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@@ -15,11 +15,11 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Install Rust
run: rustup toolchain install nightly-2024-04-10 --profile minimal --component llvm-tools-preview
run: rustup toolchain install nightly-2023-09-10 --profile minimal --component llvm-tools-preview
- uses: Swatinem/rust-cache@v2
- uses: taiki-e/install-action@cargo-llvm-cov
- name: Generate code coverage
run: cargo +nightly-2024-04-10 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
run: cargo +nightly-2023-09-10 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
continue-on-error: true

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@@ -1,65 +1,3 @@
Tantivy 0.22
================================
Tantivy 0.22 will be able to read indices created with Tantivy 0.21.
#### Bugfixes
- Fix null byte handling in JSON paths (null bytes in json keys caused panic during indexing) [#2345](https://github.com/quickwit-oss/tantivy/pull/2345)(@PSeitz)
- Fix bug that can cause `get_docids_for_value_range` to panic. [#2295](https://github.com/quickwit-oss/tantivy/pull/2295)(@fulmicoton)
- Avoid 1 document indices by increase min memory to 15MB for indexing [#2176](https://github.com/quickwit-oss/tantivy/pull/2176)(@PSeitz)
- Fix merge panic for JSON fields [#2284](https://github.com/quickwit-oss/tantivy/pull/2284)(@PSeitz)
- Fix bug occuring when merging JSON object indexed with positions. [#2253](https://github.com/quickwit-oss/tantivy/pull/2253)(@fulmicoton)
- Fix empty DateHistogram gap bug [#2183](https://github.com/quickwit-oss/tantivy/pull/2183)(@PSeitz)
- Fix range query end check (fields with less than 1 value per doc are affected) [#2226](https://github.com/quickwit-oss/tantivy/pull/2226)(@PSeitz)
- Handle exclusive out of bounds ranges on fastfield range queries [#2174](https://github.com/quickwit-oss/tantivy/pull/2174)(@PSeitz)
#### Breaking API Changes
- rename ReloadPolicy onCommit to onCommitWithDelay [#2235](https://github.com/quickwit-oss/tantivy/pull/2235)(@giovannicuccu)
- Move exports from the root into modules [#2220](https://github.com/quickwit-oss/tantivy/pull/2220)(@PSeitz)
- Accept field name instead of `Field` in FilterCollector [#2196](https://github.com/quickwit-oss/tantivy/pull/2196)(@PSeitz)
- remove deprecated IntOptions and DateTime [#2353](https://github.com/quickwit-oss/tantivy/pull/2353)(@PSeitz)
#### Features/Improvements
- Tantivy documents as a trait: Index data directly without converting to tantivy types first [#2071](https://github.com/quickwit-oss/tantivy/pull/2071)(@ChillFish8)
- encode some part of posting list as -1 instead of direct values (smaller inverted indices) [#2185](https://github.com/quickwit-oss/tantivy/pull/2185)(@trinity-1686a)
- **Aggregation**
- Support to deserialize f64 from string [#2311](https://github.com/quickwit-oss/tantivy/pull/2311)(@PSeitz)
- Add a top_hits aggregator [#2198](https://github.com/quickwit-oss/tantivy/pull/2198)(@ditsuke)
- Support bool type in term aggregation [#2318](https://github.com/quickwit-oss/tantivy/pull/2318)(@PSeitz)
- Support ip adresses in term aggregation [#2319](https://github.com/quickwit-oss/tantivy/pull/2319)(@PSeitz)
- Support date type in term aggregation [#2172](https://github.com/quickwit-oss/tantivy/pull/2172)(@PSeitz)
- Support escaped dot when addressing field [#2250](https://github.com/quickwit-oss/tantivy/pull/2250)(@PSeitz)
- Add ExistsQuery to check documents that have a value [#2160](https://github.com/quickwit-oss/tantivy/pull/2160)(@imotov)
- Expose TopDocs::order_by_u64_field again [#2282](https://github.com/quickwit-oss/tantivy/pull/2282)(@ditsuke)
- **Memory/Performance**
- Faster TopN: replace BinaryHeap with TopNComputer [#2186](https://github.com/quickwit-oss/tantivy/pull/2186)(@PSeitz)
- reduce number of allocations during indexing [#2257](https://github.com/quickwit-oss/tantivy/pull/2257)(@PSeitz)
- Less Memory while indexing: docid deltas while indexing [#2249](https://github.com/quickwit-oss/tantivy/pull/2249)(@PSeitz)
- Faster indexing: use term hashmap in fastfield [#2243](https://github.com/quickwit-oss/tantivy/pull/2243)(@PSeitz)
- term hashmap remove copy in is_empty, unused unordered_id [#2229](https://github.com/quickwit-oss/tantivy/pull/2229)(@PSeitz)
- add method to fetch block of first values in columnar [#2330](https://github.com/quickwit-oss/tantivy/pull/2330)(@PSeitz)
- Faster aggregations: add fast path for full columns in fetch_block [#2328](https://github.com/quickwit-oss/tantivy/pull/2328)(@PSeitz)
- Faster sstable loading: use fst for sstable index [#2268](https://github.com/quickwit-oss/tantivy/pull/2268)(@trinity-1686a)
- **QueryParser**
- allow newline where we allow space in query parser [#2302](https://github.com/quickwit-oss/tantivy/pull/2302)(@trinity-1686a)
- allow some mixing of occur and bool in strict query parser [#2323](https://github.com/quickwit-oss/tantivy/pull/2323)(@trinity-1686a)
- handle * inside term in lenient query parser [#2228](https://github.com/quickwit-oss/tantivy/pull/2228)(@trinity-1686a)
- add support for exists query syntax in query parser [#2170](https://github.com/quickwit-oss/tantivy/pull/2170)(@trinity-1686a)
- Add shared search executor [#2312](https://github.com/quickwit-oss/tantivy/pull/2312)(@MochiXu)
- Truncate keys to u16::MAX in term hashmap [#2299](https://github.com/quickwit-oss/tantivy/pull/2299)(@PSeitz)
- report if a term matched when warming up posting list [#2309](https://github.com/quickwit-oss/tantivy/pull/2309)(@trinity-1686a)
- Support json fields in FuzzyTermQuery [#2173](https://github.com/quickwit-oss/tantivy/pull/2173)(@PingXia-at)
- Read list of fields encoded in term dictionary for JSON fields [#2184](https://github.com/quickwit-oss/tantivy/pull/2184)(@PSeitz)
- add collect_block to BoxableSegmentCollector [#2331](https://github.com/quickwit-oss/tantivy/pull/2331)(@PSeitz)
- expose collect_block buffer size [#2326](https://github.com/quickwit-oss/tantivy/pull/2326)(@PSeitz)
- Forward regex parser errors [#2288](https://github.com/quickwit-oss/tantivy/pull/2288)(@adamreichold)
- Make FacetCounts defaultable and cloneable. [#2322](https://github.com/quickwit-oss/tantivy/pull/2322)(@adamreichold)
- Derive Debug for SchemaBuilder [#2254](https://github.com/quickwit-oss/tantivy/pull/2254)(@GodTamIt)
- add missing inlines to tantivy options [#2245](https://github.com/quickwit-oss/tantivy/pull/2245)(@PSeitz)
Tantivy 0.21.1
================================
#### Bugfixes

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@@ -1,6 +1,6 @@
[package]
name = "tantivy"
version = "0.22.0"
version = "0.22.0-dev"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -11,12 +11,12 @@ repository = "https://github.com/quickwit-oss/tantivy"
readme = "README.md"
keywords = ["search", "information", "retrieval"]
edition = "2021"
rust-version = "1.63"
rust-version = "1.62"
exclude = ["benches/*.json", "benches/*.txt"]
[dependencies]
oneshot = "0.1.5"
base64 = "0.22.0"
base64 = "0.21.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
once_cell = "1.10.0"
@@ -31,14 +31,14 @@ log = "0.4.16"
serde = { version = "1.0.136", features = ["derive"] }
serde_json = "1.0.79"
num_cpus = "1.13.1"
fs4 = { version = "0.8.0", optional = true }
fs4 = { version = "0.7.0", optional = true }
levenshtein_automata = "0.2.1"
uuid = { version = "1.0.0", features = ["v4", "serde"] }
crossbeam-channel = "0.5.4"
rust-stemmers = "1.2.0"
downcast-rs = "1.2.0"
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker4x"] }
census = "0.4.2"
census = "0.4.0"
rustc-hash = "1.1.0"
thiserror = "1.0.30"
htmlescape = "0.3.1"
@@ -52,17 +52,16 @@ itertools = "0.12.0"
measure_time = "0.8.2"
arc-swap = "1.5.0"
columnar = { version= "0.3", path="./columnar", package ="tantivy-columnar" }
sstable = { version= "0.3", path="./sstable", package ="tantivy-sstable", optional = true }
stacker = { version= "0.3", path="./stacker", package ="tantivy-stacker" }
query-grammar = { version= "0.22.0", path="./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version= "0.6", path="./bitpacker" }
common = { version= "0.7", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version= "0.3", path="./tokenizer-api", package="tantivy-tokenizer-api" }
columnar = { version= "0.2", path="./columnar", package ="tantivy-columnar" }
sstable = { version= "0.2", path="./sstable", package ="tantivy-sstable", optional = true }
stacker = { version= "0.2", path="./stacker", package ="tantivy-stacker" }
query-grammar = { version= "0.21.0", path="./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version= "0.5", path="./bitpacker" }
common = { version= "0.6", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version= "0.2", path="./tokenizer-api", package="tantivy-tokenizer-api" }
sketches-ddsketch = { version = "0.2.1", features = ["use_serde"] }
futures-util = { version = "0.3.28", optional = true }
fnv = "1.0.7"
mediumvec = "1.3.0"
[target.'cfg(windows)'.dependencies]
winapi = "0.3.9"
@@ -78,11 +77,6 @@ futures = "0.3.21"
paste = "1.0.11"
more-asserts = "0.3.1"
rand_distr = "0.4.3"
time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
postcard = { version = "1.0.4", features = [
"use-std",
], default-features = false }
peakmem-alloc = "0.3.0"
[target.'cfg(not(windows))'.dev-dependencies]
criterion = { version = "0.5", default-features = false }

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@@ -5,18 +5,19 @@
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Crates.io](https://img.shields.io/crates/v/tantivy.svg)](https://crates.io/crates/tantivy)
<img src="https://tantivy-search.github.io/logo/tantivy-logo.png" alt="Tantivy, the fastest full-text search engine library written in Rust" height="250">
![Tantivy](https://tantivy-search.github.io/logo/tantivy-logo.png)
## Fast full-text search engine library written in Rust
**Tantivy** is a **full-text search engine library** written in Rust.
**If you are looking for an alternative to Elasticsearch or Apache Solr, check out [Quickwit](https://github.com/quickwit-oss/quickwit), our distributed search engine built on top of Tantivy.**
Tantivy is closer to [Apache Lucene](https://lucene.apache.org/) than to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Apache Solr](https://lucene.apache.org/solr/) in the sense it is not
an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine.
It is closer to [Apache Lucene](https://lucene.apache.org/) than to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Apache Solr](https://lucene.apache.org/solr/) in the sense it is not
an off-the-shelf search engine server, but rather a crate that can be used
to build such a search engine.
Tantivy is, in fact, strongly inspired by Lucene's design.
## Benchmark
If you are looking for an alternative to Elasticsearch or Apache Solr, check out [Quickwit](https://github.com/quickwit-oss/quickwit), our search engine built on top of Tantivy.
# Benchmark
The following [benchmark](https://tantivy-search.github.io/bench/) breakdowns
performance for different types of queries/collections.
@@ -27,7 +28,7 @@ Your mileage WILL vary depending on the nature of queries and their load.
Details about the benchmark can be found at this [repository](https://github.com/quickwit-oss/search-benchmark-game).
## Features
# 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))
@@ -53,11 +54,11 @@ Details about the benchmark can be found at this [repository](https://github.com
- Searcher Warmer API
- Cheesy logo with a horse
### Non-features
## Non-features
Distributed search is out of the scope of Tantivy, but if you are looking for this feature, check out [Quickwit](https://github.com/quickwit-oss/quickwit/).
## Getting started
# Getting started
Tantivy works on stable Rust and supports Linux, macOS, and Windows.
@@ -67,7 +68,7 @@ index documents, and search via the CLI or a small server with a REST API.
It walks you through getting a Wikipedia search engine up and running in a few minutes.
- [Reference doc for the last released version](https://docs.rs/tantivy/)
## How can I support this project?
# How can I support this project?
There are many ways to support this project.
@@ -78,16 +79,16 @@ There are many ways to support this project.
- Contribute code (you can join [our Discord server](https://discord.gg/MT27AG5EVE))
- Talk about Tantivy around you
## Contributing code
# Contributing code
We use the GitHub Pull Request workflow: reference a GitHub ticket and/or include a comprehensive commit message when opening a PR.
Feel free to update CHANGELOG.md with your contribution.
### Tokenizer
## Tokenizer
When implementing a tokenizer for tantivy depend on the `tantivy-tokenizer-api` crate.
### Clone and build locally
## Clone and build locally
Tantivy compiles on stable Rust.
To check out and run tests, you can simply run:
@@ -98,7 +99,7 @@ cd tantivy
cargo test
```
## Companies Using Tantivy
# Companies Using Tantivy
<p align="left">
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />&nbsp;
@@ -110,7 +111,7 @@ cargo test
<img align="center" src="doc/assets/images/element-dark-theme.png#gh-dark-mode-only" alt="Element.io" height="25" width="auto" />
</p>
## FAQ
# FAQ
### Can I use Tantivy in other languages?

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@@ -1,6 +1,6 @@
[package]
name = "tantivy-bitpacker"
version = "0.6.0"
version = "0.5.0"
edition = "2021"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"

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@@ -1,3 +1,4 @@
use std::convert::TryInto;
use std::io;
use std::ops::{Range, RangeInclusive};

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@@ -1,10 +1,6 @@
# configuration file for git-cliff{ pattern = "foo", replace = "bar"}
# see https://github.com/orhun/git-cliff#configuration-file
[remote.github]
owner = "quickwit-oss"
repo = "tantivy"
[changelog]
# changelog header
header = """
@@ -12,43 +8,15 @@ header = """
# template for the changelog body
# https://tera.netlify.app/docs/#introduction
body = """
## What's Changed
{%- if version %} in {{ version }}{%- endif -%}
{% if version %}\
{{ version | trim_start_matches(pat="v") }} ({{ timestamp | date(format="%Y-%m-%d") }})
==================
{% else %}\
## [unreleased]
{% endif %}\
{% for commit in commits %}
{% if commit.github.pr_title -%}
{%- set commit_message = commit.github.pr_title -%}
{%- else -%}
{%- set commit_message = commit.message -%}
{%- endif -%}
- {{ commit_message | split(pat="\n") | first | trim }}\
{% if commit.github.pr_number %} \
[#{{ commit.github.pr_number }}]({{ self::remote_url() }}/pull/{{ commit.github.pr_number }}){% if commit.github.username %}(@{{ commit.github.username }}){%- endif -%} \
{%- endif %}
{%- endfor -%}
{% if github.contributors | filter(attribute="is_first_time", value=true) | length != 0 %}
{% raw %}\n{% endraw -%}
## New Contributors
{%- endif %}\
{% for contributor in github.contributors | filter(attribute="is_first_time", value=true) %}
* @{{ contributor.username }} made their first contribution
{%- if contributor.pr_number %} in \
[#{{ contributor.pr_number }}]({{ self::remote_url() }}/pull/{{ contributor.pr_number }}) \
{%- endif %}
{%- endfor -%}
{% if version %}
{% if previous.version %}
**Full Changelog**: {{ self::remote_url() }}/compare/{{ previous.version }}...{{ version }}
{% endif %}
{% else -%}
{% raw %}\n{% endraw %}
{% endif %}
{%- macro remote_url() -%}
https://github.com/{{ remote.github.owner }}/{{ remote.github.repo }}
{%- endmacro -%}
- {% if commit.breaking %}[**breaking**] {% endif %}{{ commit.message | split(pat="\n") | first | trim | upper_first }}(@{{ commit.author.name }})\
{% endfor %}
"""
# remove the leading and trailing whitespace from the template
trim = true
@@ -57,24 +25,53 @@ footer = """
"""
postprocessors = [
{ pattern = 'Paul Masurel', replace = "fulmicoton"}, # replace with github user
{ pattern = 'PSeitz', replace = "PSeitz"}, # replace with github user
{ pattern = 'Adam Reichold', replace = "adamreichold"}, # replace with github user
{ pattern = 'trinity-1686a', replace = "trinity-1686a"}, # replace with github user
{ pattern = 'Michael Kleen', replace = "mkleen"}, # replace with github user
{ pattern = 'Adrien Guillo', replace = "guilload"}, # replace with github user
{ pattern = 'François Massot', replace = "fmassot"}, # replace with github user
{ pattern = 'Naveen Aiathurai', replace = "naveenann"}, # replace with github user
{ pattern = '', replace = ""}, # replace with github user
]
[git]
# parse the commits based on https://www.conventionalcommits.org
# This is required or commit.message contains the whole commit message and not just the title
conventional_commits = false
conventional_commits = true
# filter out the commits that are not conventional
filter_unconventional = true
filter_unconventional = false
# process each line of a commit as an individual commit
split_commits = false
# regex for preprocessing the commit messages
commit_preprocessors = [
{ pattern = '\((\w+\s)?#([0-9]+)\)', replace = ""},
{ pattern = '\((\w+\s)?#([0-9]+)\)', replace = "[#${2}](https://github.com/quickwit-oss/tantivy/issues/${2})"}, # replace issue numbers
]
#link_parsers = [
#{ pattern = "#(\\d+)", href = "https://github.com/quickwit-oss/tantivy/pulls/$1"},
#]
# regex for parsing and grouping commits
commit_parsers = [
{ message = "^feat", group = "Features"},
{ message = "^fix", group = "Bug Fixes"},
{ message = "^doc", group = "Documentation"},
{ message = "^perf", group = "Performance"},
{ message = "^refactor", group = "Refactor"},
{ message = "^style", group = "Styling"},
{ message = "^test", group = "Testing"},
{ message = "^chore\\(release\\): prepare for", skip = true},
{ message = "(?i)clippy", skip = true},
{ message = "(?i)dependabot", skip = true},
{ message = "(?i)fmt", skip = true},
{ message = "(?i)bump", skip = true},
{ message = "(?i)readme", skip = true},
{ message = "(?i)comment", skip = true},
{ message = "(?i)spelling", skip = true},
{ message = "^chore", group = "Miscellaneous Tasks"},
{ body = ".*security", group = "Security"},
{ message = ".*", group = "Other", default_scope = "other"},
]
# protect breaking changes from being skipped due to matching a skipping commit_parser
protect_breaking_commits = false
# filter out the commits that are not matched by commit parsers

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-columnar"
version = "0.3.0"
version = "0.2.0"
edition = "2021"
license = "MIT"
homepage = "https://github.com/quickwit-oss/tantivy"
@@ -12,12 +12,11 @@ categories = ["database-implementations", "data-structures", "compression"]
itertools = "0.12.0"
fastdivide = "0.4.0"
stacker = { version= "0.3", path = "../stacker", package="tantivy-stacker"}
sstable = { version= "0.3", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.7", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.6", path = "../bitpacker/" }
stacker = { version= "0.2", path = "../stacker", package="tantivy-stacker"}
sstable = { version= "0.2", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.6", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.5", path = "../bitpacker/" }
serde = "1.0.152"
downcast-rs = "1.2.0"
[dev-dependencies]
proptest = "1"

View File

@@ -1,155 +0,0 @@
#![feature(test)]
extern crate test;
use std::sync::Arc;
use rand::prelude::*;
use tantivy_columnar::column_values::{serialize_and_load_u64_based_column_values, CodecType};
use tantivy_columnar::*;
use test::{black_box, Bencher};
struct Columns {
pub optional: Column,
pub full: Column,
pub multi: Column,
}
fn get_test_columns() -> Columns {
let data = generate_permutation();
let mut dataframe_writer = ColumnarWriter::default();
for (idx, val) in data.iter().enumerate() {
dataframe_writer.record_numerical(idx as u32, "full_values", NumericalValue::U64(*val));
if idx % 2 == 0 {
dataframe_writer.record_numerical(
idx as u32,
"optional_values",
NumericalValue::U64(*val),
);
}
dataframe_writer.record_numerical(idx as u32, "multi_values", NumericalValue::U64(*val));
dataframe_writer.record_numerical(idx as u32, "multi_values", NumericalValue::U64(*val));
}
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer
.serialize(data.len() as u32, None, &mut buffer)
.unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("optional_values").unwrap();
assert_eq!(cols.len(), 1);
let optional = cols[0].open_u64_lenient().unwrap().unwrap();
assert_eq!(optional.index.get_cardinality(), Cardinality::Optional);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("full_values").unwrap();
assert_eq!(cols.len(), 1);
let column_full = cols[0].open_u64_lenient().unwrap().unwrap();
assert_eq!(column_full.index.get_cardinality(), Cardinality::Full);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("multi_values").unwrap();
assert_eq!(cols.len(), 1);
let multi = cols[0].open_u64_lenient().unwrap().unwrap();
assert_eq!(multi.index.get_cardinality(), Cardinality::Multivalued);
Columns {
optional,
full: column_full,
multi,
}
}
const NUM_VALUES: u64 = 100_000;
fn generate_permutation() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..NUM_VALUES).collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
pub fn serialize_and_load(column: &[u64], codec_type: CodecType) -> Arc<dyn ColumnValues<u64>> {
serialize_and_load_u64_based_column_values(&column, &[codec_type])
}
fn run_bench_on_column_full_scan(b: &mut Bencher, column: Column) {
let num_iter = black_box(NUM_VALUES);
b.iter(|| {
let mut sum = 0u64;
for i in 0..num_iter as u32 {
let val = column.first(i);
sum += val.unwrap_or(0);
}
sum
});
}
fn run_bench_on_column_block_fetch(b: &mut Bencher, column: Column) {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
b.iter(move || {
column.first_vals(&fetch_docids, &mut block);
block[0]
});
}
fn run_bench_on_column_block_single_calls(b: &mut Bencher, column: Column) {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
b.iter(move || {
for i in 0..fetch_docids.len() {
block[i] = column.first(fetch_docids[i]);
}
block[0]
});
}
/// Column first method
#[bench]
fn bench_get_first_on_full_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_full_scan(b, column);
}
#[bench]
fn bench_get_first_on_optional_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_full_scan(b, column);
}
#[bench]
fn bench_get_first_on_multi_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_full_scan(b, column);
}
/// Block fetch column accessor
#[bench]
fn bench_get_block_first_on_optional_column(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_multi_column(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_full_column(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_optional_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_block_single_calls(b, column);
}
#[bench]
fn bench_get_block_first_on_multi_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_block_single_calls(b, column);
}
#[bench]
fn bench_get_block_first_on_full_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_block_single_calls(b, column);
}

View File

@@ -16,6 +16,14 @@ fn generate_permutation() -> Vec<u64> {
permutation
}
fn generate_random() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64)
.map(|el| el + random::<u16>() as u64)
.collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
// Warning: this generates the same permutation at each call
fn generate_permutation_gcd() -> Vec<u64> {
let mut permutation: Vec<u64> = (1u64..100_000u64).map(|el| el * 1000).collect();

View File

@@ -14,32 +14,20 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
ColumnBlockAccessor<T>
{
#[inline]
pub fn fetch_block<'a>(&'a mut self, docs: &'a [u32], accessor: &Column<T>) {
if accessor.index.get_cardinality().is_full() {
self.val_cache.resize(docs.len(), T::default());
accessor.values.get_vals(docs, &mut self.val_cache);
} else {
self.docid_cache.clear();
self.row_id_cache.clear();
accessor.row_ids_for_docs(docs, &mut self.docid_cache, &mut self.row_id_cache);
self.val_cache.resize(self.row_id_cache.len(), T::default());
accessor
.values
.get_vals(&self.row_id_cache, &mut self.val_cache);
}
pub fn fetch_block(&mut self, docs: &[u32], accessor: &Column<T>) {
self.docid_cache.clear();
self.row_id_cache.clear();
accessor.row_ids_for_docs(docs, &mut self.docid_cache, &mut self.row_id_cache);
self.val_cache.resize(self.row_id_cache.len(), T::default());
accessor
.values
.get_vals(&self.row_id_cache, &mut self.val_cache);
}
#[inline]
pub fn fetch_block_with_missing(&mut self, docs: &[u32], accessor: &Column<T>, missing: T) {
self.fetch_block(docs, accessor);
// no missing values
if accessor.index.get_cardinality().is_full() {
return;
}
// We can compare docid_cache length with docs to find missing docs
// For multi value columns we can't rely on the length and always need to scan
if accessor.index.get_cardinality().is_multivalue() || docs.len() != self.docid_cache.len()
{
// We can compare docid_cache with docs to find missing docs
if docs.len() != self.docid_cache.len() || accessor.index.is_multivalue() {
self.missing_docids_cache.clear();
find_missing_docs(docs, &self.docid_cache, |doc| {
self.missing_docids_cache.push(doc);
@@ -56,25 +44,11 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
}
#[inline]
/// Returns an iterator over the docids and values
/// The passed in `docs` slice needs to be the same slice that was passed to `fetch_block` or
/// `fetch_block_with_missing`.
///
/// The docs is used if the column is full (each docs has exactly one value), otherwise the
/// internal docid vec is used for the iterator, which e.g. may contain duplicate docs.
pub fn iter_docid_vals<'a>(
&'a self,
docs: &'a [u32],
accessor: &Column<T>,
) -> impl Iterator<Item = (DocId, T)> + '_ {
if accessor.index.get_cardinality().is_full() {
docs.iter().cloned().zip(self.val_cache.iter().cloned())
} else {
self.docid_cache
.iter()
.cloned()
.zip(self.val_cache.iter().cloned())
}
pub fn iter_docid_vals(&self) -> impl Iterator<Item = (DocId, T)> + '_ {
self.docid_cache
.iter()
.cloned()
.zip(self.val_cache.iter().cloned())
}
}

View File

@@ -3,17 +3,17 @@ mod serialize;
use std::fmt::{self, Debug};
use std::io::Write;
use std::ops::{Range, RangeInclusive};
use std::ops::{Deref, Range, RangeInclusive};
use std::sync::Arc;
use common::BinarySerializable;
pub use dictionary_encoded::{BytesColumn, StrColumn};
pub use serialize::{
open_column_bytes, open_column_str, open_column_u128, open_column_u128_as_compact_u64,
open_column_u64, serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
open_column_bytes, open_column_str, open_column_u128, open_column_u64,
serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
};
use crate::column_index::{ColumnIndex, Set};
use crate::column_index::ColumnIndex;
use crate::column_values::monotonic_mapping::StrictlyMonotonicMappingToInternal;
use crate::column_values::{monotonic_map_column, ColumnValues};
use crate::{Cardinality, DocId, EmptyColumnValues, MonotonicallyMappableToU64, RowId};
@@ -83,36 +83,10 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
self.values.max_value()
}
#[inline]
pub fn first(&self, row_id: RowId) -> Option<T> {
self.values_for_doc(row_id).next()
}
/// Load the first value for each docid in the provided slice.
#[inline]
pub fn first_vals(&self, docids: &[DocId], output: &mut [Option<T>]) {
match &self.index {
ColumnIndex::Empty { .. } => {}
ColumnIndex::Full => self.values.get_vals_opt(docids, output),
ColumnIndex::Optional(optional_index) => {
for (i, docid) in docids.iter().enumerate() {
output[i] = optional_index
.rank_if_exists(*docid)
.map(|rowid| self.values.get_val(rowid));
}
}
ColumnIndex::Multivalued(multivalued_index) => {
for (i, docid) in docids.iter().enumerate() {
let range = multivalued_index.range(*docid);
let is_empty = range.start == range.end;
if !is_empty {
output[i] = Some(self.values.get_val(range.start));
}
}
}
}
}
/// Translates a block of docis to row_ids.
///
/// returns the row_ids and the matching docids on the same index
@@ -131,8 +105,7 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
}
pub fn values_for_doc(&self, doc_id: DocId) -> impl Iterator<Item = T> + '_ {
self.index
.value_row_ids(doc_id)
self.value_row_ids(doc_id)
.map(|value_row_id: RowId| self.values.get_val(value_row_id))
}
@@ -174,6 +147,14 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
}
}
impl<T> Deref for Column<T> {
type Target = ColumnIndex;
fn deref(&self) -> &Self::Target {
&self.index
}
}
impl BinarySerializable for Cardinality {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
self.to_code().serialize(writer)
@@ -195,7 +176,6 @@ struct FirstValueWithDefault<T: Copy> {
impl<T: PartialOrd + Debug + Send + Sync + Copy + 'static> ColumnValues<T>
for FirstValueWithDefault<T>
{
#[inline(always)]
fn get_val(&self, idx: u32) -> T {
self.column.first(idx).unwrap_or(self.default_value)
}

View File

@@ -76,26 +76,6 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
})
}
/// Open the column as u64.
///
/// See [`open_u128_as_compact_u64`] for more details.
pub fn open_column_u128_as_compact_u64(bytes: OwnedBytes) -> io::Result<Column<u64>> {
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
let column_index_num_bytes = u32::from_le_bytes(
column_index_num_bytes_payload
.as_slice()
.try_into()
.unwrap(),
);
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
let column_index = crate::column_index::open_column_index(column_index_data)?;
let column_values = crate::column_values::open_u128_as_compact_u64(column_values_data)?;
Ok(Column {
index: column_index,
values: column_values,
})
}
pub fn open_column_bytes(data: OwnedBytes) -> io::Result<BytesColumn> {
let (body, dictionary_len_bytes) = data.rsplit(4);
let dictionary_len = u32::from_le_bytes(dictionary_len_bytes.as_slice().try_into().unwrap());

View File

@@ -140,7 +140,7 @@ mod tests {
#[test]
fn test_merge_column_index_optional_shuffle() {
let optional_index: ColumnIndex = OptionalIndex::for_test(2, &[0]).into();
let column_indexes = [optional_index, ColumnIndex::Full];
let column_indexes = vec![optional_index, ColumnIndex::Full];
let row_addrs = vec![
RowAddr {
segment_ord: 0u32,

View File

@@ -111,7 +111,10 @@ fn stack_multivalued_indexes<'a>(
let mut last_row_id = 0;
let mut current_it = multivalued_indexes.next();
Box::new(std::iter::from_fn(move || loop {
if let Some(row_id) = current_it.as_mut()?.next() {
let Some(multivalued_index) = current_it.as_mut() else {
return None;
};
if let Some(row_id) = multivalued_index.next() {
last_row_id = offset + row_id;
return Some(last_row_id);
}

View File

@@ -42,6 +42,10 @@ impl From<MultiValueIndex> for ColumnIndex {
}
impl ColumnIndex {
#[inline]
pub fn is_multivalue(&self) -> bool {
matches!(self, ColumnIndex::Multivalued(_))
}
/// Returns the cardinality of the column index.
///
/// By convention, if the column contains no docs, we consider that it is
@@ -122,18 +126,18 @@ impl ColumnIndex {
}
}
pub fn docid_range_to_rowids(&self, doc_id_range: Range<DocId>) -> Range<RowId> {
pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
match self {
ColumnIndex::Empty { .. } => 0..0,
ColumnIndex::Full => doc_id_range,
ColumnIndex::Full => doc_id,
ColumnIndex::Optional(optional_index) => {
let row_start = optional_index.rank(doc_id_range.start);
let row_end = optional_index.rank(doc_id_range.end);
let row_start = optional_index.rank(doc_id.start);
let row_end = optional_index.rank(doc_id.end);
row_start..row_end
}
ColumnIndex::Multivalued(multivalued_index) => {
let end_docid = doc_id_range.end.min(multivalued_index.num_docs() - 1) + 1;
let start_docid = doc_id_range.start.min(end_docid);
let end_docid = doc_id.end.min(multivalued_index.num_docs() - 1) + 1;
let start_docid = doc_id.start.min(end_docid);
let row_start = multivalued_index.start_index_column.get_val(start_docid);
let row_end = multivalued_index.start_index_column.get_val(end_docid);

View File

@@ -21,6 +21,8 @@ const DENSE_BLOCK_THRESHOLD: u32 =
const ELEMENTS_PER_BLOCK: u32 = u16::MAX as u32 + 1;
const BLOCK_SIZE: RowId = 1 << 16;
#[derive(Copy, Clone, Debug)]
struct BlockMeta {
non_null_rows_before_block: u32,
@@ -107,8 +109,8 @@ struct RowAddr {
#[inline(always)]
fn row_addr_from_row_id(row_id: RowId) -> RowAddr {
RowAddr {
block_id: (row_id / ELEMENTS_PER_BLOCK) as u16,
in_block_row_id: (row_id % ELEMENTS_PER_BLOCK) as u16,
block_id: (row_id / BLOCK_SIZE) as u16,
in_block_row_id: (row_id % BLOCK_SIZE) as u16,
}
}
@@ -183,13 +185,8 @@ impl Set<RowId> for OptionalIndex {
}
}
/// Any value doc_id is allowed.
/// In particular, doc_id = num_rows.
#[inline]
fn rank(&self, doc_id: DocId) -> RowId {
if doc_id >= self.num_docs() {
return self.num_non_nulls();
}
let RowAddr {
block_id,
in_block_row_id,
@@ -203,15 +200,13 @@ impl Set<RowId> for OptionalIndex {
block_meta.non_null_rows_before_block + block_offset_row_id
}
/// Any value doc_id is allowed.
/// In particular, doc_id = num_rows.
#[inline]
fn rank_if_exists(&self, doc_id: DocId) -> Option<RowId> {
let RowAddr {
block_id,
in_block_row_id,
} = row_addr_from_row_id(doc_id);
let block_meta = *self.block_metas.get(block_id as usize)?;
let block_meta = self.block_metas[block_id as usize];
let block = self.block(block_meta);
let block_offset_row_id = match block {
Block::Dense(dense_block) => dense_block.rank_if_exists(in_block_row_id),
@@ -496,7 +491,7 @@ fn deserialize_optional_index_block_metadatas(
non_null_rows_before_block += num_non_null_rows;
}
block_metas.resize(
((num_rows + ELEMENTS_PER_BLOCK - 1) / ELEMENTS_PER_BLOCK) as usize,
((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,
BlockMeta {
non_null_rows_before_block,
start_byte_offset,

View File

@@ -39,8 +39,7 @@ pub trait Set<T> {
///
/// # Panics
///
/// May panic if rank is greater or equal to the number of
/// elements in the Set.
/// May panic if rank is greater than the number of elements in the Set.
fn select(&self, rank: T) -> T;
/// Creates a brand new select cursor.

View File

@@ -1,3 +1,4 @@
use std::convert::TryInto;
use std::io::{self, Write};
use common::BinarySerializable;

View File

@@ -1,31 +1,8 @@
use proptest::prelude::*;
use proptest::prelude::{any, prop, *};
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
use super::*;
use crate::{ColumnarReader, ColumnarWriter, DynamicColumnHandle};
#[test]
fn test_optional_index_bug_2293() {
// tests for panic in docid_range_to_rowids for docid == num_docs
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK - 1);
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK);
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK + 1);
}
fn test_optional_index_with_num_docs(num_docs: u32) {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_numerical(100, "score", 80i64);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer
.serialize(num_docs, None, &mut buffer)
.unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("score").unwrap();
assert_eq!(cols.len(), 1);
let col = cols[0].open().unwrap();
col.column_index().docid_range_to_rowids(0..num_docs);
}
#[test]
fn test_dense_block_threshold() {
@@ -58,7 +35,7 @@ proptest! {
#[test]
fn test_with_random_sets_simple() {
let vals = 10..ELEMENTS_PER_BLOCK * 2;
let vals = 10..BLOCK_SIZE * 2;
let mut out: Vec<u8> = Vec::new();
serialize_optional_index(&vals, 100, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
@@ -194,7 +171,7 @@ fn test_optional_index_rank() {
test_optional_index_rank_aux(&[0u32, 1u32]);
let mut block = Vec::new();
block.push(3u32);
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
test_optional_index_rank_aux(&block);
}
@@ -208,8 +185,8 @@ fn test_optional_index_iter_empty_one() {
fn test_optional_index_iter_dense_block() {
let mut block = Vec::new();
block.push(3u32);
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
test_optional_index_iter_aux(&block, 3 * ELEMENTS_PER_BLOCK);
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
test_optional_index_iter_aux(&block, 3 * BLOCK_SIZE);
}
#[test]

View File

@@ -10,7 +10,7 @@ pub(crate) struct MergedColumnValues<'a, T> {
pub(crate) merge_row_order: &'a MergeRowOrder,
}
impl<'a, T: Copy + PartialOrd + Debug + 'static> Iterable<T> for MergedColumnValues<'a, T> {
impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
match self.merge_row_order {
MergeRowOrder::Stack(_) => Box::new(

View File

@@ -10,7 +10,6 @@ use std::fmt::Debug;
use std::ops::{Range, RangeInclusive};
use std::sync::Arc;
use downcast_rs::DowncastSync;
pub use monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
pub use monotonic_mapping_u128::MonotonicallyMappableToU128;
@@ -26,10 +25,7 @@ mod monotonic_column;
pub(crate) use merge::MergedColumnValues;
pub use stats::ColumnStats;
pub use u128_based::{
open_u128_as_compact_u64, open_u128_mapped, serialize_column_values_u128,
CompactSpaceU64Accessor,
};
pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
pub use u64_based::{
load_u64_based_column_values, serialize_and_load_u64_based_column_values,
serialize_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
@@ -45,7 +41,7 @@ use crate::RowId;
///
/// Any methods with a default and specialized implementation need to be called in the
/// wrappers that implement the trait: Arc and MonotonicMappingColumn
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
/// Return the value associated with the given idx.
///
/// This accessor should return as fast as possible.
@@ -72,40 +68,11 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
out_x4[3] = self.get_val(idx_x4[3]);
}
let out_and_idx_chunks = output
.chunks_exact_mut(4)
.into_remainder()
.iter_mut()
.zip(indexes.chunks_exact(4).remainder());
for (out, idx) in out_and_idx_chunks {
*out = self.get_val(*idx);
}
}
let step_size = 4;
let cutoff = indexes.len() - indexes.len() % step_size;
/// Allows to push down multiple fetch calls, to avoid dynamic dispatch overhead.
/// The slightly weird `Option<T>` in output allows pushdown to full columns.
///
/// idx and output should have the same length
///
/// # Panics
///
/// May panic if `idx` is greater than the column length.
fn get_vals_opt(&self, indexes: &[u32], output: &mut [Option<T>]) {
assert!(indexes.len() == output.len());
let out_and_idx_chunks = output.chunks_exact_mut(4).zip(indexes.chunks_exact(4));
for (out_x4, idx_x4) in out_and_idx_chunks {
out_x4[0] = Some(self.get_val(idx_x4[0]));
out_x4[1] = Some(self.get_val(idx_x4[1]));
out_x4[2] = Some(self.get_val(idx_x4[2]));
out_x4[3] = Some(self.get_val(idx_x4[3]));
}
let out_and_idx_chunks = output
.chunks_exact_mut(4)
.into_remainder()
.iter_mut()
.zip(indexes.chunks_exact(4).remainder());
for (out, idx) in out_and_idx_chunks {
*out = Some(self.get_val(*idx));
for idx in cutoff..indexes.len() {
output[idx] = self.get_val(indexes[idx]);
}
}
@@ -134,7 +101,7 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
row_id_hits: &mut Vec<RowId>,
) {
let row_id_range = row_id_range.start..row_id_range.end.min(self.num_vals());
for idx in row_id_range {
for idx in row_id_range.start..row_id_range.end {
let val = self.get_val(idx);
if value_range.contains(&val) {
row_id_hits.push(idx);
@@ -172,7 +139,6 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
}
}
downcast_rs::impl_downcast!(sync ColumnValues<T> where T: PartialOrd);
/// Empty column of values.
pub struct EmptyColumnValues;
@@ -195,17 +161,12 @@ impl<T: PartialOrd + Default> ColumnValues<T> for EmptyColumnValues {
}
}
impl<T: Copy + PartialOrd + Debug + 'static> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
#[inline(always)]
fn get_val(&self, idx: u32) -> T {
self.as_ref().get_val(idx)
}
#[inline(always)]
fn get_vals_opt(&self, indexes: &[u32], output: &mut [Option<T>]) {
self.as_ref().get_vals_opt(indexes, output)
}
#[inline(always)]
fn min_value(&self) -> T {
self.as_ref().min_value()

View File

@@ -31,10 +31,10 @@ pub fn monotonic_map_column<C, T, Input, Output>(
monotonic_mapping: T,
) -> impl ColumnValues<Output>
where
C: ColumnValues<Input> + 'static,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync + 'static,
Input: PartialOrd + Debug + Send + Sync + Clone + 'static,
Output: PartialOrd + Debug + Send + Sync + Clone + 'static,
C: ColumnValues<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Debug + Send + Sync + Clone,
Output: PartialOrd + Debug + Send + Sync + Clone,
{
MonotonicMappingColumn {
from_column,
@@ -45,10 +45,10 @@ where
impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
where
C: ColumnValues<Input> + 'static,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync + 'static,
Input: PartialOrd + Send + Debug + Sync + Clone + 'static,
Output: PartialOrd + Send + Debug + Sync + Clone + 'static,
C: ColumnValues<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Debug + Sync + Clone,
Output: PartialOrd + Send + Debug + Sync + Clone,
{
#[inline(always)]
fn get_val(&self, idx: u32) -> Output {
@@ -107,7 +107,7 @@ mod tests {
#[test]
fn test_monotonic_mapping_iter() {
let vals: Vec<u64> = (0..100u64).map(|el| el * 10).collect();
let col = VecColumn::from(vals);
let col = VecColumn::from(&vals);
let mapped = monotonic_map_column(
col,
StrictlyMonotonicMappingInverter::from(StrictlyMonotonicMappingToInternal::<i64>::new()),

View File

@@ -22,7 +22,7 @@ mod build_compact_space;
use build_compact_space::get_compact_space;
use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt, VIntU128};
use tantivy_bitpacker::{BitPacker, BitUnpacker};
use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
use crate::column_values::ColumnValues;
use crate::RowId;
@@ -148,7 +148,7 @@ impl CompactSpace {
.binary_search_by_key(&compact, |range_mapping| range_mapping.compact_start)
// Correctness: Overflow. The first range starts at compact space 0, the error from
// binary search can never be 0
.unwrap_or_else(|e| e - 1);
.map_or_else(|e| e - 1, |v| v);
let range_mapping = &self.ranges_mapping[pos];
let diff = compact - range_mapping.compact_start;
@@ -292,63 +292,6 @@ impl BinarySerializable for IPCodecParams {
}
}
/// Exposes the compact space compressed values as u64.
///
/// This allows faster access to the values, as u64 is faster to work with than u128.
/// It also allows to handle u128 values like u64, via the `open_u64_lenient` as a uniform
/// access interface.
///
/// When converting from the internal u64 to u128 `compact_to_u128` can be used.
pub struct CompactSpaceU64Accessor(CompactSpaceDecompressor);
impl CompactSpaceU64Accessor {
pub(crate) fn open(data: OwnedBytes) -> io::Result<CompactSpaceU64Accessor> {
let decompressor = CompactSpaceU64Accessor(CompactSpaceDecompressor::open(data)?);
Ok(decompressor)
}
/// Convert a compact space value to u128
pub fn compact_to_u128(&self, compact: u32) -> u128 {
self.0.compact_to_u128(compact)
}
}
impl ColumnValues<u64> for CompactSpaceU64Accessor {
#[inline]
fn get_val(&self, doc: u32) -> u64 {
let compact = self.0.get_compact(doc);
compact as u64
}
fn min_value(&self) -> u64 {
self.0.u128_to_compact(self.0.min_value()).unwrap() as u64
}
fn max_value(&self) -> u64 {
self.0.u128_to_compact(self.0.max_value()).unwrap() as u64
}
fn num_vals(&self) -> u32 {
self.0.params.num_vals
}
#[inline]
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(self.0.iter_compact().map(|el| el as u64))
}
#[inline]
fn get_row_ids_for_value_range(
&self,
value_range: RangeInclusive<u64>,
position_range: Range<u32>,
positions: &mut Vec<u32>,
) {
let value_range = self.0.compact_to_u128(*value_range.start() as u32)
..=self.0.compact_to_u128(*value_range.end() as u32);
self.0
.get_row_ids_for_value_range(value_range, position_range, positions)
}
}
impl ColumnValues<u128> for CompactSpaceDecompressor {
#[inline]
fn get_val(&self, doc: u32) -> u128 {
@@ -459,14 +402,9 @@ impl CompactSpaceDecompressor {
.map(|compact| self.compact_to_u128(compact))
}
#[inline]
pub fn get_compact(&self, idx: u32) -> u32 {
self.params.bit_unpacker.get(idx, &self.data) as u32
}
#[inline]
pub fn get(&self, idx: u32) -> u128 {
let compact = self.get_compact(idx);
let compact = self.params.bit_unpacker.get(idx, &self.data) as u32;
self.compact_to_u128(compact)
}

View File

@@ -6,9 +6,7 @@ use std::sync::Arc;
mod compact_space;
use common::{BinarySerializable, OwnedBytes, VInt};
pub use compact_space::{
CompactSpaceCompressor, CompactSpaceDecompressor, CompactSpaceU64Accessor,
};
use compact_space::{CompactSpaceCompressor, CompactSpaceDecompressor};
use crate::column_values::monotonic_map_column;
use crate::column_values::monotonic_mapping::{
@@ -110,23 +108,6 @@ pub fn open_u128_mapped<T: MonotonicallyMappableToU128 + Debug>(
StrictlyMonotonicMappingToInternal::<T>::new().into();
Ok(Arc::new(monotonic_map_column(reader, inverted)))
}
/// Returns the u64 representation of the u128 data.
/// The internal representation of the data as u64 is useful for faster processing.
///
/// In order to convert to u128 back cast to `CompactSpaceU64Accessor` and call
/// `compact_to_u128`.
///
/// # Notice
/// In case there are new codecs added, check for usages of `CompactSpaceDecompressorU64` and
/// also handle the new codecs.
pub fn open_u128_as_compact_u64(mut bytes: OwnedBytes) -> io::Result<Arc<dyn ColumnValues<u64>>> {
let header = U128Header::deserialize(&mut bytes)?;
assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
let reader = CompactSpaceU64Accessor::open(bytes)?;
Ok(Arc::new(reader))
}
#[cfg(test)]
pub mod tests {
use super::*;

View File

@@ -63,6 +63,7 @@ impl ColumnValues for BitpackedReader {
fn get_val(&self, doc: u32) -> u64 {
self.stats.min_value + self.stats.gcd.get() * self.bit_unpacker.get(doc, &self.data)
}
#[inline]
fn min_value(&self) -> u64 {
self.stats.min_value

View File

@@ -63,10 +63,7 @@ impl BlockwiseLinearEstimator {
if self.block.is_empty() {
return;
}
let column = VecColumn::from(std::mem::take(&mut self.block));
let line = Line::train(&column);
self.block = column.into();
let line = Line::train(&VecColumn::from(&self.block));
let mut max_value = 0u64;
for (i, buffer_val) in self.block.iter().enumerate() {
let interpolated_val = line.eval(i as u32);
@@ -128,7 +125,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
*buffer_val = gcd_divider.divide(*buffer_val - stats.min_value);
}
let line = Line::train(&VecColumn::from(buffer.to_vec()));
let line = Line::train(&VecColumn::from(&buffer));
assert!(!buffer.is_empty());

View File

@@ -184,7 +184,7 @@ mod tests {
}
fn test_eval_max_err(ys: &[u64]) -> Option<u64> {
let line = Line::train(&VecColumn::from(ys.to_vec()));
let line = Line::train(&VecColumn::from(&ys));
ys.iter()
.enumerate()
.map(|(x, y)| y.wrapping_sub(line.eval(x as u32)))

View File

@@ -173,9 +173,7 @@ impl LinearCodecEstimator {
fn collect_before_line_estimation(&mut self, value: u64) {
self.block.push(value);
if self.block.len() == LINE_ESTIMATION_BLOCK_LEN {
let column = VecColumn::from(std::mem::take(&mut self.block));
let line = Line::train(&column);
self.block = column.into();
let line = Line::train(&VecColumn::from(&self.block));
let block = std::mem::take(&mut self.block);
for val in block {
self.collect_after_line_estimation(&line, val);

View File

@@ -1,4 +1,5 @@
use proptest::prelude::*;
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
#[test]

View File

@@ -4,14 +4,14 @@ use tantivy_bitpacker::minmax;
use crate::ColumnValues;
/// VecColumn provides `Column` over a `Vec<T>`.
pub struct VecColumn<T = u64> {
pub(crate) values: Vec<T>,
/// VecColumn provides `Column` over a slice.
pub struct VecColumn<'a, T = u64> {
pub(crate) values: &'a [T],
pub(crate) min_value: T,
pub(crate) max_value: T,
}
impl<T: Copy + PartialOrd + Send + Sync + Debug + 'static> ColumnValues<T> for VecColumn<T> {
impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
fn get_val(&self, position: u32) -> T {
self.values[position as usize]
}
@@ -37,8 +37,11 @@ impl<T: Copy + PartialOrd + Send + Sync + Debug + 'static> ColumnValues<T> for V
}
}
impl<T: Copy + PartialOrd + Default> From<Vec<T>> for VecColumn<T> {
fn from(values: Vec<T>) -> Self {
impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
where V: AsRef<[T]> + ?Sized
{
fn from(values: &'a V) -> Self {
let values = values.as_ref();
let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
Self {
values,
@@ -47,8 +50,3 @@ impl<T: Copy + PartialOrd + Default> From<Vec<T>> for VecColumn<T> {
}
}
}
impl From<VecColumn> for Vec<u64> {
fn from(column: VecColumn) -> Self {
column.values
}
}

View File

@@ -1,3 +1,7 @@
use std::collections::BTreeMap;
use itertools::Itertools;
use super::*;
use crate::{Cardinality, ColumnarWriter, HasAssociatedColumnType, RowId};

View File

@@ -13,7 +13,9 @@ pub(crate) use serializer::ColumnarSerializer;
use stacker::{Addr, ArenaHashMap, MemoryArena};
use crate::column_index::SerializableColumnIndex;
use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
use crate::column_values::{
ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
};
use crate::columnar::column_type::ColumnType;
use crate::columnar::writer::column_writers::{
ColumnWriter, NumericalColumnWriter, StrOrBytesColumnWriter,
@@ -643,7 +645,10 @@ fn send_to_serialize_column_mappable_to_u128<
value_index_builders: &mut PreallocatedIndexBuilders,
values: &mut Vec<T>,
mut wrt: impl io::Write,
) -> io::Result<()> {
) -> io::Result<()>
where
for<'a> VecColumn<'a, T>: ColumnValues<T>,
{
values.clear();
// TODO: split index and values
let serializable_column_index = match cardinality {
@@ -696,7 +701,10 @@ fn send_to_serialize_column_mappable_to_u64(
value_index_builders: &mut PreallocatedIndexBuilders,
values: &mut Vec<u64>,
mut wrt: impl io::Write,
) -> io::Result<()> {
) -> io::Result<()>
where
for<'a> VecColumn<'a, u64>: ColumnValues<u64>,
{
values.clear();
let serializable_column_index = match cardinality {
Cardinality::Full => {

View File

@@ -18,12 +18,7 @@ pub struct ColumnarSerializer<W: io::Write> {
/// code.
fn prepare_key(key: &[u8], column_type: ColumnType, buffer: &mut Vec<u8>) {
buffer.clear();
// Convert 0 bytes to '0' string, as 0 bytes are reserved for the end of the path.
if key.contains(&0u8) {
buffer.extend(key.iter().map(|&b| if b == 0 { b'0' } else { b }));
} else {
buffer.extend_from_slice(key);
}
buffer.extend_from_slice(key);
buffer.push(0u8);
buffer.push(column_type.to_code());
}
@@ -101,13 +96,14 @@ impl<'a, W: io::Write> io::Write for ColumnSerializer<'a, W> {
#[cfg(test)]
mod tests {
use super::*;
use crate::columnar::column_type::ColumnType;
#[test]
fn test_prepare_key_bytes() {
let mut buffer: Vec<u8> = b"somegarbage".to_vec();
prepare_key(b"root\0child", ColumnType::Str, &mut buffer);
assert_eq!(buffer.len(), 12);
assert_eq!(&buffer[..10], b"root0child");
assert_eq!(&buffer[..10], b"root\0child");
assert_eq!(buffer[10], 0u8);
assert_eq!(buffer[11], ColumnType::Str.to_code());
}

View File

@@ -8,7 +8,7 @@ use common::{ByteCount, DateTime, HasLen, OwnedBytes};
use crate::column::{BytesColumn, Column, StrColumn};
use crate::column_values::{monotonic_map_column, StrictlyMonotonicFn};
use crate::columnar::ColumnType;
use crate::{Cardinality, ColumnIndex, ColumnValues, NumericalType};
use crate::{Cardinality, ColumnIndex, NumericalType};
#[derive(Clone)]
pub enum DynamicColumn {
@@ -247,12 +247,7 @@ impl DynamicColumnHandle {
}
/// Returns the `u64` fast field reader reader associated with `fields` of types
/// Str, u64, i64, f64, bool, ip, or datetime.
///
/// Notice that for IpAddr, the fastfield reader will return the u64 representation of the
/// IpAddr.
/// In order to convert to u128 back cast to `CompactSpaceU64Accessor` and call
/// `compact_to_u128`.
/// Str, u64, i64, f64, bool, or datetime.
///
/// If not, the fastfield reader will returns the u64-value associated with the original
/// FastValue.
@@ -263,10 +258,7 @@ impl DynamicColumnHandle {
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
Ok(Some(column.term_ord_column))
}
ColumnType::IpAddr => {
let column = crate::column::open_column_u128_as_compact_u64(column_bytes)?;
Ok(Some(column))
}
ColumnType::IpAddr => Ok(None),
ColumnType::Bool
| ColumnType::I64
| ColumnType::U64

View File

@@ -113,9 +113,6 @@ impl Cardinality {
pub fn is_multivalue(&self) -> bool {
matches!(self, Cardinality::Multivalued)
}
pub fn is_full(&self) -> bool {
matches!(self, Cardinality::Full)
}
pub(crate) fn to_code(self) -> u8 {
self as u8
}

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-common"
version = "0.7.0"
version = "0.6.0"
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
license = "MIT"
edition = "2021"
@@ -14,7 +14,7 @@ repository = "https://github.com/quickwit-oss/tantivy"
[dependencies]
byteorder = "1.4.3"
ownedbytes = { version= "0.7", path="../ownedbytes" }
ownedbytes = { version= "0.6", path="../ownedbytes" }
async-trait = "0.1"
time = { version = "0.3.10", features = ["serde-well-known"] }
serde = { version = "1.0.136", features = ["derive"] }

View File

@@ -1,5 +1,6 @@
use std::convert::TryInto;
use std::io::Write;
use std::{fmt, io};
use std::{fmt, io, u64};
use ownedbytes::OwnedBytes;

View File

@@ -1,3 +1,5 @@
#![allow(deprecated)]
use std::fmt;
use std::io::{Read, Write};
@@ -25,6 +27,9 @@ pub enum DateTimePrecision {
Nanoseconds,
}
#[deprecated(since = "0.20.0", note = "Use `DateTimePrecision` instead")]
pub type DatePrecision = DateTimePrecision;
/// A date/time value with nanoseconds precision.
///
/// This timestamp does not carry any explicit time zone information.
@@ -35,7 +40,7 @@ pub enum DateTimePrecision {
/// All constructors and conversions are provided as explicit
/// functions and not by implementing any `From`/`Into` traits
/// to prevent unintended usage.
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub struct DateTime {
// Timestamp in nanoseconds.
pub(crate) timestamp_nanos: i64,

View File

@@ -5,12 +5,6 @@ pub const JSON_PATH_SEGMENT_SEP: u8 = 1u8;
pub const JSON_PATH_SEGMENT_SEP_STR: &str =
unsafe { std::str::from_utf8_unchecked(&[JSON_PATH_SEGMENT_SEP]) };
/// Separates the json path and the value in
/// a JSON term binary representation.
pub const JSON_END_OF_PATH: u8 = 0u8;
pub const JSON_END_OF_PATH_STR: &str =
unsafe { std::str::from_utf8_unchecked(&[JSON_END_OF_PATH]) };
/// Create a new JsonPathWriter, that creates flattened json paths for tantivy.
#[derive(Clone, Debug, Default)]
pub struct JsonPathWriter {
@@ -20,14 +14,6 @@ pub struct JsonPathWriter {
}
impl JsonPathWriter {
pub fn with_expand_dots(expand_dots: bool) -> Self {
JsonPathWriter {
path: String::new(),
indices: Vec::new(),
expand_dots,
}
}
pub fn new() -> Self {
JsonPathWriter {
path: String::new(),
@@ -53,8 +39,8 @@ impl JsonPathWriter {
pub fn push(&mut self, segment: &str) {
let len_path = self.path.len();
self.indices.push(len_path);
if self.indices.len() > 1 {
self.path.push(JSON_PATH_SEGMENT_SEP as char);
if !self.path.is_empty() {
self.path.push_str(JSON_PATH_SEGMENT_SEP_STR);
}
self.path.push_str(segment);
if self.expand_dots {
@@ -69,12 +55,6 @@ impl JsonPathWriter {
}
}
/// Set the end of JSON path marker.
#[inline]
pub fn set_end(&mut self) {
self.path.push_str(JSON_END_OF_PATH_STR);
}
/// Remove the last segment. Does nothing if the path is empty.
#[inline]
pub fn pop(&mut self) {
@@ -111,7 +91,6 @@ mod tests {
#[test]
fn json_path_writer_test() {
let mut writer = JsonPathWriter::new();
writer.set_expand_dots(false);
writer.push("root");
assert_eq!(writer.as_str(), "root");
@@ -130,15 +109,4 @@ mod tests {
writer.push("k8s.node.id");
assert_eq!(writer.as_str(), "root\u{1}k8s\u{1}node\u{1}id");
}
#[test]
fn test_json_path_expand_dots_enabled_pop_segment() {
let mut json_writer = JsonPathWriter::with_expand_dots(true);
json_writer.push("hello");
assert_eq!(json_writer.as_str(), "hello");
json_writer.push("color.hue");
assert_eq!(json_writer.as_str(), "hello\x01color\x01hue");
json_writer.pop();
assert_eq!(json_writer.as_str(), "hello");
}
}

View File

@@ -9,12 +9,14 @@ mod byte_count;
mod datetime;
pub mod file_slice;
mod group_by;
pub mod json_path_writer;
mod json_path_writer;
mod serialize;
mod vint;
mod writer;
pub use bitset::*;
pub use byte_count::ByteCount;
#[allow(deprecated)]
pub use datetime::DatePrecision;
pub use datetime::{DateTime, DateTimePrecision};
pub use group_by::GroupByIteratorExtended;
pub use json_path_writer::JsonPathWriter;

View File

@@ -290,7 +290,8 @@ impl<'a> BinarySerializable for Cow<'a, [u8]> {
#[cfg(test)]
pub mod test {
use super::*;
use super::{VInt, *};
use crate::serialize::BinarySerializable;
pub fn fixed_size_test<O: BinarySerializable + FixedSize + Default>() {
let mut buffer = Vec::new();
O::default().serialize(&mut buffer).unwrap();

View File

@@ -1,335 +0,0 @@
#![allow(unused_imports)]
#![allow(dead_code)]
use std::alloc::System;
use std::env::args;
use std::net::Ipv6Addr;
use columnar::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
use common::{BinarySerializable, CountingWriter, DateTime, FixedSize};
use peakmem_alloc::*;
use tantivy::schema::{Field, FieldValue, OwnedValue, FAST, INDEXED, STRING, TEXT};
use tantivy::tokenizer::PreTokenizedString;
use tantivy::{doc, TantivyDocument};
const GH_LOGS: &str = include_str!("../benches/gh.json");
const HDFS_LOGS: &str = include_str!("../benches/hdfs.json");
#[global_allocator]
static GLOBAL: &PeakMemAlloc<System> = &INSTRUMENTED_SYSTEM;
fn main() {
dbg!(std::mem::size_of::<TantivyDocument>());
dbg!(std::mem::size_of::<DocContainerRef>());
dbg!(std::mem::size_of::<OwnedValue>());
dbg!(std::mem::size_of::<OwnedValueMedVec>());
dbg!(std::mem::size_of::<ValueContainerRef>());
dbg!(std::mem::size_of::<mediumvec::vec32::Vec32::<u8>>());
let filter = args().nth(1);
measure_fn(
test_hdfs::<TantivyDocument>,
"hdfs TantivyDocument",
&filter,
);
measure_fn(
test_hdfs::<TantivyDocumentMedVec>,
"hdfs TantivyDocumentMedVec",
&filter,
);
measure_fn(
test_hdfs::<DocContainerRef>,
"hdfs DocContainerRef",
&filter,
);
measure_fn(test_gh::<TantivyDocument>, "gh TantivyDocument", &filter);
measure_fn(
test_gh::<TantivyDocumentMedVec>,
"gh TantivyDocumentMedVec",
&filter,
);
measure_fn(test_gh::<DocContainerRef>, "gh DocContainerRef", &filter);
}
fn measure_fn<F: FnOnce()>(f: F, name: &str, filter: &Option<std::string::String>) {
if let Some(filter) = filter {
if !name.contains(filter) {
return;
}
}
GLOBAL.reset_peak_memory();
f();
println!("Peak Memory {} : {:#?}", GLOBAL.get_peak_memory(), name);
}
fn test_hdfs<T: From<TantivyDocument>>() {
let schema = {
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
schema_builder.add_u64_field("timestamp", INDEXED);
schema_builder.add_text_field("body", TEXT);
schema_builder.add_text_field("severity", STRING);
schema_builder.build()
};
let mut docs: Vec<T> = Vec::with_capacity(HDFS_LOGS.lines().count());
for doc_json in HDFS_LOGS.lines() {
let doc = TantivyDocument::parse_json(&schema, doc_json)
.unwrap()
.into();
docs.push(doc);
}
}
fn test_gh<T: From<TantivyDocument>>() {
let schema = {
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
schema_builder.add_json_field("json", FAST);
schema_builder.build()
};
let mut docs: Vec<T> = Vec::with_capacity(GH_LOGS.lines().count());
for doc_json in GH_LOGS.lines() {
let json_field = schema.get_field("json").unwrap();
let json_val: serde_json::Map<String, serde_json::Value> =
serde_json::from_str(doc_json).unwrap();
let doc = tantivy::doc!(json_field=>json_val).into();
docs.push(doc);
}
}
#[derive(Clone, Debug, Default)]
#[allow(dead_code)]
pub struct TantivyDocumentMedVec {
field_values: mediumvec::Vec32<FieldValueMedVec>,
}
#[derive(Debug, Clone, PartialEq)]
pub struct FieldValueMedVec {
pub field: Field,
pub value: OwnedValueMedVec,
}
/// This is a owned variant of `Value`, that can be passed around without lifetimes.
/// Represents the value of a any field.
/// It is an enum over all over all of the possible field type.
#[derive(Debug, Clone, PartialEq)]
pub enum OwnedValueMedVec {
/// A null value.
Null,
/// The str type is used for any text information.
Str(mediumvec::vec32::Vec32<u8>),
/// Unsigned 64-bits Integer `u64`
U64(u64),
/// Signed 64-bits Integer `i64`
I64(i64),
/// 64-bits Float `f64`
F64(f64),
/// Bool value
Bool(bool),
/// Date/time with nanoseconds precision
Date(DateTime),
Array(mediumvec::vec32::Vec32<Self>),
/// Dynamic object value.
Object(mediumvec::vec32::Vec32<(String, Self)>),
/// IpV6 Address. Internally there is no IpV4, it needs to be converted to `Ipv6Addr`.
IpAddr(Ipv6Addr),
/// Pre-tokenized str type,
PreTokStr(Box<PreTokenizedString>),
/// Arbitrarily sized byte array
Bytes(mediumvec::vec32::Vec32<u8>),
}
impl From<TantivyDocument> for TantivyDocumentMedVec {
fn from(doc: TantivyDocument) -> Self {
let field_values = doc
.into_iter()
.map(|fv| FieldValueMedVec {
field: fv.field,
value: fv.value.into(),
})
.collect();
TantivyDocumentMedVec { field_values }
}
}
impl From<OwnedValue> for OwnedValueMedVec {
fn from(value: OwnedValue) -> Self {
match value {
OwnedValue::Null => OwnedValueMedVec::Null,
OwnedValue::Str(s) => {
let bytes = s.into_bytes();
let vec = mediumvec::vec32::Vec32::from_vec(bytes);
OwnedValueMedVec::Str(vec)
}
OwnedValue::U64(u) => OwnedValueMedVec::U64(u),
OwnedValue::I64(i) => OwnedValueMedVec::I64(i),
OwnedValue::F64(f) => OwnedValueMedVec::F64(f),
OwnedValue::Bool(b) => OwnedValueMedVec::Bool(b),
OwnedValue::Date(d) => OwnedValueMedVec::Date(d),
OwnedValue::Array(arr) => {
let arr = arr.into_iter().map(|v| v.into()).collect();
OwnedValueMedVec::Array(arr)
}
OwnedValue::Object(obj) => {
let obj = obj.into_iter().map(|(k, v)| (k, v.into())).collect();
OwnedValueMedVec::Object(obj)
}
OwnedValue::IpAddr(ip) => OwnedValueMedVec::IpAddr(ip),
_ => panic!("Unsupported value type {:?}", value),
}
}
}
#[repr(packed)]
pub struct FieldValueContainerRef {
pub field: u16,
pub value: ValueContainerRef,
}
#[repr(packed)]
struct DocContainerRef {
container: OwnedValueRefContainer,
field_values: mediumvec::Vec32<FieldValueContainerRef>,
}
#[derive(Default)]
struct OwnedValueRefContainer {
nodes: mediumvec::Vec32<ValueContainerRef>,
node_data: mediumvec::Vec32<u8>,
}
impl OwnedValueRefContainer {
fn shrink_to_fit(&mut self) {
self.nodes.shrink_to_fit();
self.node_data.shrink_to_fit();
}
}
impl From<TantivyDocument> for DocContainerRef {
fn from(doc: TantivyDocument) -> Self {
let mut container = OwnedValueRefContainer::default();
let field_values = doc
.into_iter()
.map(|fv| FieldValueContainerRef {
field: fv.field.field_id().try_into().unwrap(),
value: container.add_value(fv.value),
})
.collect();
container.shrink_to_fit();
Self {
field_values,
container,
}
}
}
// References to positions in two array, one for the OwnedValueRef and the other for the encoded
// bytes
#[derive(Debug, Clone, PartialEq)]
pub enum ValueContainerRef {
/// A null value.
Null,
/// The str type is used for any text information.
Str(u32),
/// Unsigned 64-bits Integer `u64`
U64(u32), // position of the serialized 8 bytes in the data array
/// Signed 64-bits Integer `i64`
I64(u32), // position of the serialized 8 bytes in the data array
/// 64-bits Float `f64`
F64(u32), // position of the serialized 8 bytes in the data array
/// Bool value
Bool(bool), // inlined bool
/// Date/time with nanoseconds precision
Date(u32), // position of the serialized 8 byte in the data array
Array(NodeAddress),
/// Dynamic object value.
Object(NodeAddress),
/// IpV6 Address. Internally there is no IpV4, it needs to be converted to `Ipv6Addr`.
IpAddr(u32), // position of the serialized 16 bytes in the data array
/// Arbitrarily sized byte array
Bytes(u32),
}
#[derive(Debug, Clone, PartialEq)]
pub struct NodeAddress {
pos: u32,
num_nodes: u32,
}
impl OwnedValueRefContainer {
pub fn add_value(&mut self, value: OwnedValue) -> ValueContainerRef {
match value {
OwnedValue::Null => ValueContainerRef::Null,
OwnedValue::U64(num) => ValueContainerRef::U64(write_into(&mut self.node_data, num)),
OwnedValue::I64(num) => ValueContainerRef::I64(write_into(&mut self.node_data, num)),
OwnedValue::F64(num) => ValueContainerRef::F64(write_into(&mut self.node_data, num)),
OwnedValue::Bool(b) => ValueContainerRef::Bool(b),
OwnedValue::Date(date) => ValueContainerRef::Date(write_into(
&mut self.node_data,
date.into_timestamp_nanos(),
)),
OwnedValue::Str(bytes) => {
ValueContainerRef::Str(write_into(&mut self.node_data, bytes))
}
OwnedValue::Bytes(bytes) => {
ValueContainerRef::Bytes(write_into(&mut self.node_data, bytes))
}
OwnedValue::Array(elements) => {
let pos = self.nodes.len() as u32;
let len = elements.len() as u32;
for elem in elements {
let ref_elem = self.add_value(elem);
self.nodes.push(ref_elem);
}
ValueContainerRef::Array(NodeAddress {
pos,
num_nodes: len,
})
}
OwnedValue::Object(entries) => {
let pos = self.nodes.len() as u32;
let len = entries.len() as u32;
for (key, value) in entries {
let ref_key = self.add_value(OwnedValue::Str(key));
let ref_value = self.add_value(value);
self.nodes.push(ref_key);
self.nodes.push(ref_value);
}
ValueContainerRef::Object(NodeAddress {
pos,
num_nodes: len,
})
}
OwnedValue::IpAddr(num) => {
ValueContainerRef::IpAddr(write_into(&mut self.node_data, num.to_u128()))
}
OwnedValue::PreTokStr(_) => todo!(),
OwnedValue::Facet(_) => todo!(),
}
}
}
fn write_into<T: BinarySerializable>(data: &mut mediumvec::Vec32<u8>, value: T) -> u32 {
let pos = data.len() as u32;
data.as_vec(|vec| value.serialize(vec).unwrap());
pos
}
fn write_into_2<T: BinarySerializable>(data: &mut mediumvec::Vec32<u8>, value: T) -> NodeAddress {
let pos = data.len() as u32;
let mut len = 0;
data.as_vec(|vec| {
let mut wrt = CountingWriter::wrap(vec);
value.serialize(&mut wrt).unwrap();
len = wrt.written_bytes() as u32;
});
NodeAddress {
pos,
num_nodes: len,
}
}
// impl From<ContainerDocRef> for TantivyDocument {
// fn from(doc: ContainerDocRef) -> Self {
// let mut doc2 = TantivyDocument::new();
// for fv in doc.field_values {
// let field = Field::from_field_id(fv.field as u32);
// let value = doc.container.get_value(fv.value);
// doc2.add(FieldValue::new(field, value));
//}
// doc2
//}

View File

@@ -1,7 +1,7 @@
[package]
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
name = "ownedbytes"
version = "0.7.0"
version = "0.6.0"
edition = "2021"
description = "Expose data as static slice"
license = "MIT"

View File

@@ -1,3 +1,4 @@
use std::convert::TryInto;
use std::ops::{Deref, Range};
use std::sync::Arc;
use std::{fmt, io};

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-query-grammar"
version = "0.22.0"
version = "0.21.0"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]

View File

@@ -81,8 +81,8 @@ where
T: InputTakeAtPosition + Clone,
<T as InputTakeAtPosition>::Item: AsChar + Clone,
{
opt_i(nom::character::complete::multispace0)(input)
.map(|(left, (spaces, errors))| (left, (spaces.expect("multispace0 can't fail"), errors)))
opt_i(nom::character::complete::space0)(input)
.map(|(left, (spaces, errors))| (left, (spaces.expect("space0 can't fail"), errors)))
}
pub(crate) fn space1_infallible<T>(input: T) -> JResult<T, Option<T>>
@@ -90,7 +90,7 @@ where
T: InputTakeAtPosition + Clone + InputLength,
<T as InputTakeAtPosition>::Item: AsChar + Clone,
{
opt_i(nom::character::complete::multispace1)(input).map(|(left, (spaces, mut errors))| {
opt_i(nom::character::complete::space1)(input).map(|(left, (spaces, mut errors))| {
if spaces.is_none() {
errors.push(LenientErrorInternal {
pos: left.input_len(),

View File

@@ -3,11 +3,11 @@ use std::iter::once;
use nom::branch::alt;
use nom::bytes::complete::tag;
use nom::character::complete::{
anychar, char, digit1, multispace0, multispace1, none_of, one_of, satisfy, u32,
anychar, char, digit1, none_of, one_of, satisfy, space0, space1, u32,
};
use nom::combinator::{eof, map, map_res, opt, peek, recognize, value, verify};
use nom::error::{Error, ErrorKind};
use nom::multi::{many0, many1, separated_list0};
use nom::multi::{many0, many1, separated_list0, separated_list1};
use nom::sequence::{delimited, preceded, separated_pair, terminated, tuple};
use nom::IResult;
@@ -65,7 +65,7 @@ fn word_infallible(delimiter: &str) -> impl Fn(&str) -> JResult<&str, Option<&st
|inp| {
opt_i_err(
preceded(
multispace0,
space0,
recognize(many1(satisfy(|c| {
!c.is_whitespace() && !delimiter.contains(c)
}))),
@@ -218,14 +218,27 @@ fn term_or_phrase_infallible(inp: &str) -> JResult<&str, Option<UserInputLeaf>>
}
fn term_group(inp: &str) -> IResult<&str, UserInputAst> {
let occur_symbol = alt((
value(Occur::MustNot, char('-')),
value(Occur::Must, char('+')),
));
map(
tuple((
terminated(field_name, multispace0),
delimited(tuple((char('('), multispace0)), ast, char(')')),
terminated(field_name, space0),
delimited(
tuple((char('('), space0)),
separated_list0(space1, tuple((opt(occur_symbol), term_or_phrase))),
char(')'),
),
)),
|(field_name, mut ast)| {
ast.set_default_field(field_name);
ast
|(field_name, terms)| {
UserInputAst::Clause(
terms
.into_iter()
.map(|(occur, leaf)| (occur, leaf.set_field(Some(field_name.clone())).into()))
.collect(),
)
},
)(inp)
}
@@ -237,7 +250,7 @@ fn term_group_precond(inp: &str) -> IResult<&str, (), ()> {
(),
peek(tuple((
field_name,
multispace0,
space0,
char('('), // when we are here, we know it can't be anything but a term group
))),
)(inp)
@@ -245,18 +258,46 @@ fn term_group_precond(inp: &str) -> IResult<&str, (), ()> {
}
fn term_group_infallible(inp: &str) -> JResult<&str, UserInputAst> {
let (inp, (field_name, _, _, _)) =
tuple((field_name, multispace0, char('('), multispace0))(inp).expect("precondition failed");
let (mut inp, (field_name, _, _, _)) =
tuple((field_name, space0, char('('), space0))(inp).expect("precondition failed");
let res = delimited_infallible(
nothing,
map(ast_infallible, |(mut ast, errors)| {
ast.set_default_field(field_name.to_string());
(ast, errors)
}),
opt_i_err(char(')'), "expected ')'"),
)(inp);
res
let mut terms = Vec::new();
let mut errs = Vec::new();
let mut first_round = true;
loop {
let mut space_error = if first_round {
first_round = false;
Vec::new()
} else {
let (rest, (_, err)) = space1_infallible(inp)?;
inp = rest;
err
};
if inp.is_empty() {
errs.push(LenientErrorInternal {
pos: inp.len(),
message: "missing )".to_string(),
});
break Ok((inp, (UserInputAst::Clause(terms), errs)));
}
if let Some(inp) = inp.strip_prefix(')') {
break Ok((inp, (UserInputAst::Clause(terms), errs)));
}
// only append missing space error if we did not reach the end of group
errs.append(&mut space_error);
// here we do the assumption term_or_phrase_infallible always consume something if the
// first byte is not `)` or ' '. If it did not, we would end up looping.
let (rest, ((occur, leaf), mut err)) =
tuple_infallible((occur_symbol, term_or_phrase_infallible))(inp)?;
errs.append(&mut err);
if let Some(leaf) = leaf {
terms.push((occur, leaf.set_field(Some(field_name.clone())).into()));
}
inp = rest;
}
}
fn exists(inp: &str) -> IResult<&str, UserInputLeaf> {
@@ -264,7 +305,7 @@ fn exists(inp: &str) -> IResult<&str, UserInputLeaf> {
UserInputLeaf::Exists {
field: String::new(),
},
tuple((multispace0, char('*'))),
tuple((space0, char('*'))),
)(inp)
}
@@ -273,7 +314,7 @@ fn exists_precond(inp: &str) -> IResult<&str, (), ()> {
(),
peek(tuple((
field_name,
multispace0,
space0,
char('*'), // when we are here, we know it can't be anything but a exists
))),
)(inp)
@@ -282,7 +323,7 @@ fn exists_precond(inp: &str) -> IResult<&str, (), ()> {
fn exists_infallible(inp: &str) -> JResult<&str, UserInputAst> {
let (inp, (field_name, _, _)) =
tuple((field_name, multispace0, char('*')))(inp).expect("precondition failed");
tuple((field_name, space0, char('*')))(inp).expect("precondition failed");
let exists = UserInputLeaf::Exists { field: field_name }.into();
Ok((inp, (exists, Vec::new())))
@@ -308,7 +349,7 @@ fn literal_no_group_infallible(inp: &str) -> JResult<&str, Option<UserInputAst>>
alt_infallible(
(
(
value((), tuple((tag("IN"), multispace0, char('[')))),
value((), tuple((tag("IN"), space0, char('[')))),
map(set_infallible, |(set, errs)| (Some(set), errs)),
),
(
@@ -389,8 +430,8 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
// check for unbounded range in the form of <5, <=10, >5, >=5
let elastic_unbounded_range = map(
tuple((
preceded(multispace0, alt((tag(">="), tag("<="), tag("<"), tag(">")))),
preceded(multispace0, range_term_val()),
preceded(space0, alt((tag(">="), tag("<="), tag("<"), tag(">")))),
preceded(space0, range_term_val()),
)),
|(comparison_sign, bound)| match comparison_sign {
">=" => (UserInputBound::Inclusive(bound), UserInputBound::Unbounded),
@@ -403,7 +444,7 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
);
let lower_bound = map(
separated_pair(one_of("{["), multispace0, range_term_val()),
separated_pair(one_of("{["), space0, range_term_val()),
|(boundary_char, lower_bound)| {
if lower_bound == "*" {
UserInputBound::Unbounded
@@ -416,7 +457,7 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
);
let upper_bound = map(
separated_pair(range_term_val(), multispace0, one_of("}]")),
separated_pair(range_term_val(), space0, one_of("}]")),
|(upper_bound, boundary_char)| {
if upper_bound == "*" {
UserInputBound::Unbounded
@@ -428,11 +469,8 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
},
);
let lower_to_upper = separated_pair(
lower_bound,
tuple((multispace1, tag("TO"), multispace1)),
upper_bound,
);
let lower_to_upper =
separated_pair(lower_bound, tuple((space1, tag("TO"), space1)), upper_bound);
map(
alt((elastic_unbounded_range, lower_to_upper)),
@@ -452,16 +490,13 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
word_infallible("]}"),
space1_infallible,
opt_i_err(
terminated(tag("TO"), alt((value((), multispace1), value((), eof)))),
terminated(tag("TO"), alt((value((), space1), value((), eof)))),
"missing keyword TO",
),
word_infallible("]}"),
opt_i_err(one_of("]}"), "missing range delimiter"),
)),
|(
(lower_bound_kind, _multispace0, lower, _multispace1, to, upper, upper_bound_kind),
errs,
)| {
|((lower_bound_kind, _space0, lower, _space1, to, upper, upper_bound_kind), errs)| {
let lower_bound = match (lower_bound_kind, lower) {
(_, Some("*")) => UserInputBound::Unbounded,
(_, None) => UserInputBound::Unbounded,
@@ -561,10 +596,10 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
fn set(inp: &str) -> IResult<&str, UserInputLeaf> {
map(
preceded(
tuple((multispace0, tag("IN"), multispace1)),
tuple((space0, tag("IN"), space1)),
delimited(
tuple((char('['), multispace0)),
separated_list0(multispace1, map(simple_term, |(_, term)| term)),
tuple((char('['), space0)),
separated_list0(space1, map(simple_term, |(_, term)| term)),
char(']'),
),
),
@@ -632,7 +667,7 @@ fn leaf(inp: &str) -> IResult<&str, UserInputAst> {
alt((
delimited(char('('), ast, char(')')),
map(char('*'), |_| UserInputAst::from(UserInputLeaf::All)),
map(preceded(tuple((tag("NOT"), multispace1)), leaf), negate),
map(preceded(tuple((tag("NOT"), space1)), leaf), negate),
literal,
))(inp)
}
@@ -745,23 +780,27 @@ fn binary_operand(inp: &str) -> IResult<&str, BinaryOperand> {
}
fn aggregate_binary_expressions(
left: (Option<Occur>, UserInputAst),
others: Vec<(Option<BinaryOperand>, Option<Occur>, UserInputAst)>,
) -> Result<UserInputAst, LenientErrorInternal> {
let mut leafs = Vec::with_capacity(others.len() + 1);
leafs.push((None, left.0, Some(left.1)));
leafs.extend(
others
.into_iter()
.map(|(operand, occur, ast)| (operand, occur, Some(ast))),
);
// the parameters we pass should statically guarantee we can't get errors
// (no prefix BinaryOperand is provided)
let (res, mut errors) = aggregate_infallible_expressions(leafs);
if errors.is_empty() {
Ok(res)
left: UserInputAst,
others: Vec<(BinaryOperand, UserInputAst)>,
) -> UserInputAst {
let mut dnf: Vec<Vec<UserInputAst>> = vec![vec![left]];
for (operator, operand_ast) in others {
match operator {
BinaryOperand::And => {
if let Some(last) = dnf.last_mut() {
last.push(operand_ast);
}
}
BinaryOperand::Or => {
dnf.push(vec![operand_ast]);
}
}
}
if dnf.len() == 1 {
UserInputAst::and(dnf.into_iter().next().unwrap()) //< safe
} else {
Err(errors.swap_remove(0))
let conjunctions = dnf.into_iter().map(UserInputAst::and).collect();
UserInputAst::or(conjunctions)
}
}
@@ -777,10 +816,30 @@ fn aggregate_infallible_expressions(
return (UserInputAst::empty_query(), err);
}
let use_operand = leafs.iter().any(|(operand, _, _)| operand.is_some());
let all_operand = leafs
.iter()
.skip(1)
.all(|(operand, _, _)| operand.is_some());
let early_operand = leafs
.iter()
.take(1)
.all(|(operand, _, _)| operand.is_some());
let use_occur = leafs.iter().any(|(_, occur, _)| occur.is_some());
if use_operand && use_occur {
err.push(LenientErrorInternal {
pos: 0,
message: "Use of mixed occur and boolean operator".to_string(),
});
}
if use_operand && !all_operand {
err.push(LenientErrorInternal {
pos: 0,
message: "Missing boolean operator".to_string(),
});
}
if early_operand {
err.push(LenientErrorInternal {
@@ -807,15 +866,7 @@ fn aggregate_infallible_expressions(
Some(BinaryOperand::And) => Some(Occur::Must),
_ => Some(Occur::Should),
};
if occur == &Some(Occur::MustNot) && default_op == Some(Occur::Should) {
// if occur is MustNot *and* operation is OR, we synthetize a ShouldNot
clauses.push(vec![(
Some(Occur::Should),
ast.clone().unary(Occur::MustNot),
)])
} else {
clauses.push(vec![(occur.or(default_op), ast.clone())]);
}
clauses.push(vec![(occur.or(default_op), ast.clone())]);
}
None => {
let default_op = match next_operator {
@@ -823,15 +874,7 @@ fn aggregate_infallible_expressions(
Some(BinaryOperand::Or) => Some(Occur::Should),
None => None,
};
if occur == &Some(Occur::MustNot) && default_op == Some(Occur::Should) {
// if occur is MustNot *and* operation is OR, we synthetize a ShouldNot
clauses.push(vec![(
Some(Occur::Should),
ast.clone().unary(Occur::MustNot),
)])
} else {
clauses.push(vec![(occur.or(default_op), ast.clone())])
}
clauses.push(vec![(occur.or(default_op), ast.clone())])
}
}
}
@@ -848,12 +891,7 @@ fn aggregate_infallible_expressions(
}
}
Some(BinaryOperand::Or) => {
if last_occur == Some(Occur::MustNot) {
// if occur is MustNot *and* operation is OR, we synthetize a ShouldNot
clauses.push(vec![(Some(Occur::Should), last_ast.unary(Occur::MustNot))]);
} else {
clauses.push(vec![(last_occur.or(Some(Occur::Should)), last_ast)]);
}
clauses.push(vec![(last_occur.or(Some(Occur::Should)), last_ast)]);
}
None => clauses.push(vec![(last_occur, last_ast)]),
}
@@ -879,29 +917,35 @@ fn aggregate_infallible_expressions(
}
}
fn operand_leaf(inp: &str) -> IResult<&str, (Option<BinaryOperand>, Option<Occur>, UserInputAst)> {
map(
tuple((
terminated(opt(binary_operand), multispace0),
terminated(occur_leaf, multispace0),
)),
|(operand, (occur, ast))| (operand, occur, ast),
)(inp)
fn operand_leaf(inp: &str) -> IResult<&str, (BinaryOperand, UserInputAst)> {
tuple((
terminated(binary_operand, space0),
terminated(boosted_leaf, space0),
))(inp)
}
fn ast(inp: &str) -> IResult<&str, UserInputAst> {
let boolean_expr = map_res(
separated_pair(occur_leaf, multispace1, many1(operand_leaf)),
let boolean_expr = map(
separated_pair(boosted_leaf, space1, many1(operand_leaf)),
|(left, right)| aggregate_binary_expressions(left, right),
);
let single_leaf = map(occur_leaf, |(occur, ast)| {
if occur == Some(Occur::MustNot) {
ast.unary(Occur::MustNot)
let whitespace_separated_leaves = map(separated_list1(space1, occur_leaf), |subqueries| {
if subqueries.len() == 1 {
let (occur_opt, ast) = subqueries.into_iter().next().unwrap();
match occur_opt.unwrap_or(Occur::Should) {
Occur::Must | Occur::Should => ast,
Occur::MustNot => UserInputAst::Clause(vec![(Some(Occur::MustNot), ast)]),
}
} else {
ast
UserInputAst::Clause(subqueries.into_iter().collect())
}
});
delimited(multispace0, alt((boolean_expr, single_leaf)), multispace0)(inp)
delimited(
space0,
alt((boolean_expr, whitespace_separated_leaves)),
space0,
)(inp)
}
fn ast_infallible(inp: &str) -> JResult<&str, UserInputAst> {
@@ -925,7 +969,7 @@ fn ast_infallible(inp: &str) -> JResult<&str, UserInputAst> {
}
pub fn parse_to_ast(inp: &str) -> IResult<&str, UserInputAst> {
map(delimited(multispace0, opt(ast), eof), |opt_ast| {
map(delimited(space0, opt(ast), eof), |opt_ast| {
rewrite_ast(opt_ast.unwrap_or_else(UserInputAst::empty_query))
})(inp)
}
@@ -1101,43 +1145,24 @@ mod test {
#[test]
fn test_parse_query_to_ast_binary_op() {
test_parse_query_to_ast_helper("a AND b", "(+a +b)");
test_parse_query_to_ast_helper("a\nAND b", "(+a +b)");
test_parse_query_to_ast_helper("a OR b", "(?a ?b)");
test_parse_query_to_ast_helper("a OR b AND c", "(?a ?(+b +c))");
test_parse_query_to_ast_helper("a AND b AND c", "(+a +b +c)");
test_parse_query_to_ast_helper("a OR b aaa", "(?a ?b *aaa)");
test_parse_query_to_ast_helper("a AND b aaa", "(?(+a +b) *aaa)");
test_parse_query_to_ast_helper("aaa a OR b ", "(*aaa ?a ?b)");
test_parse_query_to_ast_helper("aaa ccc a OR b ", "(*aaa *ccc ?a ?b)");
test_parse_query_to_ast_helper("aaa a AND b ", "(*aaa ?(+a +b))");
test_parse_query_to_ast_helper("aaa ccc a AND b ", "(*aaa *ccc ?(+a +b))");
test_is_parse_err("a OR b aaa", "(?a ?b *aaa)");
test_is_parse_err("a AND b aaa", "(?(+a +b) *aaa)");
test_is_parse_err("aaa a OR b ", "(*aaa ?a ?b)");
test_is_parse_err("aaa ccc a OR b ", "(*aaa *ccc ?a ?b)");
test_is_parse_err("aaa a AND b ", "(*aaa ?(+a +b))");
test_is_parse_err("aaa ccc a AND b ", "(*aaa *ccc ?(+a +b))");
}
#[test]
fn test_parse_mixed_bool_occur() {
test_parse_query_to_ast_helper("+a OR +b", "(+a +b)");
test_parse_query_to_ast_helper("a AND -b", "(+a -b)");
test_parse_query_to_ast_helper("-a AND b", "(-a +b)");
test_parse_query_to_ast_helper("a AND NOT b", "(+a +(-b))");
test_parse_query_to_ast_helper("NOT a AND b", "(+(-a) +b)");
test_parse_query_to_ast_helper("a AND NOT b AND c", "(+a +(-b) +c)");
test_parse_query_to_ast_helper("a AND -b AND c", "(+a -b +c)");
test_parse_query_to_ast_helper("a OR -b", "(?a ?(-b))");
test_parse_query_to_ast_helper("-a OR b", "(?(-a) ?b)");
test_parse_query_to_ast_helper("a OR NOT b", "(?a ?(-b))");
test_parse_query_to_ast_helper("NOT a OR b", "(?(-a) ?b)");
test_parse_query_to_ast_helper("a OR NOT b OR c", "(?a ?(-b) ?c)");
test_parse_query_to_ast_helper("a OR -b OR c", "(?a ?(-b) ?c)");
test_parse_query_to_ast_helper("a OR b +aaa", "(?a ?b +aaa)");
test_parse_query_to_ast_helper("a AND b -aaa", "(?(+a +b) -aaa)");
test_parse_query_to_ast_helper("+a OR +b aaa", "(+a +b *aaa)");
test_parse_query_to_ast_helper("-a AND -b aaa", "(?(-a -b) *aaa)");
test_parse_query_to_ast_helper("-aaa +ccc -a OR b ", "(-aaa +ccc ?(-a) ?b)");
test_is_parse_err("a OR b +aaa", "(?a ?b +aaa)");
test_is_parse_err("a AND b -aaa", "(?(+a +b) -aaa)");
test_is_parse_err("+a OR +b aaa", "(+a +b *aaa)");
test_is_parse_err("-a AND -b aaa", "(?(-a -b) *aaa)");
test_is_parse_err("-aaa +ccc -a OR b ", "(-aaa +ccc -a ?b)");
}
#[test]
@@ -1427,18 +1452,8 @@ mod test {
#[test]
fn test_parse_query_term_group() {
test_parse_query_to_ast_helper(r#"field:(abc)"#, r#""field":abc"#);
test_parse_query_to_ast_helper(r#"field:(abc)"#, r#"(*"field":abc)"#);
test_parse_query_to_ast_helper(r#"field:(+a -"b c")"#, r#"(+"field":a -"field":"b c")"#);
test_parse_query_to_ast_helper(r#"field:(a AND "b c")"#, r#"(+"field":a +"field":"b c")"#);
test_parse_query_to_ast_helper(r#"field:(a OR "b c")"#, r#"(?"field":a ?"field":"b c")"#);
test_parse_query_to_ast_helper(
r#"field:(a OR (b AND c))"#,
r#"(?"field":a ?(+"field":b +"field":c))"#,
);
test_parse_query_to_ast_helper(
r#"field:(a [b TO c])"#,
r#"(*"field":a *"field":["b" TO "c"])"#,
);
test_is_parse_err(r#"field:(+a -"b c""#, r#"(+"field":a -"field":"b c")"#);
}

View File

@@ -44,26 +44,6 @@ impl UserInputLeaf {
},
}
}
pub(crate) fn set_default_field(&mut self, default_field: String) {
match self {
UserInputLeaf::Literal(ref mut literal) if literal.field_name.is_none() => {
literal.field_name = Some(default_field)
}
UserInputLeaf::All => {
*self = UserInputLeaf::Exists {
field: default_field,
}
}
UserInputLeaf::Range { ref mut field, .. } if field.is_none() => {
*field = Some(default_field)
}
UserInputLeaf::Set { ref mut field, .. } if field.is_none() => {
*field = Some(default_field)
}
_ => (), // field was already set, do nothing
}
}
}
impl Debug for UserInputLeaf {
@@ -225,16 +205,6 @@ impl UserInputAst {
pub fn or(asts: Vec<UserInputAst>) -> UserInputAst {
UserInputAst::compose(Occur::Should, asts)
}
pub(crate) fn set_default_field(&mut self, field: String) {
match self {
UserInputAst::Clause(clauses) => clauses
.iter_mut()
.for_each(|(_, ast)| ast.set_default_field(field.clone())),
UserInputAst::Leaf(leaf) => leaf.set_default_field(field),
UserInputAst::Boost(ref mut ast, _) => ast.set_default_field(field),
}
}
}
impl From<UserInputLiteral> for UserInputLeaf {

View File

@@ -290,41 +290,6 @@ mod bench {
});
}
bench_all_cardinalities!(bench_aggregation_terms_many_with_top_hits_agg);
fn bench_aggregation_terms_many_with_top_hits_agg_card(
b: &mut Bencher,
cardinality: Cardinality,
) {
let index = get_test_index_bench(cardinality).unwrap();
let reader = index.reader().unwrap();
b.iter(|| {
let agg_req: Aggregations = serde_json::from_value(json!({
"my_texts": {
"terms": { "field": "text_many_terms" },
"aggs": {
"top_hits": { "top_hits":
{
"sort": [
{ "score": "desc" }
],
"size": 2,
"doc_value_fields": ["score_f64"]
}
}
}
},
}))
.unwrap();
let collector = get_collector(agg_req);
let searcher = reader.searcher();
searcher.search(&AllQuery, &collector).unwrap()
});
}
bench_all_cardinalities!(bench_aggregation_terms_many_with_sub_agg);
fn bench_aggregation_terms_many_with_sub_agg_card(b: &mut Bencher, cardinality: Cardinality) {

View File

@@ -35,7 +35,7 @@ use super::bucket::{
};
use super::metric::{
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation,
PercentilesAggregationReq, StatsAggregation, SumAggregation, TopHitsAggregation,
PercentilesAggregationReq, StatsAggregation, SumAggregation,
};
/// The top-level aggregation request structure, which contains [`Aggregation`] and their user
@@ -93,12 +93,7 @@ impl Aggregation {
}
fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
fast_field_names.extend(
self.agg
.get_fast_field_names()
.iter()
.map(|s| s.to_string()),
);
fast_field_names.insert(self.agg.get_fast_field_name().to_string());
fast_field_names.extend(get_fast_field_names(&self.sub_aggregation));
}
}
@@ -152,27 +147,23 @@ pub enum AggregationVariants {
/// Computes the sum of the extracted values.
#[serde(rename = "percentiles")]
Percentiles(PercentilesAggregationReq),
/// Finds the top k values matching some order
#[serde(rename = "top_hits")]
TopHits(TopHitsAggregation),
}
impl AggregationVariants {
/// Returns the name of the fields used by the aggregation.
pub fn get_fast_field_names(&self) -> Vec<&str> {
/// Returns the name of the field used by the aggregation.
pub fn get_fast_field_name(&self) -> &str {
match self {
AggregationVariants::Terms(terms) => vec![terms.field.as_str()],
AggregationVariants::Range(range) => vec![range.field.as_str()],
AggregationVariants::Histogram(histogram) => vec![histogram.field.as_str()],
AggregationVariants::DateHistogram(histogram) => vec![histogram.field.as_str()],
AggregationVariants::Average(avg) => vec![avg.field_name()],
AggregationVariants::Count(count) => vec![count.field_name()],
AggregationVariants::Max(max) => vec![max.field_name()],
AggregationVariants::Min(min) => vec![min.field_name()],
AggregationVariants::Stats(stats) => vec![stats.field_name()],
AggregationVariants::Sum(sum) => vec![sum.field_name()],
AggregationVariants::Percentiles(per) => vec![per.field_name()],
AggregationVariants::TopHits(top_hits) => top_hits.field_names(),
AggregationVariants::Terms(terms) => terms.field.as_str(),
AggregationVariants::Range(range) => range.field.as_str(),
AggregationVariants::Histogram(histogram) => histogram.field.as_str(),
AggregationVariants::DateHistogram(histogram) => histogram.field.as_str(),
AggregationVariants::Average(avg) => avg.field_name(),
AggregationVariants::Count(count) => count.field_name(),
AggregationVariants::Max(max) => max.field_name(),
AggregationVariants::Min(min) => min.field_name(),
AggregationVariants::Stats(stats) => stats.field_name(),
AggregationVariants::Sum(sum) => sum.field_name(),
AggregationVariants::Percentiles(per) => per.field_name(),
}
}

View File

@@ -1,9 +1,6 @@
//! This will enhance the request tree with access to the fastfield and metadata.
use std::collections::HashMap;
use std::io;
use columnar::{Column, ColumnBlockAccessor, ColumnType, DynamicColumn, StrColumn};
use columnar::{Column, ColumnBlockAccessor, ColumnType, StrColumn};
use super::agg_limits::ResourceLimitGuard;
use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
@@ -17,7 +14,7 @@ use super::metric::{
use super::segment_agg_result::AggregationLimits;
use super::VecWithNames;
use crate::aggregation::{f64_to_fastfield_u64, Key};
use crate::{SegmentOrdinal, SegmentReader};
use crate::SegmentReader;
#[derive(Default)]
pub(crate) struct AggregationsWithAccessor {
@@ -35,7 +32,6 @@ impl AggregationsWithAccessor {
}
pub struct AggregationWithAccessor {
pub(crate) segment_ordinal: SegmentOrdinal,
/// In general there can be buckets without fast field access, e.g. buckets that are created
/// based on search terms. That is not that case currently, but eventually this needs to be
/// Option or moved.
@@ -48,16 +44,10 @@ pub struct AggregationWithAccessor {
pub(crate) limits: ResourceLimitGuard,
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
/// Used for missing term aggregation, which checks all columns for existence.
/// And also for `top_hits` aggregation, which may sort on multiple fields.
/// By convention the missing aggregation is chosen, when this property is set
/// (instead bein set in `agg`).
/// If this needs to used by other aggregations, we need to refactor this.
// NOTE: we can make all other aggregations use this instead of the `accessor` and `field_type`
// (making them obsolete) But will it have a performance impact?
pub(crate) accessors: Vec<(Column<u64>, ColumnType)>,
/// Map field names to all associated column accessors.
/// This field is used for `docvalue_fields`, which is currently only supported for `top_hits`.
pub(crate) value_accessors: HashMap<String, Vec<DynamicColumn>>,
pub(crate) accessors: Vec<Column<u64>>,
pub(crate) agg: Aggregation,
}
@@ -67,55 +57,19 @@ impl AggregationWithAccessor {
agg: &Aggregation,
sub_aggregation: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: AggregationLimits,
) -> crate::Result<Vec<AggregationWithAccessor>> {
let mut agg = agg.clone();
let add_agg_with_accessor = |agg: &Aggregation,
accessor: Column<u64>,
let add_agg_with_accessor = |accessor: Column<u64>,
column_type: ColumnType,
aggs: &mut Vec<AggregationWithAccessor>|
-> crate::Result<()> {
let res = AggregationWithAccessor {
segment_ordinal,
accessor,
accessors: Default::default(),
value_accessors: Default::default(),
accessors: Vec::new(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
limits: limits.new_guard(),
missing_value_for_accessor: None,
str_dict_column: None,
column_block_accessor: Default::default(),
};
aggs.push(res);
Ok(())
};
let add_agg_with_accessors = |agg: &Aggregation,
accessors: Vec<(Column<u64>, ColumnType)>,
aggs: &mut Vec<AggregationWithAccessor>,
value_accessors: HashMap<String, Vec<DynamicColumn>>|
-> crate::Result<()> {
let (accessor, field_type) = accessors.first().expect("at least one accessor");
let res = AggregationWithAccessor {
segment_ordinal,
// TODO: We should do away with the `accessor` field altogether
accessor: accessor.clone(),
value_accessors,
field_type: *field_type,
accessors,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
@@ -130,36 +84,32 @@ impl AggregationWithAccessor {
let mut res: Vec<AggregationWithAccessor> = Vec::new();
use AggregationVariants::*;
match agg.agg {
match &agg.agg {
Range(RangeAggregation {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
Histogram(HistogramAggregation {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
DateHistogram(DateHistogramAggregationReq {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
// Only DateTime is supported for DateHistogram
get_ff_reader(reader, field_name, Some(&[ColumnType::DateTime]))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
Terms(TermsAggregation {
field: ref field_name,
ref missing,
field: field_name,
missing,
..
}) => {
let str_dict_column = reader.fast_fields().str(field_name)?;
@@ -169,9 +119,9 @@ impl AggregationWithAccessor {
ColumnType::F64,
ColumnType::Str,
ColumnType::DateTime,
ColumnType::Bool,
ColumnType::IpAddr,
// ColumnType::Bytes Unsupported
// ColumnType::Bool Unsupported
// ColumnType::IpAddr Unsupported
];
// In case the column is empty we want the shim column to match the missing type
@@ -212,11 +162,24 @@ impl AggregationWithAccessor {
let column_and_types =
get_all_ff_reader_or_empty(reader, field_name, None, fallback_type)?;
let accessors = column_and_types
.iter()
.map(|c_t| (c_t.0.clone(), c_t.1))
.collect();
add_agg_with_accessors(&agg, accessors, &mut res, Default::default())?;
let accessors: Vec<Column> =
column_and_types.iter().map(|(a, _)| a.clone()).collect();
let agg_wit_acc = AggregationWithAccessor {
missing_value_for_accessor: None,
accessor: accessors[0].clone(),
accessors,
field_type: ColumnType::U64,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
&limits,
)?,
agg: agg.clone(),
str_dict_column: str_dict_column.clone(),
limits: limits.new_guard(),
column_block_accessor: Default::default(),
};
res.push(agg_wit_acc);
}
for (accessor, column_type) in column_and_types {
@@ -226,25 +189,21 @@ impl AggregationWithAccessor {
missing.clone()
};
let missing_value_for_accessor = if let Some(missing) =
missing_value_term_agg.as_ref()
{
get_missing_val(column_type, missing, agg.agg.get_fast_field_names()[0])?
} else {
None
};
let missing_value_for_accessor =
if let Some(missing) = missing_value_term_agg.as_ref() {
get_missing_val(column_type, missing, agg.agg.get_fast_field_name())?
} else {
None
};
let agg = AggregationWithAccessor {
segment_ordinal,
missing_value_for_accessor,
accessor,
accessors: Default::default(),
value_accessors: Default::default(),
accessors: Vec::new(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
@@ -256,63 +215,34 @@ impl AggregationWithAccessor {
}
}
Average(AverageAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Count(CountAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Max(MaxAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Min(MinAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Stats(StatsAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Sum(SumAggregation {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
Percentiles(ref percentiles) => {
Percentiles(percentiles) => {
let (accessor, column_type) = get_ff_reader(
reader,
percentiles.field_name(),
Some(get_numeric_or_date_column_types()),
)?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
TopHits(ref mut top_hits) => {
top_hits.validate_and_resolve_field_names(reader.fast_fields().columnar())?;
let accessors: Vec<(Column<u64>, ColumnType)> = top_hits
.field_names()
.iter()
.map(|field| {
get_ff_reader(reader, field, Some(get_numeric_or_date_column_types()))
})
.collect::<crate::Result<_>>()?;
let value_accessors = top_hits
.value_field_names()
.iter()
.map(|field_name| {
Ok((
field_name.to_string(),
get_dynamic_columns(reader, field_name)?,
))
})
.collect::<crate::Result<_>>()?;
add_agg_with_accessors(&agg, accessors, &mut res, value_accessors)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
};
@@ -354,7 +284,6 @@ fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
pub(crate) fn get_aggs_with_segment_accessor_and_validate(
aggs: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: &AggregationLimits,
) -> crate::Result<AggregationsWithAccessor> {
let mut aggss = Vec::new();
@@ -363,7 +292,6 @@ pub(crate) fn get_aggs_with_segment_accessor_and_validate(
agg,
agg.sub_aggregation(),
reader,
segment_ordinal,
limits.clone(),
)?;
for agg in aggs {
@@ -393,19 +321,6 @@ fn get_ff_reader(
Ok(ff_field_with_type)
}
fn get_dynamic_columns(
reader: &SegmentReader,
field_name: &str,
) -> crate::Result<Vec<columnar::DynamicColumn>> {
let ff_fields = reader.fast_fields().dynamic_column_handles(field_name)?;
let cols = ff_fields
.iter()
.map(|h| h.open())
.collect::<io::Result<_>>()?;
assert!(!ff_fields.is_empty(), "field {} not found", field_name);
Ok(cols)
}
/// Get all fast field reader or empty as default.
///
/// Is guaranteed to return at least one column.

View File

@@ -8,7 +8,7 @@ use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::bucket::GetDocCount;
use super::metric::{PercentilesMetricResult, SingleMetricResult, Stats, TopHitsMetricResult};
use super::metric::{PercentilesMetricResult, SingleMetricResult, Stats};
use super::{AggregationError, Key};
use crate::TantivyError;
@@ -90,10 +90,8 @@ pub enum MetricResult {
Stats(Stats),
/// Sum metric result.
Sum(SingleMetricResult),
/// Percentiles metric result.
/// Sum metric result.
Percentiles(PercentilesMetricResult),
/// Top hits metric result
TopHits(TopHitsMetricResult),
}
impl MetricResult {
@@ -108,9 +106,6 @@ impl MetricResult {
MetricResult::Percentiles(_) => Err(TantivyError::AggregationError(
AggregationError::InvalidRequest("percentiles can't be used to order".to_string()),
)),
MetricResult::TopHits(_) => Err(TantivyError::AggregationError(
AggregationError::InvalidRequest("top_hits can't be used to order".to_string()),
)),
}
}
}

View File

@@ -4,7 +4,6 @@ use crate::aggregation::agg_req::{Aggregation, Aggregations};
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::buf_collector::DOC_BLOCK_SIZE;
use crate::aggregation::collector::AggregationCollector;
use crate::aggregation::intermediate_agg_result::IntermediateAggregationResults;
use crate::aggregation::segment_agg_result::AggregationLimits;
use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_values_and_terms};
use crate::aggregation::DistributedAggregationCollector;
@@ -67,22 +66,6 @@ fn test_aggregation_flushing(
}
}
},
"top_hits_test":{
"terms": {
"field": "string_id"
},
"aggs": {
"bucketsL2": {
"top_hits": {
"size": 2,
"sort": [
{ "score": "asc" }
],
"docvalue_fields": ["score"]
}
}
}
},
"histogram_test":{
"histogram": {
"field": "score",
@@ -125,16 +108,6 @@ fn test_aggregation_flushing(
let searcher = reader.searcher();
let intermediate_agg_result = searcher.search(&AllQuery, &collector).unwrap();
// Test postcard roundtrip serialization
let intermediate_agg_result_bytes = postcard::to_allocvec(&intermediate_agg_result).expect(
"Postcard Serialization failed, flatten etc. is not supported in the intermediate \
result",
);
let intermediate_agg_result: IntermediateAggregationResults =
postcard::from_bytes(&intermediate_agg_result_bytes)
.expect("Post deserialization failed");
intermediate_agg_result
.into_final_result(agg_req, &Default::default())
.unwrap()
@@ -614,9 +587,6 @@ fn test_aggregation_on_json_object() {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
index_writer
.add_document(doc!(json => json!({"color": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"color": "red"})))
.unwrap();
@@ -644,8 +614,8 @@ fn test_aggregation_on_json_object() {
&serde_json::json!({
"jsonagg": {
"buckets": [
{"doc_count": 2, "key": "red"},
{"doc_count": 1, "key": "blue"},
{"doc_count": 1, "key": "red"}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
@@ -667,9 +637,6 @@ fn test_aggregation_on_nested_json_object() {
index_writer
.add_document(doc!(json => json!({"color.dot": "blue", "color": {"nested":"blue"} })))
.unwrap();
index_writer
.add_document(doc!(json => json!({"color.dot": "blue", "color": {"nested":"blue"} })))
.unwrap();
index_writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
@@ -697,7 +664,7 @@ fn test_aggregation_on_nested_json_object() {
&serde_json::json!({
"jsonagg1": {
"buckets": [
{"doc_count": 2, "key": "blue"},
{"doc_count": 1, "key": "blue"},
{"doc_count": 1, "key": "red"}
],
"doc_count_error_upper_bound": 0,
@@ -705,7 +672,7 @@ fn test_aggregation_on_nested_json_object() {
},
"jsonagg2": {
"buckets": [
{"doc_count": 2, "key": "blue"},
{"doc_count": 1, "key": "blue"},
{"doc_count": 1, "key": "red"}
],
"doc_count_error_upper_bound": 0,
@@ -843,38 +810,29 @@ fn test_aggregation_on_json_object_mixed_types() {
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(json => json!({"mixed_type": 10.0, "mixed_price": 10.0})))
.add_document(doc!(json => json!({"mixed_type": 10.0})))
.unwrap();
index_writer.commit().unwrap();
// => Segment with all values text
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue", "mixed_price": 5.0})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue", "mixed_price": 5.0})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue", "mixed_price": 5.0})))
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer.commit().unwrap();
// => Segment with all boolen
index_writer
.add_document(doc!(json => json!({"mixed_type": true, "mixed_price": "no_price"})))
.add_document(doc!(json => json!({"mixed_type": true})))
.unwrap();
index_writer.commit().unwrap();
// => Segment with mixed values
index_writer
.add_document(doc!(json => json!({"mixed_type": "red", "mixed_price": 1.0})))
.add_document(doc!(json => json!({"mixed_type": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "red", "mixed_price": 1.0})))
.add_document(doc!(json => json!({"mixed_type": -20.5})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": -20.5, "mixed_price": -20.5})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": true, "mixed_price": "no_price"})))
.add_document(doc!(json => json!({"mixed_type": true})))
.unwrap();
index_writer.commit().unwrap();
@@ -888,7 +846,7 @@ fn test_aggregation_on_json_object_mixed_types() {
"order": { "min_price": "desc" }
},
"aggs": {
"min_price": { "min": { "field": "json.mixed_price" } }
"min_price": { "min": { "field": "json.mixed_type" } }
}
},
"rangeagg": {
@@ -912,7 +870,6 @@ fn test_aggregation_on_json_object_mixed_types() {
let aggregation_results = searcher.search(&AllQuery, &aggregation_collector).unwrap();
let aggregation_res_json = serde_json::to_value(aggregation_results).unwrap();
use pretty_assertions::assert_eq;
assert_eq!(
&aggregation_res_json,
&serde_json::json!({
@@ -927,10 +884,10 @@ fn test_aggregation_on_json_object_mixed_types() {
"termagg": {
"buckets": [
{ "doc_count": 1, "key": 10.0, "min_price": { "value": 10.0 } },
{ "doc_count": 3, "key": "blue", "min_price": { "value": 5.0 } },
{ "doc_count": 2, "key": "red", "min_price": { "value": 1.0 } },
{ "doc_count": 1, "key": -20.5, "min_price": { "value": -20.5 } },
{ "doc_count": 2, "key": 1.0, "key_as_string": "true", "min_price": { "value": null } },
// TODO bool is also not yet handled in aggregation
{ "doc_count": 1, "key": "blue", "min_price": { "value": null } },
{ "doc_count": 1, "key": "red", "min_price": { "value": null } },
],
"sum_other_doc_count": 0
}

View File

@@ -1,7 +1,7 @@
use serde::{Deserialize, Serialize};
use super::{HistogramAggregation, HistogramBounds};
use crate::aggregation::*;
use crate::aggregation::AggregationError;
/// DateHistogramAggregation is similar to `HistogramAggregation`, but it can only be used with date
/// type.
@@ -307,7 +307,6 @@ pub mod tests {
) -> crate::Result<Index> {
let mut schema_builder = Schema::builder();
schema_builder.add_date_field("date", FAST);
schema_builder.add_json_field("mixed", FAST);
schema_builder.add_text_field("text", FAST | STRING);
schema_builder.add_text_field("text2", FAST | STRING);
let schema = schema_builder.build();
@@ -352,10 +351,8 @@ pub mod tests {
let docs = vec![
vec![r#"{ "date": "2015-01-01T12:10:30Z", "text": "aaa" }"#],
vec![r#"{ "date": "2015-01-01T11:11:30Z", "text": "bbb" }"#],
vec![r#"{ "date": "2015-01-01T11:11:30Z", "text": "bbb" }"#],
vec![r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb" }"#],
vec![r#"{ "date": "2015-01-06T00:00:00Z", "text": "ccc" }"#],
vec![r#"{ "date": "2015-01-06T00:00:00Z", "text": "ccc" }"#],
];
let index = get_test_index_from_docs(merge_segments, &docs).unwrap();
@@ -384,7 +381,7 @@ pub mod tests {
{
"key_as_string" : "2015-01-01T00:00:00Z",
"key" : 1420070400000.0,
"doc_count" : 6
"doc_count" : 4
}
]
}
@@ -422,15 +419,15 @@ pub mod tests {
{
"key_as_string" : "2015-01-01T00:00:00Z",
"key" : 1420070400000.0,
"doc_count" : 6,
"doc_count" : 4,
"texts": {
"buckets": [
{
"doc_count": 3,
"doc_count": 2,
"key": "bbb"
},
{
"doc_count": 2,
"doc_count": 1,
"key": "ccc"
},
{
@@ -469,7 +466,7 @@ pub mod tests {
"sales_over_time": {
"buckets": [
{
"doc_count": 3,
"doc_count": 2,
"key": 1420070400000.0,
"key_as_string": "2015-01-01T00:00:00Z"
},
@@ -494,7 +491,7 @@ pub mod tests {
"key_as_string": "2015-01-05T00:00:00Z"
},
{
"doc_count": 2,
"doc_count": 1,
"key": 1420502400000.0,
"key_as_string": "2015-01-06T00:00:00Z"
}
@@ -535,7 +532,7 @@ pub mod tests {
"key_as_string": "2014-12-31T00:00:00Z"
},
{
"doc_count": 3,
"doc_count": 2,
"key": 1420070400000.0,
"key_as_string": "2015-01-01T00:00:00Z"
},
@@ -560,7 +557,7 @@ pub mod tests {
"key_as_string": "2015-01-05T00:00:00Z"
},
{
"doc_count": 2,
"doc_count": 1,
"key": 1420502400000.0,
"key_as_string": "2015-01-06T00:00:00Z"
},

View File

@@ -1,5 +1,8 @@
use std::cmp::Ordering;
use std::fmt::Display;
use columnar::ColumnType;
use itertools::Itertools;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use tantivy_bitpacker::minmax;
@@ -15,9 +18,9 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateHistogramBucketEntry,
};
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
build_segment_agg_collector, AggregationLimits, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::aggregation::{f64_from_fastfield_u64, format_date};
use crate::TantivyError;
/// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
@@ -70,7 +73,6 @@ pub struct HistogramAggregation {
pub field: String,
/// The interval to chunk your data range. Each bucket spans a value range of [0..interval).
/// Must be a positive value.
#[serde(deserialize_with = "deserialize_f64")]
pub interval: f64,
/// Intervals implicitly defines an absolute grid of buckets `[interval * k, interval * (k +
/// 1))`.
@@ -83,7 +85,6 @@ pub struct HistogramAggregation {
/// fall into the buckets with the key 0 and 10.
/// With offset 5 and interval 10, they would both fall into the bucket with they key 5 and the
/// range [5..15)
#[serde(default, deserialize_with = "deserialize_option_f64")]
pub offset: Option<f64>,
/// The minimum number of documents in a bucket to be returned. Defaults to 0.
pub min_doc_count: Option<u64>,
@@ -307,10 +308,7 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
.column_block_accessor
.fetch_block(docs, &bucket_agg_accessor.accessor);
for (doc, val) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
for (doc, val) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_pos(val);
@@ -597,12 +595,11 @@ mod tests {
use serde_json::Value;
use super::*;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::tests::{
exec_request, exec_request_with_query, exec_request_with_query_and_memory_limit,
get_test_index_2_segments, get_test_index_from_values, get_test_index_with_num_docs,
};
use crate::query::AllQuery;
#[test]
fn histogram_test_crooked_values() -> crate::Result<()> {
@@ -1354,35 +1351,6 @@ mod tests {
})
);
Ok(())
}
#[test]
fn test_aggregation_histogram_empty_index() -> crate::Result<()> {
// test index without segments
let values = vec![];
let index = get_test_index_from_values(false, &values)?;
let agg_req_1: Aggregations = serde_json::from_value(json!({
"myhisto": {
"histogram": {
"field": "score",
"interval": 10.0
},
}
}))
.unwrap();
let collector = AggregationCollector::from_aggs(agg_req_1, Default::default());
let reader = index.reader()?;
let searcher = reader.searcher();
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
// Make sure the result structure is correct
assert_eq!(res["myhisto"]["buckets"].as_array().unwrap().len(), 0);
Ok(())
}
}

View File

@@ -28,7 +28,6 @@ mod term_agg;
mod term_missing_agg;
use std::collections::HashMap;
use std::fmt;
pub use histogram::*;
pub use range::*;
@@ -73,12 +72,12 @@ impl From<&str> for OrderTarget {
}
}
impl fmt::Display for OrderTarget {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
impl ToString for OrderTarget {
fn to_string(&self) -> String {
match self {
OrderTarget::Key => f.write_str("_key"),
OrderTarget::Count => f.write_str("_count"),
OrderTarget::SubAggregation(agg) => agg.fmt(f),
OrderTarget::Key => "_key".to_string(),
OrderTarget::Count => "_count".to_string(),
OrderTarget::SubAggregation(agg) => agg.to_string(),
}
}
}

View File

@@ -1,6 +1,7 @@
use std::fmt::Debug;
use std::ops::Range;
use columnar::{ColumnType, MonotonicallyMappableToU64};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
@@ -13,7 +14,9 @@ use crate::aggregation::intermediate_agg_result::{
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::aggregation::{
f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
};
use crate::TantivyError;
/// Provide user-defined buckets to aggregate on.
@@ -69,19 +72,11 @@ pub struct RangeAggregationRange {
pub key: Option<String>,
/// The from range value, which is inclusive in the range.
/// `None` equals to an open ended interval.
#[serde(
skip_serializing_if = "Option::is_none",
default,
deserialize_with = "deserialize_option_f64"
)]
#[serde(skip_serializing_if = "Option::is_none", default)]
pub from: Option<f64>,
/// The to range value, which is not inclusive in the range.
/// `None` equals to an open ended interval.
#[serde(
skip_serializing_if = "Option::is_none",
default,
deserialize_with = "deserialize_option_f64"
)]
#[serde(skip_serializing_if = "Option::is_none", default)]
pub to: Option<f64>,
}
@@ -235,10 +230,7 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
.column_block_accessor
.fetch_block(docs, &bucket_agg_accessor.accessor);
for (doc, val) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
for (doc, val) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
let bucket_pos = self.get_bucket_pos(val);
let bucket = &mut self.buckets[bucket_pos];
@@ -449,6 +441,7 @@ pub(crate) fn range_to_key(range: &Range<u64>, field_type: &ColumnType) -> crate
#[cfg(test)]
mod tests {
use columnar::MonotonicallyMappableToU64;
use serde_json::Value;
use super::*;
@@ -457,6 +450,7 @@ mod tests {
exec_request, exec_request_with_query, get_test_index_2_segments,
get_test_index_with_num_docs,
};
use crate::aggregation::AggregationLimits;
pub fn get_collector_from_ranges(
ranges: Vec<RangeAggregationRange>,

View File

@@ -1,10 +1,6 @@
use std::fmt::Debug;
use std::net::Ipv6Addr;
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{
BytesColumn, ColumnType, MonotonicallyMappableToU128, MonotonicallyMappableToU64, StrColumn,
};
use columnar::{BytesColumn, ColumnType, MonotonicallyMappableToU64, StrColumn};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
@@ -103,14 +99,23 @@ pub struct TermsAggregation {
#[serde(skip_serializing_if = "Option::is_none", default)]
pub size: Option<u32>,
/// To get more accurate results, we fetch more than `size` from each segment.
/// Unused by tantivy.
///
/// Since tantivy doesn't know shards, this parameter is merely there to be used by consumers
/// of tantivy. shard_size is the number of terms returned by each shard.
/// The default value in elasticsearch is size * 1.5 + 10.
///
/// Should never be smaller than size.
#[serde(skip_serializing_if = "Option::is_none", default)]
#[serde(alias = "shard_size")]
pub split_size: Option<u32>,
/// The get more accurate results, we fetch more than `size` from each segment.
///
/// Increasing this value is will increase the cost for more accuracy.
///
/// Defaults to 10 * size.
#[serde(skip_serializing_if = "Option::is_none", default)]
#[serde(alias = "shard_size")]
#[serde(alias = "split_size")]
pub segment_size: Option<u32>,
/// If you set the `show_term_doc_count_error` parameter to true, the terms aggregation will
@@ -251,7 +256,7 @@ pub struct SegmentTermCollector {
term_buckets: TermBuckets,
req: TermsAggregationInternal,
blueprint: Option<Box<dyn SegmentAggregationCollector>>,
column_type: ColumnType,
field_type: ColumnType,
accessor_idx: usize,
}
@@ -310,10 +315,7 @@ impl SegmentAggregationCollector for SegmentTermCollector {
}
// has subagg
if let Some(blueprint) = self.blueprint.as_ref() {
for (doc, term_id) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
for (doc, term_id) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
let sub_aggregations = self
.term_buckets
.sub_aggs
@@ -353,7 +355,7 @@ impl SegmentTermCollector {
field_type: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
if field_type == ColumnType::Bytes {
if field_type == ColumnType::Bytes || field_type == ColumnType::Bool {
return Err(TantivyError::InvalidArgument(format!(
"terms aggregation is not supported for column type {:?}",
field_type
@@ -387,7 +389,7 @@ impl SegmentTermCollector {
req: TermsAggregationInternal::from_req(req),
term_buckets,
blueprint,
column_type: field_type,
field_type,
accessor_idx,
})
}
@@ -464,7 +466,7 @@ impl SegmentTermCollector {
Ok(intermediate_entry)
};
if self.column_type == ColumnType::Str {
if self.field_type == ColumnType::Str {
let term_dict = agg_with_accessor
.str_dict_column
.as_ref()
@@ -529,55 +531,28 @@ impl SegmentTermCollector {
});
}
}
} else if self.column_type == ColumnType::DateTime {
} else if self.field_type == ColumnType::DateTime {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val = i64::from_u64(val);
let date = format_date(val)?;
dict.insert(IntermediateKey::Str(date), intermediate_entry);
}
} else if self.column_type == ColumnType::Bool {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val = bool::from_u64(val);
dict.insert(IntermediateKey::Bool(val), intermediate_entry);
}
} else if self.column_type == ColumnType::IpAddr {
let compact_space_accessor = agg_with_accessor
.accessor
.values
.clone()
.downcast_arc::<CompactSpaceU64Accessor>()
.map_err(|_| {
TantivyError::AggregationError(
crate::aggregation::AggregationError::InternalError(
"Type mismatch: Could not downcast to CompactSpaceU64Accessor"
.to_string(),
),
)
})?;
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val: u128 = compact_space_accessor.compact_to_u128(val as u32);
let val = Ipv6Addr::from_u128(val);
dict.insert(IntermediateKey::IpAddr(val), intermediate_entry);
}
} else {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val = f64_from_fastfield_u64(val, &self.column_type);
let val = f64_from_fastfield_u64(val, &self.field_type);
dict.insert(IntermediateKey::F64(val), intermediate_entry);
}
};
Ok(IntermediateBucketResult::Terms {
buckets: IntermediateTermBucketResult {
Ok(IntermediateBucketResult::Terms(
IntermediateTermBucketResult {
entries: dict,
sum_other_doc_count,
doc_count_error_upper_bound: term_doc_count_before_cutoff,
},
})
))
}
}
@@ -615,9 +590,6 @@ pub(crate) fn cut_off_buckets<T: GetDocCount + Debug>(
#[cfg(test)]
mod tests {
use std::net::IpAddr;
use std::str::FromStr;
use common::DateTime;
use time::{Date, Month};
@@ -628,7 +600,7 @@ mod tests {
};
use crate::aggregation::AggregationLimits;
use crate::indexer::NoMergePolicy;
use crate::schema::{IntoIpv6Addr, Schema, FAST, STRING};
use crate::schema::{Schema, FAST, STRING};
use crate::{Index, IndexWriter};
#[test]
@@ -1210,9 +1182,9 @@ mod tests {
assert_eq!(res["my_texts"]["buckets"][0]["key"], "terma");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termb");
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termc");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 0);
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termc");
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termb");
assert_eq!(res["my_texts"]["buckets"][2]["doc_count"], 0);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
@@ -1393,7 +1365,7 @@ mod tests {
#[test]
fn terms_aggregation_different_tokenizer_on_ff_test() -> crate::Result<()> {
let terms = vec!["Hello Hello", "Hallo Hallo", "Hallo Hallo"];
let terms = vec!["Hello Hello", "Hallo Hallo"];
let index = get_test_index_from_terms(true, &[terms])?;
@@ -1411,7 +1383,7 @@ mod tests {
println!("{}", serde_json::to_string_pretty(&res).unwrap());
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Hallo Hallo");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 1);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Hello Hello");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 1);
@@ -1922,80 +1894,4 @@ mod tests {
Ok(())
}
#[test]
fn terms_aggregation_bool() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_bool_field("bool_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
writer.add_document(doc!(field=>true))?;
writer.add_document(doc!(field=>false))?;
writer.add_document(doc!(field=>true))?;
writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_bool": {
"terms": {
"field": "bool_field"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(res["my_bool"]["buckets"][0]["key"], 1.0);
assert_eq!(res["my_bool"]["buckets"][0]["key_as_string"], "true");
assert_eq!(res["my_bool"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_bool"]["buckets"][1]["key"], 0.0);
assert_eq!(res["my_bool"]["buckets"][1]["key_as_string"], "false");
assert_eq!(res["my_bool"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_bool"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
#[test]
fn terms_aggregation_ip_addr() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_ip_addr_field("ip_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
// IpV6 loopback
writer.add_document(doc!(field=>IpAddr::from_str("::1").unwrap().into_ipv6_addr()))?;
writer.add_document(doc!(field=>IpAddr::from_str("::1").unwrap().into_ipv6_addr()))?;
// IpV4
writer.add_document(
doc!(field=>IpAddr::from_str("127.0.0.1").unwrap().into_ipv6_addr()),
)?;
writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_bool": {
"terms": {
"field": "ip_field"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// print as json
// println!("{}", serde_json::to_string_pretty(&res).unwrap());
assert_eq!(res["my_bool"]["buckets"][0]["key"], "::1");
assert_eq!(res["my_bool"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_bool"]["buckets"][1]["key"], "127.0.0.1");
assert_eq!(res["my_bool"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_bool"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
}

View File

@@ -73,13 +73,11 @@ impl SegmentAggregationCollector for TermMissingAgg {
entries.insert(missing.into(), missing_entry);
let bucket = IntermediateBucketResult::Terms {
buckets: IntermediateTermBucketResult {
entries,
sum_other_doc_count: 0,
doc_count_error_upper_bound: 0,
},
};
let bucket = IntermediateBucketResult::Terms(IntermediateTermBucketResult {
entries,
sum_other_doc_count: 0,
doc_count_error_upper_bound: 0,
});
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
@@ -92,10 +90,7 @@ impl SegmentAggregationCollector for TermMissingAgg {
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let agg = &mut agg_with_accessor.aggs.values[self.accessor_idx];
let has_value = agg
.accessors
.iter()
.any(|(acc, _)| acc.index.has_value(doc));
let has_value = agg.accessors.iter().any(|acc| acc.index.has_value(doc));
if !has_value {
self.missing_count += 1;
if let Some(sub_agg) = self.sub_agg.as_mut() {

View File

@@ -8,7 +8,7 @@ use super::segment_agg_result::{
};
use crate::aggregation::agg_req_with_accessor::get_aggs_with_segment_accessor_and_validate;
use crate::collector::{Collector, SegmentCollector};
use crate::{DocId, SegmentOrdinal, SegmentReader, TantivyError};
use crate::{DocId, SegmentReader, TantivyError};
/// The default max bucket count, before the aggregation fails.
pub const DEFAULT_BUCKET_LIMIT: u32 = 65000;
@@ -64,15 +64,10 @@ impl Collector for DistributedAggregationCollector {
fn for_segment(
&self,
segment_local_id: crate::SegmentOrdinal,
_segment_local_id: crate::SegmentOrdinal,
reader: &crate::SegmentReader,
) -> crate::Result<Self::Child> {
AggregationSegmentCollector::from_agg_req_and_reader(
&self.agg,
reader,
segment_local_id,
&self.limits,
)
AggregationSegmentCollector::from_agg_req_and_reader(&self.agg, reader, &self.limits)
}
fn requires_scoring(&self) -> bool {
@@ -94,15 +89,10 @@ impl Collector for AggregationCollector {
fn for_segment(
&self,
segment_local_id: crate::SegmentOrdinal,
_segment_local_id: crate::SegmentOrdinal,
reader: &crate::SegmentReader,
) -> crate::Result<Self::Child> {
AggregationSegmentCollector::from_agg_req_and_reader(
&self.agg,
reader,
segment_local_id,
&self.limits,
)
AggregationSegmentCollector::from_agg_req_and_reader(&self.agg, reader, &self.limits)
}
fn requires_scoring(&self) -> bool {
@@ -145,11 +135,10 @@ impl AggregationSegmentCollector {
pub fn from_agg_req_and_reader(
agg: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: &AggregationLimits,
) -> crate::Result<Self> {
let mut aggs_with_accessor =
get_aggs_with_segment_accessor_and_validate(agg, reader, segment_ordinal, limits)?;
get_aggs_with_segment_accessor_and_validate(agg, reader, limits)?;
let result =
BufAggregationCollector::new(build_segment_agg_collector(&mut aggs_with_accessor)?);
Ok(AggregationSegmentCollector {

View File

@@ -5,7 +5,6 @@
use std::cmp::Ordering;
use std::collections::hash_map::Entry;
use std::hash::Hash;
use std::net::Ipv6Addr;
use columnar::ColumnType;
use itertools::Itertools;
@@ -20,7 +19,7 @@ use super::bucket::{
};
use super::metric::{
IntermediateAverage, IntermediateCount, IntermediateMax, IntermediateMin, IntermediateStats,
IntermediateSum, PercentilesCollector, TopHitsTopNComputer,
IntermediateSum, PercentilesCollector,
};
use super::segment_agg_result::AggregationLimits;
use super::{format_date, AggregationError, Key, SerializedKey};
@@ -42,10 +41,6 @@ pub struct IntermediateAggregationResults {
/// This might seem redundant with `Key`, but the point is to have a different
/// Serialize implementation.
pub enum IntermediateKey {
/// Ip Addr key
IpAddr(Ipv6Addr),
/// Bool key
Bool(bool),
/// String key
Str(String),
/// `f64` key
@@ -63,16 +58,7 @@ impl From<IntermediateKey> for Key {
fn from(value: IntermediateKey) -> Self {
match value {
IntermediateKey::Str(s) => Self::Str(s),
IntermediateKey::IpAddr(s) => {
// Prefer to use the IPv4 representation if possible
if let Some(ip) = s.to_ipv4_mapped() {
Self::Str(ip.to_string())
} else {
Self::Str(s.to_string())
}
}
IntermediateKey::F64(f) => Self::F64(f),
IntermediateKey::Bool(f) => Self::F64(f as u64 as f64),
}
}
}
@@ -85,8 +71,6 @@ impl std::hash::Hash for IntermediateKey {
match self {
IntermediateKey::Str(text) => text.hash(state),
IntermediateKey::F64(val) => val.to_bits().hash(state),
IntermediateKey::Bool(val) => val.hash(state),
IntermediateKey::IpAddr(val) => val.hash(state),
}
}
}
@@ -182,9 +166,9 @@ impl IntermediateAggregationResults {
pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult {
use AggregationVariants::*;
match req.agg {
Terms(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Terms {
buckets: Default::default(),
}),
Terms(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Terms(
Default::default(),
)),
Range(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Range(
Default::default(),
)),
@@ -221,9 +205,6 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
Percentiles(_) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::Percentiles(PercentilesCollector::default()),
),
TopHits(ref req) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::TopHits(TopHitsTopNComputer::new(req.clone())),
),
}
}
@@ -284,8 +265,6 @@ pub enum IntermediateMetricResult {
Stats(IntermediateStats),
/// Intermediate sum result.
Sum(IntermediateSum),
/// Intermediate top_hits result
TopHits(TopHitsTopNComputer),
}
impl IntermediateMetricResult {
@@ -313,13 +292,9 @@ impl IntermediateMetricResult {
percentiles
.into_final_result(req.agg.as_percentile().expect("unexpected metric type")),
),
IntermediateMetricResult::TopHits(top_hits) => {
MetricResult::TopHits(top_hits.into_final_result())
}
}
}
// TODO: this is our top-of-the-chain fruit merge mech
fn merge_fruits(&mut self, other: IntermediateMetricResult) -> crate::Result<()> {
match (self, other) {
(
@@ -355,9 +330,6 @@ impl IntermediateMetricResult {
) => {
left.merge_fruits(right)?;
}
(IntermediateMetricResult::TopHits(left), IntermediateMetricResult::TopHits(right)) => {
left.merge_fruits(right)?;
}
_ => {
panic!("incompatible fruit types in tree or missing merge_fruits handler");
}
@@ -379,14 +351,11 @@ pub enum IntermediateBucketResult {
Histogram {
/// The column_type of the underlying `Column` is DateTime
is_date_agg: bool,
/// The histogram buckets
/// The buckets
buckets: Vec<IntermediateHistogramBucketEntry>,
},
/// Term aggregation
Terms {
/// The term buckets
buckets: IntermediateTermBucketResult,
},
Terms(IntermediateTermBucketResult),
}
impl IntermediateBucketResult {
@@ -463,7 +432,7 @@ impl IntermediateBucketResult {
};
Ok(BucketResult::Histogram { buckets })
}
IntermediateBucketResult::Terms { buckets: terms } => terms.into_final_result(
IntermediateBucketResult::Terms(terms) => terms.into_final_result(
req.agg
.as_term()
.expect("unexpected aggregation, expected term aggregation"),
@@ -476,12 +445,8 @@ impl IntermediateBucketResult {
fn merge_fruits(&mut self, other: IntermediateBucketResult) -> crate::Result<()> {
match (self, other) {
(
IntermediateBucketResult::Terms {
buckets: term_res_left,
},
IntermediateBucketResult::Terms {
buckets: term_res_right,
},
IntermediateBucketResult::Terms(term_res_left),
IntermediateBucketResult::Terms(term_res_right),
) => {
merge_maps(&mut term_res_left.entries, term_res_right.entries)?;
term_res_left.sum_other_doc_count += term_res_right.sum_other_doc_count;
@@ -565,15 +530,8 @@ impl IntermediateTermBucketResult {
.into_iter()
.filter(|bucket| bucket.1.doc_count as u64 >= req.min_doc_count)
.map(|(key, entry)| {
let key_as_string = match key {
IntermediateKey::Bool(key) => {
let val = if key { "true" } else { "false" };
Some(val.to_string())
}
_ => None,
};
Ok(BucketEntry {
key_as_string,
key_as_string: None,
key: key.into(),
doc_count: entry.doc_count as u64,
sub_aggregation: entry

View File

@@ -2,8 +2,7 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::*;
use super::{IntermediateStats, SegmentStatsCollector};
/// A single-value metric aggregation that computes the average of numeric values that are
/// extracted from the aggregated documents.
@@ -25,7 +24,7 @@ pub struct AverageAggregation {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default, deserialize_with = "deserialize_option_f64")]
#[serde(default)]
pub missing: Option<f64>,
}
@@ -66,71 +65,3 @@ impl IntermediateAverage {
self.stats.finalize().avg
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn deserialization_with_missing_test1() {
let json = r#"{
"field": "score",
"missing": "10.0"
}"#;
let avg: AverageAggregation = serde_json::from_str(json).unwrap();
assert_eq!(avg.field, "score");
assert_eq!(avg.missing, Some(10.0));
// no dot
let json = r#"{
"field": "score",
"missing": "10"
}"#;
let avg: AverageAggregation = serde_json::from_str(json).unwrap();
assert_eq!(avg.field, "score");
assert_eq!(avg.missing, Some(10.0));
// from value
let avg: AverageAggregation = serde_json::from_value(json!({
"field": "score_f64",
"missing": 10u64,
}))
.unwrap();
assert_eq!(avg.missing, Some(10.0));
// from value
let avg: AverageAggregation = serde_json::from_value(json!({
"field": "score_f64",
"missing": 10u32,
}))
.unwrap();
assert_eq!(avg.missing, Some(10.0));
let avg: AverageAggregation = serde_json::from_value(json!({
"field": "score_f64",
"missing": 10i8,
}))
.unwrap();
assert_eq!(avg.missing, Some(10.0));
}
#[test]
fn deserialization_with_missing_test_fail() {
let json = r#"{
"field": "score",
"missing": "a"
}"#;
let avg: Result<AverageAggregation, _> = serde_json::from_str(json);
assert!(avg.is_err());
assert!(avg
.unwrap_err()
.to_string()
.contains("Failed to parse f64 from string: \"a\""));
// Disallow NaN
let json = r#"{
"field": "score",
"missing": "NaN"
}"#;
let avg: Result<AverageAggregation, _> = serde_json::from_str(json);
assert!(avg.is_err());
assert!(avg.unwrap_err().to_string().contains("NaN"));
}
}

View File

@@ -2,8 +2,7 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::*;
use super::{IntermediateStats, SegmentStatsCollector};
/// A single-value metric aggregation that counts the number of values that are
/// extracted from the aggregated documents.
@@ -25,7 +24,7 @@ pub struct CountAggregation {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default, deserialize_with = "deserialize_option_f64")]
#[serde(default)]
pub missing: Option<f64>,
}

View File

@@ -2,8 +2,7 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::*;
use super::{IntermediateStats, SegmentStatsCollector};
/// A single-value metric aggregation that computes the maximum of numeric values that are
/// extracted from the aggregated documents.
@@ -25,7 +24,7 @@ pub struct MaxAggregation {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default, deserialize_with = "deserialize_option_f64")]
#[serde(default)]
pub missing: Option<f64>,
}

View File

@@ -2,8 +2,7 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::*;
use super::{IntermediateStats, SegmentStatsCollector};
/// A single-value metric aggregation that computes the minimum of numeric values that are
/// extracted from the aggregated documents.
@@ -25,7 +24,7 @@ pub struct MinAggregation {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default, deserialize_with = "deserialize_option_f64")]
#[serde(default)]
pub missing: Option<f64>,
}

View File

@@ -23,10 +23,6 @@ mod min;
mod percentiles;
mod stats;
mod sum;
mod top_hits;
use std::collections::HashMap;
pub use average::*;
pub use count::*;
pub use max::*;
@@ -36,9 +32,6 @@ use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
pub use stats::*;
pub use sum::*;
pub use top_hits::*;
use crate::schema::OwnedValue;
/// Single-metric aggregations use this common result structure.
///
@@ -88,28 +81,6 @@ pub struct PercentilesMetricResult {
pub values: PercentileValues,
}
/// The top_hits metric results entry
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct TopHitsVecEntry {
/// The sort values of the document, depending on the sort criteria in the request.
pub sort: Vec<Option<u64>>,
/// Search results, for queries that include field retrieval requests
/// (`docvalue_fields`).
#[serde(rename = "docvalue_fields")]
#[serde(skip_serializing_if = "HashMap::is_empty")]
pub doc_value_fields: HashMap<String, OwnedValue>,
}
/// The top_hits metric aggregation results a list of top hits by sort criteria.
///
/// The main reason for wrapping it in `hits` is to match elasticsearch output structure.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct TopHitsMetricResult {
/// The result of the top_hits metric.
pub hits: Vec<TopHitsVecEntry>,
}
#[cfg(test)]
mod tests {
use crate::aggregation::agg_req::Aggregations;

View File

@@ -1,5 +1,6 @@
use std::fmt::Debug;
use columnar::ColumnType;
use serde::{Deserialize, Serialize};
use super::*;
@@ -10,7 +11,7 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::aggregation::{f64_from_fastfield_u64, f64_to_fastfield_u64, AggregationError};
use crate::{DocId, TantivyError};
/// # Percentiles
@@ -83,11 +84,7 @@ pub struct PercentilesAggregationReq {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(
skip_serializing_if = "Option::is_none",
default,
deserialize_with = "deserialize_option_f64"
)]
#[serde(skip_serializing_if = "Option::is_none", default)]
pub missing: Option<f64>,
}
fn default_percentiles() -> &'static [f64] {
@@ -136,6 +133,7 @@ pub(crate) struct SegmentPercentilesCollector {
field_type: ColumnType,
pub(crate) percentiles: PercentilesCollector,
pub(crate) accessor_idx: usize,
val_cache: Vec<u64>,
missing: Option<u64>,
}
@@ -245,6 +243,7 @@ impl SegmentPercentilesCollector {
field_type,
percentiles: PercentilesCollector::new(),
accessor_idx,
val_cache: Default::default(),
missing,
})
}

View File

@@ -1,3 +1,4 @@
use columnar::ColumnType;
use serde::{Deserialize, Serialize};
use super::*;
@@ -8,7 +9,7 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::aggregation::{f64_from_fastfield_u64, f64_to_fastfield_u64};
use crate::{DocId, TantivyError};
/// A multi-value metric aggregation that computes a collection of statistics on numeric values that
@@ -32,7 +33,7 @@ pub struct StatsAggregation {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default, deserialize_with = "deserialize_option_f64")]
#[serde(default)]
pub missing: Option<f64>,
}
@@ -579,30 +580,6 @@ mod tests {
})
);
// From string
let agg_req: Aggregations = serde_json::from_value(json!({
"my_stats": {
"stats": {
"field": "json.partially_empty",
"missing": "0.0"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(
res["my_stats"],
json!({
"avg": 2.5,
"count": 4,
"max": 10.0,
"min": 0.0,
"sum": 10.0
})
);
Ok(())
}

View File

@@ -2,8 +2,7 @@ use std::fmt::Debug;
use serde::{Deserialize, Serialize};
use super::*;
use crate::aggregation::*;
use super::{IntermediateStats, SegmentStatsCollector};
/// A single-value metric aggregation that sums up numeric values that are
/// extracted from the aggregated documents.
@@ -25,7 +24,7 @@ pub struct SumAggregation {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default, deserialize_with = "deserialize_option_f64")]
#[serde(default)]
pub missing: Option<f64>,
}

View File

@@ -1,897 +0,0 @@
use std::collections::HashMap;
use std::net::Ipv6Addr;
use columnar::{ColumnarReader, DynamicColumn};
use common::json_path_writer::JSON_PATH_SEGMENT_SEP_STR;
use common::DateTime;
use regex::Regex;
use serde::ser::SerializeMap;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
use super::{TopHitsMetricResult, TopHitsVecEntry};
use crate::aggregation::bucket::Order;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::AggregationError;
use crate::collector::TopNComputer;
use crate::schema::OwnedValue;
use crate::{DocAddress, DocId, SegmentOrdinal};
/// # Top Hits
///
/// The top hits aggregation is a useful tool to answer questions like:
/// - "What are the most recent posts by each author?"
/// - "What are the most popular items in each category?"
///
/// It does so by keeping track of the most relevant document being aggregated,
/// in terms of a sort criterion that can consist of multiple fields and their
/// sort-orders (ascending or descending).
///
/// `top_hits` should not be used as a top-level aggregation. It is intended to be
/// used as a sub-aggregation, inside a `terms` aggregation or a `filters` aggregation,
/// for example.
///
/// Note that this aggregator does not return the actual document addresses, but
/// rather a list of the values of the fields that were requested to be retrieved.
/// These values can be specified in the `docvalue_fields` parameter, which can include
/// a list of fast fields to be retrieved. At the moment, only fast fields are supported
/// but it is possible that we support the `fields` parameter to retrieve any stored
/// field in the future.
///
/// The following example demonstrates a request for the top_hits aggregation:
/// ```JSON
/// {
/// "aggs": {
/// "top_authors": {
/// "terms": {
/// "field": "author",
/// "size": 5
/// }
/// },
/// "aggs": {
/// "top_hits": {
/// "size": 2,
/// "from": 0
/// "sort": [
/// { "date": "desc" }
/// ]
/// "docvalue_fields": ["date", "title", "iden"]
/// }
/// }
/// }
/// ```
///
/// This request will return an object containing the top two documents, sorted
/// by the `date` field in descending order. You can also sort by multiple fields, which
/// helps to resolve ties. The aggregation object for each bucket will look like:
/// ```JSON
/// {
/// "hits": [
/// {
/// "score": [<time_u64>],
/// "docvalue_fields": {
/// "date": "<date_RFC3339>",
/// "title": "<title>",
/// "iden": "<iden>"
/// }
/// },
/// {
/// "score": [<time_u64>]
/// "docvalue_fields": {
/// "date": "<date_RFC3339>",
/// "title": "<title>",
/// "iden": "<iden>"
/// }
/// }
/// ]
/// }
/// ```
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct TopHitsAggregation {
sort: Vec<KeyOrder>,
size: usize,
from: Option<usize>,
#[serde(rename = "docvalue_fields")]
#[serde(default)]
doc_value_fields: Vec<String>,
// Not supported
_source: Option<serde_json::Value>,
fields: Option<serde_json::Value>,
script_fields: Option<serde_json::Value>,
highlight: Option<serde_json::Value>,
explain: Option<serde_json::Value>,
version: Option<serde_json::Value>,
}
#[derive(Debug, Clone, PartialEq, Default)]
struct KeyOrder {
field: String,
order: Order,
}
impl Serialize for KeyOrder {
fn serialize<S: Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
let KeyOrder { field, order } = self;
let mut map = serializer.serialize_map(Some(1))?;
map.serialize_entry(field, order)?;
map.end()
}
}
impl<'de> Deserialize<'de> for KeyOrder {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where D: Deserializer<'de> {
let mut key_order = <HashMap<String, Order>>::deserialize(deserializer)?.into_iter();
let (field, order) = key_order.next().ok_or(serde::de::Error::custom(
"Expected exactly one key-value pair in sort parameter of top_hits, found none",
))?;
if key_order.next().is_some() {
return Err(serde::de::Error::custom(format!(
"Expected exactly one key-value pair in sort parameter of top_hits, found {:?}",
key_order
)));
}
Ok(Self { field, order })
}
}
// Tranform a glob (`pattern*`, for example) into a regex::Regex (`^pattern.*$`)
fn globbed_string_to_regex(glob: &str) -> Result<Regex, crate::TantivyError> {
// Replace `*` glob with `.*` regex
let sanitized = format!("^{}$", regex::escape(glob).replace(r"\*", ".*"));
Regex::new(&sanitized.replace('*', ".*")).map_err(|e| {
crate::TantivyError::SchemaError(format!(
"Invalid regex '{}' in docvalue_fields: {}",
glob, e
))
})
}
fn use_doc_value_fields_err(parameter: &str) -> crate::Result<()> {
Err(crate::TantivyError::AggregationError(
AggregationError::InvalidRequest(format!(
"The `{}` parameter is not supported, only `docvalue_fields` is supported in \
`top_hits` aggregation",
parameter
)),
))
}
fn unsupported_err(parameter: &str) -> crate::Result<()> {
Err(crate::TantivyError::AggregationError(
AggregationError::InvalidRequest(format!(
"The `{}` parameter is not supported in the `top_hits` aggregation",
parameter
)),
))
}
impl TopHitsAggregation {
/// Validate and resolve field retrieval parameters
pub fn validate_and_resolve_field_names(
&mut self,
reader: &ColumnarReader,
) -> crate::Result<()> {
if self._source.is_some() {
use_doc_value_fields_err("_source")?;
}
if self.fields.is_some() {
use_doc_value_fields_err("fields")?;
}
if self.script_fields.is_some() {
use_doc_value_fields_err("script_fields")?;
}
if self.explain.is_some() {
unsupported_err("explain")?;
}
if self.highlight.is_some() {
unsupported_err("highlight")?;
}
if self.version.is_some() {
unsupported_err("version")?;
}
self.doc_value_fields = self
.doc_value_fields
.iter()
.map(|field| {
if !field.contains('*')
&& reader
.iter_columns()?
.any(|(name, _)| name.as_str() == field)
{
return Ok(vec![field.to_owned()]);
}
let pattern = globbed_string_to_regex(field)?;
let fields = reader
.iter_columns()?
.map(|(name, _)| {
// normalize path from internal fast field repr
name.replace(JSON_PATH_SEGMENT_SEP_STR, ".")
})
.filter(|name| pattern.is_match(name))
.collect::<Vec<_>>();
assert!(
!fields.is_empty(),
"No fields matched the glob '{}' in docvalue_fields",
field
);
Ok(fields)
})
.collect::<crate::Result<Vec<_>>>()?
.into_iter()
.flatten()
.collect();
Ok(())
}
/// Return fields accessed by the aggregator, in order.
pub fn field_names(&self) -> Vec<&str> {
self.sort
.iter()
.map(|KeyOrder { field, .. }| field.as_str())
.collect()
}
/// Return fields accessed by the aggregator's value retrieval.
pub fn value_field_names(&self) -> Vec<&str> {
self.doc_value_fields.iter().map(|s| s.as_str()).collect()
}
fn get_document_field_data(
&self,
accessors: &HashMap<String, Vec<DynamicColumn>>,
doc_id: DocId,
) -> HashMap<String, FastFieldValue> {
let doc_value_fields = self
.doc_value_fields
.iter()
.map(|field| {
let accessors = accessors
.get(field)
.unwrap_or_else(|| panic!("field '{}' not found in accessors", field));
let values: Vec<FastFieldValue> = accessors
.iter()
.flat_map(|accessor| match accessor {
DynamicColumn::U64(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::U64)
.collect::<Vec<_>>(),
DynamicColumn::I64(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::I64)
.collect::<Vec<_>>(),
DynamicColumn::F64(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::F64)
.collect::<Vec<_>>(),
DynamicColumn::Bytes(accessor) => accessor
.term_ords(doc_id)
.map(|term_ord| {
let mut buffer = vec![];
assert!(
accessor
.ord_to_bytes(term_ord, &mut buffer)
.expect("could not read term dictionary"),
"term corresponding to term_ord does not exist"
);
FastFieldValue::Bytes(buffer)
})
.collect::<Vec<_>>(),
DynamicColumn::Str(accessor) => accessor
.term_ords(doc_id)
.map(|term_ord| {
let mut buffer = vec![];
assert!(
accessor
.ord_to_bytes(term_ord, &mut buffer)
.expect("could not read term dictionary"),
"term corresponding to term_ord does not exist"
);
FastFieldValue::Str(String::from_utf8(buffer).unwrap())
})
.collect::<Vec<_>>(),
DynamicColumn::Bool(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::Bool)
.collect::<Vec<_>>(),
DynamicColumn::IpAddr(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::IpAddr)
.collect::<Vec<_>>(),
DynamicColumn::DateTime(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::Date)
.collect::<Vec<_>>(),
})
.collect();
(field.to_owned(), FastFieldValue::Array(values))
})
.collect();
doc_value_fields
}
}
/// A retrieved value from a fast field.
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum FastFieldValue {
/// The str type is used for any text information.
Str(String),
/// Unsigned 64-bits Integer `u64`
U64(u64),
/// Signed 64-bits Integer `i64`
I64(i64),
/// 64-bits Float `f64`
F64(f64),
/// Bool value
Bool(bool),
/// Date/time with nanoseconds precision
Date(DateTime),
/// Arbitrarily sized byte array
Bytes(Vec<u8>),
/// IpV6 Address. Internally there is no IpV4, it needs to be converted to `Ipv6Addr`.
IpAddr(Ipv6Addr),
/// A list of values.
Array(Vec<Self>),
}
impl From<FastFieldValue> for OwnedValue {
fn from(value: FastFieldValue) -> Self {
match value {
FastFieldValue::Str(s) => OwnedValue::Str(s),
FastFieldValue::U64(u) => OwnedValue::U64(u),
FastFieldValue::I64(i) => OwnedValue::I64(i),
FastFieldValue::F64(f) => OwnedValue::F64(f),
FastFieldValue::Bool(b) => OwnedValue::Bool(b),
FastFieldValue::Date(d) => OwnedValue::Date(d),
FastFieldValue::Bytes(b) => OwnedValue::Bytes(b),
FastFieldValue::IpAddr(ip) => OwnedValue::IpAddr(ip),
FastFieldValue::Array(a) => {
OwnedValue::Array(a.into_iter().map(OwnedValue::from).collect())
}
}
}
}
/// Holds a fast field value in its u64 representation, and the order in which it should be sorted.
#[derive(Clone, Serialize, Deserialize, Debug)]
struct DocValueAndOrder {
/// A fast field value in its u64 representation.
value: Option<u64>,
/// Sort order for the value
order: Order,
}
impl Ord for DocValueAndOrder {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
let invert = |cmp: std::cmp::Ordering| match self.order {
Order::Asc => cmp,
Order::Desc => cmp.reverse(),
};
match (self.value, other.value) {
(Some(self_value), Some(other_value)) => invert(self_value.cmp(&other_value)),
(Some(_), None) => std::cmp::Ordering::Greater,
(None, Some(_)) => std::cmp::Ordering::Less,
(None, None) => std::cmp::Ordering::Equal,
}
}
}
impl PartialOrd for DocValueAndOrder {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
}
}
impl PartialEq for DocValueAndOrder {
fn eq(&self, other: &Self) -> bool {
self.value.cmp(&other.value) == std::cmp::Ordering::Equal
}
}
impl Eq for DocValueAndOrder {}
#[derive(Clone, Serialize, Deserialize, Debug)]
struct DocSortValuesAndFields {
sorts: Vec<DocValueAndOrder>,
#[serde(rename = "docvalue_fields")]
#[serde(skip_serializing_if = "HashMap::is_empty")]
doc_value_fields: HashMap<String, FastFieldValue>,
}
impl Ord for DocSortValuesAndFields {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
for (self_feature, other_feature) in self.sorts.iter().zip(other.sorts.iter()) {
let cmp = self_feature.cmp(other_feature);
if cmp != std::cmp::Ordering::Equal {
return cmp;
}
}
std::cmp::Ordering::Equal
}
}
impl PartialOrd for DocSortValuesAndFields {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
}
}
impl PartialEq for DocSortValuesAndFields {
fn eq(&self, other: &Self) -> bool {
self.cmp(other) == std::cmp::Ordering::Equal
}
}
impl Eq for DocSortValuesAndFields {}
/// The TopHitsCollector used for collecting over segments and merging results.
#[derive(Clone, Serialize, Deserialize, Debug)]
pub struct TopHitsTopNComputer {
req: TopHitsAggregation,
top_n: TopNComputer<DocSortValuesAndFields, DocAddress, false>,
}
impl std::cmp::PartialEq for TopHitsTopNComputer {
fn eq(&self, _other: &Self) -> bool {
false
}
}
impl TopHitsTopNComputer {
/// Create a new TopHitsCollector
pub fn new(req: TopHitsAggregation) -> Self {
Self {
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
req,
}
}
fn collect(&mut self, features: DocSortValuesAndFields, doc: DocAddress) {
self.top_n.push(features, doc);
}
pub(crate) fn merge_fruits(&mut self, other_fruit: Self) -> crate::Result<()> {
for doc in other_fruit.top_n.into_vec() {
self.collect(doc.feature, doc.doc);
}
Ok(())
}
/// Finalize by converting self into the final result form
pub fn into_final_result(self) -> TopHitsMetricResult {
let mut hits: Vec<TopHitsVecEntry> = self
.top_n
.into_sorted_vec()
.into_iter()
.map(|doc| TopHitsVecEntry {
sort: doc.feature.sorts.iter().map(|f| f.value).collect(),
doc_value_fields: doc
.feature
.doc_value_fields
.into_iter()
.map(|(k, v)| (k, v.into()))
.collect(),
})
.collect();
// Remove the first `from` elements
// Truncating from end would be more efficient, but we need to truncate from the front
// because `into_sorted_vec` gives us a descending order because of the inverted
// `Ord` semantics of the heap elements.
hits.drain(..self.req.from.unwrap_or(0));
TopHitsMetricResult { hits }
}
}
#[derive(Clone, Debug)]
pub(crate) struct TopHitsSegmentCollector {
segment_ordinal: SegmentOrdinal,
accessor_idx: usize,
req: TopHitsAggregation,
top_n: TopNComputer<Vec<DocValueAndOrder>, DocAddress, false>,
}
impl TopHitsSegmentCollector {
pub fn from_req(
req: &TopHitsAggregation,
accessor_idx: usize,
segment_ordinal: SegmentOrdinal,
) -> Self {
Self {
req: req.clone(),
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
segment_ordinal,
accessor_idx,
}
}
fn into_top_hits_collector(
self,
value_accessors: &HashMap<String, Vec<DynamicColumn>>,
) -> TopHitsTopNComputer {
let mut top_hits_computer = TopHitsTopNComputer::new(self.req.clone());
let top_results = self.top_n.into_vec();
for res in top_results {
let doc_value_fields = self
.req
.get_document_field_data(value_accessors, res.doc.doc_id);
top_hits_computer.collect(
DocSortValuesAndFields {
sorts: res.feature,
doc_value_fields,
},
res.doc,
);
}
top_hits_computer
}
}
impl SegmentAggregationCollector for TopHitsSegmentCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_with_accessor: &crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let value_accessors = &agg_with_accessor.aggs.values[self.accessor_idx].value_accessors;
let intermediate_result =
IntermediateMetricResult::TopHits(self.into_top_hits_collector(value_accessors));
results.push(
name,
IntermediateAggregationResult::Metric(intermediate_result),
)
}
fn collect(
&mut self,
doc_id: crate::DocId,
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
let sorts: Vec<DocValueAndOrder> = self
.req
.sort
.iter()
.enumerate()
.map(|(idx, KeyOrder { order, .. })| {
let order = *order;
let value = accessors
.get(idx)
.expect("could not find field in accessors")
.0
.values_for_doc(doc_id)
.next();
DocValueAndOrder { value, order }
})
.collect();
self.top_n.push(
sorts,
DocAddress {
segment_ord: self.segment_ordinal,
doc_id,
},
);
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
// TODO: Consider getting fields with the column block accessor.
for doc in docs {
self.collect(*doc, agg_with_accessor)?;
}
Ok(())
}
}
#[cfg(test)]
mod tests {
use common::DateTime;
use pretty_assertions::assert_eq;
use serde_json::Value;
use time::macros::datetime;
use super::{DocSortValuesAndFields, DocValueAndOrder, Order};
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::bucket::tests::get_test_index_from_docs;
use crate::aggregation::tests::get_test_index_from_values;
use crate::aggregation::AggregationCollector;
use crate::collector::ComparableDoc;
use crate::query::AllQuery;
use crate::schema::OwnedValue;
fn invert_order(cmp_feature: DocValueAndOrder) -> DocValueAndOrder {
let DocValueAndOrder { value, order } = cmp_feature;
let order = match order {
Order::Asc => Order::Desc,
Order::Desc => Order::Asc,
};
DocValueAndOrder { value, order }
}
fn collector_with_capacity(capacity: usize) -> super::TopHitsTopNComputer {
super::TopHitsTopNComputer {
top_n: super::TopNComputer::new(capacity),
req: Default::default(),
}
}
fn invert_order_features(mut cmp_features: DocSortValuesAndFields) -> DocSortValuesAndFields {
cmp_features.sorts = cmp_features
.sorts
.into_iter()
.map(invert_order)
.collect::<Vec<_>>();
cmp_features
}
#[test]
fn test_comparable_doc_feature() -> crate::Result<()> {
let small = DocValueAndOrder {
value: Some(1),
order: Order::Asc,
};
let big = DocValueAndOrder {
value: Some(2),
order: Order::Asc,
};
let none = DocValueAndOrder {
value: None,
order: Order::Asc,
};
assert!(small < big);
assert!(none < small);
assert!(none < big);
let small = invert_order(small);
let big = invert_order(big);
let none = invert_order(none);
assert!(small > big);
assert!(none < small);
assert!(none < big);
Ok(())
}
#[test]
fn test_comparable_doc_features() -> crate::Result<()> {
let features_1 = DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
value: Some(1),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
};
let features_2 = DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
value: Some(2),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
};
assert!(features_1 < features_2);
assert!(invert_order_features(features_1.clone()) > invert_order_features(features_2));
Ok(())
}
#[test]
fn test_aggregation_top_hits_empty_index() -> crate::Result<()> {
let values = vec![];
let index = get_test_index_from_values(false, &values)?;
let d: Aggregations = serde_json::from_value(json!({
"top_hits_req": {
"top_hits": {
"size": 2,
"sort": [
{ "date": "desc" }
],
"from": 0,
}
}
}))
.unwrap();
let collector = AggregationCollector::from_aggs(d, Default::default());
let reader = index.reader()?;
let searcher = reader.searcher();
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let res: Value = serde_json::from_str(
&serde_json::to_string(&agg_res).expect("JSON serialization failed"),
)
.expect("JSON parsing failed");
assert_eq!(
res,
json!({
"top_hits_req": {
"hits": []
}
})
);
Ok(())
}
#[test]
fn test_top_hits_collector_single_feature() -> crate::Result<()> {
let docs = vec![
ComparableDoc::<_, _, false> {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 0,
},
feature: DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
value: Some(1),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
},
},
ComparableDoc {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 2,
},
feature: DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
value: Some(3),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
},
},
ComparableDoc {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 1,
},
feature: DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
value: Some(5),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
},
},
];
let mut collector = collector_with_capacity(3);
for doc in docs.clone() {
collector.collect(doc.feature, doc.doc);
}
let res = collector.into_final_result();
assert_eq!(
res,
super::TopHitsMetricResult {
hits: vec![
super::TopHitsVecEntry {
sort: vec![docs[0].feature.sorts[0].value],
doc_value_fields: Default::default(),
},
super::TopHitsVecEntry {
sort: vec![docs[1].feature.sorts[0].value],
doc_value_fields: Default::default(),
},
super::TopHitsVecEntry {
sort: vec![docs[2].feature.sorts[0].value],
doc_value_fields: Default::default(),
},
]
}
);
Ok(())
}
fn test_aggregation_top_hits(merge_segments: bool) -> crate::Result<()> {
let docs = vec![
vec![
r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb", "text2": "bbb", "mixed": { "dyn_arr": [1, "2"] } }"#,
r#"{ "date": "2017-06-15T00:00:00Z", "text": "ccc", "text2": "ddd", "mixed": { "dyn_arr": [3, "4"] } }"#,
],
vec![
r#"{ "text": "aaa", "text2": "bbb", "date": "2018-01-02T00:00:00Z", "mixed": { "dyn_arr": ["9", 8] } }"#,
r#"{ "text": "aaa", "text2": "bbb", "date": "2016-01-02T00:00:00Z", "mixed": { "dyn_arr": ["7", 6] } }"#,
],
];
let index = get_test_index_from_docs(merge_segments, &docs)?;
let d: Aggregations = serde_json::from_value(json!({
"top_hits_req": {
"top_hits": {
"size": 2,
"sort": [
{ "date": "desc" }
],
"from": 1,
"docvalue_fields": [
"date",
"tex*",
"mixed.*",
],
}
}
}))?;
let collector = AggregationCollector::from_aggs(d, Default::default());
let reader = index.reader()?;
let searcher = reader.searcher();
let agg_res =
serde_json::to_value(searcher.search(&AllQuery, &collector).unwrap()).unwrap();
let date_2017 = datetime!(2017-06-15 00:00:00 UTC);
let date_2016 = datetime!(2016-01-02 00:00:00 UTC);
assert_eq!(
agg_res["top_hits_req"],
json!({
"hits": [
{
"sort": [common::i64_to_u64(date_2017.unix_timestamp_nanos() as i64)],
"docvalue_fields": {
"date": [ OwnedValue::Date(DateTime::from_utc(date_2017)) ],
"text": [ "ccc" ],
"text2": [ "ddd" ],
"mixed.dyn_arr": [ 3, "4" ],
}
},
{
"sort": [common::i64_to_u64(date_2016.unix_timestamp_nanos() as i64)],
"docvalue_fields": {
"date": [ OwnedValue::Date(DateTime::from_utc(date_2016)) ],
"text": [ "aaa" ],
"text2": [ "bbb" ],
"mixed.dyn_arr": [ 6, "7" ],
}
}
]
}),
);
Ok(())
}
#[test]
fn test_aggregation_top_hits_single_segment() -> crate::Result<()> {
test_aggregation_top_hits(true)
}
#[test]
fn test_aggregation_top_hits_multi_segment() -> crate::Result<()> {
test_aggregation_top_hits(false)
}
}

View File

@@ -145,8 +145,6 @@ mod agg_tests;
mod agg_bench;
use core::fmt;
pub use agg_limits::AggregationLimits;
pub use collector::{
AggregationCollector, AggregationSegmentCollector, DistributedAggregationCollector,
@@ -156,106 +154,7 @@ use columnar::{ColumnType, MonotonicallyMappableToU64};
pub(crate) use date::format_date;
pub use error::AggregationError;
use itertools::Itertools;
use serde::de::{self, Visitor};
use serde::{Deserialize, Deserializer, Serialize};
fn parse_str_into_f64<E: de::Error>(value: &str) -> Result<f64, E> {
let parsed = value.parse::<f64>().map_err(|_err| {
de::Error::custom(format!("Failed to parse f64 from string: {:?}", value))
})?;
// Check if the parsed value is NaN or infinity
if parsed.is_nan() || parsed.is_infinite() {
Err(de::Error::custom(format!(
"Value is not a valid f64 (NaN or Infinity): {:?}",
value
)))
} else {
Ok(parsed)
}
}
/// deserialize Option<f64> from string or float
pub(crate) fn deserialize_option_f64<'de, D>(deserializer: D) -> Result<Option<f64>, D::Error>
where D: Deserializer<'de> {
struct StringOrFloatVisitor;
impl<'de> Visitor<'de> for StringOrFloatVisitor {
type Value = Option<f64>;
fn expecting(&self, formatter: &mut fmt::Formatter) -> fmt::Result {
formatter.write_str("a string or a float")
}
fn visit_str<E>(self, value: &str) -> Result<Self::Value, E>
where E: de::Error {
parse_str_into_f64(value).map(Some)
}
fn visit_f64<E>(self, value: f64) -> Result<Self::Value, E>
where E: de::Error {
Ok(Some(value))
}
fn visit_i64<E>(self, value: i64) -> Result<Self::Value, E>
where E: de::Error {
Ok(Some(value as f64))
}
fn visit_u64<E>(self, value: u64) -> Result<Self::Value, E>
where E: de::Error {
Ok(Some(value as f64))
}
fn visit_none<E>(self) -> Result<Self::Value, E>
where E: de::Error {
Ok(None)
}
fn visit_unit<E>(self) -> Result<Self::Value, E>
where E: de::Error {
Ok(None)
}
}
deserializer.deserialize_any(StringOrFloatVisitor)
}
/// deserialize f64 from string or float
pub(crate) fn deserialize_f64<'de, D>(deserializer: D) -> Result<f64, D::Error>
where D: Deserializer<'de> {
struct StringOrFloatVisitor;
impl<'de> Visitor<'de> for StringOrFloatVisitor {
type Value = f64;
fn expecting(&self, formatter: &mut fmt::Formatter) -> fmt::Result {
formatter.write_str("a string or a float")
}
fn visit_str<E>(self, value: &str) -> Result<Self::Value, E>
where E: de::Error {
parse_str_into_f64(value)
}
fn visit_f64<E>(self, value: f64) -> Result<Self::Value, E>
where E: de::Error {
Ok(value)
}
fn visit_i64<E>(self, value: i64) -> Result<Self::Value, E>
where E: de::Error {
Ok(value as f64)
}
fn visit_u64<E>(self, value: u64) -> Result<Self::Value, E>
where E: de::Error {
Ok(value as f64)
}
}
deserializer.deserialize_any(StringOrFloatVisitor)
}
use serde::{Deserialize, Serialize};
/// Represents an associative array `(key => values)` in a very efficient manner.
#[derive(PartialEq, Serialize, Deserialize)]
@@ -382,7 +281,6 @@ pub(crate) fn f64_from_fastfield_u64(val: u64, field_type: &ColumnType) -> f64 {
ColumnType::U64 => val as f64,
ColumnType::I64 | ColumnType::DateTime => i64::from_u64(val) as f64,
ColumnType::F64 => f64::from_u64(val),
ColumnType::Bool => val as f64,
_ => {
panic!("unexpected type {field_type:?}. This should not happen")
}
@@ -403,7 +301,6 @@ pub(crate) fn f64_to_fastfield_u64(val: f64, field_type: &ColumnType) -> Option<
ColumnType::U64 => Some(val as u64),
ColumnType::I64 | ColumnType::DateTime => Some((val as i64).to_u64()),
ColumnType::F64 => Some(val.to_u64()),
ColumnType::Bool => Some(val as u64),
_ => None,
}
}
@@ -417,6 +314,7 @@ mod tests {
use time::OffsetDateTime;
use super::agg_req::Aggregations;
use super::segment_agg_result::AggregationLimits;
use super::*;
use crate::indexer::NoMergePolicy;
use crate::query::{AllQuery, TermQuery};

View File

@@ -16,7 +16,6 @@ use super::metric::{
SumAggregation,
};
use crate::aggregation::bucket::TermMissingAgg;
use crate::aggregation::metric::TopHitsSegmentCollector;
pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
fn add_intermediate_aggregation_result(
@@ -161,11 +160,6 @@ pub(crate) fn build_single_agg_segment_collector(
accessor_idx,
)?,
)),
TopHits(top_hits_req) => Ok(Box::new(TopHitsSegmentCollector::from_req(
top_hits_req,
accessor_idx,
req.segment_ordinal,
))),
}
}

View File

@@ -1,7 +1,7 @@
use std::cmp::Ordering;
use std::collections::{btree_map, BTreeMap, BTreeSet, BinaryHeap};
use std::io;
use std::ops::Bound;
use std::{io, u64, usize};
use crate::collector::{Collector, SegmentCollector};
use crate::fastfield::FacetReader;
@@ -410,7 +410,6 @@ impl SegmentCollector for FacetSegmentCollector {
/// Intermediary result of the `FacetCollector` that stores
/// the facet counts for all the segments.
#[derive(Default, Clone)]
pub struct FacetCounts {
facet_counts: BTreeMap<Facet, u64>,
}
@@ -494,7 +493,7 @@ mod tests {
use super::{FacetCollector, FacetCounts};
use crate::collector::facet_collector::compress_mapping;
use crate::collector::Count;
use crate::index::Index;
use crate::core::Index;
use crate::query::{AllQuery, QueryParser, TermQuery};
use crate::schema::{Facet, FacetOptions, IndexRecordOption, Schema, TantivyDocument};
use crate::{IndexWriter, Term};

View File

@@ -160,7 +160,7 @@ mod tests {
use super::{add_vecs, HistogramCollector, HistogramComputer};
use crate::schema::{Schema, FAST};
use crate::time::{Date, Month};
use crate::{query, DateTime, Index};
use crate::{doc, query, DateTime, Index};
#[test]
fn test_add_histograms_simple() {

View File

@@ -97,7 +97,6 @@ pub use self::multi_collector::{FruitHandle, MultiCollector, MultiFruit};
mod top_collector;
mod top_score_collector;
pub use self::top_collector::ComparableDoc;
pub use self::top_score_collector::{TopDocs, TopNComputer};
mod custom_score_top_collector;
@@ -274,10 +273,6 @@ pub trait SegmentCollector: 'static {
fn collect(&mut self, doc: DocId, score: Score);
/// The query pushes the scored document to the collector via this method.
/// This method is used when the collector does not require scoring.
///
/// See [`COLLECT_BLOCK_BUFFER_LEN`](crate::COLLECT_BLOCK_BUFFER_LEN) for the
/// buffer size passed to the collector.
fn collect_block(&mut self, docs: &[DocId]) {
for doc in docs {
self.collect(*doc, 0.0);

View File

@@ -52,16 +52,10 @@ impl<TCollector: Collector> Collector for CollectorWrapper<TCollector> {
impl SegmentCollector for Box<dyn BoxableSegmentCollector> {
type Fruit = Box<dyn Fruit>;
#[inline]
fn collect(&mut self, doc: u32, score: Score) {
self.as_mut().collect(doc, score);
}
#[inline]
fn collect_block(&mut self, docs: &[DocId]) {
self.as_mut().collect_block(docs);
}
fn harvest(self) -> Box<dyn Fruit> {
BoxableSegmentCollector::harvest_from_box(self)
}
@@ -69,11 +63,6 @@ impl SegmentCollector for Box<dyn BoxableSegmentCollector> {
pub trait BoxableSegmentCollector {
fn collect(&mut self, doc: u32, score: Score);
fn collect_block(&mut self, docs: &[DocId]) {
for &doc in docs {
self.collect(doc, 0.0);
}
}
fn harvest_from_box(self: Box<Self>) -> Box<dyn Fruit>;
}
@@ -82,14 +71,9 @@ pub struct SegmentCollectorWrapper<TSegmentCollector: SegmentCollector>(TSegment
impl<TSegmentCollector: SegmentCollector> BoxableSegmentCollector
for SegmentCollectorWrapper<TSegmentCollector>
{
#[inline]
fn collect(&mut self, doc: u32, score: Score) {
self.0.collect(doc, score);
}
#[inline]
fn collect_block(&mut self, docs: &[DocId]) {
self.0.collect_block(docs);
}
fn harvest_from_box(self: Box<Self>) -> Box<dyn Fruit> {
Box::new(self.0.harvest())

View File

@@ -1,11 +1,15 @@
use columnar::{BytesColumn, Column};
use super::*;
use crate::collector::{Count, FilterCollector, TopDocs};
use crate::core::SegmentReader;
use crate::query::{AllQuery, QueryParser};
use crate::schema::{Schema, FAST, TEXT};
use crate::time::format_description::well_known::Rfc3339;
use crate::time::OffsetDateTime;
use crate::{DateTime, DocAddress, Index, Searcher, TantivyDocument};
use crate::{
doc, DateTime, DocAddress, DocId, Index, Score, Searcher, SegmentOrdinal, TantivyDocument,
};
pub const TEST_COLLECTOR_WITH_SCORE: TestCollector = TestCollector {
compute_score: true,

View File

@@ -1,58 +1,47 @@
use std::cmp::Ordering;
use std::marker::PhantomData;
use serde::{Deserialize, Serialize};
use super::top_score_collector::TopNComputer;
use crate::{DocAddress, DocId, SegmentOrdinal, SegmentReader};
/// Contains a feature (field, score, etc.) of a document along with the document address.
///
/// It guarantees stable sorting: in case of a tie on the feature, the document
/// address is used.
/// It has a custom implementation of `PartialOrd` that reverses the order. This is because the
/// default Rust heap is a max heap, whereas a min heap is needed.
///
/// The REVERSE_ORDER generic parameter controls whether the by-feature order
/// should be reversed, which is useful for achieving for example largest-first
/// semantics without having to wrap the feature in a `Reverse`.
/// Additionally, it guarantees stable sorting: in case of a tie on the feature, the document
/// address is used.
///
/// WARNING: equality is not what you would expect here.
/// Two elements are equal if their feature is equal, and regardless of whether `doc`
/// is equal. This should be perfectly fine for this usage, but let's make sure this
/// struct is never public.
#[derive(Clone, Default, Serialize, Deserialize)]
pub struct ComparableDoc<T, D, const REVERSE_ORDER: bool = false> {
/// The feature of the document. In practice, this is
/// is any type that implements `PartialOrd`.
pub(crate) struct ComparableDoc<T, D> {
pub feature: T,
/// The document address. In practice, this is any
/// type that implements `PartialOrd`, and is guaranteed
/// to be unique for each document.
pub doc: D,
}
impl<T: std::fmt::Debug, D: std::fmt::Debug, const R: bool> std::fmt::Debug
for ComparableDoc<T, D, R>
{
impl<T: std::fmt::Debug, D: std::fmt::Debug> std::fmt::Debug for ComparableDoc<T, D> {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct(format!("ComparableDoc<_, _ {R}").as_str())
f.debug_struct("ComparableDoc")
.field("feature", &self.feature)
.field("doc", &self.doc)
.finish()
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> PartialOrd for ComparableDoc<T, D, R> {
impl<T: PartialOrd, D: PartialOrd> PartialOrd for ComparableDoc<T, D> {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
Some(self.cmp(other))
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> Ord for ComparableDoc<T, D, R> {
impl<T: PartialOrd, D: PartialOrd> Ord for ComparableDoc<T, D> {
#[inline]
fn cmp(&self, other: &Self) -> Ordering {
let by_feature = self
// Reversed to make BinaryHeap work as a min-heap
let by_feature = other
.feature
.partial_cmp(&other.feature)
.map(|ord| if R { ord.reverse() } else { ord })
.partial_cmp(&self.feature)
.unwrap_or(Ordering::Equal);
let lazy_by_doc_address = || self.doc.partial_cmp(&other.doc).unwrap_or(Ordering::Equal);
@@ -64,13 +53,13 @@ impl<T: PartialOrd, D: PartialOrd, const R: bool> Ord for ComparableDoc<T, D, R>
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> PartialEq for ComparableDoc<T, D, R> {
impl<T: PartialOrd, D: PartialOrd> PartialEq for ComparableDoc<T, D> {
fn eq(&self, other: &Self) -> bool {
self.cmp(other) == Ordering::Equal
}
}
impl<T: PartialOrd, D: PartialOrd, const R: bool> Eq for ComparableDoc<T, D, R> {}
impl<T: PartialOrd, D: PartialOrd> Eq for ComparableDoc<T, D> {}
pub(crate) struct TopCollector<T> {
pub limit: usize,
@@ -110,10 +99,10 @@ where T: PartialOrd + Clone
if self.limit == 0 {
return Ok(Vec::new());
}
let mut top_collector: TopNComputer<_, _> = TopNComputer::new(self.limit + self.offset);
let mut top_collector = TopNComputer::new(self.limit + self.offset);
for child_fruit in children {
for (feature, doc) in child_fruit {
top_collector.push(feature, doc);
top_collector.push(ComparableDoc { feature, doc });
}
}
@@ -154,8 +143,6 @@ where T: PartialOrd + Clone
/// The theoretical complexity for collecting the top `K` out of `n` documents
/// is `O(n + K)`.
pub(crate) struct TopSegmentCollector<T> {
/// We reverse the order of the feature in order to
/// have top-semantics instead of bottom semantics.
topn_computer: TopNComputer<T, DocId>,
segment_ord: u32,
}
@@ -193,7 +180,7 @@ impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
/// will compare the lowest scoring item with the given one and keep whichever is greater.
#[inline]
pub fn collect(&mut self, doc: DocId, feature: T) {
self.topn_computer.push(feature, doc);
self.topn_computer.push(ComparableDoc { feature, doc });
}
}

View File

@@ -3,8 +3,6 @@ use std::marker::PhantomData;
use std::sync::Arc;
use columnar::ColumnValues;
use serde::de::DeserializeOwned;
use serde::{Deserialize, Serialize};
use super::Collector;
use crate::collector::custom_score_top_collector::CustomScoreTopCollector;
@@ -311,7 +309,7 @@ impl TopDocs {
///
/// To comfortably work with `u64`s, `i64`s, `f64`s, or `date`s, please refer to
/// the [.order_by_fast_field(...)](TopDocs::order_by_fast_field) method.
pub fn order_by_u64_field(
fn order_by_u64_field(
self,
field: impl ToString,
order: Order,
@@ -665,7 +663,7 @@ impl Collector for TopDocs {
reader: &SegmentReader,
) -> crate::Result<<Self::Child as SegmentCollector>::Fruit> {
let heap_len = self.0.limit + self.0.offset;
let mut top_n: TopNComputer<_, _> = TopNComputer::new(heap_len);
let mut top_n = TopNComputer::new(heap_len);
if let Some(alive_bitset) = reader.alive_bitset() {
let mut threshold = Score::MIN;
@@ -674,13 +672,21 @@ impl Collector for TopDocs {
if alive_bitset.is_deleted(doc) {
return threshold;
}
top_n.push(score, doc);
let doc = ComparableDoc {
feature: score,
doc,
};
top_n.push(doc);
threshold = top_n.threshold.unwrap_or(Score::MIN);
threshold
})?;
} else {
weight.for_each_pruning(Score::MIN, reader, &mut |doc, score| {
top_n.push(score, doc);
let doc = ComparableDoc {
feature: score,
doc,
};
top_n.push(doc);
top_n.threshold.unwrap_or(Score::MIN)
})?;
}
@@ -719,78 +725,17 @@ impl SegmentCollector for TopScoreSegmentCollector {
/// Fast TopN Computation
///
/// Capacity of the vec is 2 * top_n.
/// The buffer is truncated to the top_n elements when it reaches the capacity of the Vec.
/// That means capacity has special meaning and should be carried over when cloning or serializing.
///
/// For TopN == 0, it will be relative expensive.
#[derive(Serialize, Deserialize)]
#[serde(from = "TopNComputerDeser<Score, D, REVERSE_ORDER>")]
pub struct TopNComputer<Score, D, const REVERSE_ORDER: bool = true> {
/// The buffer reverses sort order to get top-semantics instead of bottom-semantics
buffer: Vec<ComparableDoc<Score, D, REVERSE_ORDER>>,
pub struct TopNComputer<Score, DocId> {
buffer: Vec<ComparableDoc<Score, DocId>>,
top_n: usize,
pub(crate) threshold: Option<Score>,
}
impl<Score: std::fmt::Debug, D, const REVERSE_ORDER: bool> std::fmt::Debug
for TopNComputer<Score, D, REVERSE_ORDER>
{
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> std::fmt::Result {
f.debug_struct("TopNComputer")
.field("buffer_len", &self.buffer.len())
.field("top_n", &self.top_n)
.field("current_threshold", &self.threshold)
.finish()
}
}
// Intermediate struct for TopNComputer for deserialization, to keep vec capacity
#[derive(Deserialize)]
struct TopNComputerDeser<Score, D, const REVERSE_ORDER: bool> {
buffer: Vec<ComparableDoc<Score, D, REVERSE_ORDER>>,
top_n: usize,
threshold: Option<Score>,
}
// Custom clone to keep capacity
impl<Score: Clone, D: Clone, const REVERSE_ORDER: bool> Clone
for TopNComputer<Score, D, REVERSE_ORDER>
{
fn clone(&self) -> Self {
let mut buffer_clone = Vec::with_capacity(self.buffer.capacity());
buffer_clone.extend(self.buffer.iter().cloned());
TopNComputer {
buffer: buffer_clone,
top_n: self.top_n,
threshold: self.threshold.clone(),
}
}
}
impl<Score, D, const R: bool> From<TopNComputerDeser<Score, D, R>> for TopNComputer<Score, D, R> {
fn from(mut value: TopNComputerDeser<Score, D, R>) -> Self {
let expected_cap = value.top_n.max(1) * 2;
let current_cap = value.buffer.capacity();
if current_cap < expected_cap {
value.buffer.reserve_exact(expected_cap - current_cap);
} else {
value.buffer.shrink_to(expected_cap);
}
TopNComputer {
buffer: value.buffer,
top_n: value.top_n,
threshold: value.threshold,
}
}
}
impl<Score, D, const R: bool> TopNComputer<Score, D, R>
impl<Score, DocId> TopNComputer<Score, DocId>
where
Score: PartialOrd + Clone,
D: Serialize + DeserializeOwned + Ord + Clone,
DocId: Ord + Clone,
{
/// Create a new `TopNComputer`.
/// Internally it will allocate a buffer of size `2 * top_n`.
@@ -803,12 +748,10 @@ where
}
}
/// Push a new document to the top n.
/// If the document is below the current threshold, it will be ignored.
#[inline]
pub fn push(&mut self, feature: Score, doc: D) {
pub(crate) fn push(&mut self, doc: ComparableDoc<Score, DocId>) {
if let Some(last_median) = self.threshold.clone() {
if feature < last_median {
if doc.feature < last_median {
return;
}
}
@@ -823,7 +766,7 @@ where
let uninit = self.buffer.spare_capacity_mut();
// This cannot panic, because we truncate_median will at least remove one element, since
// the min capacity is 2.
uninit[0].write(ComparableDoc { doc, feature });
uninit[0].write(doc);
// This is safe because it would panic in the line above
unsafe {
self.buffer.set_len(self.buffer.len() + 1);
@@ -842,24 +785,13 @@ where
median_score
}
/// Returns the top n elements in sorted order.
pub fn into_sorted_vec(mut self) -> Vec<ComparableDoc<Score, D, R>> {
pub(crate) fn into_sorted_vec(mut self) -> Vec<ComparableDoc<Score, DocId>> {
if self.buffer.len() > self.top_n {
self.truncate_top_n();
}
self.buffer.sort_unstable();
self.buffer
}
/// Returns the top n elements in stored order.
/// Useful if you do not need the elements in sorted order,
/// for example when merging the results of multiple segments.
pub fn into_vec(mut self) -> Vec<ComparableDoc<Score, D, R>> {
if self.buffer.len() > self.top_n {
self.truncate_top_n();
}
self.buffer
}
}
#[cfg(test)]
@@ -893,44 +825,49 @@ mod tests {
crate::assert_nearly_equals!(result.0, expected.0);
}
}
#[test]
fn test_topn_computer_serde() {
let computer: TopNComputer<u32, u32> = TopNComputer::new(1);
let computer_ser = serde_json::to_string(&computer).unwrap();
let mut computer: TopNComputer<u32, u32> = serde_json::from_str(&computer_ser).unwrap();
computer.push(1u32, 5u32);
computer.push(1u32, 0u32);
computer.push(1u32, 7u32);
assert_eq!(
computer.into_sorted_vec(),
&[ComparableDoc {
feature: 1u32,
doc: 0u32,
},]
);
}
#[test]
fn test_empty_topn_computer() {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(0);
computer.push(1u32, 1u32);
computer.push(1u32, 2u32);
computer.push(1u32, 3u32);
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
computer.push(ComparableDoc {
feature: 1u32,
doc: 2u32,
});
computer.push(ComparableDoc {
feature: 1u32,
doc: 3u32,
});
assert!(computer.into_sorted_vec().is_empty());
}
#[test]
fn test_topn_computer() {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(2);
computer.push(1u32, 1u32);
computer.push(2u32, 2u32);
computer.push(3u32, 3u32);
computer.push(2u32, 4u32);
computer.push(1u32, 5u32);
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
computer.push(ComparableDoc {
feature: 2u32,
doc: 2u32,
});
computer.push(ComparableDoc {
feature: 3u32,
doc: 3u32,
});
computer.push(ComparableDoc {
feature: 2u32,
doc: 4u32,
});
computer.push(ComparableDoc {
feature: 1u32,
doc: 5u32,
});
assert_eq!(
computer.into_sorted_vec(),
&[
@@ -952,7 +889,10 @@ mod tests {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(top_n);
for _ in 0..1 + top_n * 2 {
computer.push(1u32, 1u32);
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
}
let _vals = computer.into_sorted_vec();
}

View File

@@ -6,23 +6,24 @@ use std::path::PathBuf;
use std::sync::Arc;
use super::segment::Segment;
use super::segment_reader::merge_field_meta_data;
use super::{FieldMetadata, IndexSettings};
use crate::core::{Executor, META_FILEPATH};
use super::IndexSettings;
use crate::core::single_segment_index_writer::SingleSegmentIndexWriter;
use crate::core::{
Executor, IndexMeta, SegmentId, SegmentMeta, SegmentMetaInventory, META_FILEPATH,
};
use crate::directory::error::OpenReadError;
#[cfg(feature = "mmap")]
use crate::directory::MmapDirectory;
use crate::directory::{Directory, ManagedDirectory, RamDirectory, INDEX_WRITER_LOCK};
use crate::error::{DataCorruption, TantivyError};
use crate::index::{IndexMeta, SegmentId, SegmentMeta, SegmentMetaInventory};
use crate::indexer::index_writer::{MAX_NUM_THREAD, MEMORY_BUDGET_NUM_BYTES_MIN};
use crate::indexer::segment_updater::save_metas;
use crate::indexer::{IndexWriter, SingleSegmentIndexWriter};
use crate::indexer::IndexWriter;
use crate::reader::{IndexReader, IndexReaderBuilder};
use crate::schema::document::Document;
use crate::schema::{Field, FieldType, Schema, Type};
use crate::schema::{Field, FieldType, Schema};
use crate::tokenizer::{TextAnalyzer, TokenizerManager};
use crate::SegmentReader;
use crate::{merge_field_meta_data, FieldMetadata, SegmentReader};
fn load_metas(
directory: &dyn Directory,
@@ -83,7 +84,7 @@ fn save_new_metas(
///
/// ```
/// use tantivy::schema::*;
/// use tantivy::{Index, IndexSettings};
/// use tantivy::{Index, IndexSettings, IndexSortByField, Order};
///
/// let mut schema_builder = Schema::builder();
/// let id_field = schema_builder.add_text_field("id", STRING);
@@ -96,7 +97,10 @@ fn save_new_metas(
///
/// let schema = schema_builder.build();
/// let settings = IndexSettings{
/// docstore_blocksize: 100_000,
/// sort_by_field: Some(IndexSortByField{
/// field: "number".to_string(),
/// order: Order::Asc
/// }),
/// ..Default::default()
/// };
/// let index = Index::builder().schema(schema).settings(settings).create_in_ram();
@@ -248,15 +252,6 @@ impl IndexBuilder {
sort_by_field.field
)));
}
let supported_field_types = [Type::I64, Type::U64, Type::F64, Type::Date];
let field_type = entry.field_type().value_type();
if !supported_field_types.contains(&field_type) {
return Err(TantivyError::InvalidArgument(format!(
"Unsupported field type in sort_by_field: {:?}. Supported field types: \
{:?} ",
field_type, supported_field_types,
)));
}
}
Ok(())
} else {
@@ -328,15 +323,6 @@ impl Index {
Ok(())
}
/// Custom thread pool by a outer thread pool.
pub fn set_shared_multithread_executor(
&mut self,
shared_thread_pool: Arc<Executor>,
) -> crate::Result<()> {
self.executor = shared_thread_pool.clone();
Ok(())
}
/// Replace the default single thread search executor pool
/// by a thread pool with as many threads as there are CPUs on the system.
pub fn set_default_multithread_executor(&mut self) -> crate::Result<()> {

View File

@@ -7,7 +7,7 @@ use std::sync::Arc;
use serde::{Deserialize, Serialize};
use super::SegmentComponent;
use crate::index::SegmentId;
use crate::core::SegmentId;
use crate::schema::Schema;
use crate::store::Compressor;
use crate::{Inventory, Opstamp, TrackedObject};
@@ -19,7 +19,7 @@ struct DeleteMeta {
}
#[derive(Clone, Default)]
pub(crate) struct SegmentMetaInventory {
pub struct SegmentMetaInventory {
inventory: Inventory<InnerSegmentMeta>,
}
@@ -288,10 +288,6 @@ impl Default for IndexSettings {
/// Presorting documents can greatly improve performance
/// in some scenarios, by applying top n
/// optimizations.
#[deprecated(
since = "0.22.0",
note = "We plan to remove index sorting in `0.23`. If you need index sorting, please comment on the related issue https://github.com/quickwit-oss/tantivy/issues/2352 and explain your use case."
)]
#[derive(Clone, Debug, Serialize, Deserialize, Eq, PartialEq)]
pub struct IndexSortByField {
/// The field to sort the documents by
@@ -412,7 +408,7 @@ impl fmt::Debug for IndexMeta {
mod tests {
use super::IndexMeta;
use crate::index::index_meta::UntrackedIndexMeta;
use crate::core::index_meta::UntrackedIndexMeta;
use crate::schema::{Schema, TEXT};
use crate::store::Compressor;
#[cfg(feature = "zstd-compression")]

View File

@@ -1,13 +1,12 @@
use std::io;
use common::json_path_writer::JSON_END_OF_PATH;
use common::BinarySerializable;
use fnv::FnvHashSet;
use crate::directory::FileSlice;
use crate::positions::PositionReader;
use crate::postings::{BlockSegmentPostings, SegmentPostings, TermInfo};
use crate::schema::{IndexRecordOption, Term, Type};
use crate::schema::{IndexRecordOption, Term, Type, JSON_END_OF_PATH};
use crate::termdict::TermDictionary;
/// The inverted index reader is in charge of accessing
@@ -267,9 +266,7 @@ impl InvertedIndexReader {
/// Warmup a block postings given a `Term`.
/// This method is for an advanced usage only.
///
/// returns a boolean, whether the term was found in the dictionary
pub async fn warm_postings(&self, term: &Term, with_positions: bool) -> io::Result<bool> {
pub async fn warm_postings(&self, term: &Term, with_positions: bool) -> io::Result<()> {
let term_info_opt: Option<TermInfo> = self.get_term_info_async(term).await?;
if let Some(term_info) = term_info_opt {
let postings = self
@@ -283,27 +280,23 @@ impl InvertedIndexReader {
} else {
postings.await?;
}
Ok(true)
} else {
Ok(false)
}
Ok(())
}
/// Warmup a block postings given a range of `Term`s.
/// This method is for an advanced usage only.
///
/// returns a boolean, whether a term matching the range was found in the dictionary
pub async fn warm_postings_range(
&self,
terms: impl std::ops::RangeBounds<Term>,
limit: Option<u64>,
with_positions: bool,
) -> io::Result<bool> {
) -> io::Result<()> {
let mut term_info = self.get_term_range_async(terms, limit).await?;
let Some(first_terminfo) = term_info.next() else {
// no key matches, nothing more to load
return Ok(false);
return Ok(());
};
let last_terminfo = term_info.last().unwrap_or_else(|| first_terminfo.clone());
@@ -323,7 +316,7 @@ impl InvertedIndexReader {
} else {
postings.await?;
}
Ok(true)
Ok(())
}
/// Warmup the block postings for all terms.

View File

@@ -1,10 +1,12 @@
use common::json_path_writer::JSON_PATH_SEGMENT_SEP;
use columnar::MonotonicallyMappableToU64;
use common::{replace_in_place, JsonPathWriter};
use rustc_hash::FxHashMap;
use crate::fastfield::FastValue;
use crate::postings::{IndexingContext, IndexingPosition, PostingsWriter};
use crate::schema::document::{ReferenceValue, ReferenceValueLeaf, Value};
use crate::schema::Type;
use crate::schema::term::JSON_PATH_SEGMENT_SEP;
use crate::schema::{Field, Type, DATE_TIME_PRECISION_INDEXED};
use crate::time::format_description::well_known::Rfc3339;
use crate::time::{OffsetDateTime, UtcOffset};
use crate::tokenizer::TextAnalyzer;
@@ -254,45 +256,71 @@ fn index_json_value<'a, V: Value<'a>>(
}
}
/// Tries to infer a JSON type from a string and append it to the term.
///
/// The term must be json + JSON path.
pub(crate) fn convert_to_fast_value_and_append_to_json_term(
mut term: Term,
// Tries to infer a JSON type from a string.
pub fn convert_to_fast_value_and_get_term(
json_term_writer: &mut JsonTermWriter,
phrase: &str,
) -> Option<Term> {
assert_eq!(
term.value()
.as_json_value_bytes()
.expect("expecting a Term with a json type and json path")
.as_serialized()
.len(),
0,
"JSON value bytes should be empty"
);
if let Ok(dt) = OffsetDateTime::parse(phrase, &Rfc3339) {
let dt_utc = dt.to_offset(UtcOffset::UTC);
term.append_type_and_fast_value(DateTime::from_utc(dt_utc));
return Some(term);
return Some(set_fastvalue_and_get_term(
json_term_writer,
DateTime::from_utc(dt_utc),
));
}
if let Ok(i64_val) = str::parse::<i64>(phrase) {
term.append_type_and_fast_value(i64_val);
return Some(term);
return Some(set_fastvalue_and_get_term(json_term_writer, i64_val));
}
if let Ok(u64_val) = str::parse::<u64>(phrase) {
term.append_type_and_fast_value(u64_val);
return Some(term);
return Some(set_fastvalue_and_get_term(json_term_writer, u64_val));
}
if let Ok(f64_val) = str::parse::<f64>(phrase) {
term.append_type_and_fast_value(f64_val);
return Some(term);
return Some(set_fastvalue_and_get_term(json_term_writer, f64_val));
}
if let Ok(bool_val) = str::parse::<bool>(phrase) {
term.append_type_and_fast_value(bool_val);
return Some(term);
return Some(set_fastvalue_and_get_term(json_term_writer, bool_val));
}
None
}
// helper function to generate a Term from a json fastvalue
pub(crate) fn set_fastvalue_and_get_term<T: FastValue>(
json_term_writer: &mut JsonTermWriter,
value: T,
) -> Term {
json_term_writer.set_fast_value(value);
json_term_writer.term().clone()
}
// helper function to generate a list of terms with their positions from a textual json value
pub(crate) fn set_string_and_get_terms(
json_term_writer: &mut JsonTermWriter,
value: &str,
text_analyzer: &mut TextAnalyzer,
) -> Vec<(usize, Term)> {
let mut positions_and_terms = Vec::<(usize, Term)>::new();
json_term_writer.close_path_and_set_type(Type::Str);
let term_num_bytes = json_term_writer.term_buffer.len_bytes();
let mut token_stream = text_analyzer.token_stream(value);
token_stream.process(&mut |token| {
json_term_writer
.term_buffer
.truncate_value_bytes(term_num_bytes);
json_term_writer
.term_buffer
.append_bytes(token.text.as_bytes());
positions_and_terms.push((token.position, json_term_writer.term().clone()));
});
positions_and_terms
}
/// Writes a value of a JSON field to a `Term`.
/// The Term format is as follows:
/// `[JSON_TYPE][JSON_PATH][JSON_END_OF_PATH][VALUE_BYTES]`
pub struct JsonTermWriter<'a> {
term_buffer: &'a mut Term,
path_stack: Vec<usize>,
expand_dots_enabled: bool,
}
/// Splits a json path supplied to the query parser in such a way that
/// `.` can be escaped.
@@ -349,48 +377,158 @@ pub(crate) fn encode_column_name(
path.into()
}
impl<'a> JsonTermWriter<'a> {
pub fn from_field_and_json_path(
field: Field,
json_path: &str,
expand_dots_enabled: bool,
term_buffer: &'a mut Term,
) -> Self {
term_buffer.set_field_and_type(field, Type::Json);
let mut json_term_writer = Self::wrap(term_buffer, expand_dots_enabled);
for segment in split_json_path(json_path) {
json_term_writer.push_path_segment(&segment);
}
json_term_writer
}
pub fn wrap(term_buffer: &'a mut Term, expand_dots_enabled: bool) -> Self {
term_buffer.clear_with_type(Type::Json);
let mut path_stack = Vec::with_capacity(10);
path_stack.push(0);
Self {
term_buffer,
path_stack,
expand_dots_enabled,
}
}
fn trim_to_end_of_path(&mut self) {
let end_of_path = *self.path_stack.last().unwrap();
self.term_buffer.truncate_value_bytes(end_of_path);
}
pub fn close_path_and_set_type(&mut self, typ: Type) {
self.trim_to_end_of_path();
self.term_buffer.set_json_path_end();
self.term_buffer.append_bytes(&[typ.to_code()]);
}
// TODO: Remove this function and use JsonPathWriter instead.
pub fn push_path_segment(&mut self, segment: &str) {
// the path stack should never be empty.
self.trim_to_end_of_path();
if self.path_stack.len() > 1 {
self.term_buffer.set_json_path_separator();
}
let appended_segment = self.term_buffer.append_bytes(segment.as_bytes());
if self.expand_dots_enabled {
// We need to replace `.` by JSON_PATH_SEGMENT_SEP.
replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, appended_segment);
}
self.term_buffer.add_json_path_separator();
self.path_stack.push(self.term_buffer.len_bytes());
}
pub fn pop_path_segment(&mut self) {
self.path_stack.pop();
assert!(!self.path_stack.is_empty());
self.trim_to_end_of_path();
}
/// Returns the json path of the term being currently built.
#[cfg(test)]
pub(crate) fn path(&self) -> &[u8] {
let end_of_path = self.path_stack.last().cloned().unwrap_or(1);
&self.term().serialized_value_bytes()[..end_of_path - 1]
}
pub(crate) fn set_fast_value<T: FastValue>(&mut self, val: T) {
self.close_path_and_set_type(T::to_type());
let value = if T::to_type() == Type::Date {
DateTime::from_u64(val.to_u64())
.truncate(DATE_TIME_PRECISION_INDEXED)
.to_u64()
} else {
val.to_u64()
};
self.term_buffer
.append_bytes(value.to_be_bytes().as_slice());
}
pub fn set_str(&mut self, text: &str) {
self.close_path_and_set_type(Type::Str);
self.term_buffer.append_bytes(text.as_bytes());
}
pub fn term(&self) -> &Term {
self.term_buffer
}
}
#[cfg(test)]
mod tests {
use super::split_json_path;
use crate::schema::Field;
use super::{split_json_path, JsonTermWriter};
use crate::schema::{Field, Type};
use crate::Term;
#[test]
fn test_json_writer() {
let field = Field::from_field_id(1);
let mut term = Term::from_field_json_path(field, "attributes.color", false);
term.append_type_and_str("red");
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("attributes");
json_writer.push_path_segment("color");
json_writer.set_str("red");
assert_eq!(
format!("{:?}", term),
format!("{:?}", json_writer.term()),
"Term(field=1, type=Json, path=attributes.color, type=Str, \"red\")"
);
let mut term = Term::from_field_json_path(field, "attributes.dimensions.width", false);
term.append_type_and_fast_value(400i64);
json_writer.set_str("blue");
assert_eq!(
format!("{:?}", term),
format!("{:?}", json_writer.term()),
"Term(field=1, type=Json, path=attributes.color, type=Str, \"blue\")"
);
json_writer.pop_path_segment();
json_writer.push_path_segment("dimensions");
json_writer.push_path_segment("width");
json_writer.set_fast_value(400i64);
assert_eq!(
format!("{:?}", json_writer.term()),
"Term(field=1, type=Json, path=attributes.dimensions.width, type=I64, 400)"
);
json_writer.pop_path_segment();
json_writer.push_path_segment("height");
json_writer.set_fast_value(300i64);
assert_eq!(
format!("{:?}", json_writer.term()),
"Term(field=1, type=Json, path=attributes.dimensions.height, type=I64, 300)"
);
}
#[test]
fn test_string_term() {
let field = Field::from_field_id(1);
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_str("red");
assert_eq!(term.serialized_term(), b"\x00\x00\x00\x01jcolor\x00sred")
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
json_writer.set_str("red");
assert_eq!(
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jcolor\x00sred"
)
}
#[test]
fn test_i64_term() {
let field = Field::from_field_id(1);
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_fast_value(-4i64);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
json_writer.set_fast_value(-4i64);
assert_eq!(
term.serialized_term(),
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jcolor\x00i\x7f\xff\xff\xff\xff\xff\xff\xfc"
)
}
@@ -398,11 +536,12 @@ mod tests {
#[test]
fn test_u64_term() {
let field = Field::from_field_id(1);
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_fast_value(4u64);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
json_writer.set_fast_value(4u64);
assert_eq!(
term.serialized_term(),
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jcolor\x00u\x00\x00\x00\x00\x00\x00\x00\x04"
)
}
@@ -410,10 +549,12 @@ mod tests {
#[test]
fn test_f64_term() {
let field = Field::from_field_id(1);
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_fast_value(4.0f64);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
json_writer.set_fast_value(4.0f64);
assert_eq!(
term.serialized_term(),
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jcolor\x00f\xc0\x10\x00\x00\x00\x00\x00\x00"
)
}
@@ -421,14 +562,90 @@ mod tests {
#[test]
fn test_bool_term() {
let field = Field::from_field_id(1);
let mut term = Term::from_field_json_path(field, "color", false);
term.append_type_and_fast_value(true);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
json_writer.set_fast_value(true);
assert_eq!(
term.serialized_term(),
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jcolor\x00o\x00\x00\x00\x00\x00\x00\x00\x01"
)
}
#[test]
fn test_push_after_set_path_segment() {
let field = Field::from_field_id(1);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("attribute");
json_writer.set_str("something");
json_writer.push_path_segment("color");
json_writer.set_str("red");
assert_eq!(
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jattribute\x01color\x00sred"
)
}
#[test]
fn test_pop_segment() {
let field = Field::from_field_id(1);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
json_writer.push_path_segment("hue");
json_writer.pop_path_segment();
json_writer.set_str("red");
assert_eq!(
json_writer.term().serialized_term(),
b"\x00\x00\x00\x01jcolor\x00sred"
)
}
#[test]
fn test_json_writer_path() {
let field = Field::from_field_id(1);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color");
assert_eq!(json_writer.path(), b"color");
json_writer.push_path_segment("hue");
assert_eq!(json_writer.path(), b"color\x01hue");
json_writer.set_str("pink");
assert_eq!(json_writer.path(), b"color\x01hue");
}
#[test]
fn test_json_path_expand_dots_disabled() {
let field = Field::from_field_id(1);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, false);
json_writer.push_path_segment("color.hue");
assert_eq!(json_writer.path(), b"color.hue");
}
#[test]
fn test_json_path_expand_dots_enabled() {
let field = Field::from_field_id(1);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, true);
json_writer.push_path_segment("color.hue");
assert_eq!(json_writer.path(), b"color\x01hue");
}
#[test]
fn test_json_path_expand_dots_enabled_pop_segment() {
let field = Field::from_field_id(1);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_writer = JsonTermWriter::wrap(&mut term, true);
json_writer.push_path_segment("hello");
assert_eq!(json_writer.path(), b"hello");
json_writer.push_path_segment("color.hue");
assert_eq!(json_writer.path(), b"hello\x01color\x01hue");
json_writer.pop_path_segment();
assert_eq!(json_writer.path(), b"hello");
}
#[test]
fn test_split_json_path_simple() {
let json_path = split_json_path("titi.toto");

View File

@@ -1,14 +1,32 @@
mod executor;
pub mod index;
mod index_meta;
mod inverted_index_reader;
#[doc(hidden)]
pub mod json_utils;
pub mod searcher;
mod segment;
mod segment_component;
mod segment_id;
mod segment_reader;
mod single_segment_index_writer;
use std::path::Path;
use once_cell::sync::Lazy;
pub use self::executor::Executor;
pub use self::index::{Index, IndexBuilder};
pub use self::index_meta::{
IndexMeta, IndexSettings, IndexSortByField, Order, SegmentMeta, SegmentMetaInventory,
};
pub use self::inverted_index_reader::InvertedIndexReader;
pub use self::searcher::{Searcher, SearcherGeneration};
pub use self::segment::Segment;
pub use self::segment_component::SegmentComponent;
pub use self::segment_id::SegmentId;
pub use self::segment_reader::{merge_field_meta_data, FieldMetadata, SegmentReader};
pub use self::single_segment_index_writer::SingleSegmentIndexWriter;
/// The meta file contains all the information about the list of segments and the schema
/// of the index.

View File

@@ -1,10 +1,11 @@
use std::collections::BTreeMap;
#[cfg(feature = "quickwit")]
use std::future::Future;
use std::sync::Arc;
use std::{fmt, io};
use crate::collector::Collector;
use crate::core::Executor;
use crate::index::SegmentReader;
use crate::core::{Executor, SegmentReader};
use crate::query::{Bm25StatisticsProvider, EnableScoring, Query};
use crate::schema::document::DocumentDeserialize;
use crate::schema::{Schema, Term};
@@ -113,6 +114,108 @@ impl Searcher {
store_reader.get_async(doc_address.doc_id).await
}
/// Fetches multiple documents in an asynchronous manner.
///
/// This method is more efficient than calling [`doc_async`](Self::doc_async) multiple times,
/// as it groups overlapping requests to segments and blocks and avoids concurrent requests
/// trashing the caches of each other. However, it does so using intermediate data structures
/// and independent block caches so it will be slower if documents from very few blocks are
/// fetched which would have fit into the global block cache.
///
/// The caller is expected to poll these futures concurrently (e.g. using `FuturesUnordered`)
/// or in parallel (e.g. using `JoinSet`) as fits best with the given use case, i.e. whether
/// it is predominately I/O-bound or rather CPU-bound.
///
/// Note that any blocks brought into any of the per-segment-and-block groups will not be pulled
/// into the global block cache and hence not be available for subsequent calls.
///
/// Note that there is no synchronous variant of this method as the same degree of efficiency
/// can be had by accessing documents in address order.
///
/// # Example
///
/// ```rust,no_run
/// # use futures::executor::block_on;
/// # use futures::stream::{FuturesUnordered, StreamExt};
/// #
/// # use tantivy::schema::Schema;
/// # use tantivy::{DocAddress, Index, TantivyDocument, TantivyError};
/// #
/// # let index = Index::create_in_ram(Schema::builder().build());
/// # let searcher = index.reader()?.searcher();
/// #
/// # let doc_addresses = (0..10).map(|_| DocAddress::new(0, 0));
/// #
/// let mut groups: FuturesUnordered<_> = searcher
/// .docs_async::<TantivyDocument>(doc_addresses)?
/// .collect();
///
/// let mut docs = Vec::new();
///
/// block_on(async {
/// while let Some(group) = groups.next().await {
/// docs.extend(group?);
/// }
///
/// Ok::<_, TantivyError>(())
/// })?;
/// #
/// # Ok::<_, TantivyError>(())
/// ```
#[cfg(feature = "quickwit")]
pub fn docs_async<D: DocumentDeserialize>(
&self,
doc_addresses: impl IntoIterator<Item = DocAddress>,
) -> crate::Result<
impl Iterator<Item = impl Future<Output = crate::Result<Vec<(DocAddress, D)>>>> + '_,
> {
use rustc_hash::FxHashMap;
use crate::store::CacheKey;
use crate::{DocId, SegmentOrdinal};
let mut groups: FxHashMap<(SegmentOrdinal, CacheKey), Vec<DocId>> = Default::default();
for doc_address in doc_addresses {
let store_reader = &self.inner.store_readers[doc_address.segment_ord as usize];
let cache_key = store_reader.cache_key(doc_address.doc_id)?;
groups
.entry((doc_address.segment_ord, cache_key))
.or_default()
.push(doc_address.doc_id);
}
let futures = groups
.into_iter()
.map(|((segment_ord, cache_key), doc_ids)| {
// Each group fetches documents from exactly one block and
// therefore gets an independent block cache of size one.
let store_reader =
self.inner.store_readers[segment_ord as usize].fork_cache(1, &[cache_key]);
async move {
let mut docs = Vec::new();
for doc_id in doc_ids {
let doc = store_reader.get_async(doc_id).await?;
docs.push((
DocAddress {
segment_ord,
doc_id,
},
doc,
));
}
Ok(docs)
}
});
Ok(futures)
}
/// Access the schema associated with the index of this searcher.
pub fn schema(&self) -> &Schema {
&self.inner.schema

View File

@@ -2,9 +2,9 @@ use std::fmt;
use std::path::PathBuf;
use super::SegmentComponent;
use crate::core::{Index, SegmentId, SegmentMeta};
use crate::directory::error::{OpenReadError, OpenWriteError};
use crate::directory::{Directory, FileSlice, WritePtr};
use crate::index::{Index, SegmentId, SegmentMeta};
use crate::schema::Schema;
use crate::Opstamp;

View File

@@ -1,4 +1,4 @@
use std::cmp::Ordering;
use std::cmp::{Ord, Ordering};
use std::error::Error;
use std::fmt;
use std::str::FromStr;

View File

@@ -6,11 +6,11 @@ use std::{fmt, io};
use fnv::FnvHashMap;
use itertools::Itertools;
use crate::core::{InvertedIndexReader, Segment, SegmentComponent, SegmentId};
use crate::directory::{CompositeFile, FileSlice};
use crate::error::DataCorruption;
use crate::fastfield::{intersect_alive_bitsets, AliveBitSet, FacetReader, FastFieldReaders};
use crate::fieldnorm::{FieldNormReader, FieldNormReaders};
use crate::index::{InvertedIndexReader, Segment, SegmentComponent, SegmentId};
use crate::json_utils::json_path_sep_to_dot;
use crate::schema::{Field, IndexRecordOption, Schema, Type};
use crate::space_usage::SegmentSpaceUsage;
@@ -406,7 +406,7 @@ impl SegmentReader {
}
/// Returns an iterator that will iterate over the alive document ids
pub fn doc_ids_alive(&self) -> Box<dyn Iterator<Item = DocId> + Send + '_> {
pub fn doc_ids_alive(&self) -> Box<dyn Iterator<Item = DocId> + '_> {
if let Some(alive_bitset) = &self.alive_bitset_opt {
Box::new(alive_bitset.iter_alive())
} else {
@@ -515,9 +515,9 @@ impl fmt::Debug for SegmentReader {
#[cfg(test)]
mod test {
use super::*;
use crate::index::Index;
use crate::schema::{SchemaBuilder, Term, STORED, TEXT};
use crate::IndexWriter;
use crate::core::Index;
use crate::schema::{Schema, SchemaBuilder, Term, STORED, TEXT};
use crate::{DocId, FieldMetadata, IndexWriter};
#[test]
fn test_merge_field_meta_data_same() {

View File

@@ -1,8 +1,9 @@
use crate::collector::Count;
use crate::directory::{RamDirectory, WatchCallback};
use crate::indexer::{LogMergePolicy, NoMergePolicy};
use crate::json_utils::JsonTermWriter;
use crate::query::TermQuery;
use crate::schema::{Field, IndexRecordOption, Schema, INDEXED, STRING, TEXT};
use crate::schema::{Field, IndexRecordOption, Schema, Type, INDEXED, STRING, TEXT};
use crate::tokenizer::TokenizerManager;
use crate::{
Directory, DocSet, Index, IndexBuilder, IndexReader, IndexSettings, IndexWriter, Postings,
@@ -136,6 +137,7 @@ mod mmap_specific {
use tempfile::TempDir;
use super::*;
use crate::Directory;
#[test]
fn test_index_on_commit_reload_policy_mmap() -> crate::Result<()> {
@@ -415,12 +417,16 @@ fn test_non_text_json_term_freq() {
let searcher = reader.searcher();
let segment_reader = searcher.segment_reader(0u32);
let inv_idx = segment_reader.inverted_index(field).unwrap();
let mut term = Term::from_field_json_path(field, "tenant_id", false);
term.append_type_and_fast_value(75u64);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_term_writer = JsonTermWriter::wrap(&mut term, false);
json_term_writer.push_path_segment("tenant_id");
json_term_writer.close_path_and_set_type(Type::U64);
json_term_writer.set_fast_value(75u64);
let postings = inv_idx
.read_postings(&term, IndexRecordOption::WithFreqsAndPositions)
.read_postings(
json_term_writer.term(),
IndexRecordOption::WithFreqsAndPositions,
)
.unwrap()
.unwrap();
assert_eq!(postings.doc(), 0);
@@ -449,12 +455,16 @@ fn test_non_text_json_term_freq_bitpacked() {
let searcher = reader.searcher();
let segment_reader = searcher.segment_reader(0u32);
let inv_idx = segment_reader.inverted_index(field).unwrap();
let mut term = Term::from_field_json_path(field, "tenant_id", false);
term.append_type_and_fast_value(75u64);
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_term_writer = JsonTermWriter::wrap(&mut term, false);
json_term_writer.push_path_segment("tenant_id");
json_term_writer.close_path_and_set_type(Type::U64);
json_term_writer.set_fast_value(75u64);
let mut postings = inv_idx
.read_postings(&term, IndexRecordOption::WithFreqsAndPositions)
.read_postings(
json_term_writer.term(),
IndexRecordOption::WithFreqsAndPositions,
)
.unwrap()
.unwrap();
assert_eq!(postings.doc(), 0);
@@ -464,3 +474,60 @@ fn test_non_text_json_term_freq_bitpacked() {
assert_eq!(postings.term_freq(), 1u32);
}
}
#[cfg(feature = "quickwit")]
#[test]
fn test_get_many_docs() -> crate::Result<()> {
use futures::executor::block_on;
use futures::stream::{FuturesUnordered, StreamExt};
use crate::schema::{OwnedValue, STORED};
use crate::{DocAddress, TantivyError};
let mut schema_builder = Schema::builder();
let num_field = schema_builder.add_u64_field("num", STORED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests()?;
index_writer.set_merge_policy(Box::new(NoMergePolicy));
for i in 0..10u64 {
let doc = doc!(num_field=>i);
index_writer.add_document(doc)?;
}
index_writer.commit()?;
let segment_ids = index.searchable_segment_ids()?;
index_writer.merge(&segment_ids).wait().unwrap();
let searcher = index.reader()?.searcher();
assert_eq!(searcher.num_docs(), 10);
let doc_addresses = (0..10).map(|i| DocAddress::new(0, i));
let mut groups: FuturesUnordered<_> = searcher
.docs_async::<TantivyDocument>(doc_addresses)?
.collect();
let mut doc_nums = Vec::new();
block_on(async {
while let Some(group) = groups.next().await {
for (_doc_address, doc) in group? {
let num_value = doc.get_first(num_field).unwrap();
if let OwnedValue::U64(num) = num_value {
doc_nums.push(*num);
} else {
panic!("Expected u64 value");
}
}
}
Ok::<_, TantivyError>(())
})?;
doc_nums.sort();
assert_eq!(doc_nums, (0..10).collect::<Vec<u64>>());
Ok(())
}

View File

@@ -1,5 +1,6 @@
use std::collections::HashMap;
use std::io::{self, Read, Write};
use std::iter::ExactSizeIterator;
use std::ops::Range;
use common::{BinarySerializable, CountingWriter, HasLen, VInt};

View File

@@ -1,4 +1,5 @@
use std::io::Write;
use std::marker::{Send, Sync};
use std::path::{Path, PathBuf};
use std::sync::Arc;
use std::time::Duration;
@@ -39,7 +40,6 @@ impl RetryPolicy {
/// The `DirectoryLock` is an object that represents a file lock.
///
/// It is associated with a lock file, that gets deleted on `Drop.`
#[allow(dead_code)]
pub struct DirectoryLock(Box<dyn Send + Sync + 'static>);
struct DirectoryLockGuard {

View File

@@ -479,7 +479,6 @@ impl Directory for MmapDirectory {
let file: File = OpenOptions::new()
.write(true)
.create(true) //< if the file does not exist yet, create it.
.truncate(false)
.open(full_path)
.map_err(LockError::wrap_io_error)?;
if lock.is_blocking {
@@ -674,7 +673,7 @@ mod tests {
let num_segments = reader.searcher().segment_readers().len();
assert!(num_segments <= 4);
let num_components_except_deletes_and_tempstore =
crate::index::SegmentComponent::iterator().len() - 2;
crate::core::SegmentComponent::iterator().len() - 2;
let max_num_mmapped = num_components_except_deletes_and_tempstore * num_segments;
assert_eventually(|| {
let num_mmapped = mmap_directory.get_cache_info().mmapped.len();

View File

@@ -85,7 +85,7 @@ impl InnerDirectory {
self.fs
.get(path)
.ok_or_else(|| OpenReadError::FileDoesNotExist(PathBuf::from(path)))
.cloned()
.map(Clone::clone)
}
fn delete(&mut self, path: &Path) -> result::Result<(), DeleteError> {

View File

@@ -1,6 +1,6 @@
use std::io::Write;
use std::mem;
use std::path::Path;
use std::path::{Path, PathBuf};
use std::sync::atomic::Ordering::SeqCst;
use std::sync::atomic::{AtomicBool, AtomicUsize};
use std::sync::Arc;

View File

@@ -32,7 +32,6 @@ pub struct WatchCallbackList {
/// file change is detected.
#[must_use = "This `WatchHandle` controls the lifetime of the watch and should therefore be used."]
#[derive(Clone)]
#[allow(dead_code)]
pub struct WatchHandle(Arc<WatchCallback>);
impl WatchHandle {

View File

@@ -9,10 +9,7 @@ use crate::DocId;
/// to compare `[u32; 4]`.
pub const TERMINATED: DocId = i32::MAX as u32;
/// The collect_block method on `SegmentCollector` uses a buffer of this size.
/// Passed results to `collect_block` will not exceed this size and will be
/// exactly this size as long as we can fill the buffer.
pub const COLLECT_BLOCK_BUFFER_LEN: usize = 64;
pub const BUFFER_LEN: usize = 64;
/// Represents an iterable set of sorted doc ids.
pub trait DocSet: Send {
@@ -64,7 +61,7 @@ pub trait DocSet: Send {
/// This method is only here for specific high-performance
/// use case where batching. The normal way to
/// go through the `DocId`'s is to call `.advance()`.
fn fill_buffer(&mut self, buffer: &mut [DocId; COLLECT_BLOCK_BUFFER_LEN]) -> usize {
fn fill_buffer(&mut self, buffer: &mut [DocId; BUFFER_LEN]) -> usize {
if self.doc() == TERMINATED {
return 0;
}
@@ -154,7 +151,7 @@ impl<TDocSet: DocSet + ?Sized> DocSet for Box<TDocSet> {
unboxed.seek(target)
}
fn fill_buffer(&mut self, buffer: &mut [DocId; COLLECT_BLOCK_BUFFER_LEN]) -> usize {
fn fill_buffer(&mut self, buffer: &mut [DocId; BUFFER_LEN]) -> usize {
let unboxed: &mut TDocSet = self.borrow_mut();
unboxed.fill_buffer(buffer)
}

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