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0.20.2
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experiment
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8
.github/workflows/coverage.yml
vendored
8
.github/workflows/coverage.yml
vendored
@@ -3,8 +3,6 @@ name: Coverage
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
pull_request:
|
||||
branches: [main]
|
||||
|
||||
# Ensures that we cancel running jobs for the same PR / same workflow.
|
||||
concurrency:
|
||||
@@ -15,13 +13,13 @@ jobs:
|
||||
coverage:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install Rust
|
||||
run: rustup toolchain install nightly --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 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
|
||||
|
||||
2
.github/workflows/long_running.yml
vendored
2
.github/workflows/long_running.yml
vendored
@@ -19,7 +19,7 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install stable
|
||||
uses: actions-rs/toolchain@v1
|
||||
with:
|
||||
|
||||
13
.github/workflows/test.yml
vendored
13
.github/workflows/test.yml
vendored
@@ -20,7 +20,7 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install nightly
|
||||
uses: actions-rs/toolchain@v1
|
||||
@@ -39,6 +39,13 @@ jobs:
|
||||
|
||||
- name: Check Formatting
|
||||
run: cargo +nightly fmt --all -- --check
|
||||
|
||||
- name: Check Stable Compilation
|
||||
run: cargo build --all-features
|
||||
|
||||
|
||||
- name: Check Bench Compilation
|
||||
run: cargo +nightly bench --no-run --profile=dev --all-features
|
||||
|
||||
- uses: actions-rs/clippy-check@v1
|
||||
with:
|
||||
@@ -53,14 +60,14 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
features: [
|
||||
{ label: "all", flags: "mmap,stopwords,brotli-compression,lz4-compression,snappy-compression,zstd-compression,failpoints" },
|
||||
{ label: "all", flags: "mmap,stopwords,lz4-compression,zstd-compression,failpoints" },
|
||||
{ label: "quickwit", flags: "mmap,quickwit,failpoints" }
|
||||
]
|
||||
|
||||
name: test-${{ matrix.features.label}}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install stable
|
||||
uses: actions-rs/toolchain@v1
|
||||
|
||||
46
CHANGELOG.md
46
CHANGELOG.md
@@ -1,5 +1,47 @@
|
||||
Tantivy 0.21.1
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Range queries on fast fields with less values on that field than documents had an invalid end condition, leading to missing results. [#2226](https://github.com/quickwit-oss/tantivy/issues/2226)(@appaquet @PSeitz)
|
||||
- Increase the minimum memory budget from 3MB to 15MB to avoid single doc segments (API fix). [#2176](https://github.com/quickwit-oss/tantivy/issues/2176)(@PSeitz)
|
||||
|
||||
Tantivy 0.20 [Unreleased]
|
||||
Tantivy 0.21
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Fix track fast field memory consumption, which led to higher memory consumption than the budget allowed during indexing [#2148](https://github.com/quickwit-oss/tantivy/issues/2148)[#2147](https://github.com/quickwit-oss/tantivy/issues/2147)(@PSeitz)
|
||||
- Fix a regression from 0.20 where sort index by date wasn't working anymore [#2124](https://github.com/quickwit-oss/tantivy/issues/2124)(@PSeitz)
|
||||
- Fix getting the root facet on the `FacetCollector`. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086)(@adamreichold)
|
||||
- Align numerical type priority order of columnar and query. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088)(@fmassot)
|
||||
#### Breaking Changes
|
||||
- Remove support for Brotli and Snappy compression [#2123](https://github.com/quickwit-oss/tantivy/issues/2123)(@adamreichold)
|
||||
#### Features/Improvements
|
||||
- Implement lenient query parser [#2129](https://github.com/quickwit-oss/tantivy/pull/2129)(@trinity-1686a)
|
||||
- order_by_u64_field and order_by_fast_field allow sorting in ascending and descending order [#2111](https://github.com/quickwit-oss/tantivy/issues/2111)(@naveenann)
|
||||
- Allow dynamic filters in text analyzer builder [#2110](https://github.com/quickwit-oss/tantivy/issues/2110)(@fulmicoton @fmassot)
|
||||
- **Aggregation**
|
||||
- Add missing parameter for term aggregation [#2149](https://github.com/quickwit-oss/tantivy/issues/2149)[#2103](https://github.com/quickwit-oss/tantivy/issues/2103)(@PSeitz)
|
||||
- Add missing parameter for percentiles [#2157](https://github.com/quickwit-oss/tantivy/issues/2157)(@PSeitz)
|
||||
- Add missing parameter for stats,min,max,count,sum,avg [#2151](https://github.com/quickwit-oss/tantivy/issues/2151)(@PSeitz)
|
||||
- Improve aggregation deserialization error message [#2150](https://github.com/quickwit-oss/tantivy/issues/2150)(@PSeitz)
|
||||
- Add validation for type Bytes to term_agg [#2077](https://github.com/quickwit-oss/tantivy/issues/2077)(@PSeitz)
|
||||
- Alternative mixed field collection [#2135](https://github.com/quickwit-oss/tantivy/issues/2135)(@PSeitz)
|
||||
- Add missing query_terms impl for TermSetQuery. [#2120](https://github.com/quickwit-oss/tantivy/issues/2120)(@adamreichold)
|
||||
- Minor improvements to OwnedBytes [#2134](https://github.com/quickwit-oss/tantivy/issues/2134)(@adamreichold)
|
||||
- Remove allocations in split compound words [#2080](https://github.com/quickwit-oss/tantivy/issues/2080)(@PSeitz)
|
||||
- Ngram tokenizer now returns an error with invalid arguments [#2102](https://github.com/quickwit-oss/tantivy/issues/2102)(@fmassot)
|
||||
- Make TextAnalyzerBuilder public [#2097](https://github.com/quickwit-oss/tantivy/issues/2097)(@adamreichold)
|
||||
- Return an error when tokenizer is not found while indexing [#2093](https://github.com/quickwit-oss/tantivy/issues/2093)(@naveenann)
|
||||
- Delayed column opening during merge [#2132](https://github.com/quickwit-oss/tantivy/issues/2132)(@PSeitz)
|
||||
|
||||
Tantivy 0.20.2
|
||||
================================
|
||||
- Align numerical type priority order on the search side. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088) (@fmassot)
|
||||
- Fix is_child_of function not considering the root facet. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086) (@adamreichhold)
|
||||
|
||||
Tantivy 0.20.1
|
||||
================================
|
||||
- Fix building on windows with mmap [#2070](https://github.com/quickwit-oss/tantivy/issues/2070) (@ChillFish8)
|
||||
|
||||
Tantivy 0.20
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Fix phrase queries with slop (slop supports now transpositions, algorithm that carries slop so far for num terms > 2) [#2031](https://github.com/quickwit-oss/tantivy/issues/2031)[#2020](https://github.com/quickwit-oss/tantivy/issues/2020)(@PSeitz)
|
||||
@@ -38,12 +80,14 @@ Tantivy 0.20 [Unreleased]
|
||||
- Add aggregation support for JSON type [#1888](https://github.com/quickwit-oss/tantivy/issues/1888) (@PSeitz)
|
||||
- Mixed types support on JSON fields in aggs [#1971](https://github.com/quickwit-oss/tantivy/issues/1971) (@PSeitz)
|
||||
- Perf: Fetch blocks of vals in aggregation for all cardinality [#1950](https://github.com/quickwit-oss/tantivy/issues/1950) (@PSeitz)
|
||||
- Allow histogram bounds to be passed as Rfc3339 [#2076](https://github.com/quickwit-oss/tantivy/issues/2076) (@PSeitz)
|
||||
- `Searcher` with disabled scoring via `EnableScoring::Disabled` [#1780](https://github.com/quickwit-oss/tantivy/issues/1780) (@shikhar)
|
||||
- Enable tokenizer on json fields [#2053](https://github.com/quickwit-oss/tantivy/issues/2053) (@PSeitz)
|
||||
- Enforcing "NOT" and "-" queries consistency in UserInputAst [#1609](https://github.com/quickwit-oss/tantivy/issues/1609) (@bazhenov)
|
||||
- Faster indexing
|
||||
- Refactor tokenization pipeline to use GATs [#1924](https://github.com/quickwit-oss/tantivy/issues/1924) (@trinity-1686a)
|
||||
- Faster term hash map [#2058](https://github.com/quickwit-oss/tantivy/issues/2058)[#1940](https://github.com/quickwit-oss/tantivy/issues/1940) (@PSeitz)
|
||||
- tokenizer-api: reduce Tokenizer allocation overhead [#2062](https://github.com/quickwit-oss/tantivy/issues/2062) (@PSeitz)
|
||||
- Refactor vint [#2010](https://github.com/quickwit-oss/tantivy/issues/2010) (@PSeitz)
|
||||
- Faster search
|
||||
- Work in batches of docs on the SegmentCollector (Only for cases without score for now) [#1937](https://github.com/quickwit-oss/tantivy/issues/1937) (@PSeitz)
|
||||
|
||||
66
Cargo.toml
66
Cargo.toml
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy"
|
||||
version = "0.20.2"
|
||||
version = "0.22.0-dev"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
categories = ["database-implementations", "data-structures"]
|
||||
@@ -11,60 +11,57 @@ repository = "https://github.com/quickwit-oss/tantivy"
|
||||
readme = "README.md"
|
||||
keywords = ["search", "information", "retrieval"]
|
||||
edition = "2021"
|
||||
rust-version = "1.62"
|
||||
rust-version = "1.63"
|
||||
exclude = ["benches/*.json", "benches/*.txt"]
|
||||
|
||||
[dependencies]
|
||||
oneshot = "0.1.5"
|
||||
base64 = "0.21.0"
|
||||
base64 = "0.22.0"
|
||||
byteorder = "1.4.3"
|
||||
crc32fast = "1.3.2"
|
||||
once_cell = "1.10.0"
|
||||
regex = { version = "1.5.5", default-features = false, features = ["std", "unicode"] }
|
||||
aho-corasick = "1.0"
|
||||
tantivy-fst = "0.4.0"
|
||||
memmap2 = { version = "0.6.0", optional = true }
|
||||
lz4_flex = { version = "0.10", default-features = false, features = ["checked-decode"], optional = true }
|
||||
brotli = { version = "3.3.4", optional = true }
|
||||
zstd = { version = "0.12", optional = true, default-features = false }
|
||||
snap = { version = "1.0.5", optional = true }
|
||||
tantivy-fst = "0.5"
|
||||
memmap2 = { version = "0.9.0", optional = true }
|
||||
lz4_flex = { version = "0.11", default-features = false, optional = true }
|
||||
zstd = { version = "0.13", optional = true, default-features = false }
|
||||
tempfile = { version = "3.3.0", optional = true }
|
||||
log = "0.4.16"
|
||||
serde = { version = "1.0.136", features = ["derive"] }
|
||||
serde_json = "1.0.79"
|
||||
num_cpus = "1.13.1"
|
||||
fs4 = { version = "0.6.3", optional = true }
|
||||
fs4 = { version = "0.8.0", 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 = "0.8.4", default-features = false, features = ["bitpacker4x"] }
|
||||
census = "0.4.0"
|
||||
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker4x"] }
|
||||
census = "0.4.2"
|
||||
rustc-hash = "1.1.0"
|
||||
thiserror = "1.0.30"
|
||||
htmlescape = "0.3.1"
|
||||
fail = "0.5.0"
|
||||
murmurhash32 = "0.3.0"
|
||||
fail = { version = "0.5.0", optional = true }
|
||||
time = { version = "0.3.10", features = ["serde-well-known"] }
|
||||
smallvec = "1.8.0"
|
||||
rayon = "1.5.2"
|
||||
lru = "0.10.0"
|
||||
lru = "0.12.0"
|
||||
fastdivide = "0.4.0"
|
||||
itertools = "0.10.3"
|
||||
itertools = "0.12.0"
|
||||
measure_time = "0.8.2"
|
||||
async-trait = "0.1.53"
|
||||
arc-swap = "1.5.0"
|
||||
|
||||
columnar = { version= "0.1", path="./columnar", package ="tantivy-columnar" }
|
||||
sstable = { version= "0.1", path="./sstable", package ="tantivy-sstable", optional = true }
|
||||
stacker = { version= "0.1", path="./stacker", package ="tantivy-stacker" }
|
||||
query-grammar = { version= "0.20.0", path="./query-grammar", package = "tantivy-query-grammar" }
|
||||
tantivy-bitpacker = { version= "0.4", path="./bitpacker" }
|
||||
common = { version= "0.5", path = "./common/", package = "tantivy-common" }
|
||||
tokenizer-api = { version= "0.1", 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"
|
||||
|
||||
[target.'cfg(windows)'.dependencies]
|
||||
winapi = "0.3.9"
|
||||
@@ -75,14 +72,18 @@ maplit = "1.0.2"
|
||||
matches = "0.1.9"
|
||||
pretty_assertions = "1.2.1"
|
||||
proptest = "1.0.0"
|
||||
criterion = "0.5"
|
||||
test-log = "0.2.10"
|
||||
env_logger = "0.10.0"
|
||||
pprof = { git = "https://github.com/PSeitz/pprof-rs/", rev = "53af24b", features = ["flamegraph", "criterion"] } # temp fork that works with criterion 0.5
|
||||
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 }
|
||||
|
||||
[target.'cfg(not(windows))'.dev-dependencies]
|
||||
criterion = { version = "0.5", default-features = false }
|
||||
|
||||
[dev-dependencies.fail]
|
||||
version = "0.5.0"
|
||||
@@ -107,16 +108,19 @@ default = ["mmap", "stopwords", "lz4-compression"]
|
||||
mmap = ["fs4", "tempfile", "memmap2"]
|
||||
stopwords = []
|
||||
|
||||
brotli-compression = ["brotli"]
|
||||
lz4-compression = ["lz4_flex"]
|
||||
snappy-compression = ["snap"]
|
||||
zstd-compression = ["zstd"]
|
||||
|
||||
failpoints = ["fail/failpoints"]
|
||||
failpoints = ["fail", "fail/failpoints"]
|
||||
unstable = [] # useful for benches.
|
||||
|
||||
quickwit = ["sstable", "futures-util"]
|
||||
|
||||
# Compares only the hash of a string when indexing data.
|
||||
# Increases indexing speed, but may lead to extremely rare missing terms, when there's a hash collision.
|
||||
# Uses 64bit ahash.
|
||||
compare_hash_only = ["stacker/compare_hash_only"]
|
||||
|
||||
[workspace]
|
||||
members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sstable", "tokenizer-api", "columnar"]
|
||||
|
||||
@@ -130,7 +134,7 @@ members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sst
|
||||
[[test]]
|
||||
name = "failpoints"
|
||||
path = "tests/failpoints/mod.rs"
|
||||
required-features = ["fail/failpoints"]
|
||||
required-features = ["failpoints"]
|
||||
|
||||
[[bench]]
|
||||
name = "analyzer"
|
||||
|
||||
35
README.md
35
README.md
@@ -5,19 +5,18 @@
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](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** is a **full-text search engine library** written in Rust.
|
||||
## Fast full-text search engine library written in Rust
|
||||
|
||||
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.
|
||||
**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.
|
||||
|
||||
Tantivy is, in fact, strongly inspired by Lucene's design.
|
||||
|
||||
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
|
||||
## Benchmark
|
||||
|
||||
The following [benchmark](https://tantivy-search.github.io/bench/) breakdowns
|
||||
performance for different types of queries/collections.
|
||||
@@ -28,7 +27,7 @@ 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))
|
||||
@@ -44,7 +43,7 @@ Details about the benchmark can be found at this [repository](https://github.com
|
||||
- Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene)
|
||||
- `&[u8]` fast fields
|
||||
- Text, i64, u64, f64, dates, ip, bool, and hierarchical facet fields
|
||||
- Compressed document store (LZ4, Zstd, None, Brotli, Snap)
|
||||
- Compressed document store (LZ4, Zstd, None)
|
||||
- Range queries
|
||||
- Faceted search
|
||||
- Configurable indexing (optional term frequency and position indexing)
|
||||
@@ -54,11 +53,11 @@ 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.
|
||||
|
||||
@@ -68,7 +67,7 @@ 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.
|
||||
|
||||
@@ -79,16 +78,16 @@ 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:
|
||||
@@ -99,7 +98,7 @@ 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" />
|
||||
@@ -111,7 +110,7 @@ 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?
|
||||
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
use criterion::{criterion_group, criterion_main, Criterion};
|
||||
use tantivy::tokenizer::TokenizerManager;
|
||||
use tantivy::tokenizer::{
|
||||
LowerCaser, RemoveLongFilter, SimpleTokenizer, TextAnalyzer, TokenizerManager,
|
||||
};
|
||||
|
||||
const ALICE_TXT: &str = include_str!("alice.txt");
|
||||
|
||||
@@ -16,7 +18,26 @@ pub fn criterion_benchmark(c: &mut Criterion) {
|
||||
assert_eq!(word_count, 30_731);
|
||||
})
|
||||
});
|
||||
let mut dynamic_analyzer = TextAnalyzer::builder(SimpleTokenizer::default())
|
||||
.dynamic()
|
||||
.filter_dynamic(RemoveLongFilter::limit(40))
|
||||
.filter_dynamic(LowerCaser)
|
||||
.build();
|
||||
c.bench_function("dynamic-tokenize-alice", |b| {
|
||||
b.iter(|| {
|
||||
let mut word_count = 0;
|
||||
let mut token_stream = dynamic_analyzer.token_stream(ALICE_TXT);
|
||||
while token_stream.advance() {
|
||||
word_count += 1;
|
||||
}
|
||||
assert_eq!(word_count, 30_731);
|
||||
})
|
||||
});
|
||||
}
|
||||
|
||||
criterion_group!(benches, criterion_benchmark);
|
||||
criterion_group! {
|
||||
name = benches;
|
||||
config = Criterion::default().sample_size(200);
|
||||
targets = criterion_benchmark
|
||||
}
|
||||
criterion_main!(benches);
|
||||
|
||||
@@ -1,14 +1,99 @@
|
||||
use criterion::{criterion_group, criterion_main, Criterion, Throughput};
|
||||
use pprof::criterion::{Output, PProfProfiler};
|
||||
use tantivy::schema::{FAST, INDEXED, STORED, STRING, TEXT};
|
||||
use tantivy::Index;
|
||||
use criterion::{criterion_group, criterion_main, BatchSize, Bencher, Criterion, Throughput};
|
||||
use tantivy::schema::{TantivyDocument, FAST, INDEXED, STORED, STRING, TEXT};
|
||||
use tantivy::{tokenizer, Index, IndexWriter};
|
||||
|
||||
const HDFS_LOGS: &str = include_str!("hdfs.json");
|
||||
const GH_LOGS: &str = include_str!("gh.json");
|
||||
const WIKI: &str = include_str!("wiki.json");
|
||||
|
||||
fn get_lines(input: &str) -> Vec<&str> {
|
||||
input.trim().split('\n').collect()
|
||||
fn benchmark(
|
||||
b: &mut Bencher,
|
||||
input: &str,
|
||||
schema: tantivy::schema::Schema,
|
||||
commit: bool,
|
||||
parse_json: bool,
|
||||
is_dynamic: bool,
|
||||
) {
|
||||
if is_dynamic {
|
||||
benchmark_dynamic_json(b, input, schema, commit, parse_json)
|
||||
} else {
|
||||
_benchmark(b, input, schema, commit, parse_json, |schema, doc_json| {
|
||||
TantivyDocument::parse_json(&schema, doc_json).unwrap()
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
fn get_index(schema: tantivy::schema::Schema) -> Index {
|
||||
let mut index = Index::create_in_ram(schema.clone());
|
||||
let ff_tokenizer_manager = tokenizer::TokenizerManager::default();
|
||||
ff_tokenizer_manager.register(
|
||||
"raw",
|
||||
tokenizer::TextAnalyzer::builder(tokenizer::RawTokenizer::default())
|
||||
.filter(tokenizer::RemoveLongFilter::limit(255))
|
||||
.build(),
|
||||
);
|
||||
index.set_fast_field_tokenizers(ff_tokenizer_manager.clone());
|
||||
index
|
||||
}
|
||||
|
||||
fn _benchmark(
|
||||
b: &mut Bencher,
|
||||
input: &str,
|
||||
schema: tantivy::schema::Schema,
|
||||
commit: bool,
|
||||
include_json_parsing: bool,
|
||||
create_doc: impl Fn(&tantivy::schema::Schema, &str) -> TantivyDocument,
|
||||
) {
|
||||
if include_json_parsing {
|
||||
let lines: Vec<&str> = input.trim().split('\n').collect();
|
||||
b.iter(|| {
|
||||
let index = get_index(schema.clone());
|
||||
let mut index_writer: IndexWriter =
|
||||
index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = create_doc(&schema, doc_json);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
if commit {
|
||||
index_writer.commit().unwrap();
|
||||
}
|
||||
})
|
||||
} else {
|
||||
let docs: Vec<_> = input
|
||||
.trim()
|
||||
.split('\n')
|
||||
.map(|doc_json| create_doc(&schema, doc_json))
|
||||
.collect();
|
||||
b.iter_batched(
|
||||
|| docs.clone(),
|
||||
|docs| {
|
||||
let index = get_index(schema.clone());
|
||||
let mut index_writer: IndexWriter =
|
||||
index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc in docs {
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
if commit {
|
||||
index_writer.commit().unwrap();
|
||||
}
|
||||
},
|
||||
BatchSize::SmallInput,
|
||||
)
|
||||
}
|
||||
}
|
||||
fn benchmark_dynamic_json(
|
||||
b: &mut Bencher,
|
||||
input: &str,
|
||||
schema: tantivy::schema::Schema,
|
||||
commit: bool,
|
||||
parse_json: bool,
|
||||
) {
|
||||
let json_field = schema.get_field("json").unwrap();
|
||||
_benchmark(b, input, schema, commit, parse_json, |_schema, doc_json| {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
tantivy::doc!(json_field=>json_val)
|
||||
})
|
||||
}
|
||||
|
||||
pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
@@ -19,7 +104,14 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
schema_builder.add_text_field("severity", STRING);
|
||||
schema_builder.build()
|
||||
};
|
||||
let schema_with_store = {
|
||||
let schema_only_fast = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_u64_field("timestamp", FAST);
|
||||
schema_builder.add_text_field("body", FAST);
|
||||
schema_builder.add_text_field("severity", FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
let _schema_with_store = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_u64_field("timestamp", INDEXED | STORED);
|
||||
schema_builder.add_text_field("body", TEXT | STORED);
|
||||
@@ -28,74 +120,39 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
};
|
||||
let dynamic_schema = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_json_field("json", TEXT);
|
||||
schema_builder.add_json_field("json", TEXT | FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-hdfs");
|
||||
group.throughput(Throughput::Bytes(HDFS_LOGS.len() as u64));
|
||||
group.sample_size(20);
|
||||
group.bench_function("index-hdfs-no-commit", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
|
||||
let benches = [
|
||||
("only-indexed-".to_string(), schema, false),
|
||||
//("stored-".to_string(), _schema_with_store, false),
|
||||
("only-fast-".to_string(), schema_only_fast, false),
|
||||
("dynamic-".to_string(), dynamic_schema, true),
|
||||
];
|
||||
|
||||
for (prefix, schema, is_dynamic) in benches {
|
||||
for commit in [false, true] {
|
||||
let suffix = if commit { "with-commit" } else { "no-commit" };
|
||||
for parse_json in [false] {
|
||||
// for parse_json in [false, true] {
|
||||
let suffix = if parse_json {
|
||||
format!("{}-with-json-parsing", suffix)
|
||||
} else {
|
||||
format!("{}", suffix)
|
||||
};
|
||||
|
||||
let bench_name = format!("{}{}", prefix, suffix);
|
||||
group.bench_function(bench_name, |b| {
|
||||
benchmark(b, HDFS_LOGS, schema.clone(), commit, parse_json, is_dynamic)
|
||||
});
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-no-commit-with-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema_with_store.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit-with-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema_with_store.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-no-commit-json-without-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
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);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub fn gh_index_benchmark(c: &mut Criterion) {
|
||||
@@ -104,38 +161,24 @@ pub fn gh_index_benchmark(c: &mut Criterion) {
|
||||
schema_builder.add_json_field("json", TEXT | FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
let dynamic_schema_fast = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_json_field("json", FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-gh");
|
||||
group.throughput(Throughput::Bytes(GH_LOGS.len() as u64));
|
||||
|
||||
group.bench_function("index-gh-no-commit", |b| {
|
||||
let lines = get_lines(GH_LOGS);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
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);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema.clone(), false, false)
|
||||
});
|
||||
group.bench_function("index-gh-with-commit", |b| {
|
||||
let lines = get_lines(GH_LOGS);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
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);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
group.bench_function("index-gh-fast", |b| {
|
||||
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema_fast.clone(), false, false)
|
||||
});
|
||||
|
||||
group.bench_function("index-gh-fast-with-commit", |b| {
|
||||
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema_fast.clone(), true, false)
|
||||
});
|
||||
}
|
||||
|
||||
@@ -150,33 +193,10 @@ pub fn wiki_index_benchmark(c: &mut Criterion) {
|
||||
group.throughput(Throughput::Bytes(WIKI.len() as u64));
|
||||
|
||||
group.bench_function("index-wiki-no-commit", |b| {
|
||||
let lines = get_lines(WIKI);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
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);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
benchmark_dynamic_json(b, WIKI, dynamic_schema.clone(), false, false)
|
||||
});
|
||||
group.bench_function("index-wiki-with-commit", |b| {
|
||||
let lines = get_lines(WIKI);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
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);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
benchmark_dynamic_json(b, WIKI, dynamic_schema.clone(), true, false)
|
||||
});
|
||||
}
|
||||
|
||||
@@ -187,12 +207,12 @@ criterion_group! {
|
||||
}
|
||||
criterion_group! {
|
||||
name = gh_benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
config = Criterion::default();
|
||||
targets = gh_index_benchmark
|
||||
}
|
||||
criterion_group! {
|
||||
name = wiki_benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
config = Criterion::default();
|
||||
targets = wiki_index_benchmark
|
||||
}
|
||||
criterion_main!(benches, gh_benches, wiki_benches);
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-bitpacker"
|
||||
version = "0.4.0"
|
||||
version = "0.5.0"
|
||||
edition = "2021"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
@@ -15,7 +15,7 @@ homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
|
||||
|
||||
[dependencies]
|
||||
bitpacking = {version="0.8", default-features=false, features = ["bitpacker1x"]}
|
||||
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker1x"] }
|
||||
|
||||
[dev-dependencies]
|
||||
rand = "0.8"
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io;
|
||||
use std::ops::{Range, RangeInclusive};
|
||||
|
||||
@@ -367,7 +366,7 @@ mod test {
|
||||
let mut output: Vec<u32> = Vec::new();
|
||||
for len in [0, 1, 2, 32, 33, 34, 64] {
|
||||
for start_idx in 0u32..32u32 {
|
||||
output.resize(len as usize, 0);
|
||||
output.resize(len, 0);
|
||||
bitunpacker.get_batch_u32s(start_idx, &buffer, &mut output);
|
||||
for i in 0..len {
|
||||
let expected = (start_idx + i as u32) & mask;
|
||||
|
||||
@@ -64,10 +64,8 @@ fn mem_usage<T>(items: &Vec<T>) -> usize {
|
||||
|
||||
impl BlockedBitpacker {
|
||||
pub fn new() -> Self {
|
||||
let mut compressed_blocks = vec![];
|
||||
compressed_blocks.resize(8, 0);
|
||||
Self {
|
||||
compressed_blocks,
|
||||
compressed_blocks: vec![0; 8],
|
||||
buffer: vec![],
|
||||
offset_and_bits: vec![],
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
use std::ops::RangeInclusive;
|
||||
|
||||
#[cfg(any(target_arch = "x86_64"))]
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
mod avx2;
|
||||
|
||||
mod scalar;
|
||||
|
||||
@@ -32,6 +32,7 @@ postprocessors = [
|
||||
{ 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
|
||||
]
|
||||
|
||||
|
||||
@@ -1,23 +1,23 @@
|
||||
[package]
|
||||
name = "tantivy-columnar"
|
||||
version = "0.1.0"
|
||||
version = "0.2.0"
|
||||
edition = "2021"
|
||||
license = "MIT"
|
||||
homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
repository = "https://github.com/quickwit-oss/tantivy"
|
||||
desciption = "column oriented storage for tantivy"
|
||||
description = "column oriented storage for tantivy"
|
||||
categories = ["database-implementations", "data-structures", "compression"]
|
||||
|
||||
[dependencies]
|
||||
itertools = "0.10.5"
|
||||
fnv = "1.0.7"
|
||||
itertools = "0.12.0"
|
||||
fastdivide = "0.4.0"
|
||||
|
||||
stacker = { version= "0.1", path = "../stacker", package="tantivy-stacker"}
|
||||
sstable = { version= "0.1", path = "../sstable", package = "tantivy-sstable" }
|
||||
common = { version= "0.5", path = "../common", package = "tantivy-common" }
|
||||
tantivy-bitpacker = { version= "0.4", 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"
|
||||
|
||||
155
columnar/benches/bench_first_vals.rs
Normal file
155
columnar/benches/bench_first_vals.rs
Normal file
@@ -0,0 +1,155 @@
|
||||
#![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);
|
||||
}
|
||||
@@ -16,14 +16,6 @@ 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();
|
||||
@@ -8,7 +8,6 @@ license = "MIT"
|
||||
columnar = {path="../", package="tantivy-columnar"}
|
||||
serde_json = "1"
|
||||
serde_json_borrow = {git="https://github.com/PSeitz/serde_json_borrow/"}
|
||||
serde = "1"
|
||||
|
||||
[workspace]
|
||||
members = []
|
||||
|
||||
@@ -1,9 +1,12 @@
|
||||
use std::cmp::Ordering;
|
||||
|
||||
use crate::{Column, DocId, RowId};
|
||||
|
||||
#[derive(Debug, Default, Clone)]
|
||||
pub struct ColumnBlockAccessor<T> {
|
||||
val_cache: Vec<T>,
|
||||
docid_cache: Vec<DocId>,
|
||||
missing_docids_cache: Vec<DocId>,
|
||||
row_id_cache: Vec<RowId>,
|
||||
}
|
||||
|
||||
@@ -11,14 +14,40 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
|
||||
ColumnBlockAccessor<T>
|
||||
{
|
||||
#[inline]
|
||||
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);
|
||||
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);
|
||||
}
|
||||
}
|
||||
#[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()
|
||||
{
|
||||
self.missing_docids_cache.clear();
|
||||
find_missing_docs(docs, &self.docid_cache, |doc| {
|
||||
self.missing_docids_cache.push(doc);
|
||||
self.val_cache.push(missing);
|
||||
});
|
||||
self.docid_cache
|
||||
.extend_from_slice(&self.missing_docids_cache);
|
||||
}
|
||||
}
|
||||
|
||||
#[inline]
|
||||
@@ -27,10 +56,103 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn iter_docid_vals(&self) -> impl Iterator<Item = (DocId, T)> + '_ {
|
||||
self.docid_cache
|
||||
.iter()
|
||||
.cloned()
|
||||
.zip(self.val_cache.iter().cloned())
|
||||
/// 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())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Given two sorted lists of docids `docs` and `hits`, hits is a subset of `docs`.
|
||||
/// Return all docs that are not in `hits`.
|
||||
fn find_missing_docs<F>(docs: &[u32], hits: &[u32], mut callback: F)
|
||||
where F: FnMut(u32) {
|
||||
let mut docs_iter = docs.iter();
|
||||
let mut hits_iter = hits.iter();
|
||||
|
||||
let mut doc = docs_iter.next();
|
||||
let mut hit = hits_iter.next();
|
||||
|
||||
while let (Some(¤t_doc), Some(¤t_hit)) = (doc, hit) {
|
||||
match current_doc.cmp(¤t_hit) {
|
||||
Ordering::Less => {
|
||||
callback(current_doc);
|
||||
doc = docs_iter.next();
|
||||
}
|
||||
Ordering::Equal => {
|
||||
doc = docs_iter.next();
|
||||
hit = hits_iter.next();
|
||||
}
|
||||
Ordering::Greater => {
|
||||
hit = hits_iter.next();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
while let Some(¤t_doc) = doc {
|
||||
callback(current_doc);
|
||||
doc = docs_iter.next();
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs() {
|
||||
let docs: Vec<u32> = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
|
||||
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![1, 3, 5, 7, 9]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs_empty() {
|
||||
let docs: Vec<u32> = Vec::new();
|
||||
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs_all_missing() {
|
||||
let docs: Vec<u32> = vec![1, 2, 3, 4, 5];
|
||||
let hits: Vec<u32> = Vec::new();
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![1, 2, 3, 4, 5]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -30,6 +30,13 @@ impl fmt::Debug for BytesColumn {
|
||||
}
|
||||
|
||||
impl BytesColumn {
|
||||
pub fn empty(num_docs: u32) -> BytesColumn {
|
||||
BytesColumn {
|
||||
dictionary: Arc::new(Dictionary::empty()),
|
||||
term_ord_column: Column::build_empty_column(num_docs),
|
||||
}
|
||||
}
|
||||
|
||||
/// Fills the given `output` buffer with the term associated to the ordinal `ord`.
|
||||
///
|
||||
/// Returns `false` if the term does not exist (e.g. `term_ord` is greater or equal to the
|
||||
@@ -77,7 +84,7 @@ impl From<StrColumn> for BytesColumn {
|
||||
}
|
||||
|
||||
impl StrColumn {
|
||||
pub(crate) fn wrap(bytes_column: BytesColumn) -> StrColumn {
|
||||
pub fn wrap(bytes_column: BytesColumn) -> StrColumn {
|
||||
StrColumn(bytes_column)
|
||||
}
|
||||
|
||||
|
||||
@@ -3,17 +3,17 @@ mod serialize;
|
||||
|
||||
use std::fmt::{self, Debug};
|
||||
use std::io::Write;
|
||||
use std::ops::{Deref, Range, RangeInclusive};
|
||||
use std::ops::{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_u64,
|
||||
serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
|
||||
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,
|
||||
};
|
||||
|
||||
use crate::column_index::ColumnIndex;
|
||||
use crate::column_index::{ColumnIndex, Set};
|
||||
use crate::column_values::monotonic_mapping::StrictlyMonotonicMappingToInternal;
|
||||
use crate::column_values::{monotonic_map_column, ColumnValues};
|
||||
use crate::{Cardinality, DocId, EmptyColumnValues, MonotonicallyMappableToU64, RowId};
|
||||
@@ -83,10 +83,36 @@ 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
|
||||
@@ -105,7 +131,8 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
}
|
||||
|
||||
pub fn values_for_doc(&self, doc_id: DocId) -> impl Iterator<Item = T> + '_ {
|
||||
self.value_row_ids(doc_id)
|
||||
self.index
|
||||
.value_row_ids(doc_id)
|
||||
.map(|value_row_id: RowId| self.values.get_val(value_row_id))
|
||||
}
|
||||
|
||||
@@ -130,7 +157,7 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
.select_batch_in_place(selected_docid_range.start, doc_ids);
|
||||
}
|
||||
|
||||
/// Fils the output vector with the (possibly multiple values that are associated_with
|
||||
/// Fills the output vector with the (possibly multiple values that are associated_with
|
||||
/// `row_id`.
|
||||
///
|
||||
/// This method clears the `output` vector.
|
||||
@@ -147,14 +174,6 @@ 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)
|
||||
@@ -176,6 +195,7 @@ 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)
|
||||
}
|
||||
|
||||
@@ -76,6 +76,26 @@ 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());
|
||||
|
||||
@@ -168,8 +168,9 @@ mod tests {
|
||||
)
|
||||
.into();
|
||||
let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
|
||||
else { panic!("Excpected a multivalued index") };
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
|
||||
panic!("Excpected a multivalued index")
|
||||
};
|
||||
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
|
||||
assert_eq!(&start_indexes, &[0, 3, 5]);
|
||||
}
|
||||
@@ -200,8 +201,9 @@ mod tests {
|
||||
)
|
||||
.into();
|
||||
let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
|
||||
else { panic!("Excpected a multivalued index") };
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
|
||||
panic!("Excpected a multivalued index")
|
||||
};
|
||||
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
|
||||
assert_eq!(&start_indexes, &[0, 3, 5, 6]);
|
||||
}
|
||||
|
||||
@@ -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 = vec![optional_index, ColumnIndex::Full];
|
||||
let column_indexes = [optional_index, ColumnIndex::Full];
|
||||
let row_addrs = vec![
|
||||
RowAddr {
|
||||
segment_ord: 0u32,
|
||||
@@ -157,7 +157,13 @@ mod tests {
|
||||
Cardinality::Optional,
|
||||
&shuffle_merge_order,
|
||||
);
|
||||
let SerializableColumnIndex::Optional { non_null_row_ids, num_rows } = serializable_index else { panic!() };
|
||||
let SerializableColumnIndex::Optional {
|
||||
non_null_row_ids,
|
||||
num_rows,
|
||||
} = serializable_index
|
||||
else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(num_rows, 2);
|
||||
let non_null_rows: Vec<RowId> = non_null_row_ids.boxed_iter().collect();
|
||||
assert_eq!(&non_null_rows, &[1]);
|
||||
|
||||
@@ -111,10 +111,7 @@ 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 {
|
||||
let Some(multivalued_index) = current_it.as_mut() else {
|
||||
return None;
|
||||
};
|
||||
if let Some(row_id) = multivalued_index.next() {
|
||||
if let Some(row_id) = current_it.as_mut()?.next() {
|
||||
last_row_id = offset + row_id;
|
||||
return Some(last_row_id);
|
||||
}
|
||||
|
||||
@@ -1,3 +1,8 @@
|
||||
//! # `column_index`
|
||||
//!
|
||||
//! `column_index` provides rank and select operations to associate positions when not all
|
||||
//! documents have exactly one element.
|
||||
|
||||
mod merge;
|
||||
mod multivalued_index;
|
||||
mod optional_index;
|
||||
@@ -37,10 +42,10 @@ impl From<MultiValueIndex> for ColumnIndex {
|
||||
}
|
||||
|
||||
impl ColumnIndex {
|
||||
// Returns the cardinality of the column index.
|
||||
//
|
||||
// By convention, if the column contains no docs, we consider that it is
|
||||
// full.
|
||||
/// Returns the cardinality of the column index.
|
||||
///
|
||||
/// By convention, if the column contains no docs, we consider that it is
|
||||
/// full.
|
||||
#[inline]
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
match self {
|
||||
@@ -117,18 +122,18 @@ impl ColumnIndex {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
|
||||
pub fn docid_range_to_rowids(&self, doc_id_range: Range<DocId>) -> Range<RowId> {
|
||||
match self {
|
||||
ColumnIndex::Empty { .. } => 0..0,
|
||||
ColumnIndex::Full => doc_id,
|
||||
ColumnIndex::Full => doc_id_range,
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
let row_start = optional_index.rank(doc_id.start);
|
||||
let row_end = optional_index.rank(doc_id.end);
|
||||
let row_start = optional_index.rank(doc_id_range.start);
|
||||
let row_end = optional_index.rank(doc_id_range.end);
|
||||
row_start..row_end
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => {
|
||||
let end_docid = doc_id.end.min(multivalued_index.num_docs() - 1) + 1;
|
||||
let start_docid = doc_id.start.min(end_docid);
|
||||
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 row_start = multivalued_index.start_index_column.get_val(start_docid);
|
||||
let row_end = multivalued_index.start_index_column.get_val(end_docid);
|
||||
|
||||
@@ -21,8 +21,6 @@ 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,
|
||||
@@ -109,8 +107,8 @@ struct RowAddr {
|
||||
#[inline(always)]
|
||||
fn row_addr_from_row_id(row_id: RowId) -> RowAddr {
|
||||
RowAddr {
|
||||
block_id: (row_id / BLOCK_SIZE) as u16,
|
||||
in_block_row_id: (row_id % BLOCK_SIZE) as u16,
|
||||
block_id: (row_id / ELEMENTS_PER_BLOCK) as u16,
|
||||
in_block_row_id: (row_id % ELEMENTS_PER_BLOCK) as u16,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -185,8 +183,13 @@ 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,
|
||||
@@ -200,13 +203,15 @@ 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[block_id as usize];
|
||||
let block_meta = *self.block_metas.get(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),
|
||||
@@ -491,7 +496,7 @@ fn deserialize_optional_index_block_metadatas(
|
||||
non_null_rows_before_block += num_non_null_rows;
|
||||
}
|
||||
block_metas.resize(
|
||||
((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,
|
||||
((num_rows + ELEMENTS_PER_BLOCK - 1) / ELEMENTS_PER_BLOCK) as usize,
|
||||
BlockMeta {
|
||||
non_null_rows_before_block,
|
||||
start_byte_offset,
|
||||
|
||||
@@ -39,7 +39,8 @@ pub trait Set<T> {
|
||||
///
|
||||
/// # Panics
|
||||
///
|
||||
/// May panic if rank is greater than the number of elements in the Set.
|
||||
/// May panic if rank is greater or equal to the number of
|
||||
/// elements in the Set.
|
||||
fn select(&self, rank: T) -> T;
|
||||
|
||||
/// Creates a brand new select cursor.
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io::{self, Write};
|
||||
|
||||
use common::BinarySerializable;
|
||||
|
||||
@@ -1,8 +1,31 @@
|
||||
use proptest::prelude::{any, prop, *};
|
||||
use proptest::strategy::Strategy;
|
||||
use proptest::prelude::*;
|
||||
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() {
|
||||
@@ -35,7 +58,7 @@ proptest! {
|
||||
|
||||
#[test]
|
||||
fn test_with_random_sets_simple() {
|
||||
let vals = 10..BLOCK_SIZE * 2;
|
||||
let vals = 10..ELEMENTS_PER_BLOCK * 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();
|
||||
@@ -171,7 +194,7 @@ fn test_optional_index_rank() {
|
||||
test_optional_index_rank_aux(&[0u32, 1u32]);
|
||||
let mut block = Vec::new();
|
||||
block.push(3u32);
|
||||
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
|
||||
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
|
||||
test_optional_index_rank_aux(&block);
|
||||
}
|
||||
|
||||
@@ -185,8 +208,8 @@ 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..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
|
||||
test_optional_index_iter_aux(&block, 3 * BLOCK_SIZE);
|
||||
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
|
||||
test_optional_index_iter_aux(&block, 3 * ELEMENTS_PER_BLOCK);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -215,12 +238,12 @@ mod bench {
|
||||
let vals: Vec<RowId> = (0..TOTAL_NUM_VALUES)
|
||||
.map(|_| rng.gen_bool(fill_ratio))
|
||||
.enumerate()
|
||||
.filter(|(pos, val)| *val)
|
||||
.filter(|(_pos, val)| *val)
|
||||
.map(|(pos, _)| pos as RowId)
|
||||
.collect();
|
||||
serialize_optional_index(&&vals[..], TOTAL_NUM_VALUES, &mut out).unwrap();
|
||||
let codec = open_optional_index(OwnedBytes::new(out)).unwrap();
|
||||
codec
|
||||
|
||||
open_optional_index(OwnedBytes::new(out)).unwrap()
|
||||
}
|
||||
|
||||
fn random_range_iterator(
|
||||
@@ -242,7 +265,7 @@ mod bench {
|
||||
}
|
||||
|
||||
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
|
||||
let ratio = percent as f32 / 100.0;
|
||||
let ratio = percent / 100.0;
|
||||
let step_size = (1f32 / ratio) as u32;
|
||||
let deviation = step_size - 1;
|
||||
random_range_iterator(0, num_values, step_size, deviation)
|
||||
|
||||
@@ -30,6 +30,7 @@ impl<'a> SerializableColumnIndex<'a> {
|
||||
}
|
||||
}
|
||||
|
||||
/// Serialize a column index.
|
||||
pub fn serialize_column_index(
|
||||
column_index: SerializableColumnIndex,
|
||||
output: &mut impl Write,
|
||||
@@ -51,6 +52,7 @@ pub fn serialize_column_index(
|
||||
Ok(column_index_num_bytes)
|
||||
}
|
||||
|
||||
/// Open a serialized column index.
|
||||
pub fn open_column_index(mut bytes: OwnedBytes) -> io::Result<ColumnIndex> {
|
||||
if bytes.is_empty() {
|
||||
return Err(io::Error::new(
|
||||
|
||||
@@ -10,7 +10,7 @@ pub(crate) struct MergedColumnValues<'a, T> {
|
||||
pub(crate) merge_row_order: &'a MergeRowOrder,
|
||||
}
|
||||
|
||||
impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T> {
|
||||
impl<'a, T: Copy + PartialOrd + Debug + 'static> Iterable<T> for MergedColumnValues<'a, T> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
|
||||
match self.merge_row_order {
|
||||
MergeRowOrder::Stack(_) => Box::new(
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
//! # `fastfield_codecs`
|
||||
//!
|
||||
//! - Columnar storage of data for tantivy [`Column`].
|
||||
//! - Columnar storage of data for tantivy [`crate::Column`].
|
||||
//! - Encode data in different codecs.
|
||||
//! - Monotonically map values to u64/u128
|
||||
|
||||
@@ -10,6 +10,7 @@ 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;
|
||||
|
||||
@@ -25,7 +26,10 @@ mod monotonic_column;
|
||||
|
||||
pub(crate) use merge::MergedColumnValues;
|
||||
pub use stats::ColumnStats;
|
||||
pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
|
||||
pub use u128_based::{
|
||||
open_u128_as_compact_u64, open_u128_mapped, serialize_column_values_u128,
|
||||
CompactSpaceU64Accessor,
|
||||
};
|
||||
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,
|
||||
@@ -41,7 +45,7 @@ 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 {
|
||||
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
|
||||
/// Return the value associated with the given idx.
|
||||
///
|
||||
/// This accessor should return as fast as possible.
|
||||
@@ -68,11 +72,40 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
out_x4[3] = self.get_val(idx_x4[3]);
|
||||
}
|
||||
|
||||
let step_size = 4;
|
||||
let cutoff = indexes.len() - indexes.len() % step_size;
|
||||
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);
|
||||
}
|
||||
}
|
||||
|
||||
for idx in cutoff..indexes.len() {
|
||||
output[idx] = self.get_val(indexes[idx]);
|
||||
/// 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));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -101,7 +134,7 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
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.start..row_id_range.end {
|
||||
for idx in row_id_range {
|
||||
let val = self.get_val(idx);
|
||||
if value_range.contains(&val) {
|
||||
row_id_hits.push(idx);
|
||||
@@ -139,6 +172,7 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
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;
|
||||
@@ -161,12 +195,17 @@ impl<T: PartialOrd + Default> ColumnValues<T> for EmptyColumnValues {
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
|
||||
impl<T: Copy + PartialOrd + Debug + 'static> 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()
|
||||
|
||||
@@ -31,10 +31,10 @@ pub fn monotonic_map_column<C, T, Input, Output>(
|
||||
monotonic_mapping: T,
|
||||
) -> impl ColumnValues<Output>
|
||||
where
|
||||
C: ColumnValues<Input>,
|
||||
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
|
||||
Input: PartialOrd + Debug + Send + Sync + Clone,
|
||||
Output: PartialOrd + Debug + Send + Sync + Clone,
|
||||
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,
|
||||
{
|
||||
MonotonicMappingColumn {
|
||||
from_column,
|
||||
@@ -45,10 +45,10 @@ where
|
||||
|
||||
impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
|
||||
where
|
||||
C: ColumnValues<Input>,
|
||||
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
|
||||
Input: PartialOrd + Send + Debug + Sync + Clone,
|
||||
Output: PartialOrd + Send + Debug + Sync + Clone,
|
||||
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,
|
||||
{
|
||||
#[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()),
|
||||
|
||||
@@ -38,6 +38,6 @@ impl Ord for BlankRange {
|
||||
}
|
||||
impl PartialOrd for BlankRange {
|
||||
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
|
||||
Some(self.blank_size().cmp(&other.blank_size()))
|
||||
Some(self.cmp(other))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -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::{self, BitPacker, BitUnpacker};
|
||||
use tantivy_bitpacker::{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
|
||||
.map_or_else(|e| e - 1, |v| v);
|
||||
.unwrap_or_else(|e| e - 1);
|
||||
|
||||
let range_mapping = &self.ranges_mapping[pos];
|
||||
let diff = compact - range_mapping.compact_start;
|
||||
@@ -292,6 +292,63 @@ 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 {
|
||||
@@ -402,9 +459,14 @@ 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.params.bit_unpacker.get(idx, &self.data) as u32;
|
||||
let compact = self.get_compact(idx);
|
||||
self.compact_to_u128(compact)
|
||||
}
|
||||
|
||||
|
||||
@@ -6,7 +6,9 @@ use std::sync::Arc;
|
||||
mod compact_space;
|
||||
|
||||
use common::{BinarySerializable, OwnedBytes, VInt};
|
||||
use compact_space::{CompactSpaceCompressor, CompactSpaceDecompressor};
|
||||
pub use compact_space::{
|
||||
CompactSpaceCompressor, CompactSpaceDecompressor, CompactSpaceU64Accessor,
|
||||
};
|
||||
|
||||
use crate::column_values::monotonic_map_column;
|
||||
use crate::column_values::monotonic_mapping::{
|
||||
@@ -108,6 +110,23 @@ 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::*;
|
||||
|
||||
@@ -63,7 +63,6 @@ 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
|
||||
@@ -83,7 +82,8 @@ impl ColumnValues for BitpackedReader {
|
||||
doc_id_range: Range<u32>,
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
let Some(transformed_range) = transform_range_before_linear_transformation(&self.stats, range)
|
||||
let Some(transformed_range) =
|
||||
transform_range_before_linear_transformation(&self.stats, range)
|
||||
else {
|
||||
positions.clear();
|
||||
return;
|
||||
|
||||
@@ -63,7 +63,10 @@ impl BlockwiseLinearEstimator {
|
||||
if self.block.is_empty() {
|
||||
return;
|
||||
}
|
||||
let line = Line::train(&VecColumn::from(&self.block));
|
||||
let column = VecColumn::from(std::mem::take(&mut self.block));
|
||||
let line = Line::train(&column);
|
||||
self.block = column.into();
|
||||
|
||||
let mut max_value = 0u64;
|
||||
for (i, buffer_val) in self.block.iter().enumerate() {
|
||||
let interpolated_val = line.eval(i as u32);
|
||||
@@ -125,7 +128,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
|
||||
*buffer_val = gcd_divider.divide(*buffer_val - stats.min_value);
|
||||
}
|
||||
|
||||
let line = Line::train(&VecColumn::from(&buffer));
|
||||
let line = Line::train(&VecColumn::from(buffer.to_vec()));
|
||||
|
||||
assert!(!buffer.is_empty());
|
||||
|
||||
|
||||
@@ -184,7 +184,7 @@ mod tests {
|
||||
}
|
||||
|
||||
fn test_eval_max_err(ys: &[u64]) -> Option<u64> {
|
||||
let line = Line::train(&VecColumn::from(&ys));
|
||||
let line = Line::train(&VecColumn::from(ys.to_vec()));
|
||||
ys.iter()
|
||||
.enumerate()
|
||||
.map(|(x, y)| y.wrapping_sub(line.eval(x as u32)))
|
||||
|
||||
@@ -173,7 +173,9 @@ impl LinearCodecEstimator {
|
||||
fn collect_before_line_estimation(&mut self, value: u64) {
|
||||
self.block.push(value);
|
||||
if self.block.len() == LINE_ESTIMATION_BLOCK_LEN {
|
||||
let line = Line::train(&VecColumn::from(&self.block));
|
||||
let column = VecColumn::from(std::mem::take(&mut self.block));
|
||||
let line = Line::train(&column);
|
||||
self.block = column.into();
|
||||
let block = std::mem::take(&mut self.block);
|
||||
for val in block {
|
||||
self.collect_after_line_estimation(&line, val);
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
use proptest::prelude::*;
|
||||
use proptest::strategy::Strategy;
|
||||
use proptest::{prop_oneof, proptest};
|
||||
|
||||
#[test]
|
||||
|
||||
@@ -4,14 +4,14 @@ use tantivy_bitpacker::minmax;
|
||||
|
||||
use crate::ColumnValues;
|
||||
|
||||
/// VecColumn provides `Column` over a slice.
|
||||
pub struct VecColumn<'a, T = u64> {
|
||||
pub(crate) values: &'a [T],
|
||||
/// VecColumn provides `Column` over a `Vec<T>`.
|
||||
pub struct VecColumn<T = u64> {
|
||||
pub(crate) values: Vec<T>,
|
||||
pub(crate) min_value: T,
|
||||
pub(crate) max_value: T,
|
||||
}
|
||||
|
||||
impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
|
||||
impl<T: Copy + PartialOrd + Send + Sync + Debug + 'static> ColumnValues<T> for VecColumn<T> {
|
||||
fn get_val(&self, position: u32) -> T {
|
||||
self.values[position as usize]
|
||||
}
|
||||
@@ -37,11 +37,8 @@ impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColu
|
||||
}
|
||||
}
|
||||
|
||||
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();
|
||||
impl<T: Copy + PartialOrd + Default> From<Vec<T>> for VecColumn<T> {
|
||||
fn from(values: Vec<T>) -> Self {
|
||||
let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
|
||||
Self {
|
||||
values,
|
||||
@@ -50,3 +47,8 @@ where V: AsRef<[T]> + ?Sized
|
||||
}
|
||||
}
|
||||
}
|
||||
impl From<VecColumn> for Vec<u64> {
|
||||
fn from(column: VecColumn) -> Self {
|
||||
column.values
|
||||
}
|
||||
}
|
||||
|
||||
@@ -52,8 +52,8 @@ pub enum MergeRowOrder {
|
||||
/// Columnar tables are simply stacked one above the other.
|
||||
/// If the i-th columnar_readers has n_rows_i rows, then
|
||||
/// in the resulting columnar,
|
||||
/// rows [r0..n_row_0) contains the row of columnar_readers[0], in ordder
|
||||
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of columnar_readers[1], in order.
|
||||
/// rows [r0..n_row_0) contains the row of `columnar_readers[0]`, in ordder
|
||||
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of `columnar_readers[1]`, in order.
|
||||
/// ..
|
||||
/// No documents is deleted.
|
||||
Stack(StackMergeOrder),
|
||||
|
||||
@@ -2,7 +2,7 @@ mod merge_dict_column;
|
||||
mod merge_mapping;
|
||||
mod term_merger;
|
||||
|
||||
use std::collections::{BTreeMap, HashMap, HashSet};
|
||||
use std::collections::{BTreeMap, HashSet};
|
||||
use std::io;
|
||||
use std::net::Ipv6Addr;
|
||||
use std::sync::Arc;
|
||||
@@ -18,7 +18,8 @@ use crate::columnar::writer::CompatibleNumericalTypes;
|
||||
use crate::columnar::ColumnarReader;
|
||||
use crate::dynamic_column::DynamicColumn;
|
||||
use crate::{
|
||||
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, NumericalType, NumericalValue,
|
||||
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, DynamicColumnHandle, NumericalType,
|
||||
NumericalValue,
|
||||
};
|
||||
|
||||
/// Column types are grouped into different categories.
|
||||
@@ -28,14 +29,16 @@ use crate::{
|
||||
/// In practise, today, only Numerical colummns are coerced into one type today.
|
||||
///
|
||||
/// See also [README.md].
|
||||
#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug)]
|
||||
///
|
||||
/// The ordering has to match the ordering of the variants in [ColumnType].
|
||||
#[derive(Copy, Clone, Eq, PartialOrd, Ord, PartialEq, Hash, Debug)]
|
||||
pub(crate) enum ColumnTypeCategory {
|
||||
Bool,
|
||||
Str,
|
||||
Numerical,
|
||||
DateTime,
|
||||
Bytes,
|
||||
Str,
|
||||
Bool,
|
||||
IpAddr,
|
||||
DateTime,
|
||||
}
|
||||
|
||||
impl From<ColumnType> for ColumnTypeCategory {
|
||||
@@ -83,9 +86,20 @@ pub fn merge_columnar(
|
||||
.iter()
|
||||
.map(|reader| reader.num_rows())
|
||||
.collect::<Vec<u32>>();
|
||||
|
||||
let columns_to_merge =
|
||||
group_columns_for_merge(columnar_readers, required_columns, &merge_row_order)?;
|
||||
for ((column_name, column_type), columns) in columns_to_merge {
|
||||
for res in columns_to_merge {
|
||||
let ((column_name, _column_type_category), grouped_columns) = res;
|
||||
let grouped_columns = grouped_columns.open(&merge_row_order)?;
|
||||
if grouped_columns.is_empty() {
|
||||
continue;
|
||||
}
|
||||
|
||||
let column_type = grouped_columns.column_type_after_merge();
|
||||
let mut columns = grouped_columns.columns;
|
||||
coerce_columns(column_type, &mut columns)?;
|
||||
|
||||
let mut column_serializer =
|
||||
serializer.start_serialize_column(column_name.as_bytes(), column_type);
|
||||
merge_column(
|
||||
@@ -97,6 +111,7 @@ pub fn merge_columnar(
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
|
||||
serializer.finalize(merge_row_order.num_rows())?;
|
||||
Ok(())
|
||||
}
|
||||
@@ -210,40 +225,12 @@ fn merge_column(
|
||||
struct GroupedColumns {
|
||||
required_column_type: Option<ColumnType>,
|
||||
columns: Vec<Option<DynamicColumn>>,
|
||||
column_category: ColumnTypeCategory,
|
||||
}
|
||||
|
||||
impl GroupedColumns {
|
||||
fn for_category(column_category: ColumnTypeCategory, num_columnars: usize) -> Self {
|
||||
GroupedColumns {
|
||||
required_column_type: None,
|
||||
columns: vec![None; num_columnars],
|
||||
column_category,
|
||||
}
|
||||
}
|
||||
|
||||
/// Set the dynamic column for a given columnar.
|
||||
fn set_column(&mut self, columnar_id: usize, column: DynamicColumn) {
|
||||
self.columns[columnar_id] = Some(column);
|
||||
}
|
||||
|
||||
/// Force the existence of a column, as well as its type.
|
||||
fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
|
||||
if let Some(existing_required_type) = self.required_column_type {
|
||||
if existing_required_type == required_type {
|
||||
// This was just a duplicate in the `required_columns`.
|
||||
// Nothing to do.
|
||||
return Ok(());
|
||||
} else {
|
||||
return Err(io::Error::new(
|
||||
io::ErrorKind::InvalidInput,
|
||||
"Required column conflicts with another required column of the same type \
|
||||
category.",
|
||||
));
|
||||
}
|
||||
}
|
||||
self.required_column_type = Some(required_type);
|
||||
Ok(())
|
||||
/// Check is column group can be skipped during serialization.
|
||||
fn is_empty(&self) -> bool {
|
||||
self.required_column_type.is_none() && self.columns.iter().all(Option::is_none)
|
||||
}
|
||||
|
||||
/// Returns the column type after merge.
|
||||
@@ -265,11 +252,76 @@ impl GroupedColumns {
|
||||
}
|
||||
// At the moment, only the numerical categorical column type has more than one possible
|
||||
// column type.
|
||||
assert_eq!(self.column_category, ColumnTypeCategory::Numerical);
|
||||
assert!(self
|
||||
.columns
|
||||
.iter()
|
||||
.flatten()
|
||||
.all(|el| ColumnTypeCategory::from(el.column_type()) == ColumnTypeCategory::Numerical));
|
||||
merged_numerical_columns_type(self.columns.iter().flatten()).into()
|
||||
}
|
||||
}
|
||||
|
||||
struct GroupedColumnsHandle {
|
||||
required_column_type: Option<ColumnType>,
|
||||
columns: Vec<Option<DynamicColumnHandle>>,
|
||||
}
|
||||
|
||||
impl GroupedColumnsHandle {
|
||||
fn new(num_columnars: usize) -> Self {
|
||||
GroupedColumnsHandle {
|
||||
required_column_type: None,
|
||||
columns: vec![None; num_columnars],
|
||||
}
|
||||
}
|
||||
fn open(self, merge_row_order: &MergeRowOrder) -> io::Result<GroupedColumns> {
|
||||
let mut columns: Vec<Option<DynamicColumn>> = Vec::new();
|
||||
for (columnar_id, column) in self.columns.iter().enumerate() {
|
||||
if let Some(column) = column {
|
||||
let column = column.open()?;
|
||||
// We skip columns that end up with 0 documents.
|
||||
// That way, we make sure they don't end up influencing the merge type or
|
||||
// creating empty columns.
|
||||
|
||||
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
|
||||
columns.push(None);
|
||||
} else {
|
||||
columns.push(Some(column));
|
||||
}
|
||||
} else {
|
||||
columns.push(None);
|
||||
}
|
||||
}
|
||||
Ok(GroupedColumns {
|
||||
required_column_type: self.required_column_type,
|
||||
columns,
|
||||
})
|
||||
}
|
||||
|
||||
/// Set the dynamic column for a given columnar.
|
||||
fn set_column(&mut self, columnar_id: usize, column: DynamicColumnHandle) {
|
||||
self.columns[columnar_id] = Some(column);
|
||||
}
|
||||
|
||||
/// Force the existence of a column, as well as its type.
|
||||
fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
|
||||
if let Some(existing_required_type) = self.required_column_type {
|
||||
if existing_required_type == required_type {
|
||||
// This was just a duplicate in the `required_columns`.
|
||||
// Nothing to do.
|
||||
return Ok(());
|
||||
} else {
|
||||
return Err(io::Error::new(
|
||||
io::ErrorKind::InvalidInput,
|
||||
"Required column conflicts with another required column of the same type \
|
||||
category.",
|
||||
));
|
||||
}
|
||||
}
|
||||
self.required_column_type = Some(required_type);
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the type of the merged numerical column.
|
||||
///
|
||||
/// This function picks the first numerical type out of i64, u64, f64 (order matters
|
||||
@@ -293,7 +345,7 @@ fn merged_numerical_columns_type<'a>(
|
||||
fn is_empty_after_merge(
|
||||
merge_row_order: &MergeRowOrder,
|
||||
column: &DynamicColumn,
|
||||
columnar_id: usize,
|
||||
columnar_ord: usize,
|
||||
) -> bool {
|
||||
if column.num_values() == 0u32 {
|
||||
// It was empty before the merge.
|
||||
@@ -305,7 +357,7 @@ fn is_empty_after_merge(
|
||||
false
|
||||
}
|
||||
MergeRowOrder::Shuffled(shuffled) => {
|
||||
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_id] {
|
||||
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_ord] {
|
||||
let column_index = column.column_index();
|
||||
match column_index {
|
||||
ColumnIndex::Empty { .. } => true,
|
||||
@@ -348,56 +400,34 @@ fn is_empty_after_merge(
|
||||
}
|
||||
}
|
||||
|
||||
#[allow(clippy::type_complexity)]
|
||||
fn group_columns_for_merge(
|
||||
columnar_readers: &[&ColumnarReader],
|
||||
required_columns: &[(String, ColumnType)],
|
||||
merge_row_order: &MergeRowOrder,
|
||||
) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
|
||||
// Each column name may have multiple types of column associated.
|
||||
// For merging we are interested in the same column type category since they can be merged.
|
||||
let mut columns_grouped: HashMap<(String, ColumnTypeCategory), GroupedColumns> = HashMap::new();
|
||||
/// Iterates over the columns of the columnar readers, grouped by column name.
|
||||
/// Key functionality is that `open` of the Columns is done lazy per group.
|
||||
fn group_columns_for_merge<'a>(
|
||||
columnar_readers: &'a [&'a ColumnarReader],
|
||||
required_columns: &'a [(String, ColumnType)],
|
||||
_merge_row_order: &'a MergeRowOrder,
|
||||
) -> io::Result<BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle>> {
|
||||
let mut columns: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> = BTreeMap::new();
|
||||
|
||||
for &(ref column_name, column_type) in required_columns {
|
||||
columns_grouped
|
||||
columns
|
||||
.entry((column_name.clone(), column_type.into()))
|
||||
.or_insert_with(|| {
|
||||
GroupedColumns::for_category(column_type.into(), columnar_readers.len())
|
||||
})
|
||||
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
|
||||
.require_type(column_type)?;
|
||||
}
|
||||
|
||||
for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
|
||||
let column_name_and_handle = columnar_reader.list_columns()?;
|
||||
// We skip columns that end up with 0 documents.
|
||||
// That way, we make sure they don't end up influencing the merge type or
|
||||
// creating empty columns.
|
||||
let column_name_and_handle = columnar_reader.iter_columns()?;
|
||||
|
||||
for (column_name, handle) in column_name_and_handle {
|
||||
let column_category: ColumnTypeCategory = handle.column_type().into();
|
||||
let column = handle.open()?;
|
||||
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
|
||||
continue;
|
||||
}
|
||||
columns_grouped
|
||||
columns
|
||||
.entry((column_name, column_category))
|
||||
.or_insert_with(|| {
|
||||
GroupedColumns::for_category(column_category, columnar_readers.len())
|
||||
})
|
||||
.set_column(columnar_id, column);
|
||||
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
|
||||
.set_column(columnar_id, handle);
|
||||
}
|
||||
}
|
||||
|
||||
let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
Default::default();
|
||||
|
||||
for ((column_name, _), mut grouped_columns) in columns_grouped {
|
||||
let column_type = grouped_columns.column_type_after_merge();
|
||||
coerce_columns(column_type, &mut grouped_columns.columns)?;
|
||||
merge_columns.insert((column_name, column_type), grouped_columns.columns);
|
||||
}
|
||||
|
||||
Ok(merge_columns)
|
||||
Ok(columns)
|
||||
}
|
||||
|
||||
fn coerce_columns(
|
||||
|
||||
@@ -1,5 +1,3 @@
|
||||
use itertools::Itertools;
|
||||
|
||||
use super::*;
|
||||
use crate::{Cardinality, ColumnarWriter, HasAssociatedColumnType, RowId};
|
||||
|
||||
@@ -27,22 +25,10 @@ fn test_column_coercion_to_u64() {
|
||||
let columnar2 = make_columnar("numbers", &[u64::MAX]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_column_no_coercion_if_all_the_same() {
|
||||
let columnar1 = make_columnar("numbers", &[1u64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -51,24 +37,24 @@ fn test_column_coercion_to_i64() {
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_impossible_coercion_returns_an_error() {
|
||||
let columnar1 = make_columnar("numbers", &[u64::MAX]);
|
||||
let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
|
||||
let group_error = group_columns_for_merge(
|
||||
&[&columnar1],
|
||||
&[("numbers".to_string(), ColumnType::I64)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap_err();
|
||||
assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
|
||||
}
|
||||
//#[test]
|
||||
// fn test_impossible_coercion_returns_an_error() {
|
||||
// let columnar1 = make_columnar("numbers", &[u64::MAX]);
|
||||
// let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
|
||||
// let group_error = group_columns_for_merge_iter(
|
||||
//&[&columnar1],
|
||||
//&[("numbers".to_string(), ColumnType::I64)],
|
||||
//&merge_order,
|
||||
//)
|
||||
//.unwrap_err();
|
||||
// assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
|
||||
//}
|
||||
|
||||
#[test]
|
||||
fn test_group_columns_with_required_column() {
|
||||
@@ -76,7 +62,7 @@ fn test_group_columns_with_required_column() {
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(
|
||||
&[&columnar1, &columnar2],
|
||||
&[("numbers".to_string(), ColumnType::U64)],
|
||||
@@ -84,7 +70,7 @@ fn test_group_columns_with_required_column() {
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -93,17 +79,17 @@ fn test_group_columns_required_column_with_no_existing_columns() {
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(
|
||||
columnars,
|
||||
&[("required_col".to_string(), ColumnType::Str)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
let column_map: BTreeMap<_, _> = group_columns_for_merge(
|
||||
columnars,
|
||||
&[("required_col".to_string(), ColumnType::Str)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 2);
|
||||
let columns = column_map
|
||||
.get(&("required_col".to_string(), ColumnType::Str))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("required_col".to_string(), ColumnTypeCategory::Str))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert_eq!(columns.len(), 2);
|
||||
assert!(columns[0].is_none());
|
||||
assert!(columns[1].is_none());
|
||||
@@ -115,7 +101,7 @@ fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_ru
|
||||
let columnar2 = make_columnar("numbers", &[2i64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(
|
||||
columnars,
|
||||
&[("numbers".to_string(), ColumnType::U64)],
|
||||
@@ -123,7 +109,7 @@ fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_ru
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -132,21 +118,23 @@ fn test_missing_column() {
|
||||
let columnar2 = make_columnar("numbers2", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 2);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
{
|
||||
let columns = column_map
|
||||
.get(&("numbers".to_string(), ColumnType::I64))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("numbers".to_string(), ColumnTypeCategory::Numerical))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert!(columns[0].is_some());
|
||||
assert!(columns[1].is_none());
|
||||
}
|
||||
{
|
||||
let columns = column_map
|
||||
.get(&("numbers2".to_string(), ColumnType::U64))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("numbers2".to_string(), ColumnTypeCategory::Numerical))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert!(columns[0].is_none());
|
||||
assert!(columns[1].is_some());
|
||||
}
|
||||
@@ -244,7 +232,9 @@ fn test_merge_columnar_numbers() {
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("numbers").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::F64(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::F64(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(vals.first(0u32), Some(-1f64));
|
||||
assert_eq!(vals.first(1u32), None);
|
||||
@@ -270,7 +260,9 @@ fn test_merge_columnar_texts() {
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("texts").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Str(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Str(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.ords().get_cardinality(), Cardinality::Optional);
|
||||
|
||||
let get_str_for_ord = |ord| {
|
||||
@@ -317,7 +309,9 @@ fn test_merge_columnar_byte() {
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("bytes").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
let get_bytes_for_ord = |ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(ord, &mut out).unwrap();
|
||||
@@ -371,7 +365,9 @@ fn test_merge_columnar_byte_with_missing() {
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("col").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
let get_bytes_for_ord = |ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(ord, &mut out).unwrap();
|
||||
@@ -423,7 +419,9 @@ fn test_merge_columnar_different_types() {
|
||||
|
||||
// numeric column
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::I64(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(vals.values_for_doc(0).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(1).collect_vec(), vec![]);
|
||||
@@ -433,7 +431,9 @@ fn test_merge_columnar_different_types() {
|
||||
|
||||
// text column
|
||||
let dynamic_column = cols[1].open().unwrap();
|
||||
let DynamicColumn::Str(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Str(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.ords().get_cardinality(), Cardinality::Optional);
|
||||
let get_str_for_ord = |ord| {
|
||||
let mut out = String::new();
|
||||
|
||||
@@ -102,30 +102,41 @@ impl ColumnarReader {
|
||||
pub fn num_rows(&self) -> RowId {
|
||||
self.num_rows
|
||||
}
|
||||
// Iterate over the columns in a sorted way
|
||||
pub fn iter_columns(
|
||||
&self,
|
||||
) -> io::Result<impl Iterator<Item = (String, DynamicColumnHandle)> + '_> {
|
||||
let mut stream = self.column_dictionary.stream()?;
|
||||
Ok(std::iter::from_fn(move || {
|
||||
if stream.advance() {
|
||||
let key_bytes: &[u8] = stream.key();
|
||||
let column_code: u8 = key_bytes.last().cloned().unwrap();
|
||||
// TODO Error Handling. The API gets quite ugly when returning the error here, so
|
||||
// instead we could just check the first N columns upfront.
|
||||
let column_type: ColumnType = ColumnType::try_from_code(column_code)
|
||||
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))
|
||||
.unwrap();
|
||||
let range = stream.value().clone();
|
||||
let column_name =
|
||||
// The last two bytes are respectively the 0u8 separator and the column_type.
|
||||
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
|
||||
let file_slice = self
|
||||
.column_data
|
||||
.slice(range.start as usize..range.end as usize);
|
||||
let column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
};
|
||||
Some((column_name, column_handle))
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}))
|
||||
}
|
||||
|
||||
// TODO Add unit tests
|
||||
pub fn list_columns(&self) -> io::Result<Vec<(String, DynamicColumnHandle)>> {
|
||||
let mut stream = self.column_dictionary.stream()?;
|
||||
let mut results = Vec::new();
|
||||
while stream.advance() {
|
||||
let key_bytes: &[u8] = stream.key();
|
||||
let column_code: u8 = key_bytes.last().cloned().unwrap();
|
||||
let column_type: ColumnType = ColumnType::try_from_code(column_code)
|
||||
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
|
||||
let range = stream.value().clone();
|
||||
let column_name =
|
||||
// The last two bytes are respectively the 0u8 separator and the column_type.
|
||||
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
|
||||
let file_slice = self
|
||||
.column_data
|
||||
.slice(range.start as usize..range.end as usize);
|
||||
let column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
};
|
||||
results.push((column_name, column_handle));
|
||||
}
|
||||
Ok(results)
|
||||
Ok(self.iter_columns()?.collect())
|
||||
}
|
||||
|
||||
fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {
|
||||
|
||||
@@ -269,7 +269,8 @@ impl StrOrBytesColumnWriter {
|
||||
dictionaries: &mut [DictionaryBuilder],
|
||||
arena: &mut MemoryArena,
|
||||
) {
|
||||
let unordered_id = dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes);
|
||||
let unordered_id =
|
||||
dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes, arena);
|
||||
self.column_writer.record(doc, unordered_id, arena);
|
||||
}
|
||||
|
||||
|
||||
@@ -13,9 +13,7 @@ pub(crate) use serializer::ColumnarSerializer;
|
||||
use stacker::{Addr, ArenaHashMap, MemoryArena};
|
||||
|
||||
use crate::column_index::SerializableColumnIndex;
|
||||
use crate::column_values::{
|
||||
ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
|
||||
};
|
||||
use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
|
||||
use crate::columnar::column_type::ColumnType;
|
||||
use crate::columnar::writer::column_writers::{
|
||||
ColumnWriter, NumericalColumnWriter, StrOrBytesColumnWriter,
|
||||
@@ -79,7 +77,6 @@ fn mutate_or_create_column<V, TMutator>(
|
||||
|
||||
impl ColumnarWriter {
|
||||
pub fn mem_usage(&self) -> usize {
|
||||
// TODO add dictionary builders.
|
||||
self.arena.mem_usage()
|
||||
+ self.numerical_field_hash_map.mem_usage()
|
||||
+ self.bool_field_hash_map.mem_usage()
|
||||
@@ -87,6 +84,11 @@ impl ColumnarWriter {
|
||||
+ self.str_field_hash_map.mem_usage()
|
||||
+ self.ip_addr_field_hash_map.mem_usage()
|
||||
+ self.datetime_field_hash_map.mem_usage()
|
||||
+ self
|
||||
.dictionaries
|
||||
.iter()
|
||||
.map(|dict| dict.mem_usage())
|
||||
.sum::<usize>()
|
||||
}
|
||||
|
||||
/// Returns the list of doc ids from 0..num_docs sorted by the `sort_field`
|
||||
@@ -98,9 +100,15 @@ impl ColumnarWriter {
|
||||
///
|
||||
/// The sort applied is stable.
|
||||
pub fn sort_order(&self, sort_field: &str, num_docs: RowId, reversed: bool) -> Vec<u32> {
|
||||
let Some(numerical_col_writer) =
|
||||
self.numerical_field_hash_map.get::<NumericalColumnWriter>(sort_field.as_bytes()) else {
|
||||
return Vec::new();
|
||||
let Some(numerical_col_writer) = self
|
||||
.numerical_field_hash_map
|
||||
.get::<NumericalColumnWriter>(sort_field.as_bytes())
|
||||
.or_else(|| {
|
||||
self.datetime_field_hash_map
|
||||
.get::<NumericalColumnWriter>(sort_field.as_bytes())
|
||||
})
|
||||
else {
|
||||
return Vec::new();
|
||||
};
|
||||
let mut symbols_buffer = Vec::new();
|
||||
let mut values = Vec::new();
|
||||
@@ -328,7 +336,7 @@ impl ColumnarWriter {
|
||||
let mut columns: Vec<(&[u8], ColumnType, Addr)> = self
|
||||
.numerical_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| {
|
||||
.map(|(column_name, addr)| {
|
||||
let numerical_column_writer: NumericalColumnWriter =
|
||||
self.numerical_field_hash_map.read(addr);
|
||||
let column_type = numerical_column_writer.numerical_type().into();
|
||||
@@ -338,27 +346,27 @@ impl ColumnarWriter {
|
||||
columns.extend(
|
||||
self.bytes_field_hash_map
|
||||
.iter()
|
||||
.map(|(term, addr, _)| (term, ColumnType::Bytes, addr)),
|
||||
.map(|(term, addr)| (term, ColumnType::Bytes, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.str_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::Str, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::Str, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.bool_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::Bool, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::Bool, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.ip_addr_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::IpAddr, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::IpAddr, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.datetime_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::DateTime, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::DateTime, addr)),
|
||||
);
|
||||
columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
|
||||
|
||||
@@ -427,6 +435,7 @@ impl ColumnarWriter {
|
||||
&mut symbol_byte_buffer,
|
||||
),
|
||||
buffers,
|
||||
&self.arena,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
@@ -480,6 +489,7 @@ impl ColumnarWriter {
|
||||
|
||||
// Serialize [Dictionary, Column, dictionary num bytes U32::LE]
|
||||
// Column: [Column Index, Column Values, column index num bytes U32::LE]
|
||||
#[allow(clippy::too_many_arguments)]
|
||||
fn serialize_bytes_or_str_column(
|
||||
cardinality: Cardinality,
|
||||
num_docs: RowId,
|
||||
@@ -487,6 +497,7 @@ fn serialize_bytes_or_str_column(
|
||||
dictionary_builder: &DictionaryBuilder,
|
||||
operation_it: impl Iterator<Item = ColumnOperation<UnorderedId>>,
|
||||
buffers: &mut SpareBuffers,
|
||||
arena: &MemoryArena,
|
||||
wrt: impl io::Write,
|
||||
) -> io::Result<()> {
|
||||
let SpareBuffers {
|
||||
@@ -495,7 +506,8 @@ fn serialize_bytes_or_str_column(
|
||||
..
|
||||
} = buffers;
|
||||
let mut counting_writer = CountingWriter::wrap(wrt);
|
||||
let term_id_mapping: TermIdMapping = dictionary_builder.serialize(&mut counting_writer)?;
|
||||
let term_id_mapping: TermIdMapping =
|
||||
dictionary_builder.serialize(arena, &mut counting_writer)?;
|
||||
let dictionary_num_bytes: u32 = counting_writer.written_bytes() as u32;
|
||||
let mut wrt = counting_writer.finish();
|
||||
let operation_iterator = operation_it.map(|symbol: ColumnOperation<UnorderedId>| {
|
||||
@@ -631,10 +643,7 @@ fn send_to_serialize_column_mappable_to_u128<
|
||||
value_index_builders: &mut PreallocatedIndexBuilders,
|
||||
values: &mut Vec<T>,
|
||||
mut wrt: impl io::Write,
|
||||
) -> io::Result<()>
|
||||
where
|
||||
for<'a> VecColumn<'a, T>: ColumnValues<T>,
|
||||
{
|
||||
) -> io::Result<()> {
|
||||
values.clear();
|
||||
// TODO: split index and values
|
||||
let serializable_column_index = match cardinality {
|
||||
@@ -687,10 +696,7 @@ fn send_to_serialize_column_mappable_to_u64(
|
||||
value_index_builders: &mut PreallocatedIndexBuilders,
|
||||
values: &mut Vec<u64>,
|
||||
mut wrt: impl io::Write,
|
||||
) -> io::Result<()>
|
||||
where
|
||||
for<'a> VecColumn<'a, u64>: ColumnValues<u64>,
|
||||
{
|
||||
) -> io::Result<()> {
|
||||
values.clear();
|
||||
let serializable_column_index = match cardinality {
|
||||
Cardinality::Full => {
|
||||
|
||||
@@ -18,7 +18,12 @@ pub struct ColumnarSerializer<W: io::Write> {
|
||||
/// code.
|
||||
fn prepare_key(key: &[u8], column_type: ColumnType, buffer: &mut Vec<u8>) {
|
||||
buffer.clear();
|
||||
buffer.extend_from_slice(key);
|
||||
// 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.push(0u8);
|
||||
buffer.push(column_type.to_code());
|
||||
}
|
||||
@@ -96,14 +101,13 @@ 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"root\0child");
|
||||
assert_eq!(&buffer[..10], b"root0child");
|
||||
assert_eq!(buffer[10], 0u8);
|
||||
assert_eq!(buffer[11], ColumnType::Str.to_code());
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
use std::io;
|
||||
|
||||
use fnv::FnvHashMap;
|
||||
use sstable::SSTable;
|
||||
use stacker::{MemoryArena, SharedArenaHashMap};
|
||||
|
||||
pub(crate) struct TermIdMapping {
|
||||
unordered_to_ord: Vec<OrderedId>,
|
||||
@@ -31,26 +31,38 @@ pub struct OrderedId(pub u32);
|
||||
/// mapping.
|
||||
#[derive(Default)]
|
||||
pub(crate) struct DictionaryBuilder {
|
||||
dict: FnvHashMap<Vec<u8>, UnorderedId>,
|
||||
dict: SharedArenaHashMap,
|
||||
}
|
||||
|
||||
impl DictionaryBuilder {
|
||||
/// Get or allocate an unordered id.
|
||||
/// (This ID is simply an auto-incremented id.)
|
||||
pub fn get_or_allocate_id(&mut self, term: &[u8]) -> UnorderedId {
|
||||
if let Some(term_id) = self.dict.get(term) {
|
||||
return *term_id;
|
||||
}
|
||||
let new_id = UnorderedId(self.dict.len() as u32);
|
||||
self.dict.insert(term.to_vec(), new_id);
|
||||
new_id
|
||||
pub fn get_or_allocate_id(&mut self, term: &[u8], arena: &mut MemoryArena) -> UnorderedId {
|
||||
let next_id = self.dict.len() as u32;
|
||||
let unordered_id = self
|
||||
.dict
|
||||
.mutate_or_create(term, arena, |unordered_id: Option<u32>| {
|
||||
if let Some(unordered_id) = unordered_id {
|
||||
unordered_id
|
||||
} else {
|
||||
next_id
|
||||
}
|
||||
});
|
||||
UnorderedId(unordered_id)
|
||||
}
|
||||
|
||||
/// Serialize the dictionary into an fst, and returns the
|
||||
/// `UnorderedId -> TermOrdinal` map.
|
||||
pub fn serialize<'a, W: io::Write + 'a>(&self, wrt: &mut W) -> io::Result<TermIdMapping> {
|
||||
let mut terms: Vec<(&[u8], UnorderedId)> =
|
||||
self.dict.iter().map(|(k, v)| (k.as_slice(), *v)).collect();
|
||||
pub fn serialize<'a, W: io::Write + 'a>(
|
||||
&self,
|
||||
arena: &MemoryArena,
|
||||
wrt: &mut W,
|
||||
) -> io::Result<TermIdMapping> {
|
||||
let mut terms: Vec<(&[u8], UnorderedId)> = self
|
||||
.dict
|
||||
.iter(arena)
|
||||
.map(|(k, v)| (k, arena.read(v)))
|
||||
.collect();
|
||||
terms.sort_unstable_by_key(|(key, _)| *key);
|
||||
// TODO Remove the allocation.
|
||||
let mut unordered_to_ord: Vec<OrderedId> = vec![OrderedId(0u32); terms.len()];
|
||||
@@ -63,6 +75,10 @@ impl DictionaryBuilder {
|
||||
sstable_builder.finish()?;
|
||||
Ok(TermIdMapping { unordered_to_ord })
|
||||
}
|
||||
|
||||
pub(crate) fn mem_usage(&self) -> usize {
|
||||
self.dict.mem_usage()
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -71,12 +87,13 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn test_dictionary_builder() {
|
||||
let mut arena = MemoryArena::default();
|
||||
let mut dictionary_builder = DictionaryBuilder::default();
|
||||
let hello_uid = dictionary_builder.get_or_allocate_id(b"hello");
|
||||
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy");
|
||||
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax");
|
||||
let hello_uid = dictionary_builder.get_or_allocate_id(b"hello", &mut arena);
|
||||
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy", &mut arena);
|
||||
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax", &mut arena);
|
||||
let mut buffer = Vec::new();
|
||||
let id_mapping = dictionary_builder.serialize(&mut buffer).unwrap();
|
||||
let id_mapping = dictionary_builder.serialize(&arena, &mut buffer).unwrap();
|
||||
assert_eq!(id_mapping.to_ord(hello_uid), OrderedId(1));
|
||||
assert_eq!(id_mapping.to_ord(happy_uid), OrderedId(0));
|
||||
assert_eq!(id_mapping.to_ord(tax_uid), OrderedId(2));
|
||||
|
||||
@@ -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, NumericalType};
|
||||
use crate::{Cardinality, ColumnIndex, ColumnValues, NumericalType};
|
||||
|
||||
#[derive(Clone)]
|
||||
pub enum DynamicColumn {
|
||||
@@ -228,7 +228,7 @@ static_dynamic_conversions!(StrColumn, Str);
|
||||
static_dynamic_conversions!(BytesColumn, Bytes);
|
||||
static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
|
||||
|
||||
#[derive(Clone)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct DynamicColumnHandle {
|
||||
pub(crate) file_slice: FileSlice,
|
||||
pub(crate) column_type: ColumnType,
|
||||
@@ -247,7 +247,12 @@ impl DynamicColumnHandle {
|
||||
}
|
||||
|
||||
/// Returns the `u64` fast field reader reader associated with `fields` of types
|
||||
/// Str, u64, i64, f64, or datetime.
|
||||
/// 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`.
|
||||
///
|
||||
/// If not, the fastfield reader will returns the u64-value associated with the original
|
||||
/// FastValue.
|
||||
@@ -258,9 +263,15 @@ impl DynamicColumnHandle {
|
||||
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
|
||||
Ok(Some(column.term_ord_column))
|
||||
}
|
||||
ColumnType::Bool => Ok(None),
|
||||
ColumnType::IpAddr => Ok(None),
|
||||
ColumnType::I64 | ColumnType::U64 | ColumnType::F64 | ColumnType::DateTime => {
|
||||
ColumnType::IpAddr => {
|
||||
let column = crate::column::open_column_u128_as_compact_u64(column_bytes)?;
|
||||
Ok(Some(column))
|
||||
}
|
||||
ColumnType::Bool
|
||||
| ColumnType::I64
|
||||
| ColumnType::U64
|
||||
| ColumnType::F64
|
||||
| ColumnType::DateTime => {
|
||||
let column = crate::column::open_column_u64::<u64>(column_bytes)?;
|
||||
Ok(Some(column))
|
||||
}
|
||||
|
||||
@@ -1,3 +1,22 @@
|
||||
//! # Tantivy-Columnar
|
||||
//!
|
||||
//! `tantivy-columnar`provides a columnar storage for tantivy.
|
||||
//! The crate allows for efficient read operations on specific columns rather than entire records.
|
||||
//!
|
||||
//! ## Overview
|
||||
//!
|
||||
//! - **columnar**: Reading, writing, and merging multiple columns:
|
||||
//! - **[ColumnarWriter]**: Makes it possible to create a new columnar.
|
||||
//! - **[ColumnarReader]**: The ColumnarReader makes it possible to access a set of columns
|
||||
//! associated to field names.
|
||||
//! - **[merge_columnar]**: Contains the functionalities to merge multiple ColumnarReader or
|
||||
//! segments into a single one.
|
||||
//!
|
||||
//! - **column**: A single column, which contains
|
||||
//! - [column_index]: Resolves the rows for a document id. Manages the cardinality of the
|
||||
//! column.
|
||||
//! - [column_values]: Stores the values of a column in a dense format.
|
||||
|
||||
#![cfg_attr(all(feature = "unstable", test), feature(test))]
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -12,7 +31,7 @@ use std::io;
|
||||
|
||||
mod block_accessor;
|
||||
mod column;
|
||||
mod column_index;
|
||||
pub mod column_index;
|
||||
pub mod column_values;
|
||||
mod columnar;
|
||||
mod dictionary;
|
||||
@@ -94,6 +113,9 @@ 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
|
||||
}
|
||||
|
||||
@@ -26,7 +26,7 @@ fn test_dataframe_writer_str() {
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 87);
|
||||
assert_eq!(cols[0].num_bytes(), 73);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -40,7 +40,7 @@ fn test_dataframe_writer_bytes() {
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 87);
|
||||
assert_eq!(cols[0].num_bytes(), 73);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -57,7 +57,9 @@ fn test_dataframe_writer_bool() {
|
||||
assert_eq!(cols[0].num_bytes(), 22);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::Bool);
|
||||
let dyn_bool_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bool(bool_col) = dyn_bool_col else { panic!(); };
|
||||
let DynamicColumn::Bool(bool_col) = dyn_bool_col else {
|
||||
panic!();
|
||||
};
|
||||
let vals: Vec<Option<bool>> = (0..5).map(|row_id| bool_col.first(row_id)).collect();
|
||||
assert_eq!(&vals, &[None, Some(false), None, Some(true), None,]);
|
||||
}
|
||||
@@ -79,7 +81,9 @@ fn test_dataframe_writer_u64_multivalued() {
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 29);
|
||||
let dyn_i64_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(divisor_col) = dyn_i64_col else { panic!(); };
|
||||
let DynamicColumn::I64(divisor_col) = dyn_i64_col else {
|
||||
panic!();
|
||||
};
|
||||
assert_eq!(
|
||||
divisor_col.get_cardinality(),
|
||||
crate::Cardinality::Multivalued
|
||||
@@ -101,7 +105,9 @@ fn test_dataframe_writer_ip_addr() {
|
||||
assert_eq!(cols[0].num_bytes(), 42);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::IpAddr);
|
||||
let dyn_bool_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else { panic!(); };
|
||||
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else {
|
||||
panic!();
|
||||
};
|
||||
let vals: Vec<Option<Ipv6Addr>> = (0..5).map(|row_id| ip_col.first(row_id)).collect();
|
||||
assert_eq!(
|
||||
&vals,
|
||||
@@ -134,7 +140,9 @@ fn test_dataframe_writer_numerical() {
|
||||
// - null footer 6 bytes
|
||||
assert_eq!(cols[0].num_bytes(), 33);
|
||||
let column = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(column_i64) = column else { panic!(); };
|
||||
let DynamicColumn::I64(column_i64) = column else {
|
||||
panic!();
|
||||
};
|
||||
assert_eq!(column_i64.index.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(column_i64.first(0), None);
|
||||
assert_eq!(column_i64.first(1), Some(12i64));
|
||||
@@ -198,7 +206,9 @@ fn test_dictionary_encoded_str() {
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let col_handles = columnar_reader.read_columns("my.column").unwrap();
|
||||
assert_eq!(col_handles.len(), 1);
|
||||
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else { panic!(); };
|
||||
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else {
|
||||
panic!();
|
||||
};
|
||||
let index: Vec<Option<u64>> = (0..5).map(|row_id| str_col.ords().first(row_id)).collect();
|
||||
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
|
||||
assert_eq!(str_col.num_rows(), 5);
|
||||
@@ -230,7 +240,9 @@ fn test_dictionary_encoded_bytes() {
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let col_handles = columnar_reader.read_columns("my.column").unwrap();
|
||||
assert_eq!(col_handles.len(), 1);
|
||||
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else { panic!(); };
|
||||
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else {
|
||||
panic!();
|
||||
};
|
||||
let index: Vec<Option<u64>> = (0..5)
|
||||
.map(|row_id| bytes_col.ords().first(row_id))
|
||||
.collect();
|
||||
@@ -318,9 +330,9 @@ fn bytes_strategy() -> impl Strategy<Value = &'static [u8]> {
|
||||
// A random column value
|
||||
fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
|
||||
prop_oneof![
|
||||
10 => string_strategy().prop_map(|s| ColumnValue::Str(s)),
|
||||
1 => bytes_strategy().prop_map(|b| ColumnValue::Bytes(b)),
|
||||
40 => num_strategy().prop_map(|n| ColumnValue::Numerical(n)),
|
||||
10 => string_strategy().prop_map(ColumnValue::Str),
|
||||
1 => bytes_strategy().prop_map(ColumnValue::Bytes),
|
||||
40 => num_strategy().prop_map(ColumnValue::Numerical),
|
||||
1 => (1u16..3u16).prop_map(|ip_addr_byte| ColumnValue::IpAddr(Ipv6Addr::new(
|
||||
127,
|
||||
0,
|
||||
@@ -331,7 +343,7 @@ fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
|
||||
0,
|
||||
ip_addr_byte
|
||||
))),
|
||||
1 => any::<bool>().prop_map(|b| ColumnValue::Bool(b)),
|
||||
1 => any::<bool>().prop_map(ColumnValue::Bool),
|
||||
1 => (0_679_723_993i64..1_679_723_995i64)
|
||||
.prop_map(|val| { ColumnValue::DateTime(DateTime::from_timestamp_secs(val)) })
|
||||
]
|
||||
@@ -407,8 +419,8 @@ fn build_columnar_with_mapping(
|
||||
columnar_writer
|
||||
.serialize(num_docs, old_to_new_row_ids_opt, &mut buffer)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
columnar_reader
|
||||
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
fn build_columnar(docs: &[Vec<(&'static str, ColumnValue)>]) -> ColumnarReader {
|
||||
@@ -533,28 +545,36 @@ trait AssertEqualToColumnValue {
|
||||
|
||||
impl AssertEqualToColumnValue for bool {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::Bool(val) = column_value else { panic!() };
|
||||
let ColumnValue::Bool(val) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, val);
|
||||
}
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for Ipv6Addr {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::IpAddr(val) = column_value else { panic!() };
|
||||
let ColumnValue::IpAddr(val) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, val);
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: Coerce + PartialEq + Debug + Into<NumericalValue>> AssertEqualToColumnValue for T {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::Numerical(num) = column_value else { panic!() };
|
||||
let ColumnValue::Numerical(num) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, &T::coerce(*num));
|
||||
}
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for DateTime {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::DateTime(dt) = column_value else { panic!() };
|
||||
let ColumnValue::DateTime(dt) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, dt);
|
||||
}
|
||||
}
|
||||
@@ -726,7 +746,7 @@ proptest! {
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_readers_arr[..]).into();
|
||||
crate::merge_columnar(&columnar_readers_arr[..], &[], stack_merge_order, &mut output).unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().cloned().flatten().collect();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().flatten().cloned().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
@@ -752,7 +772,7 @@ fn test_columnar_merging_empty_columnar() {
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
|
||||
columnar_docs.iter().cloned().flatten().collect();
|
||||
columnar_docs.iter().flatten().cloned().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
@@ -789,7 +809,7 @@ fn test_columnar_merging_number_columns() {
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
|
||||
columnar_docs.iter().cloned().flatten().collect();
|
||||
columnar_docs.iter().flatten().cloned().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-common"
|
||||
version = "0.5.0"
|
||||
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= "0.5", 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"] }
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io::Write;
|
||||
use std::{fmt, io, u64};
|
||||
|
||||
|
||||
@@ -1,11 +1,14 @@
|
||||
#![allow(deprecated)]
|
||||
|
||||
use std::fmt;
|
||||
use std::io::{Read, Write};
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
use time::format_description::well_known::Rfc3339;
|
||||
use time::{OffsetDateTime, PrimitiveDateTime, UtcOffset};
|
||||
|
||||
use crate::BinarySerializable;
|
||||
|
||||
/// Precision with which datetimes are truncated when stored in fast fields. This setting is only
|
||||
/// relevant for fast fields. In the docstore, datetimes are always saved with nanosecond precision.
|
||||
#[derive(
|
||||
@@ -37,7 +40,7 @@ pub type DatePrecision = 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)]
|
||||
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
|
||||
pub struct DateTime {
|
||||
// Timestamp in nanoseconds.
|
||||
pub(crate) timestamp_nanos: i64,
|
||||
@@ -164,3 +167,15 @@ impl fmt::Debug for DateTime {
|
||||
f.write_str(&utc_rfc3339)
|
||||
}
|
||||
}
|
||||
|
||||
impl BinarySerializable for DateTime {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
|
||||
let timestamp_micros = self.into_timestamp_micros();
|
||||
<i64 as BinarySerializable>::serialize(×tamp_micros, writer)
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> std::io::Result<Self> {
|
||||
let timestamp_micros = <i64 as BinarySerializable>::deserialize(reader)?;
|
||||
Ok(Self::from_timestamp_micros(timestamp_micros))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
use std::fs::File;
|
||||
use std::ops::{Deref, Range, RangeBounds};
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io};
|
||||
@@ -32,6 +33,62 @@ pub trait FileHandle: 'static + Send + Sync + HasLen + fmt::Debug {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
/// A File with it's length included.
|
||||
pub struct WrapFile {
|
||||
file: File,
|
||||
len: usize,
|
||||
}
|
||||
impl WrapFile {
|
||||
/// Creates a new WrapFile and stores its length.
|
||||
pub fn new(file: File) -> io::Result<Self> {
|
||||
let len = file.metadata()?.len() as usize;
|
||||
Ok(WrapFile { file, len })
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl FileHandle for WrapFile {
|
||||
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
|
||||
let file_len = self.len();
|
||||
|
||||
// Calculate the actual range to read, ensuring it stays within file boundaries
|
||||
let start = range.start;
|
||||
let end = range.end.min(file_len);
|
||||
|
||||
// Ensure the start is before the end of the range
|
||||
if start >= end {
|
||||
return Err(io::Error::new(io::ErrorKind::InvalidInput, "Invalid range"));
|
||||
}
|
||||
|
||||
let mut buffer = vec![0; end - start];
|
||||
|
||||
#[cfg(unix)]
|
||||
{
|
||||
use std::os::unix::prelude::FileExt;
|
||||
self.file.read_exact_at(&mut buffer, start as u64)?;
|
||||
}
|
||||
|
||||
#[cfg(not(unix))]
|
||||
{
|
||||
use std::io::{Read, Seek};
|
||||
let mut file = self.file.try_clone()?; // Clone the file to read from it separately
|
||||
// Seek to the start position in the file
|
||||
file.seek(io::SeekFrom::Start(start as u64))?;
|
||||
// Read the data into the buffer
|
||||
file.read_exact(&mut buffer)?;
|
||||
}
|
||||
|
||||
Ok(OwnedBytes::new(buffer))
|
||||
}
|
||||
// todo implement async
|
||||
}
|
||||
impl HasLen for WrapFile {
|
||||
fn len(&self) -> usize {
|
||||
self.len
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl FileHandle for &'static [u8] {
|
||||
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
|
||||
@@ -67,6 +124,30 @@ impl fmt::Debug for FileSlice {
|
||||
}
|
||||
}
|
||||
|
||||
impl FileSlice {
|
||||
pub fn stream_file_chunks(&self) -> impl Iterator<Item = io::Result<OwnedBytes>> + '_ {
|
||||
let len = self.range.end;
|
||||
let mut start = self.range.start;
|
||||
std::iter::from_fn(move || {
|
||||
/// Returns chunks of 1MB of data from the FileHandle.
|
||||
const CHUNK_SIZE: usize = 1024 * 1024; // 1MB
|
||||
|
||||
if start < len {
|
||||
let end = (start + CHUNK_SIZE).min(len);
|
||||
let range = start..end;
|
||||
let chunk = self.data.read_bytes(range);
|
||||
start += CHUNK_SIZE;
|
||||
match chunk {
|
||||
Ok(chunk) => Some(Ok(chunk)),
|
||||
Err(e) => Some(Err(e)),
|
||||
}
|
||||
} else {
|
||||
None
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
/// Takes a range, a `RangeBounds` object, and returns
|
||||
/// a `Range` that corresponds to the relative application of the
|
||||
/// `RangeBounds` object to the original `Range`.
|
||||
|
||||
@@ -27,15 +27,15 @@ pub trait GroupByIteratorExtended: Iterator {
|
||||
where
|
||||
Self: Sized,
|
||||
F: FnMut(&Self::Item) -> K,
|
||||
K: PartialEq + Copy,
|
||||
Self::Item: Copy,
|
||||
K: PartialEq + Clone,
|
||||
Self::Item: Clone,
|
||||
{
|
||||
GroupByIterator::new(self, key)
|
||||
}
|
||||
}
|
||||
impl<I: Iterator> GroupByIteratorExtended for I {}
|
||||
|
||||
pub struct GroupByIterator<I, F, K: Copy>
|
||||
pub struct GroupByIterator<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -50,7 +50,7 @@ where
|
||||
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
|
||||
}
|
||||
|
||||
struct GroupByShared<I, F, K: Copy>
|
||||
struct GroupByShared<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -63,7 +63,7 @@ impl<I, F, K> GroupByIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
K: Copy,
|
||||
K: Clone,
|
||||
{
|
||||
fn new(inner: I, group_by_fn: F) -> Self {
|
||||
let inner = GroupByShared {
|
||||
@@ -80,28 +80,28 @@ where
|
||||
impl<I, F, K> Iterator for GroupByIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
I::Item: Copy,
|
||||
I::Item: Clone,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
K: Copy,
|
||||
K: Clone,
|
||||
{
|
||||
type Item = (K, GroupIterator<I, F, K>);
|
||||
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let mut inner = self.inner.borrow_mut();
|
||||
let value = *inner.iter.peek()?;
|
||||
let value = inner.iter.peek()?.clone();
|
||||
let key = (inner.group_by_fn)(&value);
|
||||
|
||||
let inner = self.inner.clone();
|
||||
|
||||
let group_iter = GroupIterator {
|
||||
inner,
|
||||
group_key: key,
|
||||
group_key: key.clone(),
|
||||
};
|
||||
Some((key, group_iter))
|
||||
}
|
||||
}
|
||||
|
||||
pub struct GroupIterator<I, F, K: Copy>
|
||||
pub struct GroupIterator<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -110,10 +110,10 @@ where
|
||||
group_key: K,
|
||||
}
|
||||
|
||||
impl<I, F, K: PartialEq + Copy> Iterator for GroupIterator<I, F, K>
|
||||
impl<I, F, K: PartialEq + Clone> Iterator for GroupIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
I::Item: Copy,
|
||||
I::Item: Clone,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
{
|
||||
type Item = I::Item;
|
||||
@@ -121,7 +121,7 @@ where
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let mut inner = self.inner.borrow_mut();
|
||||
// peek if next value is in group
|
||||
let peek_val = *inner.iter.peek()?;
|
||||
let peek_val = inner.iter.peek()?.clone();
|
||||
if (inner.group_by_fn)(&peek_val) == self.group_key {
|
||||
inner.iter.next()
|
||||
} else {
|
||||
|
||||
112
common/src/json_path_writer.rs
Normal file
112
common/src/json_path_writer.rs
Normal file
@@ -0,0 +1,112 @@
|
||||
use crate::replace_in_place;
|
||||
|
||||
/// Separates the different segments of a json path.
|
||||
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]) };
|
||||
|
||||
/// Create a new JsonPathWriter, that creates flattened json paths for tantivy.
|
||||
#[derive(Clone, Debug, Default)]
|
||||
pub struct JsonPathWriter {
|
||||
path: String,
|
||||
indices: Vec<usize>,
|
||||
expand_dots: bool,
|
||||
}
|
||||
|
||||
impl JsonPathWriter {
|
||||
pub fn new() -> Self {
|
||||
JsonPathWriter {
|
||||
path: String::new(),
|
||||
indices: Vec::new(),
|
||||
expand_dots: false,
|
||||
}
|
||||
}
|
||||
|
||||
/// When expand_dots is enabled, json object like
|
||||
/// `{"k8s.node.id": 5}` is processed as if it was
|
||||
/// `{"k8s": {"node": {"id": 5}}}`.
|
||||
/// This option has the merit of allowing users to
|
||||
/// write queries like `k8s.node.id:5`.
|
||||
/// On the other, enabling that feature can lead to
|
||||
/// ambiguity.
|
||||
#[inline]
|
||||
pub fn set_expand_dots(&mut self, expand_dots: bool) {
|
||||
self.expand_dots = expand_dots;
|
||||
}
|
||||
|
||||
/// Push a new segment to the path.
|
||||
#[inline]
|
||||
pub fn push(&mut self, segment: &str) {
|
||||
let len_path = self.path.len();
|
||||
self.indices.push(len_path);
|
||||
if !self.path.is_empty() {
|
||||
self.path.push_str(JSON_PATH_SEGMENT_SEP_STR);
|
||||
}
|
||||
self.path.push_str(segment);
|
||||
if self.expand_dots {
|
||||
// This might include the separation byte, which is ok because it is not a dot.
|
||||
let appended_segment = &mut self.path[len_path..];
|
||||
// The unsafe below is safe as long as b'.' and JSON_PATH_SEGMENT_SEP are
|
||||
// valid single byte ut8 strings.
|
||||
// By utf-8 design, they cannot be part of another codepoint.
|
||||
unsafe {
|
||||
replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, appended_segment.as_bytes_mut())
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/// Remove the last segment. Does nothing if the path is empty.
|
||||
#[inline]
|
||||
pub fn pop(&mut self) {
|
||||
if let Some(last_idx) = self.indices.pop() {
|
||||
self.path.truncate(last_idx);
|
||||
}
|
||||
}
|
||||
|
||||
/// Clear the path.
|
||||
#[inline]
|
||||
pub fn clear(&mut self) {
|
||||
self.path.clear();
|
||||
self.indices.clear();
|
||||
}
|
||||
|
||||
/// Get the current path.
|
||||
#[inline]
|
||||
pub fn as_str(&self) -> &str {
|
||||
&self.path
|
||||
}
|
||||
}
|
||||
|
||||
impl From<JsonPathWriter> for String {
|
||||
#[inline]
|
||||
fn from(value: JsonPathWriter) -> Self {
|
||||
value.path
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn json_path_writer_test() {
|
||||
let mut writer = JsonPathWriter::new();
|
||||
|
||||
writer.push("root");
|
||||
assert_eq!(writer.as_str(), "root");
|
||||
|
||||
writer.push("child");
|
||||
assert_eq!(writer.as_str(), "root\u{1}child");
|
||||
|
||||
writer.pop();
|
||||
assert_eq!(writer.as_str(), "root");
|
||||
|
||||
writer.push("k8s.node.id");
|
||||
assert_eq!(writer.as_str(), "root\u{1}k8s.node.id");
|
||||
|
||||
writer.set_expand_dots(true);
|
||||
writer.pop();
|
||||
writer.push("k8s.node.id");
|
||||
assert_eq!(writer.as_str(), "root\u{1}k8s\u{1}node\u{1}id");
|
||||
}
|
||||
}
|
||||
@@ -9,6 +9,7 @@ mod byte_count;
|
||||
mod datetime;
|
||||
pub mod file_slice;
|
||||
mod group_by;
|
||||
mod json_path_writer;
|
||||
mod serialize;
|
||||
mod vint;
|
||||
mod writer;
|
||||
@@ -18,6 +19,7 @@ pub use byte_count::ByteCount;
|
||||
pub use datetime::DatePrecision;
|
||||
pub use datetime::{DateTime, DateTimePrecision};
|
||||
pub use group_by::GroupByIteratorExtended;
|
||||
pub use json_path_writer::JsonPathWriter;
|
||||
pub use ownedbytes::{OwnedBytes, StableDeref};
|
||||
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
|
||||
pub use vint::{
|
||||
@@ -116,6 +118,7 @@ pub fn u64_to_f64(val: u64) -> f64 {
|
||||
///
|
||||
/// This function assumes that the needle is rarely contained in the bytes string
|
||||
/// and offers a fast path if the needle is not present.
|
||||
#[inline]
|
||||
pub fn replace_in_place(needle: u8, replacement: u8, bytes: &mut [u8]) {
|
||||
if !bytes.contains(&needle) {
|
||||
return;
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
use std::borrow::Cow;
|
||||
use std::io::{Read, Write};
|
||||
use std::{fmt, io};
|
||||
|
||||
@@ -249,11 +250,47 @@ impl BinarySerializable for String {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> BinarySerializable for Cow<'a, str> {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
|
||||
let data: &[u8] = self.as_bytes();
|
||||
VInt(data.len() as u64).serialize(writer)?;
|
||||
writer.write_all(data)
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Cow<'a, str>> {
|
||||
let string_length = VInt::deserialize(reader)?.val() as usize;
|
||||
let mut result = String::with_capacity(string_length);
|
||||
reader
|
||||
.take(string_length as u64)
|
||||
.read_to_string(&mut result)?;
|
||||
Ok(Cow::Owned(result))
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> BinarySerializable for Cow<'a, [u8]> {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
|
||||
VInt(self.len() as u64).serialize(writer)?;
|
||||
for it in self.iter() {
|
||||
it.serialize(writer)?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Cow<'a, [u8]>> {
|
||||
let num_items = VInt::deserialize(reader)?.val();
|
||||
let mut items: Vec<u8> = Vec::with_capacity(num_items as usize);
|
||||
for _ in 0..num_items {
|
||||
let item = u8::deserialize(reader)?;
|
||||
items.push(item);
|
||||
}
|
||||
Ok(Cow::Owned(items))
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
pub mod test {
|
||||
|
||||
use super::{VInt, *};
|
||||
use crate::serialize::BinarySerializable;
|
||||
use super::*;
|
||||
pub fn fixed_size_test<O: BinarySerializable + FixedSize + Default>() {
|
||||
let mut buffer = Vec::new();
|
||||
O::default().serialize(&mut buffer).unwrap();
|
||||
|
||||
@@ -12,7 +12,7 @@ use tantivy::aggregation::agg_result::AggregationResults;
|
||||
use tantivy::aggregation::AggregationCollector;
|
||||
use tantivy::query::AllQuery;
|
||||
use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing, FAST};
|
||||
use tantivy::Index;
|
||||
use tantivy::{Index, IndexWriter, TantivyDocument};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// # Create Schema
|
||||
@@ -132,10 +132,10 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let stream = Deserializer::from_str(data).into_iter::<Value>();
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
let mut num_indexed = 0;
|
||||
for value in stream {
|
||||
let doc = schema.parse_document(&serde_json::to_string(&value.unwrap())?)?;
|
||||
let doc = TantivyDocument::parse_json(&schema, &serde_json::to_string(&value.unwrap())?)?;
|
||||
index_writer.add_document(doc)?;
|
||||
num_indexed += 1;
|
||||
if num_indexed > 4 {
|
||||
|
||||
@@ -15,7 +15,7 @@
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, ReloadPolicy};
|
||||
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
@@ -75,7 +75,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// Here we give tantivy a budget of `50MB`.
|
||||
// Using a bigger memory_arena for the indexer may increase
|
||||
// throughput, but 50 MB is already plenty.
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// Let's index our documents!
|
||||
// We first need a handle on the title and the body field.
|
||||
@@ -87,7 +87,7 @@ fn main() -> tantivy::Result<()> {
|
||||
let title = schema.get_field("title").unwrap();
|
||||
let body = schema.get_field("body").unwrap();
|
||||
|
||||
let mut old_man_doc = Document::default();
|
||||
let mut old_man_doc = TantivyDocument::default();
|
||||
old_man_doc.add_text(title, "The Old Man and the Sea");
|
||||
old_man_doc.add_text(
|
||||
body,
|
||||
@@ -164,7 +164,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// will reload the index automatically after each commit.
|
||||
let reader = index
|
||||
.reader_builder()
|
||||
.reload_policy(ReloadPolicy::OnCommit)
|
||||
.reload_policy(ReloadPolicy::OnCommitWithDelay)
|
||||
.try_into()?;
|
||||
|
||||
// We now need to acquire a searcher.
|
||||
@@ -217,9 +217,23 @@ fn main() -> tantivy::Result<()> {
|
||||
// the document returned will only contain
|
||||
// a title.
|
||||
for (_score, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
println!("{}", schema.to_json(&retrieved_doc));
|
||||
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
|
||||
println!("{}", retrieved_doc.to_json(&schema));
|
||||
}
|
||||
|
||||
// We can also get an explanation to understand
|
||||
// how a found document got its score.
|
||||
let query = query_parser.parse_query("title:sea^20 body:whale^70")?;
|
||||
|
||||
let (_score, doc_address) = searcher
|
||||
.search(&query, &TopDocs::with_limit(1))?
|
||||
.into_iter()
|
||||
.next()
|
||||
.unwrap();
|
||||
|
||||
let explanation = query.explain(&searcher, doc_address)?;
|
||||
|
||||
println!("{}", explanation.to_pretty_json());
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
@@ -13,7 +13,7 @@ use columnar::Column;
|
||||
use tantivy::collector::{Collector, SegmentCollector};
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
|
||||
use tantivy::{doc, Index, Score, SegmentReader};
|
||||
use tantivy::{doc, Index, IndexWriter, Score, SegmentReader};
|
||||
|
||||
#[derive(Default)]
|
||||
struct Stats {
|
||||
@@ -142,7 +142,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// this example.
|
||||
let index = Index::create_in_ram(schema);
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
index_writer.add_document(doc!(
|
||||
product_name => "Super Broom 2000",
|
||||
product_description => "While it is ok for short distance travel, this broom \
|
||||
|
||||
@@ -6,7 +6,7 @@ use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::tokenizer::NgramTokenizer;
|
||||
use tantivy::{doc, Index};
|
||||
use tantivy::{doc, Index, IndexWriter};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// # Defining the schema
|
||||
@@ -53,7 +53,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// this will store tokens of 3 characters each
|
||||
index
|
||||
.tokenizers()
|
||||
.register("ngram3", NgramTokenizer::new(3, 3, false));
|
||||
.register("ngram3", NgramTokenizer::new(3, 3, false).unwrap());
|
||||
|
||||
// To insert document we need an index writer.
|
||||
// There must be only one writer at a time.
|
||||
@@ -62,7 +62,7 @@ fn main() -> tantivy::Result<()> {
|
||||
//
|
||||
// Here we use a buffer of 50MB per thread. Using a bigger
|
||||
// memory arena for the indexer can increase its throughput.
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
index_writer.add_document(doc!(
|
||||
title => "The Old Man and the Sea",
|
||||
body => "He was an old man who fished alone in a skiff in the Gulf Stream and \
|
||||
@@ -103,8 +103,8 @@ fn main() -> tantivy::Result<()> {
|
||||
let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
|
||||
|
||||
for (_, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
println!("{}", schema.to_json(&retrieved_doc));
|
||||
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
|
||||
println!("{}", retrieved_doc.to_json(&schema));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
|
||||
@@ -4,8 +4,8 @@
|
||||
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::{DateOptions, Schema, Value, INDEXED, STORED, STRING};
|
||||
use tantivy::Index;
|
||||
use tantivy::schema::{DateOptions, Document, OwnedValue, Schema, INDEXED, STORED, STRING};
|
||||
use tantivy::{Index, IndexWriter, TantivyDocument};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// # Defining the schema
|
||||
@@ -22,16 +22,18 @@ fn main() -> tantivy::Result<()> {
|
||||
// # Indexing documents
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
// The dates are passed as string in the RFC3339 format
|
||||
let doc = schema.parse_document(
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"occurred_at": "2022-06-22T12:53:50.53Z",
|
||||
"event": "pull-request"
|
||||
}"#,
|
||||
)?;
|
||||
index_writer.add_document(doc)?;
|
||||
let doc = schema.parse_document(
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"occurred_at": "2022-06-22T13:00:00.22Z",
|
||||
"event": "comment"
|
||||
@@ -58,13 +60,13 @@ fn main() -> tantivy::Result<()> {
|
||||
let count_docs = searcher.search(&*query, &TopDocs::with_limit(4))?;
|
||||
assert_eq!(count_docs.len(), 1);
|
||||
for (_score, doc_address) in count_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
let retrieved_doc = searcher.doc::<TantivyDocument>(doc_address)?;
|
||||
assert!(matches!(
|
||||
retrieved_doc.get_first(occurred_at),
|
||||
Some(Value::Date(_))
|
||||
Some(OwnedValue::Date(_))
|
||||
));
|
||||
assert_eq!(
|
||||
schema.to_json(&retrieved_doc),
|
||||
retrieved_doc.to_json(&schema),
|
||||
r#"{"event":["comment"],"occurred_at":["2022-06-22T13:00:00.22Z"]}"#
|
||||
);
|
||||
}
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::TermQuery;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, IndexReader};
|
||||
use tantivy::{doc, Index, IndexReader, IndexWriter};
|
||||
|
||||
// A simple helper function to fetch a single document
|
||||
// given its id from our index.
|
||||
@@ -19,7 +19,7 @@ use tantivy::{doc, Index, IndexReader};
|
||||
fn extract_doc_given_isbn(
|
||||
reader: &IndexReader,
|
||||
isbn_term: &Term,
|
||||
) -> tantivy::Result<Option<Document>> {
|
||||
) -> tantivy::Result<Option<TantivyDocument>> {
|
||||
let searcher = reader.searcher();
|
||||
|
||||
// This is the simplest query you can think of.
|
||||
@@ -69,10 +69,10 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// Let's add a couple of documents, for the sake of the example.
|
||||
let mut old_man_doc = Document::default();
|
||||
let mut old_man_doc = TantivyDocument::default();
|
||||
old_man_doc.add_text(title, "The Old Man and the Sea");
|
||||
index_writer.add_document(doc!(
|
||||
isbn => "978-0099908401",
|
||||
@@ -94,7 +94,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// Oops our frankenstein doc seems misspelled
|
||||
let frankenstein_doc_misspelled = extract_doc_given_isbn(&reader, &frankenstein_isbn)?.unwrap();
|
||||
assert_eq!(
|
||||
schema.to_json(&frankenstein_doc_misspelled),
|
||||
frankenstein_doc_misspelled.to_json(&schema),
|
||||
r#"{"isbn":["978-9176370711"],"title":["Frankentein"]}"#,
|
||||
);
|
||||
|
||||
@@ -136,7 +136,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// No more typo!
|
||||
let frankenstein_new_doc = extract_doc_given_isbn(&reader, &frankenstein_isbn)?.unwrap();
|
||||
assert_eq!(
|
||||
schema.to_json(&frankenstein_new_doc),
|
||||
frankenstein_new_doc.to_json(&schema),
|
||||
r#"{"isbn":["978-9176370711"],"title":["Frankenstein"]}"#,
|
||||
);
|
||||
|
||||
|
||||
@@ -17,7 +17,7 @@
|
||||
use tantivy::collector::FacetCollector;
|
||||
use tantivy::query::{AllQuery, TermQuery};
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index};
|
||||
use tantivy::{doc, Index, IndexWriter};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// Let's create a temporary directory for the sake of this example
|
||||
@@ -30,7 +30,7 @@ fn main() -> tantivy::Result<()> {
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
|
||||
let mut index_writer = index.writer(30_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(30_000_000)?;
|
||||
|
||||
// For convenience, tantivy also comes with a macro to
|
||||
// reduce the boilerplate above.
|
||||
|
||||
@@ -12,7 +12,7 @@ use std::collections::HashSet;
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::BooleanQuery;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, DocId, Index, Score, SegmentReader};
|
||||
use tantivy::{doc, DocId, Index, IndexWriter, Score, SegmentReader};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
@@ -23,7 +23,7 @@ fn main() -> tantivy::Result<()> {
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
|
||||
let mut index_writer = index.writer(30_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(30_000_000)?;
|
||||
|
||||
index_writer.add_document(doc!(
|
||||
title => "Fried egg",
|
||||
@@ -91,11 +91,10 @@ fn main() -> tantivy::Result<()> {
|
||||
.iter()
|
||||
.map(|(_, doc_id)| {
|
||||
searcher
|
||||
.doc(*doc_id)
|
||||
.doc::<TantivyDocument>(*doc_id)
|
||||
.unwrap()
|
||||
.get_first(title)
|
||||
.unwrap()
|
||||
.as_text()
|
||||
.and_then(|v| v.as_str())
|
||||
.unwrap()
|
||||
.to_owned()
|
||||
})
|
||||
|
||||
@@ -14,7 +14,7 @@
|
||||
use tantivy::collector::{Count, TopDocs};
|
||||
use tantivy::query::FuzzyTermQuery;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, ReloadPolicy};
|
||||
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
@@ -66,7 +66,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// Here we give tantivy a budget of `50MB`.
|
||||
// Using a bigger memory_arena for the indexer may increase
|
||||
// throughput, but 50 MB is already plenty.
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// Let's index our documents!
|
||||
// We first need a handle on the title and the body field.
|
||||
@@ -123,7 +123,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// will reload the index automatically after each commit.
|
||||
let reader = index
|
||||
.reader_builder()
|
||||
.reload_policy(ReloadPolicy::OnCommit)
|
||||
.reload_policy(ReloadPolicy::OnCommitWithDelay)
|
||||
.try_into()?;
|
||||
|
||||
// We now need to acquire a searcher.
|
||||
@@ -151,10 +151,10 @@ fn main() -> tantivy::Result<()> {
|
||||
assert_eq!(count, 3);
|
||||
assert_eq!(top_docs.len(), 3);
|
||||
for (score, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
// Note that the score is not lower for the fuzzy hit.
|
||||
// There's an issue open for that: https://github.com/quickwit-oss/tantivy/issues/563
|
||||
println!("score {score:?} doc {}", schema.to_json(&retrieved_doc));
|
||||
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
|
||||
println!("score {score:?} doc {}", retrieved_doc.to_json(&schema));
|
||||
// score 1.0 doc {"title":["The Diary of Muadib"]}
|
||||
//
|
||||
// score 1.0 doc {"title":["The Diary of a Young Girl"]}
|
||||
|
||||
@@ -21,7 +21,7 @@ fn main() -> tantivy::Result<()> {
|
||||
}"#;
|
||||
|
||||
// We can parse our document
|
||||
let _mice_and_men_doc = schema.parse_document(mice_and_men_doc_json)?;
|
||||
let _mice_and_men_doc = TantivyDocument::parse_json(&schema, mice_and_men_doc_json)?;
|
||||
|
||||
// Multi-valued field are allowed, they are
|
||||
// expressed in JSON by an array.
|
||||
@@ -30,7 +30,7 @@ fn main() -> tantivy::Result<()> {
|
||||
"title": ["Frankenstein", "The Modern Prometheus"],
|
||||
"year": 1818
|
||||
}"#;
|
||||
let _frankenstein_doc = schema.parse_document(frankenstein_json)?;
|
||||
let _frankenstein_doc = TantivyDocument::parse_json(&schema, frankenstein_json)?;
|
||||
|
||||
// Note that the schema is saved in your index directory.
|
||||
//
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
use tantivy::collector::Count;
|
||||
use tantivy::query::RangeQuery;
|
||||
use tantivy::schema::{Schema, INDEXED};
|
||||
use tantivy::{doc, Index, Result};
|
||||
use tantivy::{doc, Index, IndexWriter, Result};
|
||||
|
||||
fn main() -> Result<()> {
|
||||
// For the sake of simplicity, this schema will only have 1 field
|
||||
@@ -17,7 +17,7 @@ fn main() -> Result<()> {
|
||||
let index = Index::create_in_ram(schema);
|
||||
let reader = index.reader()?;
|
||||
{
|
||||
let mut index_writer = index.writer_with_num_threads(1, 6_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer_with_num_threads(1, 6_000_000)?;
|
||||
for year in 1950u64..2019u64 {
|
||||
index_writer.add_document(doc!(year_field => year))?;
|
||||
}
|
||||
|
||||
@@ -6,7 +6,7 @@
|
||||
use tantivy::collector::{Count, TopDocs};
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::{Schema, FAST, INDEXED, STORED, STRING};
|
||||
use tantivy::Index;
|
||||
use tantivy::{Index, IndexWriter, TantivyDocument};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// # Defining the schema
|
||||
@@ -22,20 +22,22 @@ fn main() -> tantivy::Result<()> {
|
||||
// # Indexing documents
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// ### IPv4
|
||||
// Adding documents that contain an IPv4 address. Notice that the IP addresses are passed as
|
||||
// `String`. Since the field is of type ip, we parse the IP address from the string and store it
|
||||
// internally as IPv6.
|
||||
let doc = schema.parse_document(
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"ip": "192.168.0.33",
|
||||
"event_type": "login"
|
||||
}"#,
|
||||
)?;
|
||||
index_writer.add_document(doc)?;
|
||||
let doc = schema.parse_document(
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"ip": "192.168.0.80",
|
||||
"event_type": "checkout"
|
||||
@@ -44,7 +46,8 @@ fn main() -> tantivy::Result<()> {
|
||||
index_writer.add_document(doc)?;
|
||||
// ### IPv6
|
||||
// Adding a document that contains an IPv6 address.
|
||||
let doc = schema.parse_document(
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334",
|
||||
"event_type": "checkout"
|
||||
|
||||
@@ -10,7 +10,7 @@
|
||||
// ---
|
||||
// Importing tantivy...
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, DocSet, Index, Postings, TERMINATED};
|
||||
use tantivy::{doc, DocSet, Index, IndexWriter, Postings, TERMINATED};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// We first create a schema for the sake of the
|
||||
@@ -24,7 +24,7 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let index = Index::create_in_ram(schema);
|
||||
|
||||
let mut index_writer = index.writer_with_num_threads(1, 50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer_with_num_threads(1, 50_000_000)?;
|
||||
index_writer.add_document(doc!(title => "The Old Man and the Sea"))?;
|
||||
index_writer.add_document(doc!(title => "Of Mice and Men"))?;
|
||||
index_writer.add_document(doc!(title => "The modern Promotheus"))?;
|
||||
|
||||
@@ -7,7 +7,7 @@
|
||||
use tantivy::collector::{Count, TopDocs};
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::{Schema, FAST, STORED, STRING, TEXT};
|
||||
use tantivy::Index;
|
||||
use tantivy::{Index, IndexWriter, TantivyDocument};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// # Defining the schema
|
||||
@@ -20,8 +20,9 @@ fn main() -> tantivy::Result<()> {
|
||||
// # Indexing documents
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let doc = schema.parse_document(
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"timestamp": "2022-02-22T23:20:50.53Z",
|
||||
"event_type": "click",
|
||||
@@ -33,7 +34,8 @@ fn main() -> tantivy::Result<()> {
|
||||
}"#,
|
||||
)?;
|
||||
index_writer.add_document(doc)?;
|
||||
let doc = schema.parse_document(
|
||||
let doc = TantivyDocument::parse_json(
|
||||
&schema,
|
||||
r#"{
|
||||
"timestamp": "2022-02-22T23:20:51.53Z",
|
||||
"event_type": "click",
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, ReloadPolicy, Result};
|
||||
use tantivy::{doc, Index, IndexWriter, ReloadPolicy, Result};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn main() -> Result<()> {
|
||||
@@ -17,7 +17,7 @@ fn main() -> Result<()> {
|
||||
|
||||
let index = Index::create_in_dir(&index_path, schema)?;
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
index_writer.add_document(doc!(
|
||||
title => "The Old Man and the Sea",
|
||||
@@ -51,7 +51,7 @@ fn main() -> Result<()> {
|
||||
|
||||
let reader = index
|
||||
.reader_builder()
|
||||
.reload_policy(ReloadPolicy::OnCommit)
|
||||
.reload_policy(ReloadPolicy::OnCommitWithDelay)
|
||||
.try_into()?;
|
||||
|
||||
let searcher = reader.searcher();
|
||||
@@ -67,8 +67,12 @@ fn main() -> Result<()> {
|
||||
let mut titles = top_docs
|
||||
.into_iter()
|
||||
.map(|(_score, doc_address)| {
|
||||
let doc = searcher.doc(doc_address)?;
|
||||
let title = doc.get_first(title).unwrap().as_text().unwrap().to_owned();
|
||||
let doc = searcher.doc::<TantivyDocument>(doc_address)?;
|
||||
let title = doc
|
||||
.get_first(title)
|
||||
.and_then(|v| v.as_str())
|
||||
.unwrap()
|
||||
.to_owned();
|
||||
Ok(title)
|
||||
})
|
||||
.collect::<Result<Vec<_>>>()?;
|
||||
|
||||
@@ -13,7 +13,7 @@ use tantivy::collector::{Count, TopDocs};
|
||||
use tantivy::query::TermQuery;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::tokenizer::{PreTokenizedString, SimpleTokenizer, Token, TokenStream, Tokenizer};
|
||||
use tantivy::{doc, Index, ReloadPolicy};
|
||||
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn pre_tokenize_text(text: &str) -> Vec<Token> {
|
||||
@@ -38,7 +38,7 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let index = Index::create_in_dir(&index_path, schema.clone())?;
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// We can create a document manually, by setting the fields
|
||||
// one by one in a Document object.
|
||||
@@ -83,7 +83,7 @@ fn main() -> tantivy::Result<()> {
|
||||
}]
|
||||
}"#;
|
||||
|
||||
let short_man_doc = schema.parse_document(short_man_json)?;
|
||||
let short_man_doc = TantivyDocument::parse_json(&schema, short_man_json)?;
|
||||
|
||||
index_writer.add_document(short_man_doc)?;
|
||||
|
||||
@@ -94,7 +94,7 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let reader = index
|
||||
.reader_builder()
|
||||
.reload_policy(ReloadPolicy::OnCommit)
|
||||
.reload_policy(ReloadPolicy::OnCommitWithDelay)
|
||||
.try_into()?;
|
||||
|
||||
let searcher = reader.searcher();
|
||||
@@ -115,8 +115,8 @@ fn main() -> tantivy::Result<()> {
|
||||
// Note that the tokens are not stored along with the original text
|
||||
// in the document store
|
||||
for (_score, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
println!("Document: {}", schema.to_json(&retrieved_doc));
|
||||
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
|
||||
println!("{}", retrieved_doc.to_json(&schema));
|
||||
}
|
||||
|
||||
// In contrary to the previous query, when we search for the "man" term we
|
||||
|
||||
@@ -10,7 +10,8 @@
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, Snippet, SnippetGenerator};
|
||||
use tantivy::snippet::{Snippet, SnippetGenerator};
|
||||
use tantivy::{doc, Index, IndexWriter};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
@@ -27,7 +28,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// # Indexing documents
|
||||
let index = Index::create_in_dir(&index_path, schema)?;
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// we'll only need one doc for this example.
|
||||
index_writer.add_document(doc!(
|
||||
@@ -54,13 +55,10 @@ fn main() -> tantivy::Result<()> {
|
||||
let snippet_generator = SnippetGenerator::create(&searcher, &*query, body)?;
|
||||
|
||||
for (score, doc_address) in top_docs {
|
||||
let doc = searcher.doc(doc_address)?;
|
||||
let doc = searcher.doc::<TantivyDocument>(doc_address)?;
|
||||
let snippet = snippet_generator.snippet_from_doc(&doc);
|
||||
println!("Document score {score}:");
|
||||
println!(
|
||||
"title: {}",
|
||||
doc.get_first(title).unwrap().as_text().unwrap()
|
||||
);
|
||||
println!("title: {}", doc.get_first(title).unwrap().as_str().unwrap());
|
||||
println!("snippet: {}", snippet.to_html());
|
||||
println!("custom highlighting: {}", highlight(snippet));
|
||||
}
|
||||
|
||||
@@ -15,7 +15,7 @@ use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::tokenizer::*;
|
||||
use tantivy::{doc, Index};
|
||||
use tantivy::{doc, Index, IndexWriter};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// this example assumes you understand the content in `basic_search`
|
||||
@@ -60,7 +60,7 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
index.tokenizers().register("stoppy", tokenizer);
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
let title = schema.get_field("title").unwrap();
|
||||
let body = schema.get_field("body").unwrap();
|
||||
@@ -105,9 +105,9 @@ fn main() -> tantivy::Result<()> {
|
||||
let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
|
||||
|
||||
for (score, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
|
||||
println!("\n==\nDocument score {score}:");
|
||||
println!("{}", schema.to_json(&retrieved_doc));
|
||||
println!("{}", retrieved_doc.to_json(&schema));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
|
||||
@@ -6,12 +6,14 @@ use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::{Schema, FAST, TEXT};
|
||||
use tantivy::{
|
||||
doc, DocAddress, DocId, Index, IndexReader, Opstamp, Searcher, SearcherGeneration, SegmentId,
|
||||
doc, DocAddress, DocId, Index, IndexWriter, Opstamp, Searcher, SearcherGeneration, SegmentId,
|
||||
SegmentReader, Warmer,
|
||||
};
|
||||
|
||||
// This example shows how warmers can be used to
|
||||
// load a values from an external sources using the Warmer API.
|
||||
// load values from an external sources and
|
||||
// tie their lifecycle to that of the index segments
|
||||
// using the Warmer API.
|
||||
//
|
||||
// In this example, we assume an e-commerce search engine.
|
||||
|
||||
@@ -23,9 +25,11 @@ pub trait PriceFetcher: Send + Sync + 'static {
|
||||
fn fetch_prices(&self, product_ids: &[ProductId]) -> Vec<Price>;
|
||||
}
|
||||
|
||||
type SegmentKey = (SegmentId, Option<Opstamp>);
|
||||
|
||||
struct DynamicPriceColumn {
|
||||
field: String,
|
||||
price_cache: RwLock<HashMap<(SegmentId, Option<Opstamp>), Arc<Vec<Price>>>>,
|
||||
price_cache: RwLock<HashMap<SegmentKey, Arc<Vec<Price>>>>,
|
||||
price_fetcher: Box<dyn PriceFetcher>,
|
||||
}
|
||||
|
||||
@@ -46,7 +50,6 @@ impl DynamicPriceColumn {
|
||||
impl Warmer for DynamicPriceColumn {
|
||||
fn warm(&self, searcher: &Searcher) -> tantivy::Result<()> {
|
||||
for segment in searcher.segment_readers() {
|
||||
let key = (segment.segment_id(), segment.delete_opstamp());
|
||||
let product_id_reader = segment
|
||||
.fast_fields()
|
||||
.u64(&self.field)?
|
||||
@@ -55,37 +58,40 @@ impl Warmer for DynamicPriceColumn {
|
||||
.doc_ids_alive()
|
||||
.map(|doc| product_id_reader.get_val(doc))
|
||||
.collect();
|
||||
let mut prices_it = self.price_fetcher.fetch_prices(&product_ids).into_iter();
|
||||
let mut price_vals: Vec<Price> = Vec::new();
|
||||
for doc in 0..segment.max_doc() {
|
||||
if segment.is_deleted(doc) {
|
||||
price_vals.push(0);
|
||||
} else {
|
||||
price_vals.push(prices_it.next().unwrap())
|
||||
}
|
||||
}
|
||||
|
||||
let mut prices = self.price_fetcher.fetch_prices(&product_ids).into_iter();
|
||||
|
||||
let prices: Vec<Price> = (0..segment.max_doc())
|
||||
.map(|doc| {
|
||||
if !segment.is_deleted(doc) {
|
||||
prices.next().unwrap()
|
||||
} else {
|
||||
0
|
||||
}
|
||||
})
|
||||
.collect();
|
||||
|
||||
let key = (segment.segment_id(), segment.delete_opstamp());
|
||||
self.price_cache
|
||||
.write()
|
||||
.unwrap()
|
||||
.insert(key, Arc::new(price_vals));
|
||||
.insert(key, Arc::new(prices));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn garbage_collect(&self, live_generations: &[&SearcherGeneration]) {
|
||||
let live_segment_id_and_delete_ops: HashSet<(SegmentId, Option<Opstamp>)> =
|
||||
live_generations
|
||||
.iter()
|
||||
.flat_map(|gen| gen.segments())
|
||||
.map(|(&segment_id, &opstamp)| (segment_id, opstamp))
|
||||
.collect();
|
||||
let mut price_cache_wrt = self.price_cache.write().unwrap();
|
||||
// let price_cache = std::mem::take(&mut *price_cache_wrt);
|
||||
// Drain would be nicer here.
|
||||
*price_cache_wrt = std::mem::take(&mut *price_cache_wrt)
|
||||
.into_iter()
|
||||
.filter(|(seg_id_and_op, _)| !live_segment_id_and_delete_ops.contains(seg_id_and_op))
|
||||
let live_keys: HashSet<SegmentKey> = live_generations
|
||||
.iter()
|
||||
.flat_map(|gen| gen.segments())
|
||||
.map(|(&segment_id, &opstamp)| (segment_id, opstamp))
|
||||
.collect();
|
||||
|
||||
self.price_cache
|
||||
.write()
|
||||
.unwrap()
|
||||
.retain(|key, _| live_keys.contains(key));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -100,17 +106,17 @@ pub struct ExternalPriceTable {
|
||||
|
||||
impl ExternalPriceTable {
|
||||
pub fn update_price(&self, product_id: ProductId, price: Price) {
|
||||
let mut prices_wrt = self.prices.write().unwrap();
|
||||
prices_wrt.insert(product_id, price);
|
||||
self.prices.write().unwrap().insert(product_id, price);
|
||||
}
|
||||
}
|
||||
|
||||
impl PriceFetcher for ExternalPriceTable {
|
||||
fn fetch_prices(&self, product_ids: &[ProductId]) -> Vec<Price> {
|
||||
let prices_read = self.prices.read().unwrap();
|
||||
let prices = self.prices.read().unwrap();
|
||||
|
||||
product_ids
|
||||
.iter()
|
||||
.map(|product_id| prices_read.get(product_id).cloned().unwrap_or(0))
|
||||
.map(|product_id| prices.get(product_id).cloned().unwrap_or(0))
|
||||
.collect()
|
||||
}
|
||||
}
|
||||
@@ -137,17 +143,14 @@ fn main() -> tantivy::Result<()> {
|
||||
const SNEAKERS: ProductId = 23222;
|
||||
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut writer = index.writer_with_num_threads(1, 10_000_000)?;
|
||||
let mut writer: IndexWriter = index.writer_with_num_threads(1, 15_000_000)?;
|
||||
writer.add_document(doc!(product_id=>OLIVE_OIL, text=>"cooking olive oil from greece"))?;
|
||||
writer.add_document(doc!(product_id=>GLOVES, text=>"kitchen gloves, perfect for cooking"))?;
|
||||
writer.add_document(doc!(product_id=>SNEAKERS, text=>"uber sweet sneakers"))?;
|
||||
writer.commit()?;
|
||||
|
||||
let warmers: Vec<Weak<dyn Warmer>> = vec![Arc::downgrade(
|
||||
&(price_dynamic_column.clone() as Arc<dyn Warmer>),
|
||||
)];
|
||||
let reader: IndexReader = index.reader_builder().warmers(warmers).try_into()?;
|
||||
reader.reload()?;
|
||||
let warmers = vec![Arc::downgrade(&price_dynamic_column) as Weak<dyn Warmer>];
|
||||
let reader = index.reader_builder().warmers(warmers).try_into()?;
|
||||
|
||||
let query_parser = QueryParser::for_index(&index, vec![text]);
|
||||
let query = query_parser.parse_query("cooking")?;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
|
||||
name = "ownedbytes"
|
||||
version = "0.5.0"
|
||||
version = "0.6.0"
|
||||
edition = "2021"
|
||||
description = "Expose data as static slice"
|
||||
license = "MIT"
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
use std::convert::TryInto;
|
||||
use std::ops::{Deref, Range};
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io, mem};
|
||||
use std::{fmt, io};
|
||||
|
||||
pub use stable_deref_trait::StableDeref;
|
||||
|
||||
@@ -26,8 +25,8 @@ impl OwnedBytes {
|
||||
data_holder: T,
|
||||
) -> OwnedBytes {
|
||||
let box_stable_deref = Arc::new(data_holder);
|
||||
let bytes: &[u8] = box_stable_deref.as_ref();
|
||||
let data = unsafe { mem::transmute::<_, &'static [u8]>(bytes.deref()) };
|
||||
let bytes: &[u8] = box_stable_deref.deref();
|
||||
let data = unsafe { &*(bytes as *const [u8]) };
|
||||
OwnedBytes {
|
||||
data,
|
||||
box_stable_deref,
|
||||
@@ -57,6 +56,12 @@ impl OwnedBytes {
|
||||
self.data.len()
|
||||
}
|
||||
|
||||
/// Returns true iff this `OwnedBytes` is empty.
|
||||
#[inline]
|
||||
pub fn is_empty(&self) -> bool {
|
||||
self.data.is_empty()
|
||||
}
|
||||
|
||||
/// Splits the OwnedBytes into two OwnedBytes `(left, right)`.
|
||||
///
|
||||
/// Left will hold `split_len` bytes.
|
||||
@@ -68,13 +73,14 @@ impl OwnedBytes {
|
||||
#[inline]
|
||||
#[must_use]
|
||||
pub fn split(self, split_len: usize) -> (OwnedBytes, OwnedBytes) {
|
||||
let (left_data, right_data) = self.data.split_at(split_len);
|
||||
let right_box_stable_deref = self.box_stable_deref.clone();
|
||||
let left = OwnedBytes {
|
||||
data: &self.data[..split_len],
|
||||
data: left_data,
|
||||
box_stable_deref: self.box_stable_deref,
|
||||
};
|
||||
let right = OwnedBytes {
|
||||
data: &self.data[split_len..],
|
||||
data: right_data,
|
||||
box_stable_deref: right_box_stable_deref,
|
||||
};
|
||||
(left, right)
|
||||
@@ -99,55 +105,45 @@ impl OwnedBytes {
|
||||
///
|
||||
/// `self` is truncated to `split_len`, left with the remaining bytes.
|
||||
pub fn split_off(&mut self, split_len: usize) -> OwnedBytes {
|
||||
let (left, right) = self.data.split_at(split_len);
|
||||
let right_box_stable_deref = self.box_stable_deref.clone();
|
||||
let right_piece = OwnedBytes {
|
||||
data: &self.data[split_len..],
|
||||
data: right,
|
||||
box_stable_deref: right_box_stable_deref,
|
||||
};
|
||||
self.data = &self.data[..split_len];
|
||||
self.data = left;
|
||||
right_piece
|
||||
}
|
||||
|
||||
/// Returns true iff this `OwnedBytes` is empty.
|
||||
#[inline]
|
||||
pub fn is_empty(&self) -> bool {
|
||||
self.as_slice().is_empty()
|
||||
}
|
||||
|
||||
/// Drops the left most `advance_len` bytes.
|
||||
#[inline]
|
||||
pub fn advance(&mut self, advance_len: usize) {
|
||||
self.data = &self.data[advance_len..]
|
||||
pub fn advance(&mut self, advance_len: usize) -> &[u8] {
|
||||
let (data, rest) = self.data.split_at(advance_len);
|
||||
self.data = rest;
|
||||
data
|
||||
}
|
||||
|
||||
/// Reads an `u8` from the `OwnedBytes` and advance by one byte.
|
||||
#[inline]
|
||||
pub fn read_u8(&mut self) -> u8 {
|
||||
assert!(!self.is_empty());
|
||||
|
||||
let byte = self.as_slice()[0];
|
||||
self.advance(1);
|
||||
byte
|
||||
self.advance(1)[0]
|
||||
}
|
||||
|
||||
/// Reads an `u64` encoded as little-endian from the `OwnedBytes` and advance by 8 bytes.
|
||||
#[inline]
|
||||
pub fn read_u64(&mut self) -> u64 {
|
||||
assert!(self.len() > 7);
|
||||
|
||||
let octlet: [u8; 8] = self.as_slice()[..8].try_into().unwrap();
|
||||
self.advance(8);
|
||||
u64::from_le_bytes(octlet)
|
||||
fn read_n<const N: usize>(&mut self) -> [u8; N] {
|
||||
self.advance(N).try_into().unwrap()
|
||||
}
|
||||
|
||||
/// Reads an `u32` encoded as little-endian from the `OwnedBytes` and advance by 4 bytes.
|
||||
#[inline]
|
||||
pub fn read_u32(&mut self) -> u32 {
|
||||
assert!(self.len() > 3);
|
||||
u32::from_le_bytes(self.read_n())
|
||||
}
|
||||
|
||||
let quad: [u8; 4] = self.as_slice()[..4].try_into().unwrap();
|
||||
self.advance(4);
|
||||
u32::from_le_bytes(quad)
|
||||
/// Reads an `u64` encoded as little-endian from the `OwnedBytes` and advance by 8 bytes.
|
||||
#[inline]
|
||||
pub fn read_u64(&mut self) -> u64 {
|
||||
u64::from_le_bytes(self.read_n())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -201,32 +197,33 @@ impl Deref for OwnedBytes {
|
||||
}
|
||||
}
|
||||
|
||||
impl AsRef<[u8]> for OwnedBytes {
|
||||
#[inline]
|
||||
fn as_ref(&self) -> &[u8] {
|
||||
self.as_slice()
|
||||
}
|
||||
}
|
||||
|
||||
impl io::Read for OwnedBytes {
|
||||
#[inline]
|
||||
fn read(&mut self, buf: &mut [u8]) -> io::Result<usize> {
|
||||
let read_len = {
|
||||
let data = self.as_slice();
|
||||
if data.len() >= buf.len() {
|
||||
let buf_len = buf.len();
|
||||
buf.copy_from_slice(&data[..buf_len]);
|
||||
buf.len()
|
||||
} else {
|
||||
let data_len = data.len();
|
||||
buf[..data_len].copy_from_slice(data);
|
||||
data_len
|
||||
}
|
||||
};
|
||||
self.advance(read_len);
|
||||
Ok(read_len)
|
||||
let data_len = self.data.len();
|
||||
let buf_len = buf.len();
|
||||
if data_len >= buf_len {
|
||||
let data = self.advance(buf_len);
|
||||
buf.copy_from_slice(data);
|
||||
Ok(buf_len)
|
||||
} else {
|
||||
buf[..data_len].copy_from_slice(self.data);
|
||||
self.data = &[];
|
||||
Ok(data_len)
|
||||
}
|
||||
}
|
||||
#[inline]
|
||||
fn read_to_end(&mut self, buf: &mut Vec<u8>) -> io::Result<usize> {
|
||||
let read_len = {
|
||||
let data = self.as_slice();
|
||||
buf.extend(data);
|
||||
data.len()
|
||||
};
|
||||
self.advance(read_len);
|
||||
buf.extend(self.data);
|
||||
let read_len = self.data.len();
|
||||
self.data = &[];
|
||||
Ok(read_len)
|
||||
}
|
||||
#[inline]
|
||||
@@ -242,13 +239,6 @@ impl io::Read for OwnedBytes {
|
||||
}
|
||||
}
|
||||
|
||||
impl AsRef<[u8]> for OwnedBytes {
|
||||
#[inline]
|
||||
fn as_ref(&self) -> &[u8] {
|
||||
self.as_slice()
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::io::{self, Read};
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-query-grammar"
|
||||
version = "0.20.0"
|
||||
version = "0.21.0"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
categories = ["database-implementations", "data-structures"]
|
||||
@@ -12,6 +12,4 @@ keywords = ["search", "information", "retrieval"]
|
||||
edition = "2021"
|
||||
|
||||
[dependencies]
|
||||
combine = {version="4", default-features=false, features=[] }
|
||||
once_cell = "1.7.2"
|
||||
regex ={ version = "1.5.4", default-features = false, features = ["std", "unicode"] }
|
||||
nom = "7"
|
||||
|
||||
353
query-grammar/src/infallible.rs
Normal file
353
query-grammar/src/infallible.rs
Normal file
@@ -0,0 +1,353 @@
|
||||
//! nom combinators for infallible operations
|
||||
|
||||
use std::convert::Infallible;
|
||||
|
||||
use nom::{AsChar, IResult, InputLength, InputTakeAtPosition};
|
||||
|
||||
pub(crate) type ErrorList = Vec<LenientErrorInternal>;
|
||||
pub(crate) type JResult<I, O> = IResult<I, (O, ErrorList), Infallible>;
|
||||
|
||||
/// An error, with an end-of-string based offset
|
||||
#[derive(Debug)]
|
||||
pub(crate) struct LenientErrorInternal {
|
||||
pub pos: usize,
|
||||
pub message: String,
|
||||
}
|
||||
|
||||
/// A recoverable error and the position it happened at
|
||||
#[derive(Debug, PartialEq)]
|
||||
pub struct LenientError {
|
||||
pub pos: usize,
|
||||
pub message: String,
|
||||
}
|
||||
|
||||
impl LenientError {
|
||||
pub(crate) fn from_internal(internal: LenientErrorInternal, str_len: usize) -> LenientError {
|
||||
LenientError {
|
||||
pos: str_len - internal.pos,
|
||||
message: internal.message,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn unwrap_infallible<T>(res: Result<T, nom::Err<Infallible>>) -> T {
|
||||
match res {
|
||||
Ok(val) => val,
|
||||
Err(_) => unreachable!(),
|
||||
}
|
||||
}
|
||||
|
||||
// when rfcs#1733 get stabilized, this can make things clearer
|
||||
// trait InfallibleParser<I, O> = nom::Parser<I, (O, ErrorList), std::convert::Infallible>;
|
||||
|
||||
/// A variant of the classical `opt` parser, except it returns an infallible error type.
|
||||
///
|
||||
/// It's less generic than the original to ease type resolution in the rest of the code.
|
||||
pub(crate) fn opt_i<I: Clone, O, F>(mut f: F) -> impl FnMut(I) -> JResult<I, Option<O>>
|
||||
where F: nom::Parser<I, O, nom::error::Error<I>> {
|
||||
move |input: I| {
|
||||
let i = input.clone();
|
||||
match f.parse(input) {
|
||||
Ok((i, o)) => Ok((i, (Some(o), Vec::new()))),
|
||||
Err(_) => Ok((i, (None, Vec::new()))),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn opt_i_err<'a, I: Clone + InputLength, O, F>(
|
||||
mut f: F,
|
||||
message: impl ToString + 'a,
|
||||
) -> impl FnMut(I) -> JResult<I, Option<O>> + 'a
|
||||
where
|
||||
F: nom::Parser<I, O, nom::error::Error<I>> + 'a,
|
||||
{
|
||||
move |input: I| {
|
||||
let i = input.clone();
|
||||
match f.parse(input) {
|
||||
Ok((i, o)) => Ok((i, (Some(o), Vec::new()))),
|
||||
Err(_) => {
|
||||
let errs = vec![LenientErrorInternal {
|
||||
pos: i.input_len(),
|
||||
message: message.to_string(),
|
||||
}];
|
||||
Ok((i, (None, errs)))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn space0_infallible<T>(input: T) -> JResult<T, T>
|
||||
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)))
|
||||
}
|
||||
|
||||
pub(crate) fn space1_infallible<T>(input: T) -> JResult<T, Option<T>>
|
||||
where
|
||||
T: InputTakeAtPosition + Clone + InputLength,
|
||||
<T as InputTakeAtPosition>::Item: AsChar + Clone,
|
||||
{
|
||||
opt_i(nom::character::complete::multispace1)(input).map(|(left, (spaces, mut errors))| {
|
||||
if spaces.is_none() {
|
||||
errors.push(LenientErrorInternal {
|
||||
pos: left.input_len(),
|
||||
message: "missing space".to_string(),
|
||||
})
|
||||
}
|
||||
(left, (spaces, errors))
|
||||
})
|
||||
}
|
||||
|
||||
pub(crate) fn fallible<I, O, E: nom::error::ParseError<I>, F>(
|
||||
mut f: F,
|
||||
) -> impl FnMut(I) -> IResult<I, O, E>
|
||||
where F: nom::Parser<I, (O, ErrorList), Infallible> {
|
||||
use nom::Err;
|
||||
move |input: I| match f.parse(input) {
|
||||
Ok((input, (output, _err))) => Ok((input, output)),
|
||||
Err(Err::Incomplete(needed)) => Err(Err::Incomplete(needed)),
|
||||
Err(Err::Error(val)) | Err(Err::Failure(val)) => match val {},
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn delimited_infallible<I, O1, O2, O3, F, G, H>(
|
||||
mut first: F,
|
||||
mut second: G,
|
||||
mut third: H,
|
||||
) -> impl FnMut(I) -> JResult<I, O2>
|
||||
where
|
||||
F: nom::Parser<I, (O1, ErrorList), Infallible>,
|
||||
G: nom::Parser<I, (O2, ErrorList), Infallible>,
|
||||
H: nom::Parser<I, (O3, ErrorList), Infallible>,
|
||||
{
|
||||
move |input: I| {
|
||||
let (input, (_, mut err)) = first.parse(input)?;
|
||||
let (input, (o2, mut err2)) = second.parse(input)?;
|
||||
err.append(&mut err2);
|
||||
let (input, (_, mut err3)) = third.parse(input)?;
|
||||
err.append(&mut err3);
|
||||
Ok((input, (o2, err)))
|
||||
}
|
||||
}
|
||||
|
||||
// Parse nothing. Just a lazy way to not implement terminated/preceded and use delimited instead
|
||||
pub(crate) fn nothing(i: &str) -> JResult<&str, ()> {
|
||||
Ok((i, ((), Vec::new())))
|
||||
}
|
||||
|
||||
pub(crate) trait TupleInfallible<I, O> {
|
||||
/// Parses the input and returns a tuple of results of each parser.
|
||||
fn parse(&mut self, input: I) -> JResult<I, O>;
|
||||
}
|
||||
|
||||
impl<Input, Output, F: nom::Parser<Input, (Output, ErrorList), Infallible>>
|
||||
TupleInfallible<Input, (Output,)> for (F,)
|
||||
{
|
||||
fn parse(&mut self, input: Input) -> JResult<Input, (Output,)> {
|
||||
self.0.parse(input).map(|(i, (o, e))| (i, ((o,), e)))
|
||||
}
|
||||
}
|
||||
|
||||
// these macros are heavily copied from nom, with some minor adaptations for our type
|
||||
macro_rules! tuple_trait(
|
||||
($name1:ident $ty1:ident, $name2: ident $ty2:ident, $($name:ident $ty:ident),*) => (
|
||||
tuple_trait!(__impl $name1 $ty1, $name2 $ty2; $($name $ty),*);
|
||||
);
|
||||
(__impl $($name:ident $ty: ident),+; $name1:ident $ty1:ident, $($name2:ident $ty2:ident),*) => (
|
||||
tuple_trait_impl!($($name $ty),+);
|
||||
tuple_trait!(__impl $($name $ty),+ , $name1 $ty1; $($name2 $ty2),*);
|
||||
);
|
||||
(__impl $($name:ident $ty: ident),+; $name1:ident $ty1:ident) => (
|
||||
tuple_trait_impl!($($name $ty),+);
|
||||
tuple_trait_impl!($($name $ty),+, $name1 $ty1);
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! tuple_trait_impl(
|
||||
($($name:ident $ty: ident),+) => (
|
||||
impl<
|
||||
Input: Clone, $($ty),+ ,
|
||||
$($name: nom::Parser<Input, ($ty, ErrorList), Infallible>),+
|
||||
> TupleInfallible<Input, ( $($ty),+ )> for ( $($name),+ ) {
|
||||
|
||||
fn parse(&mut self, input: Input) -> JResult<Input, ( $($ty),+ )> {
|
||||
let mut error_list = Vec::new();
|
||||
tuple_trait_inner!(0, self, input, (), error_list, $($name)+)
|
||||
}
|
||||
}
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! tuple_trait_inner(
|
||||
($it:tt, $self:expr, $input:expr, (), $error_list:expr, $head:ident $($id:ident)+) => ({
|
||||
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
|
||||
$error_list.append(&mut err);
|
||||
|
||||
succ!($it, tuple_trait_inner!($self, i, ( o ), $error_list, $($id)+))
|
||||
});
|
||||
($it:tt, $self:expr, $input:expr, ($($parsed:tt)*), $error_list:expr, $head:ident $($id:ident)+) => ({
|
||||
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
|
||||
$error_list.append(&mut err);
|
||||
|
||||
succ!($it, tuple_trait_inner!($self, i, ($($parsed)* , o), $error_list, $($id)+))
|
||||
});
|
||||
($it:tt, $self:expr, $input:expr, ($($parsed:tt)*), $error_list:expr, $head:ident) => ({
|
||||
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
|
||||
$error_list.append(&mut err);
|
||||
|
||||
Ok((i, (($($parsed)* , o), $error_list)))
|
||||
});
|
||||
);
|
||||
|
||||
macro_rules! succ (
|
||||
(0, $submac:ident ! ($($rest:tt)*)) => ($submac!(1, $($rest)*));
|
||||
(1, $submac:ident ! ($($rest:tt)*)) => ($submac!(2, $($rest)*));
|
||||
(2, $submac:ident ! ($($rest:tt)*)) => ($submac!(3, $($rest)*));
|
||||
(3, $submac:ident ! ($($rest:tt)*)) => ($submac!(4, $($rest)*));
|
||||
(4, $submac:ident ! ($($rest:tt)*)) => ($submac!(5, $($rest)*));
|
||||
(5, $submac:ident ! ($($rest:tt)*)) => ($submac!(6, $($rest)*));
|
||||
(6, $submac:ident ! ($($rest:tt)*)) => ($submac!(7, $($rest)*));
|
||||
(7, $submac:ident ! ($($rest:tt)*)) => ($submac!(8, $($rest)*));
|
||||
(8, $submac:ident ! ($($rest:tt)*)) => ($submac!(9, $($rest)*));
|
||||
(9, $submac:ident ! ($($rest:tt)*)) => ($submac!(10, $($rest)*));
|
||||
(10, $submac:ident ! ($($rest:tt)*)) => ($submac!(11, $($rest)*));
|
||||
(11, $submac:ident ! ($($rest:tt)*)) => ($submac!(12, $($rest)*));
|
||||
(12, $submac:ident ! ($($rest:tt)*)) => ($submac!(13, $($rest)*));
|
||||
(13, $submac:ident ! ($($rest:tt)*)) => ($submac!(14, $($rest)*));
|
||||
(14, $submac:ident ! ($($rest:tt)*)) => ($submac!(15, $($rest)*));
|
||||
(15, $submac:ident ! ($($rest:tt)*)) => ($submac!(16, $($rest)*));
|
||||
(16, $submac:ident ! ($($rest:tt)*)) => ($submac!(17, $($rest)*));
|
||||
(17, $submac:ident ! ($($rest:tt)*)) => ($submac!(18, $($rest)*));
|
||||
(18, $submac:ident ! ($($rest:tt)*)) => ($submac!(19, $($rest)*));
|
||||
(19, $submac:ident ! ($($rest:tt)*)) => ($submac!(20, $($rest)*));
|
||||
(20, $submac:ident ! ($($rest:tt)*)) => ($submac!(21, $($rest)*));
|
||||
);
|
||||
|
||||
tuple_trait!(FnA A, FnB B, FnC C, FnD D, FnE E, FnF F, FnG G, FnH H, FnI I, FnJ J, FnK K, FnL L,
|
||||
FnM M, FnN N, FnO O, FnP P, FnQ Q, FnR R, FnS S, FnT T, FnU U);
|
||||
|
||||
// Special case: implement `TupleInfallible` for `()`, the unit type.
|
||||
// This can come up in macros which accept a variable number of arguments.
|
||||
// Literally, `()` is an empty tuple, so it should simply parse nothing.
|
||||
impl<I> TupleInfallible<I, ()> for () {
|
||||
fn parse(&mut self, input: I) -> JResult<I, ()> {
|
||||
Ok((input, ((), Vec::new())))
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn tuple_infallible<I, O, List: TupleInfallible<I, O>>(
|
||||
mut l: List,
|
||||
) -> impl FnMut(I) -> JResult<I, O> {
|
||||
move |i: I| l.parse(i)
|
||||
}
|
||||
|
||||
pub(crate) fn separated_list_infallible<I, O, O2, F, G>(
|
||||
mut sep: G,
|
||||
mut f: F,
|
||||
) -> impl FnMut(I) -> JResult<I, Vec<O>>
|
||||
where
|
||||
I: Clone + InputLength,
|
||||
F: nom::Parser<I, (O, ErrorList), Infallible>,
|
||||
G: nom::Parser<I, (O2, ErrorList), Infallible>,
|
||||
{
|
||||
move |i: I| {
|
||||
let mut res: Vec<O> = Vec::new();
|
||||
let mut errors: ErrorList = Vec::new();
|
||||
|
||||
let (mut i, (o, mut err)) = unwrap_infallible(f.parse(i.clone()));
|
||||
errors.append(&mut err);
|
||||
res.push(o);
|
||||
|
||||
loop {
|
||||
let (i_sep_parsed, (_, mut err_sep)) = unwrap_infallible(sep.parse(i.clone()));
|
||||
let len_before = i_sep_parsed.input_len();
|
||||
|
||||
let (i_elem_parsed, (o, mut err_elem)) =
|
||||
unwrap_infallible(f.parse(i_sep_parsed.clone()));
|
||||
|
||||
// infinite loop check: the parser must always consume
|
||||
// if we consumed nothing here, don't produce an element.
|
||||
if i_elem_parsed.input_len() == len_before {
|
||||
return Ok((i, (res, errors)));
|
||||
}
|
||||
res.push(o);
|
||||
errors.append(&mut err_sep);
|
||||
errors.append(&mut err_elem);
|
||||
i = i_elem_parsed;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) trait Alt<I, O> {
|
||||
/// Tests each parser in the tuple and returns the result of the first one that succeeds
|
||||
fn choice(&mut self, input: I) -> Option<JResult<I, O>>;
|
||||
}
|
||||
|
||||
macro_rules! alt_trait(
|
||||
($first_cond:ident $first:ident, $($id_cond:ident $id: ident),+) => (
|
||||
alt_trait!(__impl $first_cond $first; $($id_cond $id),+);
|
||||
);
|
||||
(__impl $($current_cond:ident $current:ident),*; $head_cond:ident $head:ident, $($id_cond:ident $id:ident),+) => (
|
||||
alt_trait_impl!($($current_cond $current),*);
|
||||
|
||||
alt_trait!(__impl $($current_cond $current,)* $head_cond $head; $($id_cond $id),+);
|
||||
);
|
||||
(__impl $($current_cond:ident $current:ident),*; $head_cond:ident $head:ident) => (
|
||||
alt_trait_impl!($($current_cond $current),*);
|
||||
alt_trait_impl!($($current_cond $current,)* $head_cond $head);
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! alt_trait_impl(
|
||||
($($id_cond:ident $id:ident),+) => (
|
||||
impl<
|
||||
Input: Clone, Output,
|
||||
$(
|
||||
// () are to make things easier on me, but I'm not entirely sure whether we can do better
|
||||
// with rule E0207
|
||||
$id_cond: nom::Parser<Input, (), ()>,
|
||||
$id: nom::Parser<Input, (Output, ErrorList), Infallible>
|
||||
),+
|
||||
> Alt<Input, Output> for ( $(($id_cond, $id),)+ ) {
|
||||
|
||||
fn choice(&mut self, input: Input) -> Option<JResult<Input, Output>> {
|
||||
match self.0.0.parse(input.clone()) {
|
||||
Err(_) => alt_trait_inner!(1, self, input, $($id_cond $id),+),
|
||||
Ok((input_left, _)) => Some(self.0.1.parse(input_left)),
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! alt_trait_inner(
|
||||
($it:tt, $self:expr, $input:expr, $head_cond:ident $head:ident, $($id_cond:ident $id:ident),+) => (
|
||||
match $self.$it.0.parse($input.clone()) {
|
||||
Err(_) => succ!($it, alt_trait_inner!($self, $input, $($id_cond $id),+)),
|
||||
Ok((input_left, _)) => Some($self.$it.1.parse(input_left)),
|
||||
}
|
||||
);
|
||||
($it:tt, $self:expr, $input:expr, $head_cond:ident $head:ident) => (
|
||||
None
|
||||
);
|
||||
);
|
||||
|
||||
alt_trait!(A1 A, B1 B, C1 C, D1 D, E1 E, F1 F, G1 G, H1 H, I1 I, J1 J, K1 K,
|
||||
L1 L, M1 M, N1 N, O1 O, P1 P, Q1 Q, R1 R, S1 S, T1 T, U1 U);
|
||||
|
||||
/// An alt() like combinator. For each branch, it first tries a fallible parser, which commits to
|
||||
/// this branch, or tells to check next branch, and the execute the infallible parser which follow.
|
||||
///
|
||||
/// In case no branch match, the default (fallible) parser is executed.
|
||||
pub(crate) fn alt_infallible<I: Clone, O, F, List: Alt<I, O>>(
|
||||
mut l: List,
|
||||
mut default: F,
|
||||
) -> impl FnMut(I) -> JResult<I, O>
|
||||
where
|
||||
F: nom::Parser<I, (O, ErrorList), Infallible>,
|
||||
{
|
||||
move |i: I| l.choice(i.clone()).unwrap_or_else(|| default.parse(i))
|
||||
}
|
||||
@@ -1,19 +1,26 @@
|
||||
#![allow(clippy::derive_partial_eq_without_eq)]
|
||||
|
||||
mod infallible;
|
||||
mod occur;
|
||||
mod query_grammar;
|
||||
mod user_input_ast;
|
||||
use combine::parser::Parser;
|
||||
|
||||
pub use crate::infallible::LenientError;
|
||||
pub use crate::occur::Occur;
|
||||
use crate::query_grammar::parse_to_ast;
|
||||
use crate::query_grammar::{parse_to_ast, parse_to_ast_lenient};
|
||||
pub use crate::user_input_ast::{
|
||||
Delimiter, UserInputAst, UserInputBound, UserInputLeaf, UserInputLiteral,
|
||||
};
|
||||
|
||||
pub struct Error;
|
||||
|
||||
/// Parse a query
|
||||
pub fn parse_query(query: &str) -> Result<UserInputAst, Error> {
|
||||
let (user_input_ast, _remaining) = parse_to_ast().parse(query).map_err(|_| Error)?;
|
||||
let (_remaining, user_input_ast) = parse_to_ast(query).map_err(|_| Error)?;
|
||||
Ok(user_input_ast)
|
||||
}
|
||||
|
||||
/// Parse a query, trying to recover from syntax errors, and giving hints toward fixing errors.
|
||||
pub fn parse_query_lenient(query: &str) -> (UserInputAst, Vec<LenientError>) {
|
||||
parse_to_ast_lenient(query)
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -3,7 +3,7 @@ use std::fmt::{Debug, Formatter};
|
||||
|
||||
use crate::Occur;
|
||||
|
||||
#[derive(PartialEq)]
|
||||
#[derive(PartialEq, Clone)]
|
||||
pub enum UserInputLeaf {
|
||||
Literal(UserInputLiteral),
|
||||
All,
|
||||
@@ -16,6 +16,34 @@ pub enum UserInputLeaf {
|
||||
field: Option<String>,
|
||||
elements: Vec<String>,
|
||||
},
|
||||
Exists {
|
||||
field: String,
|
||||
},
|
||||
}
|
||||
|
||||
impl UserInputLeaf {
|
||||
pub(crate) fn set_field(self, field: Option<String>) -> Self {
|
||||
match self {
|
||||
UserInputLeaf::Literal(mut literal) => {
|
||||
literal.field_name = field;
|
||||
UserInputLeaf::Literal(literal)
|
||||
}
|
||||
UserInputLeaf::All => UserInputLeaf::All,
|
||||
UserInputLeaf::Range {
|
||||
field: _,
|
||||
lower,
|
||||
upper,
|
||||
} => UserInputLeaf::Range {
|
||||
field,
|
||||
lower,
|
||||
upper,
|
||||
},
|
||||
UserInputLeaf::Set { field: _, elements } => UserInputLeaf::Set { field, elements },
|
||||
UserInputLeaf::Exists { field: _ } => UserInputLeaf::Exists {
|
||||
field: field.expect("Exist query without a field isn't allowed"),
|
||||
},
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Debug for UserInputLeaf {
|
||||
@@ -28,6 +56,7 @@ impl Debug for UserInputLeaf {
|
||||
ref upper,
|
||||
} => {
|
||||
if let Some(ref field) = field {
|
||||
// TODO properly escape field (in case of \")
|
||||
write!(formatter, "\"{field}\":")?;
|
||||
}
|
||||
lower.display_lower(formatter)?;
|
||||
@@ -37,6 +66,7 @@ impl Debug for UserInputLeaf {
|
||||
}
|
||||
UserInputLeaf::Set { field, elements } => {
|
||||
if let Some(ref field) = field {
|
||||
// TODO properly escape field (in case of \")
|
||||
write!(formatter, "\"{field}\": ")?;
|
||||
}
|
||||
write!(formatter, "IN [")?;
|
||||
@@ -44,11 +74,15 @@ impl Debug for UserInputLeaf {
|
||||
if i != 0 {
|
||||
write!(formatter, " ")?;
|
||||
}
|
||||
// TODO properly escape element
|
||||
write!(formatter, "\"{text}\"")?;
|
||||
}
|
||||
write!(formatter, "]")
|
||||
}
|
||||
UserInputLeaf::All => write!(formatter, "*"),
|
||||
UserInputLeaf::Exists { field } => {
|
||||
write!(formatter, "\"{field}\":*")
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -60,7 +94,7 @@ pub enum Delimiter {
|
||||
None,
|
||||
}
|
||||
|
||||
#[derive(PartialEq)]
|
||||
#[derive(PartialEq, Clone)]
|
||||
pub struct UserInputLiteral {
|
||||
pub field_name: Option<String>,
|
||||
pub phrase: String,
|
||||
@@ -72,16 +106,20 @@ pub struct UserInputLiteral {
|
||||
impl fmt::Debug for UserInputLiteral {
|
||||
fn fmt(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
|
||||
if let Some(ref field) = self.field_name {
|
||||
// TODO properly escape field (in case of \")
|
||||
write!(formatter, "\"{field}\":")?;
|
||||
}
|
||||
match self.delimiter {
|
||||
Delimiter::SingleQuotes => {
|
||||
// TODO properly escape element (in case of \')
|
||||
write!(formatter, "'{}'", self.phrase)?;
|
||||
}
|
||||
Delimiter::DoubleQuotes => {
|
||||
// TODO properly escape element (in case of \")
|
||||
write!(formatter, "\"{}\"", self.phrase)?;
|
||||
}
|
||||
Delimiter::None => {
|
||||
// TODO properly escape element
|
||||
write!(formatter, "{}", self.phrase)?;
|
||||
}
|
||||
}
|
||||
@@ -94,7 +132,7 @@ impl fmt::Debug for UserInputLiteral {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(PartialEq)]
|
||||
#[derive(PartialEq, Debug, Clone)]
|
||||
pub enum UserInputBound {
|
||||
Inclusive(String),
|
||||
Exclusive(String),
|
||||
@@ -104,6 +142,7 @@ pub enum UserInputBound {
|
||||
impl UserInputBound {
|
||||
fn display_lower(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
|
||||
match *self {
|
||||
// TODO properly escape word if required
|
||||
UserInputBound::Inclusive(ref word) => write!(formatter, "[\"{word}\""),
|
||||
UserInputBound::Exclusive(ref word) => write!(formatter, "{{\"{word}\""),
|
||||
UserInputBound::Unbounded => write!(formatter, "{{\"*\""),
|
||||
@@ -112,6 +151,7 @@ impl UserInputBound {
|
||||
|
||||
fn display_upper(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
|
||||
match *self {
|
||||
// TODO properly escape word if required
|
||||
UserInputBound::Inclusive(ref word) => write!(formatter, "\"{word}\"]"),
|
||||
UserInputBound::Exclusive(ref word) => write!(formatter, "\"{word}\"}}"),
|
||||
UserInputBound::Unbounded => write!(formatter, "\"*\"}}"),
|
||||
@@ -127,6 +167,7 @@ impl UserInputBound {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(PartialEq, Clone)]
|
||||
pub enum UserInputAst {
|
||||
Clause(Vec<(Option<Occur>, UserInputAst)>),
|
||||
Leaf(Box<UserInputLeaf>),
|
||||
@@ -196,6 +237,7 @@ impl fmt::Debug for UserInputAst {
|
||||
match *self {
|
||||
UserInputAst::Clause(ref subqueries) => {
|
||||
if subqueries.is_empty() {
|
||||
// TODO this will break ast reserialization, is writing "( )" enought?
|
||||
write!(formatter, "<emptyclause>")?;
|
||||
} else {
|
||||
write!(formatter, "(")?;
|
||||
|
||||
@@ -48,7 +48,7 @@ mod bench {
|
||||
let score_field_f64 = schema_builder.add_f64_field("score_f64", score_fieldtype.clone());
|
||||
let score_field_i64 = schema_builder.add_i64_field("score_i64", score_fieldtype);
|
||||
let index = Index::create_from_tempdir(schema_builder.build())?;
|
||||
let few_terms_data = vec!["INFO", "ERROR", "WARN", "DEBUG"];
|
||||
let few_terms_data = ["INFO", "ERROR", "WARN", "DEBUG"];
|
||||
|
||||
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
|
||||
|
||||
@@ -85,7 +85,7 @@ mod bench {
|
||||
if cardinality == Cardinality::Sparse {
|
||||
doc_with_value /= 20;
|
||||
}
|
||||
let val_max = 1_000_000.0;
|
||||
let _val_max = 1_000_000.0;
|
||||
for _ in 0..doc_with_value {
|
||||
let val: f64 = rng.gen_range(0.0..1_000_000.0);
|
||||
let json = if rng.gen_bool(0.1) {
|
||||
@@ -290,6 +290,41 @@ 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) {
|
||||
|
||||
@@ -73,9 +73,9 @@ impl AggregationLimits {
|
||||
/// Create a new ResourceLimitGuard, that will release the memory when dropped.
|
||||
pub fn new_guard(&self) -> ResourceLimitGuard {
|
||||
ResourceLimitGuard {
|
||||
/// The counter which is shared between the aggregations for one request.
|
||||
// The counter which is shared between the aggregations for one request.
|
||||
memory_consumption: Arc::clone(&self.memory_consumption),
|
||||
/// The memory_limit in bytes
|
||||
// The memory_limit in bytes
|
||||
memory_limit: self.memory_limit,
|
||||
allocated_with_the_guard: 0,
|
||||
}
|
||||
@@ -134,3 +134,142 @@ impl Drop for ResourceLimitGuard {
|
||||
.fetch_sub(self.allocated_with_the_guard, Ordering::Relaxed);
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::aggregation::tests::exec_request_with_query;
|
||||
|
||||
// https://github.com/quickwit-oss/quickwit/issues/3837
|
||||
#[test]
|
||||
fn test_agg_limits_with_empty_merge() {
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::bucket::tests::get_test_index_from_docs;
|
||||
|
||||
let docs = vec![
|
||||
vec![r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb", "text2": "bbb" }"#],
|
||||
vec![r#"{ "text": "aaa", "text2": "bbb" }"#],
|
||||
];
|
||||
let index = get_test_index_from_docs(false, &docs).unwrap();
|
||||
|
||||
{
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"1": {
|
||||
"terms": {"field": "text2", "min_doc_count": 0},
|
||||
"aggs": {
|
||||
"2":{
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d",
|
||||
"extended_bounds": {
|
||||
"min": "2015-01-01T00:00:00Z",
|
||||
"max": "2015-01-10T00:00:00Z"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request_with_query(agg_req, &index, Some(("text", "bbb"))).unwrap();
|
||||
let expected_res = json!({
|
||||
"1": {
|
||||
"buckets": [
|
||||
{
|
||||
"2": {
|
||||
"buckets": [
|
||||
{ "doc_count": 0, "key": 1420070400000.0, "key_as_string": "2015-01-01T00:00:00Z" },
|
||||
{ "doc_count": 1, "key": 1420156800000.0, "key_as_string": "2015-01-02T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420243200000.0, "key_as_string": "2015-01-03T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420329600000.0, "key_as_string": "2015-01-04T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420416000000.0, "key_as_string": "2015-01-05T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420502400000.0, "key_as_string": "2015-01-06T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420588800000.0, "key_as_string": "2015-01-07T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420675200000.0, "key_as_string": "2015-01-08T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420761600000.0, "key_as_string": "2015-01-09T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420848000000.0, "key_as_string": "2015-01-10T00:00:00Z" }
|
||||
]
|
||||
},
|
||||
"doc_count": 1,
|
||||
"key": "bbb"
|
||||
}
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
}
|
||||
|
||||
// https://github.com/quickwit-oss/quickwit/issues/3837
|
||||
#[test]
|
||||
fn test_agg_limits_with_empty_data() {
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::bucket::tests::get_test_index_from_docs;
|
||||
|
||||
let docs = vec![vec![r#"{ "text": "aaa", "text2": "bbb" }"#]];
|
||||
let index = get_test_index_from_docs(false, &docs).unwrap();
|
||||
|
||||
{
|
||||
// Empty result since there is no doc with dates
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"1": {
|
||||
"terms": {"field": "text2", "min_doc_count": 0},
|
||||
"aggs": {
|
||||
"2":{
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d",
|
||||
"extended_bounds": {
|
||||
"min": "2015-01-01T00:00:00Z",
|
||||
"max": "2015-01-10T00:00:00Z"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request_with_query(agg_req, &index, Some(("text", "bbb"))).unwrap();
|
||||
let expected_res = json!({
|
||||
"1": {
|
||||
"buckets": [
|
||||
{
|
||||
"2": {
|
||||
"buckets": [
|
||||
{ "doc_count": 0, "key": 1420070400000.0, "key_as_string": "2015-01-01T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420156800000.0, "key_as_string": "2015-01-02T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420243200000.0, "key_as_string": "2015-01-03T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420329600000.0, "key_as_string": "2015-01-04T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420416000000.0, "key_as_string": "2015-01-05T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420502400000.0, "key_as_string": "2015-01-06T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420588800000.0, "key_as_string": "2015-01-07T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420675200000.0, "key_as_string": "2015-01-08T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420761600000.0, "key_as_string": "2015-01-09T00:00:00Z" },
|
||||
{ "doc_count": 0, "key": 1420848000000.0, "key_as_string": "2015-01-10T00:00:00Z" }
|
||||
]
|
||||
},
|
||||
"doc_count": 0,
|
||||
"key": "bbb"
|
||||
}
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -35,7 +35,7 @@ use super::bucket::{
|
||||
};
|
||||
use super::metric::{
|
||||
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation,
|
||||
PercentilesAggregationReq, StatsAggregation, SumAggregation,
|
||||
PercentilesAggregationReq, StatsAggregation, SumAggregation, TopHitsAggregation,
|
||||
};
|
||||
|
||||
/// The top-level aggregation request structure, which contains [`Aggregation`] and their user
|
||||
@@ -44,29 +44,61 @@ use super::metric::{
|
||||
/// The key is the user defined name of the aggregation.
|
||||
pub type Aggregations = HashMap<String, Aggregation>;
|
||||
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
/// Aggregation request.
|
||||
///
|
||||
/// An aggregation is either a bucket or a metric.
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
#[serde(try_from = "AggregationForDeserialization")]
|
||||
pub struct Aggregation {
|
||||
/// The aggregation variant, which can be either a bucket or a metric.
|
||||
#[serde(flatten)]
|
||||
pub agg: AggregationVariants,
|
||||
/// The sub_aggregations, only valid for bucket type aggregations. Each bucket will aggregate
|
||||
/// on the document set in the bucket.
|
||||
#[serde(rename = "aggs")]
|
||||
#[serde(default)]
|
||||
#[serde(skip_serializing_if = "Aggregations::is_empty")]
|
||||
pub sub_aggregation: Aggregations,
|
||||
}
|
||||
|
||||
/// In order to display proper error message, we cannot rely on flattening
|
||||
/// the json enum. Instead we introduce an intermediary struct to separate
|
||||
/// the aggregation from the subaggregation.
|
||||
#[derive(Deserialize)]
|
||||
struct AggregationForDeserialization {
|
||||
#[serde(flatten)]
|
||||
pub aggs_remaining_json: serde_json::Value,
|
||||
#[serde(rename = "aggs")]
|
||||
#[serde(default)]
|
||||
pub sub_aggregation: Aggregations,
|
||||
}
|
||||
|
||||
impl TryFrom<AggregationForDeserialization> for Aggregation {
|
||||
type Error = serde_json::Error;
|
||||
|
||||
fn try_from(value: AggregationForDeserialization) -> serde_json::Result<Self> {
|
||||
let AggregationForDeserialization {
|
||||
aggs_remaining_json,
|
||||
sub_aggregation,
|
||||
} = value;
|
||||
let agg: AggregationVariants = serde_json::from_value(aggs_remaining_json)?;
|
||||
Ok(Aggregation {
|
||||
agg,
|
||||
sub_aggregation,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
impl Aggregation {
|
||||
pub(crate) fn sub_aggregation(&self) -> &Aggregations {
|
||||
&self.sub_aggregation
|
||||
}
|
||||
|
||||
fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
|
||||
fast_field_names.insert(self.agg.get_fast_field_name().to_string());
|
||||
fast_field_names.extend(
|
||||
self.agg
|
||||
.get_fast_field_names()
|
||||
.iter()
|
||||
.map(|s| s.to_string()),
|
||||
);
|
||||
fast_field_names.extend(get_fast_field_names(&self.sub_aggregation));
|
||||
}
|
||||
}
|
||||
@@ -120,22 +152,27 @@ 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 {
|
||||
fn get_fast_field_name(&self) -> &str {
|
||||
/// Returns the name of the fields used by the aggregation.
|
||||
pub fn get_fast_field_names(&self) -> Vec<&str> {
|
||||
match self {
|
||||
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(),
|
||||
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(),
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -1,6 +1,9 @@
|
||||
//! This will enhance the request tree with access to the fastfield and metadata.
|
||||
|
||||
use columnar::{Column, ColumnBlockAccessor, ColumnType, StrColumn};
|
||||
use std::collections::HashMap;
|
||||
use std::io;
|
||||
|
||||
use columnar::{Column, ColumnBlockAccessor, ColumnType, DynamicColumn, StrColumn};
|
||||
|
||||
use super::agg_limits::ResourceLimitGuard;
|
||||
use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
|
||||
@@ -13,7 +16,8 @@ use super::metric::{
|
||||
};
|
||||
use super::segment_agg_result::AggregationLimits;
|
||||
use super::VecWithNames;
|
||||
use crate::SegmentReader;
|
||||
use crate::aggregation::{f64_to_fastfield_u64, Key};
|
||||
use crate::{SegmentOrdinal, SegmentReader};
|
||||
|
||||
#[derive(Default)]
|
||||
pub(crate) struct AggregationsWithAccessor {
|
||||
@@ -31,100 +35,313 @@ 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.
|
||||
pub(crate) accessor: Column<u64>,
|
||||
/// Load insert u64 for missing use case
|
||||
pub(crate) missing_value_for_accessor: Option<u64>,
|
||||
pub(crate) str_dict_column: Option<StrColumn>,
|
||||
pub(crate) field_type: ColumnType,
|
||||
/// In case there are multiple types of fast fields, e.g. string and numeric.
|
||||
/// Only used for term aggregations currently.
|
||||
pub(crate) accessor2: Option<(Column<u64>, ColumnType)>,
|
||||
pub(crate) sub_aggregation: AggregationsWithAccessor,
|
||||
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) agg: Aggregation,
|
||||
}
|
||||
|
||||
impl AggregationWithAccessor {
|
||||
/// May return multiple accessors if the aggregation is e.g. on mixed field types.
|
||||
fn try_from_agg(
|
||||
agg: &Aggregation,
|
||||
sub_aggregation: &Aggregations,
|
||||
reader: &SegmentReader,
|
||||
segment_ordinal: SegmentOrdinal,
|
||||
limits: AggregationLimits,
|
||||
) -> crate::Result<AggregationWithAccessor> {
|
||||
let mut str_dict_column = None;
|
||||
let mut accessor2 = None;
|
||||
) -> crate::Result<Vec<AggregationWithAccessor>> {
|
||||
let mut agg = agg.clone();
|
||||
|
||||
let add_agg_with_accessor = |agg: &Aggregation,
|
||||
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(),
|
||||
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(),
|
||||
limits: limits.new_guard(),
|
||||
missing_value_for_accessor: None,
|
||||
str_dict_column: None,
|
||||
column_block_accessor: Default::default(),
|
||||
};
|
||||
aggs.push(res);
|
||||
Ok(())
|
||||
};
|
||||
|
||||
let mut res: Vec<AggregationWithAccessor> = Vec::new();
|
||||
use AggregationVariants::*;
|
||||
let (accessor, field_type) = match &agg.agg {
|
||||
|
||||
match agg.agg {
|
||||
Range(RangeAggregation {
|
||||
field: field_name, ..
|
||||
}) => get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?,
|
||||
Histogram(HistogramAggregation {
|
||||
field: field_name, ..
|
||||
}) => get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?,
|
||||
DateHistogram(DateHistogramAggregationReq {
|
||||
field: field_name, ..
|
||||
}) => get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?,
|
||||
Terms(TermsAggregation {
|
||||
field: field_name, ..
|
||||
field: ref field_name,
|
||||
..
|
||||
}) => {
|
||||
str_dict_column = reader.fast_fields().str(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)?;
|
||||
}
|
||||
Histogram(HistogramAggregation {
|
||||
field: ref 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)?;
|
||||
}
|
||||
DateHistogram(DateHistogramAggregationReq {
|
||||
field: ref 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)?;
|
||||
}
|
||||
Terms(TermsAggregation {
|
||||
field: ref field_name,
|
||||
ref missing,
|
||||
..
|
||||
}) => {
|
||||
let str_dict_column = reader.fast_fields().str(field_name)?;
|
||||
let allowed_column_types = [
|
||||
ColumnType::I64,
|
||||
ColumnType::U64,
|
||||
ColumnType::F64,
|
||||
ColumnType::Str,
|
||||
ColumnType::DateTime,
|
||||
ColumnType::Bool,
|
||||
ColumnType::IpAddr,
|
||||
// ColumnType::Bytes Unsupported
|
||||
// ColumnType::Bool Unsupported
|
||||
// ColumnType::IpAddr Unsupported
|
||||
// ColumnType::DateTime Unsupported
|
||||
];
|
||||
let mut columns =
|
||||
get_all_ff_reader_or_empty(reader, field_name, Some(&allowed_column_types))?;
|
||||
let first = columns.pop().unwrap();
|
||||
accessor2 = columns.pop();
|
||||
first
|
||||
}
|
||||
Average(AverageAggregation { field: field_name })
|
||||
| Count(CountAggregation { field: field_name })
|
||||
| Max(MaxAggregation { field: field_name })
|
||||
| Min(MinAggregation { field: field_name })
|
||||
| Stats(StatsAggregation { field: field_name })
|
||||
| Sum(SumAggregation { field: field_name }) => {
|
||||
let (accessor, field_type) =
|
||||
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
|
||||
|
||||
(accessor, field_type)
|
||||
// In case the column is empty we want the shim column to match the missing type
|
||||
let fallback_type = missing
|
||||
.as_ref()
|
||||
.map(|missing| match missing {
|
||||
Key::Str(_) => ColumnType::Str,
|
||||
Key::F64(_) => ColumnType::F64,
|
||||
})
|
||||
.unwrap_or(ColumnType::U64);
|
||||
let column_and_types = get_all_ff_reader_or_empty(
|
||||
reader,
|
||||
field_name,
|
||||
Some(&allowed_column_types),
|
||||
fallback_type,
|
||||
)?;
|
||||
let missing_and_more_than_one_col = column_and_types.len() > 1 && missing.is_some();
|
||||
let text_on_non_text_col = column_and_types.len() == 1
|
||||
&& column_and_types[0].1.numerical_type().is_some()
|
||||
&& missing
|
||||
.as_ref()
|
||||
.map(|m| matches!(m, Key::Str(_)))
|
||||
.unwrap_or(false);
|
||||
|
||||
// Actually we could convert the text to a number and have the fast path, if it is
|
||||
// provided in Rfc3339 format. But this use case is probably common
|
||||
// enough to justify the effort.
|
||||
let text_on_date_col = column_and_types.len() == 1
|
||||
&& column_and_types[0].1 == ColumnType::DateTime
|
||||
&& missing
|
||||
.as_ref()
|
||||
.map(|m| matches!(m, Key::Str(_)))
|
||||
.unwrap_or(false);
|
||||
|
||||
let use_special_missing_agg =
|
||||
missing_and_more_than_one_col || text_on_non_text_col || text_on_date_col;
|
||||
if use_special_missing_agg {
|
||||
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())?;
|
||||
}
|
||||
|
||||
for (accessor, column_type) in column_and_types {
|
||||
let missing_value_term_agg = if use_special_missing_agg {
|
||||
None
|
||||
} else {
|
||||
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 agg = AggregationWithAccessor {
|
||||
segment_ordinal,
|
||||
missing_value_for_accessor,
|
||||
accessor,
|
||||
accessors: Default::default(),
|
||||
value_accessors: Default::default(),
|
||||
field_type: column_type,
|
||||
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
|
||||
sub_aggregation,
|
||||
reader,
|
||||
segment_ordinal,
|
||||
&limits,
|
||||
)?,
|
||||
agg: agg.clone(),
|
||||
str_dict_column: str_dict_column.clone(),
|
||||
limits: limits.new_guard(),
|
||||
column_block_accessor: Default::default(),
|
||||
};
|
||||
res.push(agg);
|
||||
}
|
||||
}
|
||||
Percentiles(percentiles) => {
|
||||
let (accessor, field_type) = get_ff_reader(
|
||||
Average(AverageAggregation {
|
||||
field: ref field_name,
|
||||
..
|
||||
})
|
||||
| Count(CountAggregation {
|
||||
field: ref field_name,
|
||||
..
|
||||
})
|
||||
| Max(MaxAggregation {
|
||||
field: ref field_name,
|
||||
..
|
||||
})
|
||||
| Min(MinAggregation {
|
||||
field: ref field_name,
|
||||
..
|
||||
})
|
||||
| Stats(StatsAggregation {
|
||||
field: ref field_name,
|
||||
..
|
||||
})
|
||||
| Sum(SumAggregation {
|
||||
field: ref 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)?;
|
||||
}
|
||||
Percentiles(ref percentiles) => {
|
||||
let (accessor, column_type) = get_ff_reader(
|
||||
reader,
|
||||
percentiles.field_name(),
|
||||
Some(get_numeric_or_date_column_types()),
|
||||
)?;
|
||||
(accessor, field_type)
|
||||
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)?;
|
||||
}
|
||||
};
|
||||
|
||||
let sub_aggregation = sub_aggregation.clone();
|
||||
Ok(AggregationWithAccessor {
|
||||
accessor,
|
||||
accessor2,
|
||||
field_type,
|
||||
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
|
||||
&sub_aggregation,
|
||||
reader,
|
||||
&limits,
|
||||
)?,
|
||||
agg: agg.clone(),
|
||||
str_dict_column,
|
||||
limits: limits.new_guard(),
|
||||
column_block_accessor: Default::default(),
|
||||
})
|
||||
Ok(res)
|
||||
}
|
||||
}
|
||||
|
||||
fn get_missing_val(
|
||||
column_type: ColumnType,
|
||||
missing: &Key,
|
||||
field_name: &str,
|
||||
) -> crate::Result<Option<u64>> {
|
||||
let missing_val = match missing {
|
||||
Key::Str(_) if column_type == ColumnType::Str => Some(u64::MAX),
|
||||
// Allow fallback to number on text fields
|
||||
Key::F64(_) if column_type == ColumnType::Str => Some(u64::MAX),
|
||||
Key::F64(val) if column_type.numerical_type().is_some() => {
|
||||
f64_to_fastfield_u64(*val, &column_type)
|
||||
}
|
||||
_ => {
|
||||
return Err(crate::TantivyError::InvalidArgument(format!(
|
||||
"Missing value {:?} for field {} is not supported for column type {:?}",
|
||||
missing, field_name, column_type
|
||||
)));
|
||||
}
|
||||
};
|
||||
Ok(missing_val)
|
||||
}
|
||||
|
||||
fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
|
||||
&[
|
||||
ColumnType::F64,
|
||||
@@ -137,19 +354,21 @@ 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();
|
||||
for (key, agg) in aggs.iter() {
|
||||
aggss.push((
|
||||
key.to_string(),
|
||||
AggregationWithAccessor::try_from_agg(
|
||||
agg,
|
||||
agg.sub_aggregation(),
|
||||
reader,
|
||||
limits.clone(),
|
||||
)?,
|
||||
));
|
||||
let aggs = AggregationWithAccessor::try_from_agg(
|
||||
agg,
|
||||
agg.sub_aggregation(),
|
||||
reader,
|
||||
segment_ordinal,
|
||||
limits.clone(),
|
||||
)?;
|
||||
for agg in aggs {
|
||||
aggss.push((key.to_string(), agg));
|
||||
}
|
||||
}
|
||||
Ok(AggregationsWithAccessor::from_data(
|
||||
VecWithNames::from_entries(aggss),
|
||||
@@ -174,6 +393,19 @@ 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.
|
||||
@@ -181,15 +413,13 @@ fn get_all_ff_reader_or_empty(
|
||||
reader: &SegmentReader,
|
||||
field_name: &str,
|
||||
allowed_column_types: Option<&[ColumnType]>,
|
||||
fallback_type: ColumnType,
|
||||
) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
|
||||
let ff_fields = reader.fast_fields();
|
||||
let mut ff_field_with_type =
|
||||
ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
|
||||
if ff_field_with_type.is_empty() {
|
||||
ff_field_with_type.push((
|
||||
Column::build_empty_column(reader.num_docs()),
|
||||
ColumnType::U64,
|
||||
));
|
||||
ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
|
||||
}
|
||||
Ok(ff_field_with_type)
|
||||
}
|
||||
|
||||
@@ -8,7 +8,7 @@ use rustc_hash::FxHashMap;
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use super::bucket::GetDocCount;
|
||||
use super::metric::{PercentilesMetricResult, SingleMetricResult, Stats};
|
||||
use super::metric::{PercentilesMetricResult, SingleMetricResult, Stats, TopHitsMetricResult};
|
||||
use super::{AggregationError, Key};
|
||||
use crate::TantivyError;
|
||||
|
||||
@@ -90,8 +90,10 @@ pub enum MetricResult {
|
||||
Stats(Stats),
|
||||
/// Sum metric result.
|
||||
Sum(SingleMetricResult),
|
||||
/// Sum metric result.
|
||||
/// Percentiles metric result.
|
||||
Percentiles(PercentilesMetricResult),
|
||||
/// Top hits metric result
|
||||
TopHits(TopHitsMetricResult),
|
||||
}
|
||||
|
||||
impl MetricResult {
|
||||
@@ -106,6 +108,9 @@ 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()),
|
||||
)),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -4,12 +4,13 @@ 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;
|
||||
use crate::query::{AllQuery, TermQuery};
|
||||
use crate::schema::{IndexRecordOption, Schema, FAST};
|
||||
use crate::{Index, Term};
|
||||
use crate::{Index, IndexWriter, Term};
|
||||
|
||||
fn get_avg_req(field_name: &str) -> Aggregation {
|
||||
serde_json::from_value(json!({
|
||||
@@ -66,6 +67,22 @@ 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",
|
||||
@@ -108,6 +125,16 @@ 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()
|
||||
@@ -558,10 +585,10 @@ fn test_aggregation_invalid_requests() -> crate::Result<()> {
|
||||
|
||||
assert_eq!(agg_req_1.is_err(), true);
|
||||
// TODO: This should list valid values
|
||||
assert_eq!(
|
||||
agg_req_1.unwrap_err().to_string(),
|
||||
"no variant of enum AggregationVariants found in flattened data"
|
||||
);
|
||||
assert!(agg_req_1
|
||||
.unwrap_err()
|
||||
.to_string()
|
||||
.contains("unknown variant `doesnotmatchanyagg`, expected one of"));
|
||||
|
||||
// TODO: This should return an error
|
||||
// let agg_res = avg_on_field("not_exist_field").unwrap_err();
|
||||
@@ -586,7 +613,10 @@ fn test_aggregation_on_json_object() {
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
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();
|
||||
@@ -614,12 +644,74 @@ fn test_aggregation_on_json_object() {
|
||||
&serde_json::json!({
|
||||
"jsonagg": {
|
||||
"buckets": [
|
||||
{"doc_count": 2, "key": "red"},
|
||||
{"doc_count": 1, "key": "blue"},
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
})
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_aggregation_on_nested_json_object() {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json.blub", FAST);
|
||||
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.dot": "red", "color": {"nested":"red"} })))
|
||||
.unwrap();
|
||||
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();
|
||||
|
||||
let agg: Aggregations = serde_json::from_value(json!({
|
||||
"jsonagg1": {
|
||||
"terms": {
|
||||
"field": "json\\.blub.color\\.dot",
|
||||
}
|
||||
},
|
||||
"jsonagg2": {
|
||||
"terms": {
|
||||
"field": "json\\.blub.color.nested",
|
||||
}
|
||||
}
|
||||
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let aggregation_collector = get_collector(agg);
|
||||
let aggregation_results = searcher.search(&AllQuery, &aggregation_collector).unwrap();
|
||||
let aggregation_res_json = serde_json::to_value(aggregation_results).unwrap();
|
||||
assert_eq!(
|
||||
&aggregation_res_json,
|
||||
&serde_json::json!({
|
||||
"jsonagg1": {
|
||||
"buckets": [
|
||||
{"doc_count": 2, "key": "blue"},
|
||||
{"doc_count": 1, "key": "red"}
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
},
|
||||
"jsonagg2": {
|
||||
"buckets": [
|
||||
{"doc_count": 2, "key": "blue"},
|
||||
{"doc_count": 1, "key": "red"}
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
|
||||
})
|
||||
);
|
||||
}
|
||||
@@ -630,7 +722,7 @@ fn test_aggregation_on_json_object_empty_columns() {
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
|
||||
// => Empty column when accessing color
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"price": 10.0})))
|
||||
@@ -748,32 +840,41 @@ fn test_aggregation_on_json_object_mixed_types() {
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
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})))
|
||||
.add_document(doc!(json => json!({"mixed_type": 10.0, "mixed_price": 10.0})))
|
||||
.unwrap();
|
||||
index_writer.commit().unwrap();
|
||||
// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "blue"})))
|
||||
.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})))
|
||||
.unwrap();
|
||||
index_writer.commit().unwrap();
|
||||
// => Segment with all boolen
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": true})))
|
||||
.add_document(doc!(json => json!({"mixed_type": true, "mixed_price": "no_price"})))
|
||||
.unwrap();
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "red"})))
|
||||
.add_document(doc!(json => json!({"mixed_type": "red", "mixed_price": 1.0})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.add_document(doc!(json => json!({"mixed_type": "red", "mixed_price": 1.0})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": true})))
|
||||
.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"})))
|
||||
.unwrap();
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
@@ -787,7 +888,7 @@ fn test_aggregation_on_json_object_mixed_types() {
|
||||
"order": { "min_price": "desc" }
|
||||
},
|
||||
"aggs": {
|
||||
"min_price": { "min": { "field": "json.mixed_type" } }
|
||||
"min_price": { "min": { "field": "json.mixed_price" } }
|
||||
}
|
||||
},
|
||||
"rangeagg": {
|
||||
@@ -811,6 +912,7 @@ 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!({
|
||||
@@ -825,10 +927,10 @@ 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 } },
|
||||
// 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 } },
|
||||
{ "doc_count": 2, "key": 1.0, "key_as_string": "true", "min_price": { "value": null } },
|
||||
],
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use super::{HistogramAggregation, HistogramBounds};
|
||||
use crate::aggregation::AggregationError;
|
||||
use crate::aggregation::*;
|
||||
|
||||
/// DateHistogramAggregation is similar to `HistogramAggregation`, but it can only be used with date
|
||||
/// type.
|
||||
@@ -132,6 +132,7 @@ impl DateHistogramAggregationReq {
|
||||
hard_bounds: self.hard_bounds,
|
||||
extended_bounds: self.extended_bounds,
|
||||
keyed: self.keyed,
|
||||
is_normalized_to_ns: false,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -243,15 +244,15 @@ fn parse_into_milliseconds(input: &str) -> Result<i64, AggregationError> {
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
pub mod tests {
|
||||
use pretty_assertions::assert_eq;
|
||||
|
||||
use super::*;
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::tests::exec_request;
|
||||
use crate::indexer::NoMergePolicy;
|
||||
use crate::schema::{Schema, FAST};
|
||||
use crate::Index;
|
||||
use crate::schema::{Schema, FAST, STRING};
|
||||
use crate::{Index, IndexWriter, TantivyDocument};
|
||||
|
||||
#[test]
|
||||
fn test_parse_into_millisecs() {
|
||||
@@ -306,7 +307,9 @@ mod tests {
|
||||
) -> crate::Result<Index> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
schema_builder.add_date_field("date", FAST);
|
||||
schema_builder.add_text_field("text", 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();
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
{
|
||||
@@ -314,7 +317,7 @@ mod tests {
|
||||
index_writer.set_merge_policy(Box::new(NoMergePolicy));
|
||||
for values in segment_and_docs {
|
||||
for doc_str in values {
|
||||
let doc = schema.parse_document(doc_str)?;
|
||||
let doc = TantivyDocument::parse_json(&schema, doc_str)?;
|
||||
index_writer.add_document(doc)?;
|
||||
}
|
||||
// writing the segment
|
||||
@@ -326,7 +329,7 @@ mod tests {
|
||||
.searchable_segment_ids()
|
||||
.expect("Searchable segments failed.");
|
||||
if segment_ids.len() > 1 {
|
||||
let mut index_writer = index.writer_for_tests()?;
|
||||
let mut index_writer: IndexWriter = index.writer_for_tests()?;
|
||||
index_writer.merge(&segment_ids).wait()?;
|
||||
index_writer.wait_merging_threads()?;
|
||||
}
|
||||
@@ -349,8 +352,10 @@ 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();
|
||||
|
||||
@@ -379,7 +384,7 @@ mod tests {
|
||||
{
|
||||
"key_as_string" : "2015-01-01T00:00:00Z",
|
||||
"key" : 1420070400000.0,
|
||||
"doc_count" : 4
|
||||
"doc_count" : 6
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -417,15 +422,15 @@ mod tests {
|
||||
{
|
||||
"key_as_string" : "2015-01-01T00:00:00Z",
|
||||
"key" : 1420070400000.0,
|
||||
"doc_count" : 4,
|
||||
"doc_count" : 6,
|
||||
"texts": {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 2,
|
||||
"doc_count": 3,
|
||||
"key": "bbb"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"doc_count": 2,
|
||||
"key": "ccc"
|
||||
},
|
||||
{
|
||||
@@ -464,7 +469,7 @@ mod tests {
|
||||
"sales_over_time": {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 2,
|
||||
"doc_count": 3,
|
||||
"key": 1420070400000.0,
|
||||
"key_as_string": "2015-01-01T00:00:00Z"
|
||||
},
|
||||
@@ -489,7 +494,7 @@ mod tests {
|
||||
"key_as_string": "2015-01-05T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"doc_count": 2,
|
||||
"key": 1420502400000.0,
|
||||
"key_as_string": "2015-01-06T00:00:00Z"
|
||||
}
|
||||
@@ -530,7 +535,7 @@ mod tests {
|
||||
"key_as_string": "2014-12-31T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 2,
|
||||
"doc_count": 3,
|
||||
"key": 1420070400000.0,
|
||||
"key_as_string": "2015-01-01T00:00:00Z"
|
||||
},
|
||||
@@ -555,7 +560,7 @@ mod tests {
|
||||
"key_as_string": "2015-01-05T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"doc_count": 2,
|
||||
"key": 1420502400000.0,
|
||||
"key_as_string": "2015-01-06T00:00:00Z"
|
||||
},
|
||||
|
||||
@@ -1,8 +1,5 @@
|
||||
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;
|
||||
@@ -18,9 +15,9 @@ use crate::aggregation::intermediate_agg_result::{
|
||||
IntermediateHistogramBucketEntry,
|
||||
};
|
||||
use crate::aggregation::segment_agg_result::{
|
||||
build_segment_agg_collector, AggregationLimits, SegmentAggregationCollector,
|
||||
build_segment_agg_collector, SegmentAggregationCollector,
|
||||
};
|
||||
use crate::aggregation::{f64_from_fastfield_u64, format_date};
|
||||
use crate::aggregation::*;
|
||||
use crate::TantivyError;
|
||||
|
||||
/// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
|
||||
@@ -73,6 +70,7 @@ 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))`.
|
||||
@@ -85,6 +83,7 @@ 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>,
|
||||
@@ -122,11 +121,14 @@ pub struct HistogramAggregation {
|
||||
/// Whether to return the buckets as a hash map
|
||||
#[serde(default)]
|
||||
pub keyed: bool,
|
||||
/// Whether the values are normalized to ns for date time values. Defaults to false.
|
||||
#[serde(default)]
|
||||
pub is_normalized_to_ns: bool,
|
||||
}
|
||||
|
||||
impl HistogramAggregation {
|
||||
pub(crate) fn normalize(&mut self, column_type: ColumnType) {
|
||||
if column_type.is_date_time() {
|
||||
pub(crate) fn normalize_date_time(&mut self) {
|
||||
if !self.is_normalized_to_ns {
|
||||
// values are provided in ms, but the fastfield is in nano seconds
|
||||
self.interval *= 1_000_000.0;
|
||||
self.offset = self.offset.map(|off| off * 1_000_000.0);
|
||||
@@ -138,6 +140,7 @@ impl HistogramAggregation {
|
||||
min: bounds.min * 1_000_000.0,
|
||||
max: bounds.max * 1_000_000.0,
|
||||
});
|
||||
self.is_normalized_to_ns = true;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -304,7 +307,10 @@ 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() {
|
||||
for (doc, val) in bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
|
||||
{
|
||||
let val = self.f64_from_fastfield_u64(val);
|
||||
|
||||
let bucket_pos = get_bucket_pos(val);
|
||||
@@ -351,6 +357,7 @@ impl SegmentHistogramCollector {
|
||||
let buckets_mem = self.buckets.memory_consumption();
|
||||
self_mem + sub_aggs_mem + buckets_mem
|
||||
}
|
||||
/// Converts the collector result into a intermediate bucket result.
|
||||
pub fn into_intermediate_bucket_result(
|
||||
self,
|
||||
agg_with_accessor: &AggregationWithAccessor,
|
||||
@@ -369,7 +376,7 @@ impl SegmentHistogramCollector {
|
||||
|
||||
Ok(IntermediateBucketResult::Histogram {
|
||||
buckets,
|
||||
column_type: Some(self.column_type),
|
||||
is_date_agg: self.column_type == ColumnType::DateTime,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -380,7 +387,9 @@ impl SegmentHistogramCollector {
|
||||
accessor_idx: usize,
|
||||
) -> crate::Result<Self> {
|
||||
req.validate()?;
|
||||
req.normalize(field_type);
|
||||
if field_type == ColumnType::DateTime {
|
||||
req.normalize_date_time();
|
||||
}
|
||||
|
||||
let sub_aggregation_blueprint = if sub_aggregation.is_empty() {
|
||||
None
|
||||
@@ -438,6 +447,7 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
|
||||
// memory check upfront
|
||||
let (_, first_bucket_num, last_bucket_num) =
|
||||
generate_bucket_pos_with_opt_minmax(histogram_req, min_max);
|
||||
|
||||
// It's based on user input, so we need to account for overflows
|
||||
let added_buckets = ((last_bucket_num.saturating_sub(first_bucket_num)).max(0) as u64)
|
||||
.saturating_sub(buckets.len() as u64);
|
||||
@@ -453,15 +463,12 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
|
||||
|
||||
let final_buckets: Vec<BucketEntry> = buckets
|
||||
.into_iter()
|
||||
.merge_join_by(
|
||||
fill_gaps_buckets.into_iter(),
|
||||
|existing_bucket, fill_gaps_bucket| {
|
||||
existing_bucket
|
||||
.key
|
||||
.partial_cmp(fill_gaps_bucket)
|
||||
.unwrap_or(Ordering::Equal)
|
||||
},
|
||||
)
|
||||
.merge_join_by(fill_gaps_buckets, |existing_bucket, fill_gaps_bucket| {
|
||||
existing_bucket
|
||||
.key
|
||||
.partial_cmp(fill_gaps_bucket)
|
||||
.unwrap_or(Ordering::Equal)
|
||||
})
|
||||
.map(|either| match either {
|
||||
// Ignore the generated bucket
|
||||
itertools::EitherOrBoth::Both(existing, _) => existing,
|
||||
@@ -484,7 +491,7 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
|
||||
// Convert to BucketEntry
|
||||
pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
|
||||
buckets: Vec<IntermediateHistogramBucketEntry>,
|
||||
column_type: Option<ColumnType>,
|
||||
is_date_agg: bool,
|
||||
histogram_req: &HistogramAggregation,
|
||||
sub_aggregation: &Aggregations,
|
||||
limits: &AggregationLimits,
|
||||
@@ -493,8 +500,8 @@ pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
|
||||
// The request used in the the call to final is not yet be normalized.
|
||||
// Normalization is changing the precision from milliseconds to nanoseconds.
|
||||
let mut histogram_req = histogram_req.clone();
|
||||
if let Some(column_type) = column_type {
|
||||
histogram_req.normalize(column_type);
|
||||
if is_date_agg {
|
||||
histogram_req.normalize_date_time();
|
||||
}
|
||||
let mut buckets = if histogram_req.min_doc_count() == 0 {
|
||||
// With min_doc_count != 0, we may need to add buckets, so that there are no
|
||||
@@ -518,7 +525,7 @@ pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
|
||||
|
||||
// If we have a date type on the histogram buckets, we add the `key_as_string` field as rfc339
|
||||
// and normalize from nanoseconds to milliseconds
|
||||
if column_type == Some(ColumnType::DateTime) {
|
||||
if is_date_agg {
|
||||
for bucket in buckets.iter_mut() {
|
||||
if let crate::aggregation::Key::F64(ref mut val) = bucket.key {
|
||||
let key_as_string = format_date(*val as i64)?;
|
||||
@@ -590,11 +597,12 @@ mod tests {
|
||||
use serde_json::Value;
|
||||
|
||||
use super::*;
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::agg_result::AggregationResults;
|
||||
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<()> {
|
||||
@@ -1346,6 +1354,35 @@ 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(())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -15,19 +15,25 @@
|
||||
//! Results of final buckets are [`BucketResult`](super::agg_result::BucketResult).
|
||||
//! Results of intermediate buckets are
|
||||
//! [`IntermediateBucketResult`](super::intermediate_agg_result::IntermediateBucketResult)
|
||||
//!
|
||||
//! ## Supported Bucket Aggregations
|
||||
//! - [Histogram](HistogramAggregation)
|
||||
//! - [DateHistogram](DateHistogramAggregationReq)
|
||||
//! - [Range](RangeAggregation)
|
||||
//! - [Terms](TermsAggregation)
|
||||
|
||||
mod histogram;
|
||||
mod range;
|
||||
mod term_agg;
|
||||
mod term_missing_agg;
|
||||
|
||||
use std::collections::HashMap;
|
||||
|
||||
pub(crate) use histogram::SegmentHistogramCollector;
|
||||
pub use histogram::*;
|
||||
pub(crate) use range::SegmentRangeCollector;
|
||||
pub use range::*;
|
||||
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
|
||||
pub use term_agg::*;
|
||||
pub use term_missing_agg::*;
|
||||
|
||||
/// Order for buckets in a bucket aggregation.
|
||||
#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize, Default)]
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
use std::fmt::Debug;
|
||||
use std::ops::Range;
|
||||
|
||||
use columnar::{ColumnType, MonotonicallyMappableToU64};
|
||||
use rustc_hash::FxHashMap;
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
@@ -14,9 +13,7 @@ use crate::aggregation::intermediate_agg_result::{
|
||||
use crate::aggregation::segment_agg_result::{
|
||||
build_segment_agg_collector, SegmentAggregationCollector,
|
||||
};
|
||||
use crate::aggregation::{
|
||||
f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
|
||||
};
|
||||
use crate::aggregation::*;
|
||||
use crate::TantivyError;
|
||||
|
||||
/// Provide user-defined buckets to aggregate on.
|
||||
@@ -72,11 +69,19 @@ 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)]
|
||||
#[serde(
|
||||
skip_serializing_if = "Option::is_none",
|
||||
default,
|
||||
deserialize_with = "deserialize_option_f64"
|
||||
)]
|
||||
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)]
|
||||
#[serde(
|
||||
skip_serializing_if = "Option::is_none",
|
||||
default,
|
||||
deserialize_with = "deserialize_option_f64"
|
||||
)]
|
||||
pub to: Option<f64>,
|
||||
}
|
||||
|
||||
@@ -230,7 +235,10 @@ 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() {
|
||||
for (doc, val) in bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
|
||||
{
|
||||
let bucket_pos = self.get_bucket_pos(val);
|
||||
|
||||
let bucket = &mut self.buckets[bucket_pos];
|
||||
@@ -262,7 +270,7 @@ impl SegmentRangeCollector {
|
||||
pub(crate) fn from_req_and_validate(
|
||||
req: &RangeAggregation,
|
||||
sub_aggregation: &mut AggregationsWithAccessor,
|
||||
limits: &mut ResourceLimitGuard,
|
||||
limits: &ResourceLimitGuard,
|
||||
field_type: ColumnType,
|
||||
accessor_idx: usize,
|
||||
) -> crate::Result<Self> {
|
||||
@@ -441,7 +449,6 @@ 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::*;
|
||||
@@ -450,7 +457,6 @@ 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>,
|
||||
@@ -465,7 +471,7 @@ mod tests {
|
||||
SegmentRangeCollector::from_req_and_validate(
|
||||
&req,
|
||||
&mut Default::default(),
|
||||
&mut AggregationLimits::default().new_guard(),
|
||||
&AggregationLimits::default().new_guard(),
|
||||
field_type,
|
||||
0,
|
||||
)
|
||||
|
||||
@@ -1,6 +1,10 @@
|
||||
use std::fmt::Debug;
|
||||
use std::net::Ipv6Addr;
|
||||
|
||||
use columnar::ColumnType;
|
||||
use columnar::column_values::CompactSpaceU64Accessor;
|
||||
use columnar::{
|
||||
BytesColumn, ColumnType, MonotonicallyMappableToU128, MonotonicallyMappableToU64, StrColumn,
|
||||
};
|
||||
use rustc_hash::FxHashMap;
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
@@ -9,7 +13,6 @@ use crate::aggregation::agg_limits::MemoryConsumption;
|
||||
use crate::aggregation::agg_req_with_accessor::{
|
||||
AggregationWithAccessor, AggregationsWithAccessor,
|
||||
};
|
||||
use crate::aggregation::f64_from_fastfield_u64;
|
||||
use crate::aggregation::intermediate_agg_result::{
|
||||
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
|
||||
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
|
||||
@@ -17,6 +20,7 @@ use crate::aggregation::intermediate_agg_result::{
|
||||
use crate::aggregation::segment_agg_result::{
|
||||
build_segment_agg_collector, SegmentAggregationCollector,
|
||||
};
|
||||
use crate::aggregation::{f64_from_fastfield_u64, format_date, Key};
|
||||
use crate::error::DataCorruption;
|
||||
use crate::TantivyError;
|
||||
|
||||
@@ -99,23 +103,14 @@ pub struct TermsAggregation {
|
||||
#[serde(skip_serializing_if = "Option::is_none", default)]
|
||||
pub size: Option<u32>,
|
||||
|
||||
/// 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.
|
||||
/// To 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
|
||||
@@ -146,6 +141,28 @@ pub struct TermsAggregation {
|
||||
/// { "average_price": "asc" }
|
||||
#[serde(skip_serializing_if = "Option::is_none", default)]
|
||||
pub order: Option<CustomOrder>,
|
||||
|
||||
/// The missing parameter defines how documents that are missing a value should be treated.
|
||||
/// By default they will be ignored but it is also possible to treat them as if they had a
|
||||
/// value. Examples in JSON format:
|
||||
/// { "missing": "NO_DATA" }
|
||||
///
|
||||
/// # Internal
|
||||
///
|
||||
/// Internally, `missing` requires some specialized handling in some scenarios.
|
||||
///
|
||||
/// Simple Case:
|
||||
/// In the simplest case, we can just put the missing value in the termmap use that. In case of
|
||||
/// text we put a special u64::MAX and replace it at the end with the actual missing value,
|
||||
/// when loading the text.
|
||||
/// Special Case 1:
|
||||
/// If we have multiple columns on one field, we need to have a union on the indices on both
|
||||
/// columns, to find docids without a value. That requires a special missing aggreggation.
|
||||
/// Special Case 2: if the key is of type text and the column is numerical, we also need to use
|
||||
/// the special missing aggregation, since there is no mechanism in the numerical column to
|
||||
/// add text.
|
||||
#[serde(skip_serializing_if = "Option::is_none", default)]
|
||||
pub missing: Option<Key>,
|
||||
}
|
||||
|
||||
/// Same as TermsAggregation, but with populated defaults.
|
||||
@@ -176,6 +193,7 @@ pub(crate) struct TermsAggregationInternal {
|
||||
pub min_doc_count: u64,
|
||||
|
||||
pub order: CustomOrder,
|
||||
pub missing: Option<Key>,
|
||||
}
|
||||
|
||||
impl TermsAggregationInternal {
|
||||
@@ -195,6 +213,7 @@ impl TermsAggregationInternal {
|
||||
.unwrap_or_else(|| order == CustomOrder::default()),
|
||||
min_doc_count: req.min_doc_count.unwrap_or(1),
|
||||
order,
|
||||
missing: req.missing.clone(),
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -224,110 +243,6 @@ impl TermBuckets {
|
||||
}
|
||||
}
|
||||
|
||||
/// The composite collector is used, when we have different types under one field, to support a term
|
||||
/// aggregation on both.
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct SegmentTermCollectorComposite {
|
||||
term_agg1: SegmentTermCollector, // field type 1, e.g. strings
|
||||
term_agg2: SegmentTermCollector, // field type 2, e.g. u64
|
||||
accessor_idx: usize,
|
||||
}
|
||||
impl SegmentAggregationCollector for SegmentTermCollectorComposite {
|
||||
fn add_intermediate_aggregation_result(
|
||||
self: Box<Self>,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
results: &mut IntermediateAggregationResults,
|
||||
) -> crate::Result<()> {
|
||||
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
|
||||
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
|
||||
|
||||
let bucket = self
|
||||
.term_agg1
|
||||
.into_intermediate_bucket_result(agg_with_accessor)?;
|
||||
results.push(
|
||||
name.to_string(),
|
||||
IntermediateAggregationResult::Bucket(bucket),
|
||||
)?;
|
||||
let bucket = self
|
||||
.term_agg2
|
||||
.into_intermediate_bucket_result(agg_with_accessor)?;
|
||||
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn collect(
|
||||
&mut self,
|
||||
doc: crate::DocId,
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
self.term_agg1.collect_block(&[doc], agg_with_accessor)?;
|
||||
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
|
||||
self.term_agg2.collect_block(&[doc], agg_with_accessor)?;
|
||||
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn collect_block(
|
||||
&mut self,
|
||||
docs: &[crate::DocId],
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
self.term_agg1.collect_block(docs, agg_with_accessor)?;
|
||||
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
|
||||
self.term_agg2.collect_block(docs, agg_with_accessor)?;
|
||||
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
|
||||
self.term_agg1.flush(agg_with_accessor)?;
|
||||
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
|
||||
self.term_agg2.flush(agg_with_accessor)?;
|
||||
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl SegmentTermCollectorComposite {
|
||||
/// Swaps the accessor and field type with the second accessor and field type.
|
||||
/// This way we can use the same code for both aggregations.
|
||||
fn swap_accessor(&self, aggregations: &mut AggregationWithAccessor) {
|
||||
if let Some(accessor) = aggregations.accessor2.as_mut() {
|
||||
std::mem::swap(&mut accessor.0, &mut aggregations.accessor);
|
||||
std::mem::swap(&mut accessor.1, &mut aggregations.field_type);
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn from_req_and_validate(
|
||||
req: &TermsAggregation,
|
||||
sub_aggregations: &mut AggregationsWithAccessor,
|
||||
field_type: ColumnType,
|
||||
field_type2: ColumnType,
|
||||
accessor_idx: usize,
|
||||
) -> crate::Result<Self> {
|
||||
Ok(Self {
|
||||
term_agg1: SegmentTermCollector::from_req_and_validate(
|
||||
req,
|
||||
sub_aggregations,
|
||||
field_type,
|
||||
accessor_idx,
|
||||
)?,
|
||||
term_agg2: SegmentTermCollector::from_req_and_validate(
|
||||
req,
|
||||
sub_aggregations,
|
||||
field_type2,
|
||||
accessor_idx,
|
||||
)?,
|
||||
accessor_idx,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
/// The collector puts values from the fast field into the correct buckets and does a conversion to
|
||||
/// the correct datatype.
|
||||
#[derive(Clone, Debug)]
|
||||
@@ -336,7 +251,7 @@ pub struct SegmentTermCollector {
|
||||
term_buckets: TermBuckets,
|
||||
req: TermsAggregationInternal,
|
||||
blueprint: Option<Box<dyn SegmentAggregationCollector>>,
|
||||
field_type: ColumnType,
|
||||
column_type: ColumnType,
|
||||
accessor_idx: usize,
|
||||
}
|
||||
|
||||
@@ -379,16 +294,26 @@ impl SegmentAggregationCollector for SegmentTermCollector {
|
||||
|
||||
let mem_pre = self.get_memory_consumption();
|
||||
|
||||
bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.fetch_block(docs, &bucket_agg_accessor.accessor);
|
||||
if let Some(missing) = bucket_agg_accessor.missing_value_for_accessor {
|
||||
bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.fetch_block_with_missing(docs, &bucket_agg_accessor.accessor, missing);
|
||||
} else {
|
||||
bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.fetch_block(docs, &bucket_agg_accessor.accessor);
|
||||
}
|
||||
|
||||
for term_id in bucket_agg_accessor.column_block_accessor.iter_vals() {
|
||||
let entry = self.term_buckets.entries.entry(term_id).or_default();
|
||||
*entry += 1;
|
||||
}
|
||||
// has subagg
|
||||
if let Some(blueprint) = self.blueprint.as_ref() {
|
||||
for (doc, term_id) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
|
||||
for (doc, term_id) in bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
|
||||
{
|
||||
let sub_aggregations = self
|
||||
.term_buckets
|
||||
.sub_aggs
|
||||
@@ -428,7 +353,7 @@ impl SegmentTermCollector {
|
||||
field_type: ColumnType,
|
||||
accessor_idx: usize,
|
||||
) -> crate::Result<Self> {
|
||||
if field_type == ColumnType::Bytes || field_type == ColumnType::Bool {
|
||||
if field_type == ColumnType::Bytes {
|
||||
return Err(TantivyError::InvalidArgument(format!(
|
||||
"terms aggregation is not supported for column type {:?}",
|
||||
field_type
|
||||
@@ -462,7 +387,7 @@ impl SegmentTermCollector {
|
||||
req: TermsAggregationInternal::from_req(req),
|
||||
term_buckets,
|
||||
blueprint,
|
||||
field_type,
|
||||
column_type: field_type,
|
||||
accessor_idx,
|
||||
})
|
||||
}
|
||||
@@ -539,23 +464,46 @@ impl SegmentTermCollector {
|
||||
Ok(intermediate_entry)
|
||||
};
|
||||
|
||||
if self.field_type == ColumnType::Str {
|
||||
if self.column_type == ColumnType::Str {
|
||||
let term_dict = agg_with_accessor
|
||||
.str_dict_column
|
||||
.as_ref()
|
||||
.expect("internal error: term dictionary not found for term aggregation");
|
||||
|
||||
.cloned()
|
||||
.unwrap_or_else(|| {
|
||||
StrColumn::wrap(BytesColumn::empty(agg_with_accessor.accessor.num_docs()))
|
||||
});
|
||||
let mut buffer = String::new();
|
||||
for (term_id, doc_count) in entries {
|
||||
if !term_dict.ord_to_str(term_id, &mut buffer)? {
|
||||
return Err(TantivyError::InternalError(format!(
|
||||
"Couldn't find term_id {term_id} in dict"
|
||||
)));
|
||||
}
|
||||
|
||||
let intermediate_entry = into_intermediate_bucket_entry(term_id, doc_count)?;
|
||||
|
||||
dict.insert(IntermediateKey::Str(buffer.to_string()), intermediate_entry);
|
||||
// Special case for missing key
|
||||
if term_id == u64::MAX {
|
||||
let missing_key = self
|
||||
.req
|
||||
.missing
|
||||
.as_ref()
|
||||
.expect("Found placeholder term_id but `missing` is None");
|
||||
match missing_key {
|
||||
Key::Str(missing) => {
|
||||
buffer.clear();
|
||||
buffer.push_str(missing);
|
||||
dict.insert(
|
||||
IntermediateKey::Str(buffer.to_string()),
|
||||
intermediate_entry,
|
||||
);
|
||||
}
|
||||
Key::F64(val) => {
|
||||
buffer.push_str(&val.to_string());
|
||||
dict.insert(IntermediateKey::F64(*val), intermediate_entry);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
if !term_dict.ord_to_str(term_id, &mut buffer)? {
|
||||
return Err(TantivyError::InternalError(format!(
|
||||
"Couldn't find term_id {term_id} in dict"
|
||||
)));
|
||||
}
|
||||
dict.insert(IntermediateKey::Str(buffer.to_string()), intermediate_entry);
|
||||
}
|
||||
}
|
||||
if self.req.min_doc_count == 0 {
|
||||
// TODO: Handle rev streaming for descending sorting by keys
|
||||
@@ -581,21 +529,55 @@ impl SegmentTermCollector {
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if self.column_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.field_type);
|
||||
let val = f64_from_fastfield_u64(val, &self.column_type);
|
||||
dict.insert(IntermediateKey::F64(val), intermediate_entry);
|
||||
}
|
||||
};
|
||||
|
||||
Ok(IntermediateBucketResult::Terms(
|
||||
IntermediateTermBucketResult {
|
||||
Ok(IntermediateBucketResult::Terms {
|
||||
buckets: IntermediateTermBucketResult {
|
||||
entries: dict,
|
||||
sum_other_doc_count,
|
||||
doc_count_error_upper_bound: term_doc_count_before_cutoff,
|
||||
},
|
||||
))
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
@@ -633,6 +615,12 @@ 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};
|
||||
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::tests::{
|
||||
exec_request, exec_request_with_query, exec_request_with_query_and_memory_limit,
|
||||
@@ -640,8 +628,8 @@ mod tests {
|
||||
};
|
||||
use crate::aggregation::AggregationLimits;
|
||||
use crate::indexer::NoMergePolicy;
|
||||
use crate::schema::{Schema, FAST, STRING};
|
||||
use crate::Index;
|
||||
use crate::schema::{IntoIpv6Addr, Schema, FAST, STRING};
|
||||
use crate::{Index, IndexWriter};
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_test_single_segment() -> crate::Result<()> {
|
||||
@@ -1222,9 +1210,9 @@ 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"], "termc");
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termb");
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 0);
|
||||
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termb");
|
||||
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termc");
|
||||
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);
|
||||
@@ -1321,6 +1309,7 @@ mod tests {
|
||||
];
|
||||
|
||||
let index = get_test_index_from_terms(false, &terms_per_segment)?;
|
||||
assert_eq!(index.searchable_segments().unwrap().len(), 2);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
@@ -1404,7 +1393,7 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_different_tokenizer_on_ff_test() -> crate::Result<()> {
|
||||
let terms = vec!["Hello Hello", "Hallo Hallo"];
|
||||
let terms = vec!["Hello Hello", "Hallo Hallo", "Hallo Hallo"];
|
||||
|
||||
let index = get_test_index_from_terms(true, &[terms])?;
|
||||
|
||||
@@ -1422,7 +1411,7 @@ 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"], 1);
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
|
||||
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Hello Hello");
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 1);
|
||||
@@ -1506,6 +1495,47 @@ mod tests {
|
||||
|
||||
Ok(())
|
||||
}
|
||||
#[test]
|
||||
fn terms_empty_json() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
|
||||
// => Segment with empty json
|
||||
index_writer.add_document(doc!()).unwrap();
|
||||
index_writer.commit().unwrap();
|
||||
// => Segment with json, but no field partially_empty
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"different_field": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.commit().unwrap();
|
||||
//// => Segment with field partially_empty
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"partially_empty": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
"terms": {
|
||||
"field": "json.partially_empty"
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["key"], "blue");
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 1);
|
||||
assert_eq!(res["my_texts"]["buckets"][1], serde_json::Value::Null);
|
||||
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_bytes() -> crate::Result<()> {
|
||||
@@ -1543,4 +1573,429 @@ mod tests {
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_multi_value() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let text_field = schema_builder.add_text_field("text", FAST);
|
||||
let id_field = schema_builder.add_u64_field("id", FAST);
|
||||
let index = Index::create_in_ram(schema_builder.build());
|
||||
{
|
||||
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
|
||||
index_writer.set_merge_policy(Box::new(NoMergePolicy));
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
text_field => "Hello Hello",
|
||||
id_field => 1u64,
|
||||
id_field => 1u64,
|
||||
))?;
|
||||
// Missing
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
))?;
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
))?;
|
||||
index_writer.commit()?;
|
||||
// Empty segment special case
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit()?;
|
||||
// Full segment special case
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
id_field => 1u64,
|
||||
))?;
|
||||
index_writer.commit()?;
|
||||
}
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
"terms": {
|
||||
"field": "text",
|
||||
"missing": "Empty"
|
||||
},
|
||||
},
|
||||
"my_texts2": {
|
||||
"terms": {
|
||||
"field": "text",
|
||||
"missing": 1337
|
||||
},
|
||||
},
|
||||
"my_ids": {
|
||||
"terms": {
|
||||
"field": "id",
|
||||
"missing": 1337
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Hello Hello");
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 5);
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Empty");
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
|
||||
assert_eq!(
|
||||
res["my_texts"]["buckets"][2]["key"],
|
||||
serde_json::Value::Null
|
||||
);
|
||||
// text field with numner as missing fallback
|
||||
assert_eq!(res["my_texts2"]["buckets"][0]["key"], "Hello Hello");
|
||||
assert_eq!(res["my_texts2"]["buckets"][0]["doc_count"], 5);
|
||||
assert_eq!(res["my_texts2"]["buckets"][1]["key"], 1337.0);
|
||||
assert_eq!(res["my_texts2"]["buckets"][1]["doc_count"], 2);
|
||||
assert_eq!(
|
||||
res["my_texts2"]["buckets"][2]["key"],
|
||||
serde_json::Value::Null
|
||||
);
|
||||
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
// id field
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 4);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["key"], 1.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["doc_count"], 3);
|
||||
assert_eq!(res["my_ids"]["buckets"][2]["key"], serde_json::Value::Null);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
#[test]
|
||||
fn terms_aggregation_missing_simple_id() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let id_field = schema_builder.add_u64_field("id", FAST);
|
||||
let index = Index::create_in_ram(schema_builder.build());
|
||||
{
|
||||
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
|
||||
index_writer.set_merge_policy(Box::new(NoMergePolicy));
|
||||
index_writer.add_document(doc!(
|
||||
id_field => 1u64,
|
||||
))?;
|
||||
// Missing
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit()?;
|
||||
}
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_ids": {
|
||||
"terms": {
|
||||
"field": "id",
|
||||
"missing": 1337
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// id field
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 2);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["key"], 1.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["doc_count"], 1);
|
||||
assert_eq!(res["my_ids"]["buckets"][2]["key"], serde_json::Value::Null);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing1() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let text_field = schema_builder.add_text_field("text", FAST);
|
||||
let id_field = schema_builder.add_u64_field("id", FAST);
|
||||
let index = Index::create_in_ram(schema_builder.build());
|
||||
{
|
||||
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
|
||||
index_writer.set_merge_policy(Box::new(NoMergePolicy));
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
id_field => 1u64,
|
||||
))?;
|
||||
// Missing
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
))?;
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
))?;
|
||||
index_writer.commit()?;
|
||||
// Empty segment special case
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit()?;
|
||||
// Full segment special case
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "Hello Hello",
|
||||
id_field => 1u64,
|
||||
))?;
|
||||
index_writer.commit()?;
|
||||
}
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
"terms": {
|
||||
"field": "text",
|
||||
"missing": "Empty"
|
||||
},
|
||||
},
|
||||
"my_texts2": {
|
||||
"terms": {
|
||||
"field": "text",
|
||||
"missing": 1337
|
||||
},
|
||||
},
|
||||
"my_ids": {
|
||||
"terms": {
|
||||
"field": "id",
|
||||
"missing": 1337
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Hello Hello");
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 4);
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Empty");
|
||||
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
|
||||
assert_eq!(
|
||||
res["my_texts"]["buckets"][2]["key"],
|
||||
serde_json::Value::Null
|
||||
);
|
||||
// text field with numner as missing fallback
|
||||
assert_eq!(res["my_texts2"]["buckets"][0]["key"], "Hello Hello");
|
||||
assert_eq!(res["my_texts2"]["buckets"][0]["doc_count"], 4);
|
||||
assert_eq!(res["my_texts2"]["buckets"][1]["key"], 1337.0);
|
||||
assert_eq!(res["my_texts2"]["buckets"][1]["doc_count"], 2);
|
||||
assert_eq!(
|
||||
res["my_texts2"]["buckets"][2]["key"],
|
||||
serde_json::Value::Null
|
||||
);
|
||||
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
// id field
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 4);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["key"], 1.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["doc_count"], 2);
|
||||
assert_eq!(res["my_ids"]["buckets"][2]["key"], serde_json::Value::Null);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
#[test]
|
||||
fn terms_aggregation_missing_empty() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
schema_builder.add_text_field("text", FAST);
|
||||
schema_builder.add_u64_field("id", FAST);
|
||||
let index = Index::create_in_ram(schema_builder.build());
|
||||
{
|
||||
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
|
||||
index_writer.set_merge_policy(Box::new(NoMergePolicy));
|
||||
// Empty segment special case
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit()?;
|
||||
}
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
"terms": {
|
||||
"field": "text",
|
||||
"missing": "Empty"
|
||||
},
|
||||
},
|
||||
"my_texts2": {
|
||||
"terms": {
|
||||
"field": "text",
|
||||
"missing": 1337
|
||||
},
|
||||
},
|
||||
"my_ids": {
|
||||
"terms": {
|
||||
"field": "id",
|
||||
"missing": 1337
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Empty");
|
||||
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 1);
|
||||
assert_eq!(
|
||||
res["my_texts"]["buckets"][1]["key"],
|
||||
serde_json::Value::Null
|
||||
);
|
||||
// text field with number as missing fallback
|
||||
assert_eq!(res["my_texts2"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["my_texts2"]["buckets"][0]["doc_count"], 1);
|
||||
assert_eq!(
|
||||
res["my_texts2"]["buckets"][1]["key"],
|
||||
serde_json::Value::Null
|
||||
);
|
||||
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
// id field
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 1);
|
||||
assert_eq!(res["my_ids"]["buckets"][1]["key"], serde_json::Value::Null);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_date() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let date_field = schema_builder.add_date_field("date_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!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
|
||||
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
|
||||
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1983, Month::September, 27)?.with_hms(0, 0, 0)?)))?;
|
||||
writer.commit()?;
|
||||
}
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_date": {
|
||||
"terms": {
|
||||
"field": "date_field"
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// date_field field
|
||||
assert_eq!(res["my_date"]["buckets"][0]["key"], "1982-09-17T00:00:00Z");
|
||||
assert_eq!(res["my_date"]["buckets"][0]["doc_count"], 2);
|
||||
assert_eq!(res["my_date"]["buckets"][1]["key"], "1983-09-27T00:00:00Z");
|
||||
assert_eq!(res["my_date"]["buckets"][1]["doc_count"], 1);
|
||||
assert_eq!(res["my_date"]["buckets"][2]["key"], serde_json::Value::Null);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
#[test]
|
||||
fn terms_aggregation_date_missing() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let date_field = schema_builder.add_date_field("date_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!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
|
||||
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
|
||||
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1983, Month::September, 27)?.with_hms(0, 0, 0)?)))?;
|
||||
writer.add_document(doc!())?;
|
||||
writer.commit()?;
|
||||
}
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_date": {
|
||||
"terms": {
|
||||
"field": "date_field",
|
||||
"missing": "1982-09-17T00:00:00Z"
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// date_field field
|
||||
assert_eq!(res["my_date"]["buckets"][0]["key"], "1982-09-17T00:00:00Z");
|
||||
assert_eq!(res["my_date"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["my_date"]["buckets"][1]["key"], "1983-09-27T00:00:00Z");
|
||||
assert_eq!(res["my_date"]["buckets"][1]["doc_count"], 1);
|
||||
assert_eq!(res["my_date"]["buckets"][2]["key"], serde_json::Value::Null);
|
||||
|
||||
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(())
|
||||
}
|
||||
}
|
||||
|
||||
481
src/aggregation/bucket/term_missing_agg.rs
Normal file
481
src/aggregation/bucket/term_missing_agg.rs
Normal file
@@ -0,0 +1,481 @@
|
||||
use rustc_hash::FxHashMap;
|
||||
|
||||
use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
|
||||
use crate::aggregation::intermediate_agg_result::{
|
||||
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
|
||||
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
|
||||
};
|
||||
use crate::aggregation::segment_agg_result::{
|
||||
build_segment_agg_collector, SegmentAggregationCollector,
|
||||
};
|
||||
|
||||
/// The specialized missing term aggregation.
|
||||
#[derive(Default, Debug, Clone)]
|
||||
pub struct TermMissingAgg {
|
||||
missing_count: u32,
|
||||
accessor_idx: usize,
|
||||
sub_agg: Option<Box<dyn SegmentAggregationCollector>>,
|
||||
}
|
||||
impl TermMissingAgg {
|
||||
pub(crate) fn new(
|
||||
accessor_idx: usize,
|
||||
sub_aggregations: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<Self> {
|
||||
let has_sub_aggregations = !sub_aggregations.is_empty();
|
||||
let sub_agg = if has_sub_aggregations {
|
||||
let sub_aggregation = build_segment_agg_collector(sub_aggregations)?;
|
||||
Some(sub_aggregation)
|
||||
} else {
|
||||
None
|
||||
};
|
||||
|
||||
Ok(Self {
|
||||
accessor_idx,
|
||||
sub_agg,
|
||||
..Default::default()
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
impl SegmentAggregationCollector for TermMissingAgg {
|
||||
fn add_intermediate_aggregation_result(
|
||||
self: Box<Self>,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
results: &mut IntermediateAggregationResults,
|
||||
) -> crate::Result<()> {
|
||||
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
|
||||
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
|
||||
let term_agg = agg_with_accessor
|
||||
.agg
|
||||
.agg
|
||||
.as_term()
|
||||
.expect("TermMissingAgg collector must be term agg req");
|
||||
let missing = term_agg
|
||||
.missing
|
||||
.as_ref()
|
||||
.expect("TermMissingAgg collector, but no missing found in agg req")
|
||||
.clone();
|
||||
let mut entries: FxHashMap<IntermediateKey, IntermediateTermBucketEntry> =
|
||||
Default::default();
|
||||
|
||||
let mut missing_entry = IntermediateTermBucketEntry {
|
||||
doc_count: self.missing_count,
|
||||
sub_aggregation: Default::default(),
|
||||
};
|
||||
if let Some(sub_agg) = self.sub_agg {
|
||||
let mut res = IntermediateAggregationResults::default();
|
||||
sub_agg.add_intermediate_aggregation_result(
|
||||
&agg_with_accessor.sub_aggregation,
|
||||
&mut res,
|
||||
)?;
|
||||
missing_entry.sub_aggregation = res;
|
||||
}
|
||||
|
||||
entries.insert(missing.into(), missing_entry);
|
||||
|
||||
let bucket = IntermediateBucketResult::Terms {
|
||||
buckets: IntermediateTermBucketResult {
|
||||
entries,
|
||||
sum_other_doc_count: 0,
|
||||
doc_count_error_upper_bound: 0,
|
||||
},
|
||||
};
|
||||
|
||||
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn collect(
|
||||
&mut self,
|
||||
doc: crate::DocId,
|
||||
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));
|
||||
if !has_value {
|
||||
self.missing_count += 1;
|
||||
if let Some(sub_agg) = self.sub_agg.as_mut() {
|
||||
sub_agg.collect(doc, &mut agg.sub_aggregation)?;
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn collect_block(
|
||||
&mut self,
|
||||
docs: &[crate::DocId],
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
for doc in docs {
|
||||
self.collect(*doc, agg_with_accessor)?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::tests::exec_request_with_query;
|
||||
use crate::schema::{Schema, FAST};
|
||||
use crate::{Index, IndexWriter};
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_mult_seg_sub_agg() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer
|
||||
.add_document(doc!(score => 1.0, json => json!({"mixed_type": 10.0})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
// index_writer.commit().unwrap();
|
||||
//// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(score => 1.0, json => json!({"mixed_type": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
// index_writer.commit().unwrap();
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer.add_document(doc!(json => json!({"mixed_type": "red"})))?;
|
||||
index_writer.add_document(doc!(json => json!({"mixed_type": -20.5})))?;
|
||||
index_writer.add_document(doc!(json => json!({"mixed_type": true})))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
15.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_sub_agg_reg1() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer.add_document(doc!(score => 1.0, json => json!({"mixed_type": 10.0})))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 2);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
10.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mult_seg_empty() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
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!(score => 5.0))?;
|
||||
index_writer.commit().unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.commit().unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
15.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_single_seg_empty() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
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!(score => 5.0))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
15.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_mult_seg() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
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})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit().unwrap();
|
||||
//// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "red"})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": true})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
},
|
||||
"replace_num": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": 1337
|
||||
},
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_num"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["replace_num"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_str_on_numeric_field() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
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})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_one_seg() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
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})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
//// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "red"})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": true})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user