Z TO
/// 2002-10-02T18:00:00Z}`
@@ -181,9 +174,6 @@ fn trim_ast(logical_ast: LogicalAst) -> Option<LogicalAst> {
/// (See [`set_field_boost(...)`](QueryParser::set_field_boost)). Typically you may want to boost a
/// title field.
///
/// Additionally, specific fields can be marked to use fuzzy term queries for each literal
/// via the [`QueryParser::set_field_fuzzy`] method.
///
/// 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"`.
#[derive(Clone)]
@@ -192,15 +182,7 @@ pub struct QueryParser {
default_fields: Vec<Field>,
conjunction_by_default: bool,
tokenizer_manager: TokenizerManager,
boost: FxHashMap<Field, Score>,
fuzzy: FxHashMap<Field, Fuzzy>,
}
#[derive(Clone)]
struct Fuzzy {
prefix: bool,
distance: u8,
transpose_cost_one: bool,
boost: HashMap<Field, Score>,
}
fn all_negative(ast: &LogicalAst) -> bool {
@@ -228,7 +210,6 @@ impl QueryParser {
tokenizer_manager,
conjunction_by_default: false,
boost: Default::default(),
fuzzy: Default::default(),
}
}
@@ -266,30 +247,6 @@ impl QueryParser {
self.boost.insert(field, boost);
}
/// Sets the given [field][`Field`] to use [fuzzy term queries][`FuzzyTermQuery`]
///
/// If set, the parse will produce queries using fuzzy term queries
/// with the given parameters for each literal matched against the given field.
///
/// See the [`FuzzyTermQuery::new`] and [`FuzzyTermQuery::new_prefix`] methods
/// for the meaning of the individual parameters.
pub fn set_field_fuzzy(
&mut self,
field: Field,
prefix: bool,
distance: u8,
transpose_cost_one: bool,
) {
self.fuzzy.insert(
field,
Fuzzy {
prefix,
distance,
transpose_cost_one,
},
);
}
/// Parse a query
///
/// Note that `parse_query` returns an error if the input
@@ -302,7 +259,7 @@ impl QueryParser {
/// in [Issue 5](https://github.com/fulmicoton/tantivy/issues/5)
pub fn parse_query(&self, query: &str) -> Result<Box<dyn Query>, QueryParserError> {
let logical_ast = self.parse_query_to_logical_ast(query)?;
Ok(convert_to_query(&self.fuzzy, logical_ast))
Ok(convert_to_query(logical_ast))
}
/// Parse the user query into an AST.
@@ -336,10 +293,9 @@ impl QueryParser {
) -> Result<Term, QueryParserError> {
let field_entry = self.schema.get_field_entry(field);
let field_type = field_entry.field_type();
let field_supports_ff_range_queries = field_type.is_fast()
&& is_type_valid_for_fastfield_range_query(field_type.value_type());
if !field_type.is_indexed() && !field_supports_ff_range_queries {
let is_ip_and_fast = field_type.is_ip_addr() && field_type.is_fast();
if !field_type.is_indexed() && !is_ip_and_fast {
return Err(QueryParserError::FieldNotIndexed(
field_entry.name().to_string(),
));
@@ -407,9 +363,7 @@ impl QueryParser {
Err(e) => Err(QueryParserError::from(e)),
},
FieldType::Bytes(_) => {
let bytes = BASE64
.decode(phrase)
.map_err(QueryParserError::ExpectedBase64)?;
let bytes = base64::decode(phrase).map_err(QueryParserError::ExpectedBase64)?;
Ok(Term::from_field_bytes(field, &bytes))
}
FieldType::IpAddr(_) => {
@@ -504,9 +458,7 @@ impl QueryParser {
Err(e) => Err(QueryParserError::from(e)),
},
FieldType::Bytes(_) => {
let bytes = BASE64
.decode(phrase)
.map_err(QueryParserError::ExpectedBase64)?;
let bytes = base64::decode(phrase).map_err(QueryParserError::ExpectedBase64)?;
let bytes_term = Term::from_field_bytes(field, &bytes);
Ok(vec![LogicalLiteral::Term(bytes_term)])
}
@@ -708,30 +660,9 @@ impl QueryParser {
}
}
fn convert_literal_to_query(
fuzzy: &FxHashMap<Field, Fuzzy>,
logical_literal: LogicalLiteral,
) -> Box<dyn Query> {
fn convert_literal_to_query(logical_literal: LogicalLiteral) -> Box<dyn Query> {
match logical_literal {
LogicalLiteral::Term(term) => {
if let Some(fuzzy) = fuzzy.get(&term.field()) {
if fuzzy.prefix {
Box::new(FuzzyTermQuery::new_prefix(
term,
fuzzy.distance,
fuzzy.transpose_cost_one,
))
} else {
Box::new(FuzzyTermQuery::new(
term,
fuzzy.distance,
fuzzy.transpose_cost_one,
))
}
} else {
Box::new(TermQuery::new(term, IndexRecordOption::WithFreqs))
}
}
LogicalLiteral::Term(term) => Box::new(TermQuery::new(term, IndexRecordOption::WithFreqs)),
LogicalLiteral::Phrase(term_with_offsets, slop) => Box::new(
PhraseQuery::new_with_offset_and_slop(term_with_offsets, slop),
),
@@ -824,12 +755,12 @@ fn generate_literals_for_json_object(
Ok(logical_literals)
}
fn convert_to_query(fuzzy: &FxHashMap<Field, Fuzzy>, logical_ast: LogicalAst) -> Box<dyn Query> {
fn convert_to_query(logical_ast: LogicalAst) -> Box<dyn Query> {
match trim_ast(logical_ast) {
Some(LogicalAst::Clause(trimmed_clause)) => {
let occur_subqueries = trimmed_clause
.into_iter()
.map(|(occur, subquery)| (occur, convert_to_query(fuzzy, subquery)))
.map(|(occur, subquery)| (occur, convert_to_query(subquery)))
.collect::<Vec<_>>();
assert!(
!occur_subqueries.is_empty(),
@@ -838,10 +769,10 @@ fn convert_to_query(fuzzy: &FxHashMap<Field, Fuzzy>, logical_ast: LogicalAst) ->
Box::new(BooleanQuery::new(occur_subqueries))
}
Some(LogicalAst::Leaf(trimmed_logical_literal)) => {
convert_literal_to_query(fuzzy, *trimmed_logical_literal)
convert_literal_to_query(*trimmed_logical_literal)
}
Some(LogicalAst::Boost(ast, boost)) => {
let query = convert_to_query(fuzzy, *ast);
let query = convert_to_query(*ast);
let boosted_query = BoostQuery::new(query, boost);
Box::new(boosted_query)
}
@@ -857,7 +788,7 @@ mod test {
use super::{QueryParser, QueryParserError};
use crate::query::Query;
use crate::schema::{
FacetOptions, Field, IndexRecordOption, Schema, Term, TextFieldIndexing, TextOptions, FAST,
FacetOptions, Field, IndexRecordOption, Schema, Term, TextFieldIndexing, TextOptions,
INDEXED, STORED, STRING, TEXT,
};
use crate::tokenizer::{
@@ -891,7 +822,6 @@ mod test {
schema_builder.add_json_field("json_not_indexed", STORED);
schema_builder.add_bool_field("bool", INDEXED);
schema_builder.add_bool_field("notindexed_bool", STORED);
schema_builder.add_u64_field("u64_ff", FAST);
schema_builder.build()
}
@@ -1347,11 +1277,6 @@ mod test {
r#"(Excluded(Term(type=F64, field=10, -1.5)) TO Excluded(Term(type=F64, field=10, 1.5)))"#,
false,
);
test_parse_query_to_logical_ast_helper(
"u64_ff:[7 TO 77]",
r#"(Included(Term(type=U64, field=18, 7)) TO Included(Term(type=U64, field=18, 77)))"#,
false,
);
}
#[test]
@@ -1643,41 +1568,4 @@ mod test {
false,
);
}
#[test]
pub fn test_set_field_fuzzy() {
{
let mut query_parser = make_query_parser();
query_parser.set_field_fuzzy(
query_parser.schema.get_field("title").unwrap(),
false,
1,
true,
);
let query = query_parser.parse_query("abc").unwrap();
assert_eq!(
format!("{:?}", query),
"BooleanQuery { subqueries: [(Should, FuzzyTermQuery { term: Term(type=Str, \
field=0, \"abc\"), distance: 1, transposition_cost_one: true, prefix: false }), \
(Should, TermQuery(Term(type=Str, field=1, \"abc\")))] }"
);
}
{
let mut query_parser = make_query_parser();
query_parser.set_field_fuzzy(
query_parser.schema.get_field("text").unwrap(),
true,
2,
false,
);
let query = query_parser.parse_query("abc").unwrap();
assert_eq!(
format!("{:?}", query),
"BooleanQuery { subqueries: [(Should, TermQuery(Term(type=Str, field=0, \
\"abc\"))), (Should, FuzzyTermQuery { term: Term(type=Str, field=1, \"abc\"), \
distance: 2, transposition_cost_one: false, prefix: true })] }"
);
}
}
}

View File

@@ -1,17 +1,16 @@
use std::io;
use std::ops::{Bound, Range};
use common::{BinarySerializable, BitSet};
use common::BitSet;
use super::range_query_u64_fastfield::FastFieldRangeWeight;
use crate::core::SegmentReader;
use crate::error::TantivyError;
use crate::query::explanation::does_not_match;
use crate::query::range_query::range_query_ip_fastfield::IPFastFieldRangeWeight;
use crate::query::range_query_ip_fastfield::IPFastFieldRangeWeight;
use crate::query::{BitSetDocSet, ConstScorer, EnableScoring, Explanation, Query, Scorer, Weight};
use crate::schema::{Field, IndexRecordOption, Term, Type};
use crate::termdict::{TermDictionary, TermStreamer};
use crate::{DateTime, DocId, Score};
use crate::{DocId, Score};
pub(crate) fn map_bound<TFrom, TTo, Transform: Fn(&TFrom) -> TTo>(
bound: &Bound<TFrom>,
@@ -204,40 +203,6 @@ impl RangeQuery {
)
}
/// Create a new `RangeQuery` over a `date` field.
///
/// The two `Bound` arguments make it possible to create more complex
/// ranges than semi-inclusive range.
///
/// If the field is not of the type `date`, tantivy
/// will panic when the `Weight` object is created.
pub fn new_date_bounds(
field: Field,
left_bound: Bound<DateTime>,
right_bound: Bound<DateTime>,
) -> RangeQuery {
let make_term_val =
|val: &DateTime| Term::from_field_date(field, *val).value_bytes().to_owned();
RangeQuery {
field,
value_type: Type::Date,
left_bound: map_bound(&left_bound, &make_term_val),
right_bound: map_bound(&right_bound, &make_term_val),
}
}
/// Create a new `RangeQuery` over a `date` field.
///
/// If the field is not of the type `date`, tantivy
/// will panic when the `Weight` object is created.
pub fn new_date(field: Field, range: Range<DateTime>) -> RangeQuery {
RangeQuery::new_date_bounds(
field,
Bound::Included(range.start),
Bound::Excluded(range.end),
)
}
/// Create a new `RangeQuery` over a `Str` field.
///
/// The two `Bound` arguments make it possible to create more complex
@@ -287,23 +252,6 @@ impl RangeQuery {
}
}
pub(crate) fn is_type_valid_for_fastfield_range_query(typ: Type) -> bool {
match typ {
Type::U64 | Type::I64 | Type::F64 | Type::Bool | Type::Date => true,
Type::IpAddr => true,
Type::Str | Type::Facet | Type::Bytes | Type::Json => false,
}
}
/// Returns true if the type maps to a u64 fast field
pub(crate) fn maps_to_u64_fastfield(typ: Type) -> bool {
match typ {
Type::U64 | Type::I64 | Type::F64 | Type::Bool | Type::Date => true,
Type::IpAddr => false,
Type::Str | Type::Facet | Type::Bytes | Type::Json => false,
}
}
impl Query for RangeQuery {
fn weight(&self, enable_scoring: EnableScoring<'_>) -> crate::Result<Box<dyn Weight>> {
let schema = enable_scoring.schema();
@@ -317,29 +265,12 @@ impl Query for RangeQuery {
return Err(TantivyError::SchemaError(err_msg));
}
if field_type.is_fast() && is_type_valid_for_fastfield_range_query(self.value_type) {
if field_type.is_ip_addr() {
Ok(Box::new(IPFastFieldRangeWeight::new(
self.field,
&self.left_bound,
&self.right_bound,
)))
} else {
// We run the range query on u64 value space for performance reasons and simpicity
// assert the type maps to u64
assert!(maps_to_u64_fastfield(self.value_type));
let parse_from_bytes = |data: &Vec<u8>| {
u64::from_be(BinarySerializable::deserialize(&mut &data[..]).unwrap())
};
let left_bound = map_bound(&self.left_bound, &parse_from_bytes);
let right_bound = map_bound(&self.right_bound, &parse_from_bytes);
Ok(Box::new(FastFieldRangeWeight::new(
self.field,
left_bound,
right_bound,
)))
}
if field_type.is_ip_addr() && field_type.is_fast() {
Ok(Box::new(IPFastFieldRangeWeight::new(
self.field,
&self.left_bound,
&self.right_bound,
)))
} else {
Ok(Box::new(RangeWeight {
field: self.field,

View File

@@ -1,210 +0,0 @@
use core::fmt;
use std::ops::RangeInclusive;
use std::sync::Arc;
use fastfield_codecs::Column;
use crate::fastfield::{MakeZero, MultiValuedFastFieldReader};
use crate::{DocId, DocSet, TERMINATED};
/// Helper to have a cursor over a vec of docids
struct VecCursor {
docs: Vec<u32>,
current_pos: usize,
}
impl VecCursor {
fn new() -> Self {
Self {
docs: Vec::with_capacity(32),
current_pos: 0,
}
}
fn next(&mut self) -> Option<u32> {
self.current_pos += 1;
self.current()
}
#[inline]
fn current(&self) -> Option<u32> {
self.docs.get(self.current_pos).copied()
}
fn get_cleared_data(&mut self) -> &mut Vec<u32> {
self.docs.clear();
self.current_pos = 0;
&mut self.docs
}
fn last_value(&self) -> Option<u32> {
self.docs.iter().last().cloned()
}
fn is_empty(&self) -> bool {
self.current().is_none()
}
}
pub(crate) enum FastFieldCardinality<T: MakeZero> {
SingleValue(Arc<dyn Column<T>>),
MultiValue(MultiValuedFastFieldReader<T>),
}
impl<T: MakeZero + PartialOrd + Copy + fmt::Debug> FastFieldCardinality<T> {
fn num_docs(&self) -> u32 {
match self {
FastFieldCardinality::SingleValue(single_value) => single_value.num_vals(),
FastFieldCardinality::MultiValue(multi_value) => {
multi_value.get_index_reader().num_docs()
}
}
}
}
pub(crate) struct RangeDocSet<T: MakeZero> {
/// The range filter on the values.
value_range: RangeInclusive<T>,
fast_field: FastFieldCardinality<T>,
/// The next docid start range to fetch (inclusive).
next_fetch_start: u32,
/// Number of docs range checked in a batch.
///
/// There are two patterns.
/// - We do a full scan. => We can load large chunks. We don't know in advance if seek call
/// will come, so we start with small chunks
/// - We load docs, interspersed with seek calls. When there are big jumps in the seek, we
/// should load small chunks. When the seeks are small, we can employ the same strategy as on a
/// full scan.
fetch_horizon: u32,
/// Current batch of loaded docs.
loaded_docs: VecCursor,
last_seek_pos_opt: Option<u32>,
}
const DEFAULT_FETCH_HORIZON: u32 = 128;
impl<T: MakeZero + Send + PartialOrd + Copy + fmt::Debug> RangeDocSet<T> {
pub(crate) fn new(value_range: RangeInclusive<T>, fast_field: FastFieldCardinality<T>) -> Self {
let mut range_docset = Self {
value_range,
fast_field,
loaded_docs: VecCursor::new(),
next_fetch_start: 0,
fetch_horizon: DEFAULT_FETCH_HORIZON,
last_seek_pos_opt: None,
};
range_docset.reset_fetch_range();
range_docset.fetch_block();
range_docset
}
fn reset_fetch_range(&mut self) {
self.fetch_horizon = DEFAULT_FETCH_HORIZON;
}
/// Returns true if more data could be fetched
fn fetch_block(&mut self) {
const MAX_HORIZON: u32 = 100_000;
while self.loaded_docs.is_empty() {
let finished_to_end = self.fetch_horizon(self.fetch_horizon);
if finished_to_end {
break;
}
// Fetch more data, increase horizon. Horizon only gets reset when doing a seek.
self.fetch_horizon = (self.fetch_horizon * 2).min(MAX_HORIZON);
}
}
/// check if the distance between the seek calls is large
fn is_last_seek_distance_large(&self, new_seek: DocId) -> bool {
if let Some(last_seek_pos) = self.last_seek_pos_opt {
(new_seek - last_seek_pos) >= 128
} else {
true
}
}
/// Fetches a block for docid range [next_fetch_start .. next_fetch_start + HORIZON]
fn fetch_horizon(&mut self, horizon: u32) -> bool {
let mut finished_to_end = false;
let limit = self.fast_field.num_docs();
let mut end = self.next_fetch_start + horizon;
if end >= limit {
end = limit;
finished_to_end = true;
}
match &self.fast_field {
FastFieldCardinality::MultiValue(multi) => {
let last_value = self.loaded_docs.last_value();
multi.get_docids_for_value_range(
self.value_range.clone(),
self.next_fetch_start..end,
self.loaded_docs.get_cleared_data(),
);
// In case of multivalues, we may have an overlap of the same docid between fetching
// blocks
if let Some(last_value) = last_value {
while self.loaded_docs.current() == Some(last_value) {
self.loaded_docs.next();
}
}
}
FastFieldCardinality::SingleValue(single) => {
single.get_docids_for_value_range(
self.value_range.clone(),
self.next_fetch_start..end,
self.loaded_docs.get_cleared_data(),
);
}
}
self.next_fetch_start = end;
finished_to_end
}
}
impl<T: MakeZero + Send + PartialOrd + Copy + fmt::Debug> DocSet for RangeDocSet<T> {
#[inline]
fn advance(&mut self) -> DocId {
if let Some(docid) = self.loaded_docs.next() {
docid
} else {
if self.next_fetch_start >= self.fast_field.num_docs() {
return TERMINATED;
}
self.fetch_block();
self.loaded_docs.current().unwrap_or(TERMINATED)
}
}
#[inline]
fn doc(&self) -> DocId {
self.loaded_docs.current().unwrap_or(TERMINATED)
}
/// 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.
///
/// 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`.
fn seek(&mut self, target: DocId) -> DocId {
if self.is_last_seek_distance_large(target) {
self.reset_fetch_range();
}
if target > self.next_fetch_start {
self.next_fetch_start = target;
}
let mut doc = self.doc();
debug_assert!(doc <= target);
while doc < target {
doc = self.advance();
}
self.last_seek_pos_opt = Some(target);
doc
}
fn size_hint(&self) -> u32 {
0 // heuristic possible by checking number of hits when fetching a block
}
}

View File

@@ -1,8 +0,0 @@
mod fast_field_range_query;
mod range_query;
mod range_query_ip_fastfield;
mod range_query_u64_fastfield;
pub(crate) use range_query::is_type_valid_for_fastfield_range_query;
pub use self::range_query::RangeQuery;

View File

@@ -1,557 +0,0 @@
//! Fastfields support efficient scanning for range queries.
//! We use this variant only if the fastfield exists, otherwise the default in `range_query` is
//! used, which uses the term dictionary + postings.
use std::ops::{Bound, RangeInclusive};
use fastfield_codecs::MonotonicallyMappableToU64;
use super::fast_field_range_query::{FastFieldCardinality, RangeDocSet};
use super::range_query::map_bound;
use crate::query::{ConstScorer, Explanation, Scorer, Weight};
use crate::schema::{Cardinality, Field};
use crate::{DocId, DocSet, Score, SegmentReader, TantivyError};
/// `FastFieldRangeWeight` uses the fast field to execute range queries.
pub struct FastFieldRangeWeight {
field: Field,
left_bound: Bound<u64>,
right_bound: Bound<u64>,
}
impl FastFieldRangeWeight {
pub fn new(field: Field, left_bound: Bound<u64>, right_bound: Bound<u64>) -> Self {
let left_bound = map_bound(&left_bound, &|val| *val);
let right_bound = map_bound(&right_bound, &|val| *val);
Self {
field,
left_bound,
right_bound,
}
}
}
impl Weight for FastFieldRangeWeight {
fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>> {
let field_type = reader.schema().get_field_entry(self.field).field_type();
match field_type.fastfield_cardinality().unwrap() {
Cardinality::SingleValue => {
let fast_field = reader.fast_fields().u64_lenient(self.field)?;
let value_range = bound_to_value_range(
&self.left_bound,
&self.right_bound,
fast_field.min_value(),
fast_field.max_value(),
);
let docset =
RangeDocSet::new(value_range, FastFieldCardinality::SingleValue(fast_field));
Ok(Box::new(ConstScorer::new(docset, boost)))
}
Cardinality::MultiValues => {
let fast_field = reader.fast_fields().u64s_lenient(self.field)?;
let value_range = bound_to_value_range(
&self.left_bound,
&self.right_bound,
fast_field.min_value(),
fast_field.max_value(),
);
let docset =
RangeDocSet::new(value_range, FastFieldCardinality::MultiValue(fast_field));
Ok(Box::new(ConstScorer::new(docset, boost)))
}
}
}
fn explain(&self, reader: &SegmentReader, doc: DocId) -> crate::Result<Explanation> {
let mut scorer = self.scorer(reader, 1.0)?;
if scorer.seek(doc) != doc {
return Err(TantivyError::InvalidArgument(format!(
"Document #({}) does not match",
doc
)));
}
let explanation = Explanation::new("Const", scorer.score());
Ok(explanation)
}
}
fn bound_to_value_range<T: MonotonicallyMappableToU64>(
left_bound: &Bound<T>,
right_bound: &Bound<T>,
min_value: T,
max_value: T,
) -> RangeInclusive<T> {
let start_value = match left_bound {
Bound::Included(val) => *val,
Bound::Excluded(val) => T::from_u64(val.to_u64() + 1),
Bound::Unbounded => min_value,
};
let end_value = match right_bound {
Bound::Included(val) => *val,
Bound::Excluded(val) => T::from_u64(val.to_u64() - 1),
Bound::Unbounded => max_value,
};
start_value..=end_value
}
#[cfg(test)]
mod tests {
use proptest::prelude::ProptestConfig;
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
use rand::rngs::StdRng;
use rand::seq::SliceRandom;
use rand::SeedableRng;
use super::*;
use crate::collector::Count;
use crate::query::QueryParser;
use crate::schema::{NumericOptions, Schema, FAST, INDEXED, STORED, STRING};
use crate::Index;
#[derive(Clone, Debug)]
pub struct Doc {
pub id_name: String,
pub id: u64,
}
fn operation_strategy() -> impl Strategy<Value = Doc> {
prop_oneof![
(0u64..10_000u64).prop_map(doc_from_id_1),
(1u64..10_000u64).prop_map(doc_from_id_2),
]
}
pub fn doc_from_id_1(id: u64) -> Doc {
let id = id * 1000;
Doc {
id_name: id.to_string(),
id,
}
}
fn doc_from_id_2(id: u64) -> Doc {
let id = id * 1000;
Doc {
id_name: (id - 1).to_string(),
id,
}
}
proptest! {
#![proptest_config(ProptestConfig::with_cases(10))]
#[test]
fn test_range_for_docs_prop(ops in proptest::collection::vec(operation_strategy(), 1..1000)) {
assert!(test_id_range_for_docs(ops).is_ok());
}
}
#[test]
fn range_regression1_test() {
let ops = vec![doc_from_id_1(0)];
assert!(test_id_range_for_docs(ops).is_ok());
}
#[test]
fn range_regression2_test() {
let ops = vec![
doc_from_id_1(52),
doc_from_id_1(63),
doc_from_id_1(12),
doc_from_id_2(91),
doc_from_id_2(33),
];
assert!(test_id_range_for_docs(ops).is_ok());
}
#[test]
fn range_regression3_test() {
let ops = vec![doc_from_id_1(1), doc_from_id_1(2), doc_from_id_1(3)];
assert!(test_id_range_for_docs(ops).is_ok());
}
#[test]
fn range_regression4_test() {
let ops = vec![doc_from_id_2(100)];
assert!(test_id_range_for_docs(ops).is_ok());
}
pub fn create_index_from_docs(docs: &[Doc]) -> Index {
let mut schema_builder = Schema::builder();
let id_u64_field = schema_builder.add_u64_field("id", INDEXED | STORED | FAST);
let ids_u64_field = schema_builder.add_u64_field(
"ids",
NumericOptions::default()
.set_fast(Cardinality::MultiValues)
.set_indexed(),
);
let id_f64_field = schema_builder.add_f64_field("id_f64", INDEXED | STORED | FAST);
let ids_f64_field = schema_builder.add_f64_field(
"ids_f64",
NumericOptions::default()
.set_fast(Cardinality::MultiValues)
.set_indexed(),
);
let id_i64_field = schema_builder.add_i64_field("id_i64", INDEXED | STORED | FAST);
let ids_i64_field = schema_builder.add_i64_field(
"ids_i64",
NumericOptions::default()
.set_fast(Cardinality::MultiValues)
.set_indexed(),
);
let text_field = schema_builder.add_text_field("id_name", STRING | STORED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer(3_000_000).unwrap();
for doc in docs.iter() {
index_writer
.add_document(doc!(
ids_i64_field => doc.id as i64,
ids_i64_field => doc.id as i64,
ids_f64_field => doc.id as f64,
ids_f64_field => doc.id as f64,
ids_u64_field => doc.id,
ids_u64_field => doc.id,
id_u64_field => doc.id,
id_f64_field => doc.id as f64,
id_i64_field => doc.id as i64,
text_field => doc.id_name.to_string(),
))
.unwrap();
}
index_writer.commit().unwrap();
}
index
}
fn test_id_range_for_docs(docs: Vec<Doc>) -> crate::Result<()> {
let index = create_index_from_docs(&docs);
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let get_num_hits = |query| searcher.search(&query, &(Count)).unwrap();
let query_from_text = |text: &str| {
QueryParser::for_index(&index, vec![])
.parse_query(text)
.unwrap()
};
let gen_query_inclusive = |field: &str, from: u64, to: u64| {
format!("{}:[{} TO {}]", field, &from.to_string(), &to.to_string())
};
let test_sample = |sample_docs: Vec<Doc>| {
let mut ids: Vec<u64> = sample_docs.iter().map(|doc| doc.id).collect();
ids.sort();
let expected_num_hits = docs
.iter()
.filter(|doc| (ids[0]..=ids[1]).contains(&doc.id))
.count();
let query = gen_query_inclusive("id", ids[0], ids[1]);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
let query = gen_query_inclusive("ids", ids[0], ids[1]);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
// Intersection search
let id_filter = sample_docs[0].id_name.to_string();
let expected_num_hits = docs
.iter()
.filter(|doc| (ids[0]..=ids[1]).contains(&doc.id) && doc.id_name == id_filter)
.count();
let query = format!(
"{} AND id_name:{}",
gen_query_inclusive("id", ids[0], ids[1]),
&id_filter
);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
let query = format!(
"{} AND id_name:{}",
gen_query_inclusive("id_f64", ids[0], ids[1]),
&id_filter
);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
let query = format!(
"{} AND id_name:{}",
gen_query_inclusive("id_i64", ids[0], ids[1]),
&id_filter
);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
// Intersection search on multivalue id field
let id_filter = sample_docs[0].id_name.to_string();
let query = format!(
"{} AND id_name:{}",
gen_query_inclusive("ids", ids[0], ids[1]),
&id_filter
);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
let query = format!(
"{} AND id_name:{}",
gen_query_inclusive("ids_f64", ids[0], ids[1]),
&id_filter
);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
let query = format!(
"{} AND id_name:{}",
gen_query_inclusive("ids_i64", ids[0], ids[1]),
&id_filter
);
assert_eq!(get_num_hits(query_from_text(&query)), expected_num_hits);
};
test_sample(vec![docs[0].clone(), docs[0].clone()]);
let samples: Vec<_> = docs.choose_multiple(&mut rng, 3).collect();
if samples.len() > 1 {
test_sample(vec![samples[0].clone(), samples[1].clone()]);
test_sample(vec![samples[1].clone(), samples[1].clone()]);
}
if samples.len() > 2 {
test_sample(vec![samples[1].clone(), samples[2].clone()]);
}
Ok(())
}
}
#[cfg(all(test, feature = "unstable"))]
mod bench {
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use test::Bencher;
use super::tests::*;
use super::*;
use crate::collector::Count;
use crate::query::QueryParser;
use crate::Index;
fn get_index_0_to_100() -> Index {
let mut rng = StdRng::from_seed([1u8; 32]);
let num_vals = 100_000;
let docs: Vec<_> = (0..num_vals)
.map(|_i| {
let id_name = if rng.gen_bool(0.01) {
"veryfew".to_string() // 1%
} else if rng.gen_bool(0.1) {
"few".to_string() // 9%
} else {
"many".to_string() // 90%
};
Doc {
id_name,
id: rng.gen_range(0..100),
}
})
.collect();
create_index_from_docs(&docs)
}
fn get_90_percent() -> RangeInclusive<u64> {
0..=90
}
fn get_10_percent() -> RangeInclusive<u64> {
0..=10
}
fn get_1_percent() -> RangeInclusive<u64> {
10..=10
}
fn excute_query(
field: &str,
id_range: RangeInclusive<u64>,
suffix: &str,
index: &Index,
) -> usize {
let gen_query_inclusive = |from: &u64, to: &u64| {
format!(
"{}:[{} TO {}] {}",
field,
&from.to_string(),
&to.to_string(),
suffix
)
};
let query = gen_query_inclusive(id_range.start(), id_range.end());
let query_from_text = |text: &str| {
QueryParser::for_index(index, vec![])
.parse_query(text)
.unwrap()
};
let query = query_from_text(&query);
let reader = index.reader().unwrap();
let searcher = reader.searcher();
searcher.search(&query, &(Count)).unwrap()
}
#[bench]
fn bench_id_range_hit_90_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_90_percent(), "", &index));
}
#[bench]
fn bench_id_range_hit_10_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_10_percent(), "", &index));
}
#[bench]
fn bench_id_range_hit_1_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_1_percent(), "", &index));
}
#[bench]
fn bench_id_range_hit_10_percent_intersect_with_10_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_10_percent(), "AND id_name:few", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_intersect_with_10_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_1_percent(), "AND id_name:few", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_intersect_with_90_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_1_percent(), "AND id_name:many", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_intersect_with_1_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_1_percent(), "AND id_name:veryfew", &index));
}
#[bench]
fn bench_id_range_hit_10_percent_intersect_with_90_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_10_percent(), "AND id_name:many", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_intersect_with_90_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_90_percent(), "AND id_name:many", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_intersect_with_10_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_90_percent(), "AND id_name:few", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_intersect_with_1_percent(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("id", get_90_percent(), "AND id_name:veryfew", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_90_percent(), "", &index));
}
#[bench]
fn bench_id_range_hit_10_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_10_percent(), "", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_1_percent(), "", &index));
}
#[bench]
fn bench_id_range_hit_10_percent_intersect_with_10_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_10_percent(), "AND id_name:few", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_intersect_with_10_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_1_percent(), "AND id_name:few", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_intersect_with_90_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_1_percent(), "AND id_name:many", &index));
}
#[bench]
fn bench_id_range_hit_1_percent_intersect_with_1_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_1_percent(), "AND id_name:veryfew", &index));
}
#[bench]
fn bench_id_range_hit_10_percent_intersect_with_90_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_10_percent(), "AND id_name:many", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_intersect_with_90_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_90_percent(), "AND id_name:many", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_intersect_with_10_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_90_percent(), "AND id_name:few", &index));
}
#[bench]
fn bench_id_range_hit_90_percent_intersect_with_1_percent_multi(bench: &mut Bencher) {
let index = get_index_0_to_100();
bench.iter(|| excute_query("ids", get_90_percent(), "AND id_name:veryfew", &index));
}
}

View File

@@ -4,15 +4,16 @@
use std::net::Ipv6Addr;
use std::ops::{Bound, RangeInclusive};
use std::sync::Arc;
use common::BinarySerializable;
use fastfield_codecs::MonotonicallyMappableToU128;
use fastfield_codecs::{Column, MonotonicallyMappableToU128};
use super::fast_field_range_query::{FastFieldCardinality, RangeDocSet};
use super::range_query::map_bound;
use crate::query::{ConstScorer, Explanation, Scorer, Weight};
use super::{ConstScorer, Explanation, Scorer, Weight};
use crate::fastfield::MultiValuedU128FastFieldReader;
use crate::schema::{Cardinality, Field};
use crate::{DocId, DocSet, Score, SegmentReader, TantivyError};
use crate::{DocId, DocSet, Score, SegmentReader, TantivyError, TERMINATED};
/// `IPFastFieldRangeWeight` uses the ip address fast field to execute range queries.
pub struct IPFastFieldRangeWeight {
@@ -23,13 +24,13 @@ pub struct IPFastFieldRangeWeight {
impl IPFastFieldRangeWeight {
pub fn new(field: Field, left_bound: &Bound<Vec<u8>>, right_bound: &Bound<Vec<u8>>) -> Self {
let parse_ip_from_bytes = |data: &Vec<u8>| {
let ip_u128: u128 =
let ip_from_bound_raw_data = |data: &Vec<u8>| {
let left_ip_u128: u128 =
u128::from_be(BinarySerializable::deserialize(&mut &data[..]).unwrap());
Ipv6Addr::from_u128(ip_u128)
Ipv6Addr::from_u128(left_ip_u128)
};
let left_bound = map_bound(left_bound, &parse_ip_from_bytes);
let right_bound = map_bound(right_bound, &parse_ip_from_bytes);
let left_bound = map_bound(left_bound, &ip_from_bound_raw_data);
let right_bound = map_bound(right_bound, &ip_from_bound_raw_data);
Self {
field,
left_bound,
@@ -50,9 +51,9 @@ impl Weight for IPFastFieldRangeWeight {
ip_addr_fast_field.min_value(),
ip_addr_fast_field.max_value(),
);
let docset = RangeDocSet::new(
let docset = IpRangeDocSet::new(
value_range,
FastFieldCardinality::SingleValue(ip_addr_fast_field),
IpFastFieldCardinality::SingleValue(ip_addr_fast_field),
);
Ok(Box::new(ConstScorer::new(docset, boost)))
}
@@ -64,9 +65,9 @@ impl Weight for IPFastFieldRangeWeight {
ip_addr_fast_field.min_value(),
ip_addr_fast_field.max_value(),
);
let docset = RangeDocSet::new(
let docset = IpRangeDocSet::new(
value_range,
FastFieldCardinality::MultiValue(ip_addr_fast_field),
IpFastFieldCardinality::MultiValue(ip_addr_fast_field),
);
Ok(Box::new(ConstScorer::new(docset, boost)))
}
@@ -107,6 +108,213 @@ fn bound_to_value_range(
start_value..=end_value
}
/// Helper to have a cursor over a vec of docids
struct VecCursor {
docs: Vec<u32>,
current_pos: usize,
}
impl VecCursor {
fn new() -> Self {
Self {
docs: Vec::with_capacity(32),
current_pos: 0,
}
}
fn next(&mut self) -> Option<u32> {
self.current_pos += 1;
self.current()
}
#[inline]
fn current(&self) -> Option<u32> {
self.docs.get(self.current_pos).copied()
}
fn get_cleared_data(&mut self) -> &mut Vec<u32> {
self.docs.clear();
self.current_pos = 0;
&mut self.docs
}
fn last_value(&self) -> Option<u32> {
self.docs.iter().last().cloned()
}
fn is_empty(&self) -> bool {
self.current_pos >= self.docs.len()
}
}
pub(crate) enum IpFastFieldCardinality {
SingleValue(Arc<dyn Column<Ipv6Addr>>),
MultiValue(MultiValuedU128FastFieldReader<Ipv6Addr>),
}
impl IpFastFieldCardinality {
fn num_docs(&self) -> u32 {
match self {
IpFastFieldCardinality::SingleValue(single_value) => single_value.num_vals(),
IpFastFieldCardinality::MultiValue(multi_value) => {
multi_value.get_index_reader().num_docs()
}
}
}
}
struct IpRangeDocSet {
/// The range filter on the values.
value_range: RangeInclusive<Ipv6Addr>,
ip_addr_fast_field: IpFastFieldCardinality,
/// The next docid start range to fetch (inclusive).
next_fetch_start: u32,
/// Number of docs range checked in a batch.
///
/// There are two patterns.
/// - We do a full scan. => We can load large chunks. We don't know in advance if seek call
/// will come, so we start with small chunks
/// - We load docs, interspersed with seek calls. When there are big jumps in the seek, we
/// should load small chunks. When the seeks are small, we can employ the same strategy as on a
/// full scan.
fetch_horizon: u32,
/// Current batch of loaded docs.
loaded_docs: VecCursor,
last_seek_pos_opt: Option<u32>,
}
const DEFAULT_FETCH_HORIZON: u32 = 128;
impl IpRangeDocSet {
fn new(
value_range: RangeInclusive<Ipv6Addr>,
ip_addr_fast_field: IpFastFieldCardinality,
) -> Self {
let mut ip_range_docset = Self {
value_range,
ip_addr_fast_field,
loaded_docs: VecCursor::new(),
next_fetch_start: 0,
fetch_horizon: DEFAULT_FETCH_HORIZON,
last_seek_pos_opt: None,
};
ip_range_docset.reset_fetch_range();
ip_range_docset.fetch_block();
ip_range_docset
}
fn reset_fetch_range(&mut self) {
self.fetch_horizon = DEFAULT_FETCH_HORIZON;
}
/// Returns true if more data could be fetched
fn fetch_block(&mut self) {
const MAX_HORIZON: u32 = 100_000;
while self.loaded_docs.is_empty() {
let finished_to_end = self.fetch_horizon(self.fetch_horizon);
if finished_to_end {
break;
}
// Fetch more data, increase horizon. Horizon only gets reset when doing a seek.
self.fetch_horizon = (self.fetch_horizon * 2).min(MAX_HORIZON);
}
}
/// check if the distance between the seek calls is large
fn is_last_seek_distance_large(&self, new_seek: DocId) -> bool {
if let Some(last_seek_pos) = self.last_seek_pos_opt {
(new_seek - last_seek_pos) >= 128
} else {
true
}
}
/// Fetches a block for docid range [next_fetch_start .. next_fetch_start + HORIZON]
fn fetch_horizon(&mut self, horizon: u32) -> bool {
let mut finished_to_end = false;
let limit = self.ip_addr_fast_field.num_docs();
let mut end = self.next_fetch_start + horizon;
if end >= limit {
end = limit;
finished_to_end = true;
}
match &self.ip_addr_fast_field {
IpFastFieldCardinality::MultiValue(multi) => {
let last_value = self.loaded_docs.last_value();
multi.get_docids_for_value_range(
self.value_range.clone(),
self.next_fetch_start..end,
self.loaded_docs.get_cleared_data(),
);
// In case of multivalues, we may have an overlap of the same docid between fetching
// blocks
if let Some(last_value) = last_value {
while self.loaded_docs.current() == Some(last_value) {
self.loaded_docs.next();
}
}
}
IpFastFieldCardinality::SingleValue(single) => {
single.get_docids_for_value_range(
self.value_range.clone(),
self.next_fetch_start..end,
self.loaded_docs.get_cleared_data(),
);
}
}
self.next_fetch_start = end;
finished_to_end
}
}
impl DocSet for IpRangeDocSet {
#[inline]
fn advance(&mut self) -> DocId {
if let Some(docid) = self.loaded_docs.next() {
docid
} else {
if self.next_fetch_start >= self.ip_addr_fast_field.num_docs() {
return TERMINATED;
}
self.fetch_block();
self.loaded_docs.current().unwrap_or(TERMINATED)
}
}
#[inline]
fn doc(&self) -> DocId {
self.loaded_docs
.current()
.unwrap_or(TERMINATED)
}
/// 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.
///
/// 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`.
fn seek(&mut self, target: DocId) -> DocId {
if self.is_last_seek_distance_large(target) {
self.reset_fetch_range();
}
if target > self.next_fetch_start {
self.next_fetch_start = target;
}
let mut doc = self.doc();
debug_assert!(doc <= target);
while doc < target {
doc = self.advance();
}
self.last_seek_pos_opt = Some(target);
doc
}
fn size_hint(&self) -> u32 {
0 // heuristic possible by checking number of hits when fetching a block
}
}
#[cfg(test)]
mod tests {
use proptest::prelude::ProptestConfig;
@@ -195,7 +403,7 @@ mod tests {
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer(10_000_000).unwrap();
let mut index_writer = index.writer(3_000_000).unwrap();
for doc in docs.iter() {
index_writer
.add_document(doc!(
@@ -313,7 +521,8 @@ mod bench {
})
.collect();
create_index_from_docs(&docs)
let index = create_index_from_docs(&docs);
index
}
fn get_90_percent() -> RangeInclusive<Ipv6Addr> {
@@ -352,7 +561,7 @@ mod bench {
let query = gen_query_inclusive(ip_range.start(), ip_range.end());
let query_from_text = |text: &str| {
QueryParser::for_index(index, vec![])
QueryParser::for_index(&index, vec![])
.parse_query(text)
.unwrap()
};

View File

@@ -158,8 +158,7 @@ mod tests {
let term_a = Term::from_field_text(text_field, "a");
let term_query = TermQuery::new(term_a, IndexRecordOption::Basic);
let searcher = index.reader()?.searcher();
let term_weight =
term_query.weight(EnableScoring::disabled_from_schema(searcher.schema()))?;
let term_weight = term_query.weight(EnableScoring::Disabled(searcher.schema()))?;
let mut term_scorer = term_weight.scorer(searcher.segment_reader(0u32), 1.0)?;
assert_eq!(term_scorer.doc(), 0u32);
term_scorer.seek(1u32);

View File

@@ -99,7 +99,7 @@ impl TermQuery {
EnableScoring::Enabled(searcher) => {
Bm25Weight::for_terms(searcher, &[self.term.clone()])?
}
EnableScoring::Disabled { .. } => {
EnableScoring::Disabled(_schema) => {
Bm25Weight::new(Explanation::new("<no score>".to_string(), 1.0f32), 1.0f32)
}
};

View File

@@ -1,8 +1,6 @@
use std::net::IpAddr;
use std::str::FromStr;
use base64::engine::general_purpose::STANDARD as BASE64;
use base64::Engine;
use serde::{Deserialize, Serialize};
use serde_json::Value as JsonValue;
use thiserror::Error;
@@ -360,8 +358,7 @@ impl FieldType {
json: JsonValue::String(field_text),
}),
FieldType::Facet(_) => Ok(Value::Facet(Facet::from(&field_text))),
FieldType::Bytes(_) => BASE64
.decode(&field_text)
FieldType::Bytes(_) => base64::decode(&field_text)
.map(Value::Bytes)
.map_err(|_| ValueParsingError::InvalidBase64 { base64: field_text }),
FieldType::JsonObject(_) => Err(ValueParsingError::TypeError {

View File

@@ -258,7 +258,7 @@ mod tests {
let field = schema.get_field("body").unwrap();
let field_entry = schema.get_field_entry(field);
assert!(matches!(field_entry.field_type(),
FieldType::Str(text_options)
&FieldType::Str(ref text_options)
if text_options.get_indexing_options().unwrap().tokenizer() == "default"));
}

View File

@@ -1,8 +1,6 @@
use std::fmt;
use std::net::Ipv6Addr;
use base64::engine::general_purpose::STANDARD as BASE64;
use base64::Engine;
use serde::de::Visitor;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
use serde_json::Map;
@@ -53,7 +51,7 @@ impl Serialize for Value {
Value::Bool(b) => serializer.serialize_bool(b),
Value::Date(ref date) => time::serde::rfc3339::serialize(&date.into_utc(), serializer),
Value::Facet(ref facet) => facet.serialize(serializer),
Value::Bytes(ref bytes) => serializer.serialize_str(&BASE64.encode(bytes)),
Value::Bytes(ref bytes) => serializer.serialize_str(&base64::encode(bytes)),
Value::JsonObject(ref obj) => obj.serialize(serializer),
Value::IpAddr(ref obj) => {
// Ensure IpV4 addresses get serialized as IpV4, but excluding IpV6 loopback.

View File

@@ -124,9 +124,9 @@ impl Snippet {
///
/// Fragments must be valid in the sense that `&text[fragment.start..fragment.stop]`\
/// has to be a valid string.
fn search_fragments(
fn search_fragments<'a>(
tokenizer: &TextAnalyzer,
text: &str,
text: &'a str,
terms: &BTreeMap<String, Score>,
max_num_chars: usize,
) -> Vec<FragmentCandidate> {

View File

@@ -1,12 +1,12 @@
use std::io;
use std::iter::Sum;
use std::num::NonZeroUsize;
use std::ops::{AddAssign, Range};
use std::sync::atomic::{AtomicUsize, Ordering};
use std::sync::{Arc, Mutex};
use common::{BinarySerializable, HasLen, OwnedBytes};
use common::{BinarySerializable, HasLen};
use lru::LruCache;
use ownedbytes::OwnedBytes;
use super::footer::DocStoreFooter;
use super::index::SkipIndex;
@@ -34,29 +34,23 @@ pub struct StoreReader {
/// The cache for decompressed blocks.
struct BlockCache {
cache: Option<Mutex<LruCache<usize, Block>>>,
cache_hits: AtomicUsize,
cache_misses: AtomicUsize,
cache: Mutex<LruCache<usize, Block>>,
cache_hits: Arc<AtomicUsize>,
cache_misses: Arc<AtomicUsize>,
}
impl BlockCache {
fn get_from_cache(&self, pos: usize) -> Option<Block> {
if let Some(block) = self
.cache
.as_ref()
.and_then(|cache| cache.lock().unwrap().get(&pos).cloned())
{
if let Some(block) = self.cache.lock().unwrap().get(&pos) {
self.cache_hits.fetch_add(1, Ordering::SeqCst);
return Some(block);
return Some(block.clone());
}
self.cache_misses.fetch_add(1, Ordering::SeqCst);
None
}
fn put_into_cache(&self, pos: usize, data: Block) {
if let Some(cache) = self.cache.as_ref() {
cache.lock().unwrap().put(pos, data);
}
self.cache.lock().unwrap().put(pos, data);
}
fn stats(&self) -> CacheStats {
@@ -66,18 +60,13 @@ impl BlockCache {
num_entries: self.len(),
}
}
fn len(&self) -> usize {
self.cache
.as_ref()
.map_or(0, |cache| cache.lock().unwrap().len())
self.cache.lock().unwrap().len()
}
#[cfg(test)]
fn peek_lru(&self) -> Option<usize> {
self.cache
.as_ref()
.and_then(|cache| cache.lock().unwrap().peek_lru().map(|(&k, _)| k))
self.cache.lock().unwrap().peek_lru().map(|(&k, _)| k)
}
}
@@ -125,8 +114,7 @@ impl StoreReader {
decompressor: footer.decompressor,
data: data_file,
cache: BlockCache {
cache: NonZeroUsize::new(cache_size)
.map(|cache_size| Mutex::new(LruCache::new(cache_size))),
cache: Mutex::new(LruCache::new(cache_size)),
cache_hits: Default::default(),
cache_misses: Default::default(),
},

View File

@@ -113,7 +113,7 @@ mod bench {
}
/// Create a dictionary of random strings.
fn rand_dict(num_terms: usize) -> std::io::Result<TermDictionary> {
fn rand_dict(num_terms: usize) -> crate::Result<TermDictionary> {
let buffer: Vec<u8> = {
let mut terms = vec![];
for _i in 0..num_terms {

View File

@@ -1,6 +1,7 @@
use std::io;
mod merger;
mod termdict;
use std::iter::ExactSizeIterator;
@@ -12,39 +13,26 @@ use tantivy_fst::automaton::AlwaysMatch;
pub use self::merger::TermMerger;
use crate::postings::TermInfo;
/// The term dictionary contains all of the terms in
/// `tantivy index` in a sorted manner.
///
/// The `Fst` crate is used to associate terms to their
/// respective `TermOrdinal`. The `TermInfoStore` then makes it
/// possible to fetch the associated `TermInfo`.
pub type TermDictionary = sstable::Dictionary<TermSSTable>;
/// Builder for the new term dictionary.
pub type TermDictionaryBuilder<W> = sstable::Writer<W, TermInfoValueWriter>;
/// `TermStreamer` acts as a cursor over a range of terms of a segment.
/// Terms are guaranteed to be sorted.
pub type TermDictionaryBuilder<W> = sstable::Writer<W, TermInfoWriter>;
pub type TermStreamer<'a, A = AlwaysMatch> = sstable::Streamer<'a, TermSSTable, A>;
/// SSTable used to store TermInfo objects.
pub struct TermSSTable;
impl SSTable for TermSSTable {
type Value = TermInfo;
type ValueReader = TermInfoValueReader;
type ValueWriter = TermInfoValueWriter;
type ValueReader = TermInfoReader;
type ValueWriter = TermInfoWriter;
}
#[derive(Default)]
pub struct TermInfoValueReader {
pub struct TermInfoReader {
term_infos: Vec<TermInfo>,
}
impl ValueReader for TermInfoValueReader {
impl ValueReader for TermInfoReader {
type Value = TermInfo;
#[inline(always)]
fn value(&self, idx: usize) -> &TermInfo {
&self.term_infos[idx]
}
@@ -76,18 +64,18 @@ impl ValueReader for TermInfoValueReader {
}
#[derive(Default)]
pub struct TermInfoValueWriter {
pub struct TermInfoWriter {
term_infos: Vec<TermInfo>,
}
impl ValueWriter for TermInfoValueWriter {
impl ValueWriter for TermInfoWriter {
type Value = TermInfo;
fn write(&mut self, term_info: &TermInfo) {
self.term_infos.push(term_info.clone());
}
fn serialize_block(&self, buffer: &mut Vec<u8>) {
fn serialize_block(&mut self, buffer: &mut Vec<u8>) {
VInt(self.term_infos.len() as u64).serialize_into_vec(buffer);
if self.term_infos.is_empty() {
return;
@@ -99,9 +87,6 @@ impl ValueWriter for TermInfoValueWriter {
VInt(term_info.postings_range.len() as u64).serialize_into_vec(buffer);
VInt(term_info.positions_range.len() as u64).serialize_into_vec(buffer);
}
}
fn clear(&mut self) {
self.term_infos.clear();
}
}
@@ -111,11 +96,11 @@ mod tests {
use sstable::value::{ValueReader, ValueWriter};
use crate::postings::TermInfo;
use crate::termdict::sstable_termdict::TermInfoValueReader;
use crate::termdict::sstable_termdict::TermInfoReader;
#[test]
fn test_block_terminfos() {
let mut term_info_writer = super::TermInfoValueWriter::default();
let mut term_info_writer = super::TermInfoWriter::default();
term_info_writer.write(&TermInfo {
doc_freq: 120u32,
postings_range: 17..45,
@@ -133,7 +118,8 @@ mod tests {
});
let mut buffer = Vec::new();
term_info_writer.serialize_block(&mut buffer);
let mut term_info_reader = TermInfoValueReader::default();
// let mut block_reader = make_block_reader(&buffer[..]);
let mut term_info_reader = TermInfoReader::default();
let num_bytes: usize = term_info_reader.load(&buffer[..]).unwrap();
assert_eq!(
term_info_reader.value(0),

View File

@@ -0,0 +1,11 @@
use sstable::SSTable;
use crate::postings::TermInfo;
use crate::termdict::sstable_termdict::{TermInfoReader, TermInfoWriter};
pub struct TermInfoSSTable;
impl SSTable for TermInfoSSTable {
type Value = TermInfo;
type ValueReader = TermInfoReader;
type ValueWriter = TermInfoWriter;
}

View File

@@ -99,7 +99,7 @@ fn test_term_dictionary_stream() -> crate::Result<()> {
.collect();
let buffer: Vec<u8> = {
let mut term_dictionary_builder = TermDictionaryBuilder::create(vec![]).unwrap();
for (id, i) in &ids {
for &(ref id, ref i) in &ids {
term_dictionary_builder
.insert(id.as_bytes(), &make_term_info(*i as u64))
.unwrap();
@@ -112,14 +112,14 @@ fn test_term_dictionary_stream() -> crate::Result<()> {
let mut streamer = term_dictionary.stream()?;
let mut i = 0;
while let Some((streamer_k, streamer_v)) = streamer.next() {
let (key, v) = &ids[i];
let &(ref key, ref v) = &ids[i];
assert_eq!(streamer_k, key.as_bytes());
assert_eq!(streamer_v, &make_term_info(*v as u64));
i += 1;
}
}
let (key, val) = &ids[2047];
let &(ref key, ref val) = &ids[2047];
assert_eq!(
term_dictionary.get(key.as_bytes())?,
Some(make_term_info(*val as u64))
@@ -160,7 +160,7 @@ fn test_stream_range() -> crate::Result<()> {
.collect();
let buffer: Vec<u8> = {
let mut term_dictionary_builder = TermDictionaryBuilder::create(vec![]).unwrap();
for (id, i) in &ids {
for &(ref id, ref i) in &ids {
term_dictionary_builder
.insert(id.as_bytes(), &make_term_info(*i as u64))
.unwrap();
@@ -173,14 +173,14 @@ fn test_stream_range() -> crate::Result<()> {
let term_dictionary: TermDictionary = TermDictionary::open(file)?;
{
for i in (0..20).chain(6000..8_000) {
let (target_key, _) = &ids[i];
let &(ref target_key, _) = &ids[i];
let mut streamer = term_dictionary
.range()
.ge(target_key.as_bytes())
.into_stream()?;
for j in 0..3 {
let (streamer_k, streamer_v) = streamer.next().unwrap();
let (key, v) = &ids[i + j];
let &(ref key, ref v) = &ids[i + j];
assert_eq!(str::from_utf8(streamer_k).unwrap(), key);
assert_eq!(streamer_v.doc_freq, *v);
assert_eq!(streamer_v, &make_term_info(*v as u64));
@@ -190,14 +190,14 @@ fn test_stream_range() -> crate::Result<()> {
{
for i in (0..20).chain(BLOCK_SIZE - 10..BLOCK_SIZE + 10) {
let (target_key, _) = &ids[i];
let &(ref target_key, _) = &ids[i];
let mut streamer = term_dictionary
.range()
.gt(target_key.as_bytes())
.into_stream()?;
for j in 0..3 {
let (streamer_k, streamer_v) = streamer.next().unwrap();
let (key, v) = &ids[i + j + 1];
let &(ref key, ref v) = &ids[i + j + 1];
assert_eq!(streamer_k, key.as_bytes());
assert_eq!(streamer_v.doc_freq, *v);
}
@@ -207,8 +207,8 @@ fn test_stream_range() -> crate::Result<()> {
{
for i in (0..20).chain(BLOCK_SIZE - 10..BLOCK_SIZE + 10) {
for j in 0..3 {
let (fst_key, _) = &ids[i];
let (last_key, _) = &ids[i + j];
let &(ref fst_key, _) = &ids[i];
let &(ref last_key, _) = &ids[i + j];
let mut streamer = term_dictionary
.range()
.ge(fst_key.as_bytes())

View File

@@ -52,8 +52,6 @@
//! remove their inflection. This tokenizer is slower than the default one,
//! but is recommended to improve recall.
//!
//! # Custom tokenizer Library
//! Avoid using tantivy as dependency and prefer `tantivy-tokenizer-api` instead.
//!
//! # Custom tokenizers
//!
@@ -126,7 +124,6 @@ mod facet_tokenizer;
mod lower_caser;
mod ngram_tokenizer;
mod raw_tokenizer;
mod regex_tokenizer;
mod remove_long;
mod simple_tokenizer;
mod split_compound_words;
@@ -137,24 +134,21 @@ mod tokenizer;
mod tokenizer_manager;
mod whitespace_tokenizer;
pub use tokenizer_api::{
BoxTokenFilter, BoxTokenStream, Token, TokenFilter, TokenStream, Tokenizer,
};
pub use self::alphanum_only::AlphaNumOnlyFilter;
pub use self::ascii_folding_filter::AsciiFoldingFilter;
pub use self::facet_tokenizer::FacetTokenizer;
pub use self::lower_caser::LowerCaser;
pub use self::ngram_tokenizer::NgramTokenizer;
pub use self::raw_tokenizer::RawTokenizer;
pub use self::regex_tokenizer::RegexTokenizer;
pub use self::remove_long::RemoveLongFilter;
pub use self::simple_tokenizer::SimpleTokenizer;
pub use self::split_compound_words::SplitCompoundWords;
pub use self::stemmer::{Language, Stemmer};
pub use self::stop_word_filter::StopWordFilter;
pub use self::tokenized_string::{PreTokenizedStream, PreTokenizedString};
pub use self::tokenizer::TextAnalyzer;
pub use self::tokenizer::{
BoxTokenFilter, BoxTokenStream, TextAnalyzer, Token, TokenFilter, TokenStream, Tokenizer,
};
pub use self::tokenizer_manager::TokenizerManager;
pub use self::whitespace_tokenizer::WhitespaceTokenizer;

View File

@@ -303,7 +303,8 @@ mod tests {
use super::{utf8_codepoint_width, CodepointFrontiers, NgramTokenizer, StutteringIterator};
use crate::tokenizer::tests::assert_token;
use crate::tokenizer::{BoxTokenStream, Token, Tokenizer};
use crate::tokenizer::tokenizer::Tokenizer;
use crate::tokenizer::{BoxTokenStream, Token};
fn test_helper(mut tokenizer: BoxTokenStream) -> Vec<Token> {
let mut tokens: Vec<Token> = vec![];

View File

@@ -1,158 +0,0 @@
use regex::Regex;
use super::{BoxTokenStream, Token, TokenStream, Tokenizer};
use crate::TantivyError;
/// Tokenize the text by using a regex pattern to split.
/// Each match of the regex emits a distinct token, empty tokens will not be emitted. Anchors such
/// as `\A` will match the text from the part where the last token was emitted or the beginning of
/// the complete text if no token was emitted yet.
///
/// Example: `` 'aaa' bbb 'ccc' 'ddd' `` with the pattern `` '(?:\w*)' `` will be tokenized as
/// followed:
///
/// | Term | aaa | ccc | ddd |
/// |----------|------|--------|-------|
/// | Position | 1 | 2 | 3 |
/// | Offsets |0,5 | 10,15 | 16,21 |
///
///
/// # Example
///
/// ```rust
/// use tantivy::tokenizer::*;
///
/// let tokenizer = RegexTokenizer::new(r"'(?:\w*)'").unwrap();
/// let mut stream = tokenizer.token_stream("'aaa' bbb 'ccc' 'ddd'");
/// {
/// let token = stream.next().unwrap();
/// assert_eq!(token.text, "'aaa'");
/// assert_eq!(token.offset_from, 0);
/// assert_eq!(token.offset_to, 5);
/// }
/// {
/// let token = stream.next().unwrap();
/// assert_eq!(token.text, "'ccc'");
/// assert_eq!(token.offset_from, 10);
/// assert_eq!(token.offset_to, 15);
/// }
/// {
/// let token = stream.next().unwrap();
/// assert_eq!(token.text, "'ddd'");
/// assert_eq!(token.offset_from, 16);
/// assert_eq!(token.offset_to, 21);
/// }
/// assert!(stream.next().is_none());
/// ```
#[derive(Clone)]
pub struct RegexTokenizer {
regex: Regex,
}
impl RegexTokenizer {
/// Creates a new RegexTokenizer.
pub fn new(regex_pattern: &str) -> crate::Result<RegexTokenizer> {
Regex::new(regex_pattern)
.map_err(|_| TantivyError::InvalidArgument(regex_pattern.to_owned()))
.map(|regex| Self { regex })
}
}
impl Tokenizer for RegexTokenizer {
fn token_stream<'a>(&self, text: &'a str) -> BoxTokenStream<'a> {
BoxTokenStream::from(RegexTokenStream {
regex: self.regex.clone(),
text,
token: Token::default(),
cursor: 0,
})
}
}
pub struct RegexTokenStream<'a> {
regex: Regex,
text: &'a str,
token: Token,
cursor: usize,
}
impl<'a> TokenStream for RegexTokenStream<'a> {
fn advance(&mut self) -> bool {
let Some(regex_match) = self.regex.find(self.text) else {
return false;
};
if regex_match.as_str().is_empty() {
return false;
}
self.token.text.clear();
self.token.text.push_str(regex_match.as_str());
self.token.offset_from = self.cursor + regex_match.start();
self.cursor += regex_match.end();
self.token.offset_to = self.cursor;
self.token.position = self.token.position.wrapping_add(1);
self.text = &self.text[regex_match.end()..];
true
}
fn token(&self) -> &Token {
&self.token
}
fn token_mut(&mut self) -> &mut Token {
&mut self.token
}
}
#[cfg(test)]
mod tests {
use crate::tokenizer::regex_tokenizer::RegexTokenizer;
use crate::tokenizer::tests::assert_token;
use crate::tokenizer::{TextAnalyzer, Token};
#[test]
fn test_regex_tokenizer() {
let tokens = token_stream_helper("'aaa' bbb 'ccc' 'ddd'", r"'(?:\w*)'");
assert_eq!(tokens.len(), 3);
assert_token(&tokens[0], 0, "'aaa'", 0, 5);
assert_token(&tokens[1], 1, "'ccc'", 10, 15);
assert_token(&tokens[2], 2, "'ddd'", 16, 21);
}
#[test]
fn test_regexp_tokenizer_no_match_on_input_data() {
let tokens = token_stream_helper("aaa", r"'(?:\w*)'");
assert_eq!(tokens.len(), 0);
}
#[test]
fn test_regexp_tokenizer_no_input_data() {
let tokens = token_stream_helper("", r"'(?:\w*)'");
assert_eq!(tokens.len(), 0);
}
#[test]
fn test_regexp_tokenizer_error_on_invalid_regex() {
let tokenizer = RegexTokenizer::new(r"\@");
assert_eq!(tokenizer.is_err(), true);
assert_eq!(
tokenizer.err().unwrap().to_string(),
"An invalid argument was passed: '\\@'"
);
}
fn token_stream_helper(text: &str, pattern: &str) -> Vec<Token> {
let r = RegexTokenizer::new(pattern).unwrap();
let a = TextAnalyzer::from(r);
let mut token_stream = a.token_stream(text);
let mut tokens: Vec<Token> = vec![];
let mut add_token = |token: &Token| {
tokens.push(token.clone());
};
token_stream.process(&mut add_token);
tokens
}
}

View File

@@ -26,7 +26,7 @@ impl<'a> SimpleTokenStream<'a> {
// search for the end of the current token.
fn search_token_end(&mut self) -> usize {
(&mut self.chars)
.filter(|(_, c)| !c.is_alphanumeric())
.filter(|&(_, ref c)| !c.is_alphanumeric())
.map(|(offset, _)| offset)
.next()
.unwrap_or(self.text.len())

View File

@@ -1,9 +1,42 @@
/// The tokenizer module contains all of the tools used to process
/// text in `tantivy`.
use tokenizer_api::{BoxTokenFilter, BoxTokenStream, Tokenizer};
use std::borrow::{Borrow, BorrowMut};
use std::ops::{Deref, DerefMut};
use serde::{Deserialize, Serialize};
use crate::tokenizer::empty_tokenizer::EmptyTokenizer;
/// Token
#[derive(Debug, Clone, Serialize, Deserialize, Eq, PartialEq)]
pub struct Token {
/// Offset (byte index) of the first character of the token.
/// Offsets shall not be modified by token filters.
pub offset_from: usize,
/// Offset (byte index) of the last character of the token + 1.
/// The text that generated the token should be obtained by
/// &text[token.offset_from..token.offset_to]
pub offset_to: usize,
/// Position, expressed in number of tokens.
pub position: usize,
/// Actual text content of the token.
pub text: String,
/// Is the length expressed in term of number of original tokens.
pub position_length: usize,
}
impl Default for Token {
fn default() -> Token {
Token {
offset_from: 0,
offset_to: 0,
position: usize::MAX,
text: String::with_capacity(200),
position_length: 1,
}
}
}
/// `TextAnalyzer` tokenizes an input text into tokens and modifies the resulting `TokenStream`.
///
/// It simply wraps a `Tokenizer` and a list of `TokenFilter` that are applied sequentially.
@@ -79,3 +112,200 @@ impl Clone for TextAnalyzer {
}
}
}
/// `Tokenizer` are in charge of splitting text into a stream of token
/// before indexing.
///
/// See the [module documentation](crate::tokenizer) for more detail.
///
/// # Warning
///
/// This API may change to use associated types.
pub trait Tokenizer: 'static + Send + Sync + TokenizerClone {
/// Creates a token stream for a given `str`.
fn token_stream<'a>(&self, text: &'a str) -> BoxTokenStream<'a>;
}
pub trait TokenizerClone {
fn box_clone(&self) -> Box<dyn Tokenizer>;
}
impl<T: Tokenizer + Clone> TokenizerClone for T {
fn box_clone(&self) -> Box<dyn Tokenizer> {
Box::new(self.clone())
}
}
impl<'a> TokenStream for Box<dyn TokenStream + 'a> {
fn advance(&mut self) -> bool {
let token_stream: &mut dyn TokenStream = self.borrow_mut();
token_stream.advance()
}
fn token<'b>(&'b self) -> &'b Token {
let token_stream: &'b (dyn TokenStream + 'a) = self.borrow();
token_stream.token()
}
fn token_mut<'b>(&'b mut self) -> &'b mut Token {
let token_stream: &'b mut (dyn TokenStream + 'a) = self.borrow_mut();
token_stream.token_mut()
}
}
/// Simple wrapper of `Box<dyn TokenStream + 'a>`.
///
/// See [`TokenStream`] for more information.
pub struct BoxTokenStream<'a>(Box<dyn TokenStream + 'a>);
impl<'a, T> From<T> for BoxTokenStream<'a>
where T: TokenStream + 'a
{
fn from(token_stream: T) -> BoxTokenStream<'a> {
BoxTokenStream(Box::new(token_stream))
}
}
impl<'a> Deref for BoxTokenStream<'a> {
type Target = dyn TokenStream + 'a;
fn deref(&self) -> &Self::Target {
&*self.0
}
}
impl<'a> DerefMut for BoxTokenStream<'a> {
fn deref_mut(&mut self) -> &mut Self::Target {
&mut *self.0
}
}
/// Simple wrapper of `Box<dyn TokenFilter + 'a>`.
///
/// See [`TokenFilter`] for more information.
pub struct BoxTokenFilter(Box<dyn TokenFilter>);
impl Deref for BoxTokenFilter {
type Target = dyn TokenFilter;
fn deref(&self) -> &dyn TokenFilter {
&*self.0
}
}
impl<T: TokenFilter> From<T> for BoxTokenFilter {
fn from(tokenizer: T) -> BoxTokenFilter {
BoxTokenFilter(Box::new(tokenizer))
}
}
/// `TokenStream` is the result of the tokenization.
///
/// It consists consumable stream of `Token`s.
///
/// # Example
///
/// ```
/// use tantivy::tokenizer::*;
///
/// let tokenizer = TextAnalyzer::from(SimpleTokenizer)
/// .filter(RemoveLongFilter::limit(40))
/// .filter(LowerCaser);
/// let mut token_stream = tokenizer.token_stream("Hello, happy tax payer");
/// {
/// let token = token_stream.next().unwrap();
/// assert_eq!(&token.text, "hello");
/// assert_eq!(token.offset_from, 0);
/// assert_eq!(token.offset_to, 5);
/// assert_eq!(token.position, 0);
/// }
/// {
/// let token = token_stream.next().unwrap();
/// assert_eq!(&token.text, "happy");
/// assert_eq!(token.offset_from, 7);
/// assert_eq!(token.offset_to, 12);
/// assert_eq!(token.position, 1);
/// }
/// ```
pub trait TokenStream {
/// Advance to the next token
///
/// Returns false if there are no other tokens.
fn advance(&mut self) -> bool;
/// Returns a reference to the current token.
fn token(&self) -> &Token;
/// Returns a mutable reference to the current token.
fn token_mut(&mut self) -> &mut Token;
/// Helper to iterate over tokens. It
/// simply combines a call to `.advance()`
/// and `.token()`.
///
/// ```
/// use tantivy::tokenizer::*;
///
/// let tokenizer = TextAnalyzer::from(SimpleTokenizer)
/// .filter(RemoveLongFilter::limit(40))
/// .filter(LowerCaser);
/// let mut token_stream = tokenizer.token_stream("Hello, happy tax payer");
/// while let Some(token) = token_stream.next() {
/// println!("Token {:?}", token.text);
/// }
/// ```
fn next(&mut self) -> Option<&Token> {
if self.advance() {
Some(self.token())
} else {
None
}
}
/// Helper function to consume the entire `TokenStream`
/// and push the tokens to a sink function.
///
/// Remove this.
fn process(&mut self, sink: &mut dyn FnMut(&Token)) {
while self.advance() {
sink(self.token());
}
}
}
pub trait TokenFilterClone {
fn box_clone(&self) -> BoxTokenFilter;
}
/// Trait for the pluggable components of `Tokenizer`s.
pub trait TokenFilter: 'static + Send + Sync + TokenFilterClone {
/// Wraps a token stream and returns the modified one.
fn transform<'a>(&self, token_stream: BoxTokenStream<'a>) -> BoxTokenStream<'a>;
}
impl<T: TokenFilter + Clone> TokenFilterClone for T {
fn box_clone(&self) -> BoxTokenFilter {
BoxTokenFilter::from(self.clone())
}
}
#[cfg(test)]
mod test {
use super::Token;
#[test]
fn clone() {
let t1 = Token {
position: 1,
offset_from: 2,
offset_to: 3,
text: "abc".to_string(),
position_length: 1,
};
let t2 = t1.clone();
assert_eq!(t1.position, t2.position);
assert_eq!(t1.offset_from, t2.offset_from);
assert_eq!(t1.offset_to, t2.offset_to);
assert_eq!(t1.text, t2.text);
}
}

View File

@@ -26,7 +26,7 @@ impl<'a> WhitespaceTokenStream<'a> {
// search for the end of the current token.
fn search_token_end(&mut self) -> usize {
(&mut self.chars)
.filter(|(_, c)| c.is_ascii_whitespace())
.filter(|&(_, ref c)| c.is_ascii_whitespace())
.map(|(offset, _)| offset)
.next()
.unwrap_or(self.text.len())

View File

@@ -2,7 +2,6 @@
name = "tantivy-sstable"
version = "0.1.0"
edition = "2021"
license = "MIT"
[dependencies]
common = {path="../common", package="tantivy-common"}
@@ -12,10 +11,3 @@ tantivy-fst = "0.4"
[dev-dependencies]
proptest = "1"
criterion = "0.4"
names = "0.14"
rand = "0.8"
[[bench]]
name = "stream_bench"
harness = false

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@@ -1,28 +0,0 @@
# SSTable
The `tantivy-sstable` crate is yet another sstable crate.
It has been designed to be used in `quickwit`:
- as an alternative to the default tantivy fst dictionary.
- as a way to store the column index for dynamic fast fields.
The benefit compared to the fst crate is locality.
Searching a key in the fst crate requires downloading the entire dictionary.
Once the sstable index is downloaded, running a `get` in the sstable
crate only requires a single fetch.
Right now, the block index and the default block size have been thought
for quickwit, and the performance of a get is very bad.
# Sorted strings?
SSTable stands for Sorted String Table.
Strings have to be insert in sorted order.
That sorted order is used in different ways:
- it makes gets and streaming ranges of keys
possible.
- it allows incremental encoding of the keys
- the front compression is leveraged to optimize
the intersection with an automaton

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