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4 Commits

Author SHA1 Message Date
trinity-1686a
2b686ffa54 fix columnar tests 2023-11-10 11:46:58 +01:00
trinity-1686a
04b3a27a0a increment sstable version number 2023-11-10 11:38:58 +01:00
trinity-1686a
710cf1efa6 implement multilayer sstable writer 2023-11-10 11:09:50 +01:00
trinity-1686a
8103790c16 define and implement reading multi layer index sstable 2023-11-09 15:42:00 +01:00
136 changed files with 1748 additions and 5034 deletions

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@@ -1,6 +1,6 @@
[package]
name = "tantivy"
version = "0.22.0-dev"
version = "0.21.0"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -22,7 +22,7 @@ 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 = "0.5"
tantivy-fst = "0.4.0"
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 }
@@ -31,25 +31,27 @@ log = "0.4.16"
serde = { version = "1.0.136", features = ["derive"] }
serde_json = "1.0.79"
num_cpus = "1.13.1"
fs4 = { version = "0.8.0", optional = true }
fs4 = { version = "0.7.0", optional = true }
levenshtein_automata = "0.2.1"
uuid = { version = "1.0.0", features = ["v4", "serde"] }
crossbeam-channel = "0.5.4"
rust-stemmers = "1.2.0"
downcast-rs = "1.2.0"
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker4x"] }
census = "0.4.2"
bitpacking = { git = "https://github.com/quickwit-oss/bitpacking", rev = "f730b75", default-features = false, features = ["bitpacker4x"] }
census = "0.4.0"
rustc-hash = "1.1.0"
thiserror = "1.0.30"
htmlescape = "0.3.1"
fail = { version = "0.5.0", optional = true }
murmurhash32 = "0.3.0"
time = { version = "0.3.10", features = ["serde-well-known"] }
smallvec = "1.8.0"
rayon = "1.5.2"
lru = "0.12.0"
fastdivide = "0.4.0"
itertools = "0.12.0"
itertools = "0.11.0"
measure_time = "0.8.2"
async-trait = "0.1.53"
arc-swap = "1.5.0"
columnar = { version= "0.2", path="./columnar", package ="tantivy-columnar" }
@@ -73,14 +75,15 @@ matches = "0.1.9"
pretty_assertions = "1.2.1"
proptest = "1.0.0"
test-log = "0.2.10"
env_logger = "0.10.0"
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"] }
[target.'cfg(not(windows))'.dev-dependencies]
criterion = { version = "0.5", default-features = false }
criterion = "0.5"
pprof = { git = "https://github.com/PSeitz/pprof-rs/", rev = "53af24b", features = ["flamegraph", "criterion"] } # temp fork that works with criterion 0.5
[dev-dependencies.fail]
version = "0.5.0"

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@@ -5,18 +5,19 @@
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Crates.io](https://img.shields.io/crates/v/tantivy.svg)](https://crates.io/crates/tantivy)
<img src="https://tantivy-search.github.io/logo/tantivy-logo.png" alt="Tantivy, the fastest full-text search engine library written in Rust" height="250">
![Tantivy](https://tantivy-search.github.io/logo/tantivy-logo.png)
## Fast full-text search engine library written in Rust
**Tantivy** is a **full-text search engine library** written in Rust.
**If you are looking for an alternative to Elasticsearch or Apache Solr, check out [Quickwit](https://github.com/quickwit-oss/quickwit), our distributed search engine built on top of Tantivy.**
Tantivy is closer to [Apache Lucene](https://lucene.apache.org/) than to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Apache Solr](https://lucene.apache.org/solr/) in the sense it is not
an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine.
It is closer to [Apache Lucene](https://lucene.apache.org/) than to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Apache Solr](https://lucene.apache.org/solr/) in the sense it is not
an off-the-shelf search engine server, but rather a crate that can be used
to build such a search engine.
Tantivy is, in fact, strongly inspired by Lucene's design.
## Benchmark
If you are looking for an alternative to Elasticsearch or Apache Solr, check out [Quickwit](https://github.com/quickwit-oss/quickwit), our search engine built on top of Tantivy.
# Benchmark
The following [benchmark](https://tantivy-search.github.io/bench/) breakdowns
performance for different types of queries/collections.
@@ -27,7 +28,7 @@ Your mileage WILL vary depending on the nature of queries and their load.
Details about the benchmark can be found at this [repository](https://github.com/quickwit-oss/search-benchmark-game).
## Features
# Features
- Full-text search
- Configurable tokenizer (stemming available for 17 Latin languages) with third party support for Chinese ([tantivy-jieba](https://crates.io/crates/tantivy-jieba) and [cang-jie](https://crates.io/crates/cang-jie)), Japanese ([lindera](https://github.com/lindera-morphology/lindera-tantivy), [Vaporetto](https://crates.io/crates/vaporetto_tantivy), and [tantivy-tokenizer-tiny-segmenter](https://crates.io/crates/tantivy-tokenizer-tiny-segmenter)) and Korean ([lindera](https://github.com/lindera-morphology/lindera-tantivy) + [lindera-ko-dic-builder](https://github.com/lindera-morphology/lindera-ko-dic-builder))
@@ -53,11 +54,11 @@ Details about the benchmark can be found at this [repository](https://github.com
- Searcher Warmer API
- Cheesy logo with a horse
### Non-features
## Non-features
Distributed search is out of the scope of Tantivy, but if you are looking for this feature, check out [Quickwit](https://github.com/quickwit-oss/quickwit/).
## Getting started
# Getting started
Tantivy works on stable Rust and supports Linux, macOS, and Windows.
@@ -67,7 +68,7 @@ index documents, and search via the CLI or a small server with a REST API.
It walks you through getting a Wikipedia search engine up and running in a few minutes.
- [Reference doc for the last released version](https://docs.rs/tantivy/)
## How can I support this project?
# How can I support this project?
There are many ways to support this project.
@@ -78,16 +79,16 @@ There are many ways to support this project.
- Contribute code (you can join [our Discord server](https://discord.gg/MT27AG5EVE))
- Talk about Tantivy around you
## Contributing code
# Contributing code
We use the GitHub Pull Request workflow: reference a GitHub ticket and/or include a comprehensive commit message when opening a PR.
Feel free to update CHANGELOG.md with your contribution.
### Tokenizer
## Tokenizer
When implementing a tokenizer for tantivy depend on the `tantivy-tokenizer-api` crate.
### Clone and build locally
## Clone and build locally
Tantivy compiles on stable Rust.
To check out and run tests, you can simply run:
@@ -98,7 +99,7 @@ cd tantivy
cargo test
```
## Companies Using Tantivy
# Companies Using Tantivy
<p align="left">
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />&nbsp;
@@ -110,7 +111,7 @@ cargo test
<img align="center" src="doc/assets/images/element-dark-theme.png#gh-dark-mode-only" alt="Element.io" height="25" width="auto" />
</p>
## FAQ
# FAQ
### Can I use Tantivy in other languages?

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@@ -1,99 +1,14 @@
use criterion::{criterion_group, criterion_main, BatchSize, Bencher, Criterion, Throughput};
use criterion::{criterion_group, criterion_main, Criterion, Throughput};
use pprof::criterion::{Output, PProfProfiler};
use tantivy::schema::{TantivyDocument, FAST, INDEXED, STORED, STRING, TEXT};
use tantivy::{tokenizer, Index, IndexWriter};
use tantivy::{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 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)
})
fn get_lines(input: &str) -> Vec<&str> {
input.trim().split('\n').collect()
}
pub fn hdfs_index_benchmark(c: &mut Criterion) {
@@ -104,14 +19,7 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
schema_builder.add_text_field("severity", STRING);
schema_builder.build()
};
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 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);
@@ -120,39 +28,77 @@ 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 | FAST);
schema_builder.add_json_field("json", TEXT);
schema_builder.build()
};
let mut group = c.benchmark_group("index-hdfs");
group.throughput(Throughput::Bytes(HDFS_LOGS.len() as u64));
group.sample_size(20);
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-no-commit", |b| {
let lines = get_lines(HDFS_LOGS);
b.iter(|| {
let index = Index::create_in_ram(schema.clone());
let index_writer: IndexWriter = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = TantivyDocument::parse_json(&schema, doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
}
}
})
});
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: IndexWriter =
index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = TantivyDocument::parse_json(&schema, 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: IndexWriter = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = TantivyDocument::parse_json(&schema, 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: IndexWriter =
index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = TantivyDocument::parse_json(&schema, 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: IndexWriter =
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) {
@@ -161,24 +107,39 @@ 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| {
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema.clone(), false, false)
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: IndexWriter = 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();
}
})
});
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)
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: IndexWriter =
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();
})
});
}
@@ -193,10 +154,34 @@ pub fn wiki_index_benchmark(c: &mut Criterion) {
group.throughput(Throughput::Bytes(WIKI.len() as u64));
group.bench_function("index-wiki-no-commit", |b| {
benchmark_dynamic_json(b, WIKI, dynamic_schema.clone(), false, false)
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: IndexWriter = 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();
}
})
});
group.bench_function("index-wiki-with-commit", |b| {
benchmark_dynamic_json(b, WIKI, dynamic_schema.clone(), true, false)
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: IndexWriter =
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();
})
});
}
@@ -207,12 +192,12 @@ criterion_group! {
}
criterion_group! {
name = gh_benches;
config = Criterion::default();
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
targets = gh_index_benchmark
}
criterion_group! {
name = wiki_benches;
config = Criterion::default();
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
targets = wiki_index_benchmark
}
criterion_main!(benches, gh_benches, wiki_benches);

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@@ -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 = "0.9.2", default-features = false, features = ["bitpacker1x"] }
bitpacking = {version="0.8", default-features=false, features = ["bitpacker1x"]}
[dev-dependencies]
rand = "0.8"

View File

@@ -125,8 +125,6 @@ impl BitUnpacker {
// Decodes the range of bitpacked `u32` values with idx
// in [start_idx, start_idx + output.len()).
// It is guaranteed to completely fill `output` and not read from it, so passing a vector with
// un-initialized values is safe.
//
// #Panics
//
@@ -239,19 +237,7 @@ impl BitUnpacker {
data: &[u8],
positions: &mut Vec<u32>,
) {
// We use the code below instead of positions.resize(id_range.len(), 0u32) for performance
// reasons: on some queries, the CPU cost of memsetting the array and of using a bigger
// vector than necessary is noticeable (~5%).
// In particular, searches are a few percent faster when using reserve_exact() as below
// instead of reserve().
// The un-initialized values are safe as get_batch_u32s() completely fills `positions`
// and does not read from it.
positions.clear();
positions.reserve_exact(id_range.len());
#[allow(clippy::uninit_vec)]
unsafe {
positions.set_len(id_range.len());
}
positions.resize(id_range.len(), 0u32);
self.get_batch_u32s(id_range.start, data, positions);
crate::filter_vec::filter_vec_in_place(value_range, id_range.start, positions)
}

View File

@@ -9,7 +9,8 @@ description = "column oriented storage for tantivy"
categories = ["database-implementations", "data-structures", "compression"]
[dependencies]
itertools = "0.12.0"
itertools = "0.11.0"
fnv = "1.0.7"
fastdivide = "0.4.0"
stacker = { version= "0.2", path = "../stacker", package="tantivy-stacker"}

View File

@@ -8,6 +8,7 @@ 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 = []

View File

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

View File

@@ -126,18 +126,18 @@ impl ColumnIndex {
}
}
pub fn docid_range_to_rowids(&self, doc_id_range: Range<DocId>) -> Range<RowId> {
pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
match self {
ColumnIndex::Empty { .. } => 0..0,
ColumnIndex::Full => doc_id_range,
ColumnIndex::Full => doc_id,
ColumnIndex::Optional(optional_index) => {
let row_start = optional_index.rank(doc_id_range.start);
let row_end = optional_index.rank(doc_id_range.end);
let row_start = optional_index.rank(doc_id.start);
let row_end = optional_index.rank(doc_id.end);
row_start..row_end
}
ColumnIndex::Multivalued(multivalued_index) => {
let end_docid = doc_id_range.end.min(multivalued_index.num_docs() - 1) + 1;
let start_docid = doc_id_range.start.min(end_docid);
let end_docid = doc_id.end.min(multivalued_index.num_docs() - 1) + 1;
let start_docid = doc_id.start.min(end_docid);
let row_start = multivalued_index.start_index_column.get_val(start_docid);
let row_end = multivalued_index.start_index_column.get_val(end_docid);

View File

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

View File

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

View File

@@ -3,30 +3,6 @@ use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
use super::*;
use crate::{ColumnarReader, ColumnarWriter, DynamicColumnHandle};
#[test]
fn test_optional_index_bug_2293() {
// tests for panic in docid_range_to_rowids for docid == num_docs
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK - 1);
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK);
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK + 1);
}
fn test_optional_index_with_num_docs(num_docs: u32) {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_numerical(100, "score", 80i64);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer
.serialize(num_docs, None, &mut buffer)
.unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("score").unwrap();
assert_eq!(cols.len(), 1);
let col = cols[0].open().unwrap();
col.column_index().docid_range_to_rowids(0..num_docs);
}
#[test]
fn test_dense_block_threshold() {
@@ -59,7 +35,7 @@ proptest! {
#[test]
fn test_with_random_sets_simple() {
let vals = 10..ELEMENTS_PER_BLOCK * 2;
let vals = 10..BLOCK_SIZE * 2;
let mut out: Vec<u8> = Vec::new();
serialize_optional_index(&vals, 100, &mut out).unwrap();
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
@@ -195,7 +171,7 @@ fn test_optional_index_rank() {
test_optional_index_rank_aux(&[0u32, 1u32]);
let mut block = Vec::new();
block.push(3u32);
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
test_optional_index_rank_aux(&block);
}
@@ -209,8 +185,8 @@ fn test_optional_index_iter_empty_one() {
fn test_optional_index_iter_dense_block() {
let mut block = Vec::new();
block.push(3u32);
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
test_optional_index_iter_aux(&block, 3 * ELEMENTS_PER_BLOCK);
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
test_optional_index_iter_aux(&block, 3 * BLOCK_SIZE);
}
#[test]

View File

@@ -101,7 +101,7 @@ 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 {
for idx in row_id_range.start..row_id_range.end {
let val = self.get_val(idx);
if value_range.contains(&val) {
row_id_hits.push(idx);

View File

@@ -269,8 +269,7 @@ impl StrOrBytesColumnWriter {
dictionaries: &mut [DictionaryBuilder],
arena: &mut MemoryArena,
) {
let unordered_id =
dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes, arena);
let unordered_id = dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes);
self.column_writer.record(doc, unordered_id, arena);
}

View File

@@ -437,7 +437,6 @@ impl ColumnarWriter {
&mut symbol_byte_buffer,
),
buffers,
&self.arena,
&mut column_serializer,
)?;
column_serializer.finalize()?;
@@ -491,7 +490,6 @@ 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,
@@ -499,7 +497,6 @@ 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 {
@@ -508,8 +505,7 @@ fn serialize_bytes_or_str_column(
..
} = buffers;
let mut counting_writer = CountingWriter::wrap(wrt);
let term_id_mapping: TermIdMapping =
dictionary_builder.serialize(arena, &mut counting_writer)?;
let term_id_mapping: TermIdMapping = dictionary_builder.serialize(&mut counting_writer)?;
let dictionary_num_bytes: u32 = counting_writer.written_bytes() as u32;
let mut wrt = counting_writer.finish();
let operation_iterator = operation_it.map(|symbol: ColumnOperation<UnorderedId>| {

View File

@@ -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>,
@@ -31,38 +31,29 @@ pub struct OrderedId(pub u32);
/// mapping.
#[derive(Default)]
pub(crate) struct DictionaryBuilder {
dict: SharedArenaHashMap,
dict: FnvHashMap<Vec<u8>, UnorderedId>,
memory_consumption: usize,
}
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], 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)
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);
self.memory_consumption += term.len();
self.memory_consumption += 40; // Term Metadata + HashMap overhead
new_id
}
/// Serialize the dictionary into an fst, and returns the
/// `UnorderedId -> TermOrdinal` map.
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();
pub fn serialize<'a, W: io::Write + 'a>(&self, wrt: &mut W) -> io::Result<TermIdMapping> {
let mut terms: Vec<(&[u8], UnorderedId)> =
self.dict.iter().map(|(k, v)| (k.as_slice(), *v)).collect();
terms.sort_unstable_by_key(|(key, _)| *key);
// TODO Remove the allocation.
let mut unordered_to_ord: Vec<OrderedId> = vec![OrderedId(0u32); terms.len()];
@@ -77,7 +68,7 @@ impl DictionaryBuilder {
}
pub(crate) fn mem_usage(&self) -> usize {
self.dict.mem_usage()
self.memory_consumption
}
}
@@ -87,13 +78,12 @@ 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", &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 hello_uid = dictionary_builder.get_or_allocate_id(b"hello");
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy");
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax");
let mut buffer = Vec::new();
let id_mapping = dictionary_builder.serialize(&arena, &mut buffer).unwrap();
let id_mapping = dictionary_builder.serialize(&mut buffer).unwrap();
assert_eq!(id_mapping.to_ord(hello_uid), OrderedId(1));
assert_eq!(id_mapping.to_ord(happy_uid), OrderedId(0));
assert_eq!(id_mapping.to_ord(tax_uid), OrderedId(2));

View File

@@ -1,22 +1,3 @@
//! # 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)]

View File

@@ -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(), 73);
assert_eq!(cols[0].num_bytes(), 99);
}
#[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(), 73);
assert_eq!(cols[0].num_bytes(), 99);
}
#[test]

View File

@@ -1,5 +1,5 @@
use std::convert::TryInto;
use std::ops::{Deref, Range};
use std::ops::Deref;
use std::sync::Arc;
use std::{fmt, io};
@@ -37,7 +37,7 @@ impl OwnedBytes {
/// creates a fileslice that is just a view over a slice of the data.
#[must_use]
#[inline]
pub fn slice(&self, range: Range<usize>) -> Self {
pub fn slice(&self, range: impl std::slice::SliceIndex<[u8], Output = [u8]>) -> Self {
OwnedBytes {
data: &self.data[range],
box_stable_deref: self.box_stable_deref.clone(),

View File

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

View File

@@ -3,11 +3,11 @@ use std::iter::once;
use nom::branch::alt;
use nom::bytes::complete::tag;
use nom::character::complete::{
anychar, char, digit1, multispace0, multispace1, none_of, one_of, satisfy, u32,
anychar, char, digit1, none_of, one_of, satisfy, space0, space1, u32,
};
use nom::combinator::{eof, map, map_res, opt, peek, recognize, value, verify};
use nom::error::{Error, ErrorKind};
use nom::multi::{many0, many1, separated_list0};
use nom::multi::{many0, many1, separated_list0, separated_list1};
use nom::sequence::{delimited, preceded, separated_pair, terminated, tuple};
use nom::IResult;
@@ -65,7 +65,7 @@ fn word_infallible(delimiter: &str) -> impl Fn(&str) -> JResult<&str, Option<&st
|inp| {
opt_i_err(
preceded(
multispace0,
space0,
recognize(many1(satisfy(|c| {
!c.is_whitespace() && !delimiter.contains(c)
}))),
@@ -225,10 +225,10 @@ fn term_group(inp: &str) -> IResult<&str, UserInputAst> {
map(
tuple((
terminated(field_name, multispace0),
terminated(field_name, space0),
delimited(
tuple((char('('), multispace0)),
separated_list0(multispace1, tuple((opt(occur_symbol), term_or_phrase))),
tuple((char('('), space0)),
separated_list0(space1, tuple((opt(occur_symbol), term_or_phrase))),
char(')'),
),
)),
@@ -250,7 +250,7 @@ fn term_group_precond(inp: &str) -> IResult<&str, (), ()> {
(),
peek(tuple((
field_name,
multispace0,
space0,
char('('), // when we are here, we know it can't be anything but a term group
))),
)(inp)
@@ -259,7 +259,7 @@ fn term_group_precond(inp: &str) -> IResult<&str, (), ()> {
fn term_group_infallible(inp: &str) -> JResult<&str, UserInputAst> {
let (mut inp, (field_name, _, _, _)) =
tuple((field_name, multispace0, char('('), multispace0))(inp).expect("precondition failed");
tuple((field_name, space0, char('('), space0))(inp).expect("precondition failed");
let mut terms = Vec::new();
let mut errs = Vec::new();
@@ -305,7 +305,7 @@ fn exists(inp: &str) -> IResult<&str, UserInputLeaf> {
UserInputLeaf::Exists {
field: String::new(),
},
tuple((multispace0, char('*'))),
tuple((space0, char('*'))),
)(inp)
}
@@ -314,7 +314,7 @@ fn exists_precond(inp: &str) -> IResult<&str, (), ()> {
(),
peek(tuple((
field_name,
multispace0,
space0,
char('*'), // when we are here, we know it can't be anything but a exists
))),
)(inp)
@@ -323,7 +323,7 @@ fn exists_precond(inp: &str) -> IResult<&str, (), ()> {
fn exists_infallible(inp: &str) -> JResult<&str, UserInputAst> {
let (inp, (field_name, _, _)) =
tuple((field_name, multispace0, char('*')))(inp).expect("precondition failed");
tuple((field_name, space0, char('*')))(inp).expect("precondition failed");
let exists = UserInputLeaf::Exists { field: field_name }.into();
Ok((inp, (exists, Vec::new())))
@@ -349,7 +349,7 @@ fn literal_no_group_infallible(inp: &str) -> JResult<&str, Option<UserInputAst>>
alt_infallible(
(
(
value((), tuple((tag("IN"), multispace0, char('[')))),
value((), tuple((tag("IN"), space0, char('[')))),
map(set_infallible, |(set, errs)| (Some(set), errs)),
),
(
@@ -430,8 +430,8 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
// check for unbounded range in the form of <5, <=10, >5, >=5
let elastic_unbounded_range = map(
tuple((
preceded(multispace0, alt((tag(">="), tag("<="), tag("<"), tag(">")))),
preceded(multispace0, range_term_val()),
preceded(space0, alt((tag(">="), tag("<="), tag("<"), tag(">")))),
preceded(space0, range_term_val()),
)),
|(comparison_sign, bound)| match comparison_sign {
">=" => (UserInputBound::Inclusive(bound), UserInputBound::Unbounded),
@@ -444,7 +444,7 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
);
let lower_bound = map(
separated_pair(one_of("{["), multispace0, range_term_val()),
separated_pair(one_of("{["), space0, range_term_val()),
|(boundary_char, lower_bound)| {
if lower_bound == "*" {
UserInputBound::Unbounded
@@ -457,7 +457,7 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
);
let upper_bound = map(
separated_pair(range_term_val(), multispace0, one_of("}]")),
separated_pair(range_term_val(), space0, one_of("}]")),
|(upper_bound, boundary_char)| {
if upper_bound == "*" {
UserInputBound::Unbounded
@@ -469,11 +469,8 @@ fn range(inp: &str) -> IResult<&str, UserInputLeaf> {
},
);
let lower_to_upper = separated_pair(
lower_bound,
tuple((multispace1, tag("TO"), multispace1)),
upper_bound,
);
let lower_to_upper =
separated_pair(lower_bound, tuple((space1, tag("TO"), space1)), upper_bound);
map(
alt((elastic_unbounded_range, lower_to_upper)),
@@ -493,16 +490,13 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
word_infallible("]}"),
space1_infallible,
opt_i_err(
terminated(tag("TO"), alt((value((), multispace1), value((), eof)))),
terminated(tag("TO"), alt((value((), space1), value((), eof)))),
"missing keyword TO",
),
word_infallible("]}"),
opt_i_err(one_of("]}"), "missing range delimiter"),
)),
|(
(lower_bound_kind, _multispace0, lower, _multispace1, to, upper, upper_bound_kind),
errs,
)| {
|((lower_bound_kind, _space0, lower, _space1, to, upper, upper_bound_kind), errs)| {
let lower_bound = match (lower_bound_kind, lower) {
(_, Some("*")) => UserInputBound::Unbounded,
(_, None) => UserInputBound::Unbounded,
@@ -602,10 +596,10 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
fn set(inp: &str) -> IResult<&str, UserInputLeaf> {
map(
preceded(
tuple((multispace0, tag("IN"), multispace1)),
tuple((space0, tag("IN"), space1)),
delimited(
tuple((char('['), multispace0)),
separated_list0(multispace1, map(simple_term, |(_, term)| term)),
tuple((char('['), space0)),
separated_list0(space1, map(simple_term, |(_, term)| term)),
char(']'),
),
),
@@ -673,7 +667,7 @@ fn leaf(inp: &str) -> IResult<&str, UserInputAst> {
alt((
delimited(char('('), ast, char(')')),
map(char('*'), |_| UserInputAst::from(UserInputLeaf::All)),
map(preceded(tuple((tag("NOT"), multispace1)), leaf), negate),
map(preceded(tuple((tag("NOT"), space1)), leaf), negate),
literal,
))(inp)
}
@@ -786,23 +780,27 @@ fn binary_operand(inp: &str) -> IResult<&str, BinaryOperand> {
}
fn aggregate_binary_expressions(
left: (Option<Occur>, UserInputAst),
others: Vec<(Option<BinaryOperand>, Option<Occur>, UserInputAst)>,
) -> Result<UserInputAst, LenientErrorInternal> {
let mut leafs = Vec::with_capacity(others.len() + 1);
leafs.push((None, left.0, Some(left.1)));
leafs.extend(
others
.into_iter()
.map(|(operand, occur, ast)| (operand, occur, Some(ast))),
);
// the parameters we pass should statically guarantee we can't get errors
// (no prefix BinaryOperand is provided)
let (res, mut errors) = aggregate_infallible_expressions(leafs);
if errors.is_empty() {
Ok(res)
left: UserInputAst,
others: Vec<(BinaryOperand, UserInputAst)>,
) -> UserInputAst {
let mut dnf: Vec<Vec<UserInputAst>> = vec![vec![left]];
for (operator, operand_ast) in others {
match operator {
BinaryOperand::And => {
if let Some(last) = dnf.last_mut() {
last.push(operand_ast);
}
}
BinaryOperand::Or => {
dnf.push(vec![operand_ast]);
}
}
}
if dnf.len() == 1 {
UserInputAst::and(dnf.into_iter().next().unwrap()) //< safe
} else {
Err(errors.swap_remove(0))
let conjunctions = dnf.into_iter().map(UserInputAst::and).collect();
UserInputAst::or(conjunctions)
}
}
@@ -818,10 +816,30 @@ fn aggregate_infallible_expressions(
return (UserInputAst::empty_query(), err);
}
let use_operand = leafs.iter().any(|(operand, _, _)| operand.is_some());
let all_operand = leafs
.iter()
.skip(1)
.all(|(operand, _, _)| operand.is_some());
let early_operand = leafs
.iter()
.take(1)
.all(|(operand, _, _)| operand.is_some());
let use_occur = leafs.iter().any(|(_, occur, _)| occur.is_some());
if use_operand && use_occur {
err.push(LenientErrorInternal {
pos: 0,
message: "Use of mixed occur and boolean operator".to_string(),
});
}
if use_operand && !all_operand {
err.push(LenientErrorInternal {
pos: 0,
message: "Missing boolean operator".to_string(),
});
}
if early_operand {
err.push(LenientErrorInternal {
@@ -848,15 +866,7 @@ fn aggregate_infallible_expressions(
Some(BinaryOperand::And) => Some(Occur::Must),
_ => Some(Occur::Should),
};
if occur == &Some(Occur::MustNot) && default_op == Some(Occur::Should) {
// if occur is MustNot *and* operation is OR, we synthetize a ShouldNot
clauses.push(vec![(
Some(Occur::Should),
ast.clone().unary(Occur::MustNot),
)])
} else {
clauses.push(vec![(occur.or(default_op), ast.clone())]);
}
clauses.push(vec![(occur.or(default_op), ast.clone())]);
}
None => {
let default_op = match next_operator {
@@ -864,15 +874,7 @@ fn aggregate_infallible_expressions(
Some(BinaryOperand::Or) => Some(Occur::Should),
None => None,
};
if occur == &Some(Occur::MustNot) && default_op == Some(Occur::Should) {
// if occur is MustNot *and* operation is OR, we synthetize a ShouldNot
clauses.push(vec![(
Some(Occur::Should),
ast.clone().unary(Occur::MustNot),
)])
} else {
clauses.push(vec![(occur.or(default_op), ast.clone())])
}
clauses.push(vec![(occur.or(default_op), ast.clone())])
}
}
}
@@ -889,12 +891,7 @@ fn aggregate_infallible_expressions(
}
}
Some(BinaryOperand::Or) => {
if last_occur == Some(Occur::MustNot) {
// if occur is MustNot *and* operation is OR, we synthetize a ShouldNot
clauses.push(vec![(Some(Occur::Should), last_ast.unary(Occur::MustNot))]);
} else {
clauses.push(vec![(last_occur.or(Some(Occur::Should)), last_ast)]);
}
clauses.push(vec![(last_occur.or(Some(Occur::Should)), last_ast)]);
}
None => clauses.push(vec![(last_occur, last_ast)]),
}
@@ -920,29 +917,35 @@ fn aggregate_infallible_expressions(
}
}
fn operand_leaf(inp: &str) -> IResult<&str, (Option<BinaryOperand>, Option<Occur>, UserInputAst)> {
map(
tuple((
terminated(opt(binary_operand), multispace0),
terminated(occur_leaf, multispace0),
)),
|(operand, (occur, ast))| (operand, occur, ast),
)(inp)
fn operand_leaf(inp: &str) -> IResult<&str, (BinaryOperand, UserInputAst)> {
tuple((
terminated(binary_operand, space0),
terminated(boosted_leaf, space0),
))(inp)
}
fn ast(inp: &str) -> IResult<&str, UserInputAst> {
let boolean_expr = map_res(
separated_pair(occur_leaf, multispace1, many1(operand_leaf)),
let boolean_expr = map(
separated_pair(boosted_leaf, space1, many1(operand_leaf)),
|(left, right)| aggregate_binary_expressions(left, right),
);
let single_leaf = map(occur_leaf, |(occur, ast)| {
if occur == Some(Occur::MustNot) {
ast.unary(Occur::MustNot)
let whitespace_separated_leaves = map(separated_list1(space1, occur_leaf), |subqueries| {
if subqueries.len() == 1 {
let (occur_opt, ast) = subqueries.into_iter().next().unwrap();
match occur_opt.unwrap_or(Occur::Should) {
Occur::Must | Occur::Should => ast,
Occur::MustNot => UserInputAst::Clause(vec![(Some(Occur::MustNot), ast)]),
}
} else {
ast
UserInputAst::Clause(subqueries.into_iter().collect())
}
});
delimited(multispace0, alt((boolean_expr, single_leaf)), multispace0)(inp)
delimited(
space0,
alt((boolean_expr, whitespace_separated_leaves)),
space0,
)(inp)
}
fn ast_infallible(inp: &str) -> JResult<&str, UserInputAst> {
@@ -966,7 +969,7 @@ fn ast_infallible(inp: &str) -> JResult<&str, UserInputAst> {
}
pub fn parse_to_ast(inp: &str) -> IResult<&str, UserInputAst> {
map(delimited(multispace0, opt(ast), eof), |opt_ast| {
map(delimited(space0, opt(ast), eof), |opt_ast| {
rewrite_ast(opt_ast.unwrap_or_else(UserInputAst::empty_query))
})(inp)
}
@@ -1142,43 +1145,24 @@ mod test {
#[test]
fn test_parse_query_to_ast_binary_op() {
test_parse_query_to_ast_helper("a AND b", "(+a +b)");
test_parse_query_to_ast_helper("a\nAND b", "(+a +b)");
test_parse_query_to_ast_helper("a OR b", "(?a ?b)");
test_parse_query_to_ast_helper("a OR b AND c", "(?a ?(+b +c))");
test_parse_query_to_ast_helper("a AND b AND c", "(+a +b +c)");
test_parse_query_to_ast_helper("a OR b aaa", "(?a ?b *aaa)");
test_parse_query_to_ast_helper("a AND b aaa", "(?(+a +b) *aaa)");
test_parse_query_to_ast_helper("aaa a OR b ", "(*aaa ?a ?b)");
test_parse_query_to_ast_helper("aaa ccc a OR b ", "(*aaa *ccc ?a ?b)");
test_parse_query_to_ast_helper("aaa a AND b ", "(*aaa ?(+a +b))");
test_parse_query_to_ast_helper("aaa ccc a AND b ", "(*aaa *ccc ?(+a +b))");
test_is_parse_err("a OR b aaa", "(?a ?b *aaa)");
test_is_parse_err("a AND b aaa", "(?(+a +b) *aaa)");
test_is_parse_err("aaa a OR b ", "(*aaa ?a ?b)");
test_is_parse_err("aaa ccc a OR b ", "(*aaa *ccc ?a ?b)");
test_is_parse_err("aaa a AND b ", "(*aaa ?(+a +b))");
test_is_parse_err("aaa ccc a AND b ", "(*aaa *ccc ?(+a +b))");
}
#[test]
fn test_parse_mixed_bool_occur() {
test_parse_query_to_ast_helper("+a OR +b", "(+a +b)");
test_parse_query_to_ast_helper("a AND -b", "(+a -b)");
test_parse_query_to_ast_helper("-a AND b", "(-a +b)");
test_parse_query_to_ast_helper("a AND NOT b", "(+a +(-b))");
test_parse_query_to_ast_helper("NOT a AND b", "(+(-a) +b)");
test_parse_query_to_ast_helper("a AND NOT b AND c", "(+a +(-b) +c)");
test_parse_query_to_ast_helper("a AND -b AND c", "(+a -b +c)");
test_parse_query_to_ast_helper("a OR -b", "(?a ?(-b))");
test_parse_query_to_ast_helper("-a OR b", "(?(-a) ?b)");
test_parse_query_to_ast_helper("a OR NOT b", "(?a ?(-b))");
test_parse_query_to_ast_helper("NOT a OR b", "(?(-a) ?b)");
test_parse_query_to_ast_helper("a OR NOT b OR c", "(?a ?(-b) ?c)");
test_parse_query_to_ast_helper("a OR -b OR c", "(?a ?(-b) ?c)");
test_parse_query_to_ast_helper("a OR b +aaa", "(?a ?b +aaa)");
test_parse_query_to_ast_helper("a AND b -aaa", "(?(+a +b) -aaa)");
test_parse_query_to_ast_helper("+a OR +b aaa", "(+a +b *aaa)");
test_parse_query_to_ast_helper("-a AND -b aaa", "(?(-a -b) *aaa)");
test_parse_query_to_ast_helper("-aaa +ccc -a OR b ", "(-aaa +ccc ?(-a) ?b)");
test_is_parse_err("a OR b +aaa", "(?a ?b +aaa)");
test_is_parse_err("a AND b -aaa", "(?(+a +b) -aaa)");
test_is_parse_err("+a OR +b aaa", "(+a +b *aaa)");
test_is_parse_err("-a AND -b aaa", "(?(-a -b) *aaa)");
test_is_parse_err("-aaa +ccc -a OR b ", "(-aaa +ccc -a ?b)");
}
#[test]

View File

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

View File

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

View File

@@ -1,9 +1,6 @@
//! This will enhance the request tree with access to the fastfield and metadata.
use std::collections::HashMap;
use std::io;
use columnar::{Column, ColumnBlockAccessor, ColumnType, DynamicColumn, StrColumn};
use columnar::{Column, ColumnBlockAccessor, ColumnType, StrColumn};
use super::agg_limits::ResourceLimitGuard;
use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
@@ -17,7 +14,7 @@ use super::metric::{
use super::segment_agg_result::AggregationLimits;
use super::VecWithNames;
use crate::aggregation::{f64_to_fastfield_u64, Key};
use crate::{SegmentOrdinal, SegmentReader};
use crate::SegmentReader;
#[derive(Default)]
pub(crate) struct AggregationsWithAccessor {
@@ -35,7 +32,6 @@ impl AggregationsWithAccessor {
}
pub struct AggregationWithAccessor {
pub(crate) segment_ordinal: SegmentOrdinal,
/// In general there can be buckets without fast field access, e.g. buckets that are created
/// based on search terms. That is not that case currently, but eventually this needs to be
/// Option or moved.
@@ -48,16 +44,10 @@ pub struct AggregationWithAccessor {
pub(crate) limits: ResourceLimitGuard,
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
/// Used for missing term aggregation, which checks all columns for existence.
/// And also for `top_hits` aggregation, which may sort on multiple fields.
/// By convention the missing aggregation is chosen, when this property is set
/// (instead bein set in `agg`).
/// If this needs to used by other aggregations, we need to refactor this.
// NOTE: we can make all other aggregations use this instead of the `accessor` and `field_type`
// (making them obsolete) But will it have a performance impact?
pub(crate) accessors: Vec<(Column<u64>, ColumnType)>,
/// Map field names to all associated column accessors.
/// This field is used for `docvalue_fields`, which is currently only supported for `top_hits`.
pub(crate) value_accessors: HashMap<String, Vec<DynamicColumn>>,
pub(crate) accessors: Vec<Column<u64>>,
pub(crate) agg: Aggregation,
}
@@ -67,55 +57,19 @@ impl AggregationWithAccessor {
agg: &Aggregation,
sub_aggregation: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: AggregationLimits,
) -> crate::Result<Vec<AggregationWithAccessor>> {
let mut agg = agg.clone();
let add_agg_with_accessor = |agg: &Aggregation,
accessor: Column<u64>,
let add_agg_with_accessor = |accessor: Column<u64>,
column_type: ColumnType,
aggs: &mut Vec<AggregationWithAccessor>|
-> crate::Result<()> {
let res = AggregationWithAccessor {
segment_ordinal,
accessor,
accessors: Default::default(),
value_accessors: Default::default(),
accessors: Vec::new(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
limits: limits.new_guard(),
missing_value_for_accessor: None,
str_dict_column: None,
column_block_accessor: Default::default(),
};
aggs.push(res);
Ok(())
};
let add_agg_with_accessors = |agg: &Aggregation,
accessors: Vec<(Column<u64>, ColumnType)>,
aggs: &mut Vec<AggregationWithAccessor>,
value_accessors: HashMap<String, Vec<DynamicColumn>>|
-> crate::Result<()> {
let (accessor, field_type) = accessors.first().expect("at least one accessor");
let res = AggregationWithAccessor {
segment_ordinal,
// TODO: We should do away with the `accessor` field altogether
accessor: accessor.clone(),
value_accessors,
field_type: *field_type,
accessors,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
@@ -130,36 +84,32 @@ impl AggregationWithAccessor {
let mut res: Vec<AggregationWithAccessor> = Vec::new();
use AggregationVariants::*;
match agg.agg {
match &agg.agg {
Range(RangeAggregation {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
Histogram(HistogramAggregation {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
DateHistogram(DateHistogramAggregationReq {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
// Only DateTime is supported for DateHistogram
get_ff_reader(reader, field_name, Some(&[ColumnType::DateTime]))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
Terms(TermsAggregation {
field: ref field_name,
ref missing,
field: field_name,
missing,
..
}) => {
let str_dict_column = reader.fast_fields().str(field_name)?;
@@ -169,8 +119,8 @@ impl AggregationWithAccessor {
ColumnType::F64,
ColumnType::Str,
ColumnType::DateTime,
ColumnType::Bool,
// ColumnType::Bytes Unsupported
// ColumnType::Bool Unsupported
// ColumnType::IpAddr Unsupported
];
@@ -212,11 +162,24 @@ impl AggregationWithAccessor {
let column_and_types =
get_all_ff_reader_or_empty(reader, field_name, None, fallback_type)?;
let accessors = column_and_types
.iter()
.map(|c_t| (c_t.0.clone(), c_t.1))
.collect();
add_agg_with_accessors(&agg, accessors, &mut res, Default::default())?;
let accessors: Vec<Column> =
column_and_types.iter().map(|(a, _)| a.clone()).collect();
let agg_wit_acc = AggregationWithAccessor {
missing_value_for_accessor: None,
accessor: accessors[0].clone(),
accessors,
field_type: ColumnType::U64,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
&limits,
)?,
agg: agg.clone(),
str_dict_column: str_dict_column.clone(),
limits: limits.new_guard(),
column_block_accessor: Default::default(),
};
res.push(agg_wit_acc);
}
for (accessor, column_type) in column_and_types {
@@ -226,25 +189,21 @@ impl AggregationWithAccessor {
missing.clone()
};
let missing_value_for_accessor = if let Some(missing) =
missing_value_term_agg.as_ref()
{
get_missing_val(column_type, missing, agg.agg.get_fast_field_names()[0])?
} else {
None
};
let missing_value_for_accessor =
if let Some(missing) = missing_value_term_agg.as_ref() {
get_missing_val(column_type, missing, agg.agg.get_fast_field_name())?
} else {
None
};
let agg = AggregationWithAccessor {
segment_ordinal,
missing_value_for_accessor,
accessor,
accessors: Default::default(),
value_accessors: Default::default(),
accessors: Vec::new(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
segment_ordinal,
&limits,
)?,
agg: agg.clone(),
@@ -256,63 +215,34 @@ impl AggregationWithAccessor {
}
}
Average(AverageAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Count(CountAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Max(MaxAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Min(MinAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Stats(StatsAggregation {
field: ref field_name,
..
field: field_name, ..
})
| Sum(SumAggregation {
field: ref field_name,
..
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
Percentiles(ref percentiles) => {
Percentiles(percentiles) => {
let (accessor, column_type) = get_ff_reader(
reader,
percentiles.field_name(),
Some(get_numeric_or_date_column_types()),
)?;
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
TopHits(ref mut top_hits) => {
top_hits.validate_and_resolve(reader.fast_fields().columnar())?;
let accessors: Vec<(Column<u64>, ColumnType)> = top_hits
.field_names()
.iter()
.map(|field| {
get_ff_reader(reader, field, Some(get_numeric_or_date_column_types()))
})
.collect::<crate::Result<_>>()?;
let value_accessors = top_hits
.value_field_names()
.iter()
.map(|field_name| {
Ok((
field_name.to_string(),
get_dynamic_columns(reader, field_name)?,
))
})
.collect::<crate::Result<_>>()?;
add_agg_with_accessors(&agg, accessors, &mut res, value_accessors)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
};
@@ -354,7 +284,6 @@ fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
pub(crate) fn get_aggs_with_segment_accessor_and_validate(
aggs: &Aggregations,
reader: &SegmentReader,
segment_ordinal: SegmentOrdinal,
limits: &AggregationLimits,
) -> crate::Result<AggregationsWithAccessor> {
let mut aggss = Vec::new();
@@ -363,7 +292,6 @@ pub(crate) fn get_aggs_with_segment_accessor_and_validate(
agg,
agg.sub_aggregation(),
reader,
segment_ordinal,
limits.clone(),
)?;
for agg in aggs {
@@ -393,19 +321,6 @@ fn get_ff_reader(
Ok(ff_field_with_type)
}
fn get_dynamic_columns(
reader: &SegmentReader,
field_name: &str,
) -> crate::Result<Vec<columnar::DynamicColumn>> {
let ff_fields = reader.fast_fields().dynamic_column_handles(field_name)?;
let cols = ff_fields
.iter()
.map(|h| h.open())
.collect::<io::Result<_>>()?;
assert!(!ff_fields.is_empty(), "field {} not found", field_name);
Ok(cols)
}
/// Get all fast field reader or empty as default.
///
/// Is guaranteed to return at least one column.

View File

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

View File

@@ -587,9 +587,6 @@ fn test_aggregation_on_json_object() {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
index_writer
.add_document(doc!(json => json!({"color": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"color": "red"})))
.unwrap();
@@ -617,74 +614,12 @@ 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
}
})
);
}
@@ -820,12 +755,6 @@ fn test_aggregation_on_json_object_mixed_types() {
.unwrap();
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!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
@@ -837,9 +766,6 @@ fn test_aggregation_on_json_object_mixed_types() {
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": "red"})))
.unwrap();
@@ -885,8 +811,6 @@ fn test_aggregation_on_json_object_mixed_types() {
let aggregation_results = searcher.search(&AllQuery, &aggregation_collector).unwrap();
let aggregation_res_json = serde_json::to_value(aggregation_results).unwrap();
// pretty print as json
use pretty_assertions::assert_eq;
assert_eq!(
&aggregation_res_json,
&serde_json::json!({
@@ -902,9 +826,9 @@ fn test_aggregation_on_json_object_mixed_types() {
"buckets": [
{ "doc_count": 1, "key": 10.0, "min_price": { "value": 10.0 } },
{ "doc_count": 1, "key": -20.5, "min_price": { "value": -20.5 } },
{ "doc_count": 2, "key": "red", "min_price": { "value": null } },
{ "doc_count": 2, "key": 1.0, "key_as_string": "true", "min_price": { "value": null } },
{ "doc_count": 3, "key": "blue", "min_price": { "value": null } },
// TODO bool is also not yet handled in aggregation
{ "doc_count": 1, "key": "blue", "min_price": { "value": null } },
{ "doc_count": 1, "key": "red", "min_price": { "value": null } },
],
"sum_other_doc_count": 0
}

View File

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

View File

@@ -20,7 +20,7 @@ use crate::aggregation::intermediate_agg_result::{
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, AggregationLimits, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::aggregation::{f64_from_fastfield_u64, format_date};
use crate::TantivyError;
/// Histogram is a bucket aggregation, where buckets are created dynamically for given `interval`.
@@ -73,7 +73,6 @@ pub struct HistogramAggregation {
pub field: String,
/// The interval to chunk your data range. Each bucket spans a value range of [0..interval).
/// Must be a positive value.
#[serde(deserialize_with = "deserialize_f64")]
pub interval: f64,
/// Intervals implicitly defines an absolute grid of buckets `[interval * k, interval * (k +
/// 1))`.
@@ -86,7 +85,6 @@ pub struct HistogramAggregation {
/// fall into the buckets with the key 0 and 10.
/// With offset 5 and interval 10, they would both fall into the bucket with they key 5 and the
/// range [5..15)
#[serde(default, deserialize_with = "deserialize_option_f64")]
pub offset: Option<f64>,
/// The minimum number of documents in a bucket to be returned. Defaults to 0.
pub min_doc_count: Option<u64>,
@@ -598,13 +596,10 @@ mod tests {
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::aggregation::AggregationCollector;
use crate::query::AllQuery;
#[test]
fn histogram_test_crooked_values() -> crate::Result<()> {
@@ -1356,35 +1351,6 @@ mod tests {
})
);
Ok(())
}
#[test]
fn test_aggregation_histogram_empty_index() -> crate::Result<()> {
// test index without segments
let values = vec![];
let index = get_test_index_from_values(false, &values)?;
let agg_req_1: Aggregations = serde_json::from_value(json!({
"myhisto": {
"histogram": {
"field": "score",
"interval": 10.0
},
}
}))
.unwrap();
let collector = AggregationCollector::from_aggs(agg_req_1, Default::default());
let reader = index.reader()?;
let searcher = reader.searcher();
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let res: Value = serde_json::from_str(&serde_json::to_string(&agg_res)?)?;
// Make sure the result structure is correct
assert_eq!(res["myhisto"]["buckets"].as_array().unwrap().len(), 0);
Ok(())
}
}

View File

@@ -14,7 +14,9 @@ use crate::aggregation::intermediate_agg_result::{
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::aggregation::{
f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
};
use crate::TantivyError;
/// Provide user-defined buckets to aggregate on.
@@ -70,19 +72,11 @@ pub struct RangeAggregationRange {
pub key: Option<String>,
/// The from range value, which is inclusive in the range.
/// `None` equals to an open ended interval.
#[serde(
skip_serializing_if = "Option::is_none",
default,
deserialize_with = "deserialize_option_f64"
)]
#[serde(skip_serializing_if = "Option::is_none", default)]
pub from: Option<f64>,
/// The to range value, which is not inclusive in the range.
/// `None` equals to an open ended interval.
#[serde(
skip_serializing_if = "Option::is_none",
default,
deserialize_with = "deserialize_option_f64"
)]
#[serde(skip_serializing_if = "Option::is_none", default)]
pub to: Option<f64>,
}

View File

@@ -99,15 +99,24 @@ pub struct TermsAggregation {
#[serde(skip_serializing_if = "Option::is_none", default)]
pub size: Option<u32>,
/// To get more accurate results, we fetch more than `size` from each segment.
/// Unused by tantivy.
///
/// Since tantivy doesn't know shards, this parameter is merely there to be used by consumers
/// of tantivy. shard_size is the number of terms returned by each shard.
/// The default value in elasticsearch is size * 1.5 + 10.
///
/// Should never be smaller than size.
#[serde(skip_serializing_if = "Option::is_none", default)]
#[serde(alias = "shard_size")]
pub split_size: Option<u32>,
/// The get more accurate results, we fetch more than `size` from each segment.
///
/// Increasing this value is will increase the cost for more accuracy.
///
/// Defaults to 10 * size.
#[serde(skip_serializing_if = "Option::is_none", default)]
#[serde(alias = "segment_size")]
#[serde(alias = "split_size")]
pub shard_size: Option<u32>,
pub segment_size: Option<u32>,
/// If you set the `show_term_doc_count_error` parameter to true, the terms aggregation will
/// include doc_count_error_upper_bound, which is an upper bound to the error on the
@@ -196,7 +205,7 @@ impl TermsAggregationInternal {
pub(crate) fn from_req(req: &TermsAggregation) -> Self {
let size = req.size.unwrap_or(10);
let mut segment_size = req.shard_size.unwrap_or(size * 10);
let mut segment_size = req.segment_size.unwrap_or(size * 10);
let order = req.order.clone().unwrap_or_default();
segment_size = segment_size.max(size);
@@ -247,7 +256,7 @@ pub struct SegmentTermCollector {
term_buckets: TermBuckets,
req: TermsAggregationInternal,
blueprint: Option<Box<dyn SegmentAggregationCollector>>,
column_type: ColumnType,
field_type: ColumnType,
accessor_idx: usize,
}
@@ -346,7 +355,7 @@ impl SegmentTermCollector {
field_type: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
if field_type == ColumnType::Bytes {
if field_type == ColumnType::Bytes || field_type == ColumnType::Bool {
return Err(TantivyError::InvalidArgument(format!(
"terms aggregation is not supported for column type {:?}",
field_type
@@ -380,7 +389,7 @@ impl SegmentTermCollector {
req: TermsAggregationInternal::from_req(req),
term_buckets,
blueprint,
column_type: field_type,
field_type,
accessor_idx,
})
}
@@ -457,7 +466,7 @@ impl SegmentTermCollector {
Ok(intermediate_entry)
};
if self.column_type == ColumnType::Str {
if self.field_type == ColumnType::Str {
let term_dict = agg_with_accessor
.str_dict_column
.as_ref()
@@ -522,34 +531,28 @@ impl SegmentTermCollector {
});
}
}
} else if self.column_type == ColumnType::DateTime {
} else if self.field_type == ColumnType::DateTime {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val = i64::from_u64(val);
let date = format_date(val)?;
dict.insert(IntermediateKey::Str(date), intermediate_entry);
}
} else if self.column_type == ColumnType::Bool {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val = bool::from_u64(val);
dict.insert(IntermediateKey::Bool(val), intermediate_entry);
}
} else {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val = f64_from_fastfield_u64(val, &self.column_type);
let val = f64_from_fastfield_u64(val, &self.field_type);
dict.insert(IntermediateKey::F64(val), intermediate_entry);
}
};
Ok(IntermediateBucketResult::Terms {
buckets: IntermediateTermBucketResult {
Ok(IntermediateBucketResult::Terms(
IntermediateTermBucketResult {
entries: dict,
sum_other_doc_count,
doc_count_error_upper_bound: term_doc_count_before_cutoff,
},
})
))
}
}
@@ -1362,7 +1365,7 @@ mod tests {
#[test]
fn terms_aggregation_different_tokenizer_on_ff_test() -> crate::Result<()> {
let terms = vec!["Hello Hello", "Hallo Hallo", "Hallo Hallo"];
let terms = vec!["Hello Hello", "Hallo Hallo"];
let index = get_test_index_from_terms(true, &[terms])?;
@@ -1380,7 +1383,7 @@ mod tests {
println!("{}", serde_json::to_string_pretty(&res).unwrap());
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Hallo Hallo");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 1);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Hello Hello");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 1);
@@ -1891,40 +1894,4 @@ mod tests {
Ok(())
}
#[test]
fn terms_aggregation_bool() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_bool_field("bool_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
writer.add_document(doc!(field=>true))?;
writer.add_document(doc!(field=>false))?;
writer.add_document(doc!(field=>true))?;
writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_bool": {
"terms": {
"field": "bool_field"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(res["my_bool"]["buckets"][0]["key"], 1.0);
assert_eq!(res["my_bool"]["buckets"][0]["key_as_string"], "true");
assert_eq!(res["my_bool"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_bool"]["buckets"][1]["key"], 0.0);
assert_eq!(res["my_bool"]["buckets"][1]["key_as_string"], "false");
assert_eq!(res["my_bool"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_bool"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
}

View File

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

View File

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

View File

@@ -19,7 +19,7 @@ use super::bucket::{
};
use super::metric::{
IntermediateAverage, IntermediateCount, IntermediateMax, IntermediateMin, IntermediateStats,
IntermediateSum, PercentilesCollector, TopHitsCollector,
IntermediateSum, PercentilesCollector,
};
use super::segment_agg_result::AggregationLimits;
use super::{format_date, AggregationError, Key, SerializedKey};
@@ -41,8 +41,6 @@ pub struct IntermediateAggregationResults {
/// This might seem redundant with `Key`, but the point is to have a different
/// Serialize implementation.
pub enum IntermediateKey {
/// Bool key
Bool(bool),
/// String key
Str(String),
/// `f64` key
@@ -61,7 +59,6 @@ impl From<IntermediateKey> for Key {
match value {
IntermediateKey::Str(s) => Self::Str(s),
IntermediateKey::F64(f) => Self::F64(f),
IntermediateKey::Bool(f) => Self::F64(f as u64 as f64),
}
}
}
@@ -74,7 +71,6 @@ impl std::hash::Hash for IntermediateKey {
match self {
IntermediateKey::Str(text) => text.hash(state),
IntermediateKey::F64(val) => val.to_bits().hash(state),
IntermediateKey::Bool(val) => val.hash(state),
}
}
}
@@ -170,9 +166,9 @@ impl IntermediateAggregationResults {
pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult {
use AggregationVariants::*;
match req.agg {
Terms(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Terms {
buckets: Default::default(),
}),
Terms(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Terms(
Default::default(),
)),
Range(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Range(
Default::default(),
)),
@@ -209,9 +205,6 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
Percentiles(_) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::Percentiles(PercentilesCollector::default()),
),
TopHits(_) => IntermediateAggregationResult::Metric(IntermediateMetricResult::TopHits(
TopHitsCollector::default(),
)),
}
}
@@ -272,8 +265,6 @@ pub enum IntermediateMetricResult {
Stats(IntermediateStats),
/// Intermediate sum result.
Sum(IntermediateSum),
/// Intermediate top_hits result
TopHits(TopHitsCollector),
}
impl IntermediateMetricResult {
@@ -301,13 +292,9 @@ impl IntermediateMetricResult {
percentiles
.into_final_result(req.agg.as_percentile().expect("unexpected metric type")),
),
IntermediateMetricResult::TopHits(top_hits) => {
MetricResult::TopHits(top_hits.finalize())
}
}
}
// TODO: this is our top-of-the-chain fruit merge mech
fn merge_fruits(&mut self, other: IntermediateMetricResult) -> crate::Result<()> {
match (self, other) {
(
@@ -343,9 +330,6 @@ impl IntermediateMetricResult {
) => {
left.merge_fruits(right)?;
}
(IntermediateMetricResult::TopHits(left), IntermediateMetricResult::TopHits(right)) => {
left.merge_fruits(right)?;
}
_ => {
panic!("incompatible fruit types in tree or missing merge_fruits handler");
}
@@ -367,14 +351,11 @@ pub enum IntermediateBucketResult {
Histogram {
/// The column_type of the underlying `Column` is DateTime
is_date_agg: bool,
/// The histogram buckets
/// The buckets
buckets: Vec<IntermediateHistogramBucketEntry>,
},
/// Term aggregation
Terms {
/// The term buckets
buckets: IntermediateTermBucketResult,
},
Terms(IntermediateTermBucketResult),
}
impl IntermediateBucketResult {
@@ -451,7 +432,7 @@ impl IntermediateBucketResult {
};
Ok(BucketResult::Histogram { buckets })
}
IntermediateBucketResult::Terms { buckets: terms } => terms.into_final_result(
IntermediateBucketResult::Terms(terms) => terms.into_final_result(
req.agg
.as_term()
.expect("unexpected aggregation, expected term aggregation"),
@@ -464,12 +445,8 @@ impl IntermediateBucketResult {
fn merge_fruits(&mut self, other: IntermediateBucketResult) -> crate::Result<()> {
match (self, other) {
(
IntermediateBucketResult::Terms {
buckets: term_res_left,
},
IntermediateBucketResult::Terms {
buckets: term_res_right,
},
IntermediateBucketResult::Terms(term_res_left),
IntermediateBucketResult::Terms(term_res_right),
) => {
merge_maps(&mut term_res_left.entries, term_res_right.entries)?;
term_res_left.sum_other_doc_count += term_res_right.sum_other_doc_count;
@@ -553,15 +530,8 @@ impl IntermediateTermBucketResult {
.into_iter()
.filter(|bucket| bucket.1.doc_count as u64 >= req.min_doc_count)
.map(|(key, entry)| {
let key_as_string = match key {
IntermediateKey::Bool(key) => {
let val = if key { "true" } else { "false" };
Some(val.to_string())
}
_ => None,
};
Ok(BucketEntry {
key_as_string,
key_as_string: None,
key: key.into(),
doc_count: entry.doc_count as u64,
sub_aggregation: entry

View File

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

View File

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

View File

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

View File

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

View File

@@ -23,8 +23,6 @@ mod min;
mod percentiles;
mod stats;
mod sum;
mod top_hits;
pub use average::*;
pub use count::*;
pub use max::*;
@@ -34,7 +32,6 @@ use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
pub use stats::*;
pub use sum::*;
pub use top_hits::*;
/// Single-metric aggregations use this common result structure.
///
@@ -84,27 +81,6 @@ pub struct PercentilesMetricResult {
pub values: PercentileValues,
}
/// The top_hits metric results entry
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct TopHitsVecEntry {
/// The sort values of the document, depending on the sort criteria in the request.
pub sort: Vec<Option<u64>>,
/// Search results, for queries that include field retrieval requests
/// (`docvalue_fields`).
#[serde(flatten)]
pub search_results: FieldRetrivalResult,
}
/// The top_hits metric aggregation results a list of top hits by sort criteria.
///
/// The main reason for wrapping it in `hits` is to match elasticsearch output structure.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct TopHitsMetricResult {
/// The result of the top_hits metric.
pub hits: Vec<TopHitsVecEntry>,
}
#[cfg(test)]
mod tests {
use crate::aggregation::agg_req::Aggregations;

View File

@@ -11,7 +11,7 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::aggregation::{f64_from_fastfield_u64, f64_to_fastfield_u64, AggregationError};
use crate::{DocId, TantivyError};
/// # Percentiles
@@ -84,11 +84,7 @@ pub struct PercentilesAggregationReq {
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(
skip_serializing_if = "Option::is_none",
default,
deserialize_with = "deserialize_option_f64"
)]
#[serde(skip_serializing_if = "Option::is_none", default)]
pub missing: Option<f64>,
}
fn default_percentiles() -> &'static [f64] {
@@ -137,6 +133,7 @@ pub(crate) struct SegmentPercentilesCollector {
field_type: ColumnType,
pub(crate) percentiles: PercentilesCollector,
pub(crate) accessor_idx: usize,
val_cache: Vec<u64>,
missing: Option<u64>,
}
@@ -246,6 +243,7 @@ impl SegmentPercentilesCollector {
field_type,
percentiles: PercentilesCollector::new(),
accessor_idx,
val_cache: Default::default(),
missing,
})
}

View File

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

View File

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

View File

@@ -1,837 +0,0 @@
use std::collections::HashMap;
use std::fmt::Formatter;
use columnar::{ColumnarReader, DynamicColumn};
use regex::Regex;
use serde::ser::SerializeMap;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
use super::{TopHitsMetricResult, TopHitsVecEntry};
use crate::aggregation::bucket::Order;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::collector::TopNComputer;
use crate::schema::term::JSON_PATH_SEGMENT_SEP_STR;
use crate::schema::OwnedValue;
use crate::{DocAddress, DocId, SegmentOrdinal};
/// # Top Hits
///
/// The top hits aggregation is a useful tool to answer questions like:
/// - "What are the most recent posts by each author?"
/// - "What are the most popular items in each category?"
///
/// It does so by keeping track of the most relevant document being aggregated,
/// in terms of a sort criterion that can consist of multiple fields and their
/// sort-orders (ascending or descending).
///
/// `top_hits` should not be used as a top-level aggregation. It is intended to be
/// used as a sub-aggregation, inside a `terms` aggregation or a `filters` aggregation,
/// for example.
///
/// Note that this aggregator does not return the actual document addresses, but
/// rather a list of the values of the fields that were requested to be retrieved.
/// These values can be specified in the `docvalue_fields` parameter, which can include
/// a list of fast fields to be retrieved. At the moment, only fast fields are supported
/// but it is possible that we support the `fields` parameter to retrieve any stored
/// field in the future.
///
/// The following example demonstrates a request for the top_hits aggregation:
/// ```JSON
/// {
/// "aggs": {
/// "top_authors": {
/// "terms": {
/// "field": "author",
/// "size": 5
/// }
/// },
/// "aggs": {
/// "top_hits": {
/// "size": 2,
/// "from": 0
/// "sort": [
/// { "date": "desc" }
/// ]
/// "docvalue_fields": ["date", "title", "iden"]
/// }
/// }
/// }
/// ```
///
/// This request will return an object containing the top two documents, sorted
/// by the `date` field in descending order. You can also sort by multiple fields, which
/// helps to resolve ties. The aggregation object for each bucket will look like:
/// ```JSON
/// {
/// "hits": [
/// {
/// "score": [<time_u64>],
/// "docvalue_fields": {
/// "date": "<date_RFC3339>",
/// "title": "<title>",
/// "iden": "<iden>"
/// }
/// },
/// {
/// "score": [<time_u64>]
/// "docvalue_fields": {
/// "date": "<date_RFC3339>",
/// "title": "<title>",
/// "iden": "<iden>"
/// }
/// }
/// ]
/// }
/// ```
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct TopHitsAggregation {
sort: Vec<KeyOrder>,
size: usize,
from: Option<usize>,
#[serde(flatten)]
retrieval: RetrievalFields,
}
const fn default_doc_value_fields() -> Vec<String> {
Vec::new()
}
/// Search query spec for each matched document
/// TODO: move this to a common module
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct RetrievalFields {
/// The fast fields to return for each hit.
/// This is the only variant supported for now.
/// TODO: support the {field, format} variant for custom formatting.
#[serde(rename = "docvalue_fields")]
#[serde(default = "default_doc_value_fields")]
pub doc_value_fields: Vec<String>,
}
/// Search query result for each matched document
/// TODO: move this to a common module
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct FieldRetrivalResult {
/// The fast fields returned for each hit.
#[serde(rename = "docvalue_fields")]
#[serde(skip_serializing_if = "HashMap::is_empty")]
pub doc_value_fields: HashMap<String, OwnedValue>,
}
impl RetrievalFields {
fn get_field_names(&self) -> Vec<&str> {
self.doc_value_fields.iter().map(|s| s.as_str()).collect()
}
fn resolve_field_names(&mut self, reader: &ColumnarReader) -> crate::Result<()> {
// Tranform a glob (`pattern*`, for example) into a regex::Regex (`^pattern.*$`)
let globbed_string_to_regex = |glob: &str| {
// Replace `*` glob with `.*` regex
let sanitized = format!("^{}$", regex::escape(glob).replace(r"\*", ".*"));
Regex::new(&sanitized.replace('*', ".*")).map_err(|e| {
crate::TantivyError::SchemaError(format!(
"Invalid regex '{}' in docvalue_fields: {}",
glob, e
))
})
};
self.doc_value_fields = self
.doc_value_fields
.iter()
.map(|field| {
if !field.contains('*')
&& reader
.iter_columns()?
.any(|(name, _)| name.as_str() == field)
{
return Ok(vec![field.to_owned()]);
}
let pattern = globbed_string_to_regex(field)?;
let fields = reader
.iter_columns()?
.map(|(name, _)| {
// normalize path from internal fast field repr
name.replace(JSON_PATH_SEGMENT_SEP_STR, ".")
})
.filter(|name| pattern.is_match(name))
.collect::<Vec<_>>();
assert!(
!fields.is_empty(),
"No fields matched the glob '{}' in docvalue_fields",
field
);
Ok(fields)
})
.collect::<crate::Result<Vec<_>>>()?
.into_iter()
.flatten()
.collect();
Ok(())
}
fn get_document_field_data(
&self,
accessors: &HashMap<String, Vec<DynamicColumn>>,
doc_id: DocId,
) -> FieldRetrivalResult {
let dvf = self
.doc_value_fields
.iter()
.map(|field| {
let accessors = accessors
.get(field)
.unwrap_or_else(|| panic!("field '{}' not found in accessors", field));
let values: Vec<OwnedValue> = accessors
.iter()
.flat_map(|accessor| match accessor {
DynamicColumn::U64(accessor) => accessor
.values_for_doc(doc_id)
.map(OwnedValue::U64)
.collect::<Vec<_>>(),
DynamicColumn::I64(accessor) => accessor
.values_for_doc(doc_id)
.map(OwnedValue::I64)
.collect::<Vec<_>>(),
DynamicColumn::F64(accessor) => accessor
.values_for_doc(doc_id)
.map(OwnedValue::F64)
.collect::<Vec<_>>(),
DynamicColumn::Bytes(accessor) => accessor
.term_ords(doc_id)
.map(|term_ord| {
let mut buffer = vec![];
assert!(
accessor
.ord_to_bytes(term_ord, &mut buffer)
.expect("could not read term dictionary"),
"term corresponding to term_ord does not exist"
);
OwnedValue::Bytes(buffer)
})
.collect::<Vec<_>>(),
DynamicColumn::Str(accessor) => accessor
.term_ords(doc_id)
.map(|term_ord| {
let mut buffer = vec![];
assert!(
accessor
.ord_to_bytes(term_ord, &mut buffer)
.expect("could not read term dictionary"),
"term corresponding to term_ord does not exist"
);
OwnedValue::Str(String::from_utf8(buffer).unwrap())
})
.collect::<Vec<_>>(),
DynamicColumn::Bool(accessor) => accessor
.values_for_doc(doc_id)
.map(OwnedValue::Bool)
.collect::<Vec<_>>(),
DynamicColumn::IpAddr(accessor) => accessor
.values_for_doc(doc_id)
.map(OwnedValue::IpAddr)
.collect::<Vec<_>>(),
DynamicColumn::DateTime(accessor) => accessor
.values_for_doc(doc_id)
.map(OwnedValue::Date)
.collect::<Vec<_>>(),
})
.collect();
(field.to_owned(), OwnedValue::Array(values))
})
.collect();
FieldRetrivalResult {
doc_value_fields: dvf,
}
}
}
#[derive(Debug, Clone, PartialEq, Default)]
struct KeyOrder {
field: String,
order: Order,
}
impl Serialize for KeyOrder {
fn serialize<S: Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
let KeyOrder { field, order } = self;
let mut map = serializer.serialize_map(Some(1))?;
map.serialize_entry(field, order)?;
map.end()
}
}
impl<'de> Deserialize<'de> for KeyOrder {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where D: Deserializer<'de> {
let mut k_o = <HashMap<String, Order>>::deserialize(deserializer)?.into_iter();
let (k, v) = k_o.next().ok_or(serde::de::Error::custom(
"Expected exactly one key-value pair in KeyOrder, found none",
))?;
if k_o.next().is_some() {
return Err(serde::de::Error::custom(
"Expected exactly one key-value pair in KeyOrder, found more",
));
}
Ok(Self { field: k, order: v })
}
}
impl TopHitsAggregation {
/// Validate and resolve field retrieval parameters
pub fn validate_and_resolve(&mut self, reader: &ColumnarReader) -> crate::Result<()> {
self.retrieval.resolve_field_names(reader)
}
/// Return fields accessed by the aggregator, in order.
pub fn field_names(&self) -> Vec<&str> {
self.sort
.iter()
.map(|KeyOrder { field, .. }| field.as_str())
.collect()
}
/// Return fields accessed by the aggregator's value retrieval.
pub fn value_field_names(&self) -> Vec<&str> {
self.retrieval.get_field_names()
}
}
/// Holds a single comparable doc feature, and the order in which it should be sorted.
#[derive(Clone, Serialize, Deserialize, Debug)]
struct ComparableDocFeature {
/// Stores any u64-mappable feature.
value: Option<u64>,
/// Sort order for the doc feature
order: Order,
}
impl Ord for ComparableDocFeature {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
let invert = |cmp: std::cmp::Ordering| match self.order {
Order::Asc => cmp,
Order::Desc => cmp.reverse(),
};
match (self.value, other.value) {
(Some(self_value), Some(other_value)) => invert(self_value.cmp(&other_value)),
(Some(_), None) => std::cmp::Ordering::Greater,
(None, Some(_)) => std::cmp::Ordering::Less,
(None, None) => std::cmp::Ordering::Equal,
}
}
}
impl PartialOrd for ComparableDocFeature {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
}
}
impl PartialEq for ComparableDocFeature {
fn eq(&self, other: &Self) -> bool {
self.value.cmp(&other.value) == std::cmp::Ordering::Equal
}
}
impl Eq for ComparableDocFeature {}
#[derive(Clone, Serialize, Deserialize, Debug)]
struct ComparableDocFeatures(Vec<ComparableDocFeature>, FieldRetrivalResult);
impl Ord for ComparableDocFeatures {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
for (self_feature, other_feature) in self.0.iter().zip(other.0.iter()) {
let cmp = self_feature.cmp(other_feature);
if cmp != std::cmp::Ordering::Equal {
return cmp;
}
}
std::cmp::Ordering::Equal
}
}
impl PartialOrd for ComparableDocFeatures {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
}
}
impl PartialEq for ComparableDocFeatures {
fn eq(&self, other: &Self) -> bool {
self.cmp(other) == std::cmp::Ordering::Equal
}
}
impl Eq for ComparableDocFeatures {}
/// The TopHitsCollector used for collecting over segments and merging results.
#[derive(Clone, Serialize, Deserialize)]
pub struct TopHitsCollector {
req: TopHitsAggregation,
top_n: TopNComputer<ComparableDocFeatures, DocAddress, false>,
}
impl Default for TopHitsCollector {
fn default() -> Self {
Self {
req: TopHitsAggregation::default(),
top_n: TopNComputer::new(1),
}
}
}
impl std::fmt::Debug for TopHitsCollector {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
f.debug_struct("TopHitsCollector")
.field("req", &self.req)
.field("top_n_threshold", &self.top_n.threshold)
.finish()
}
}
impl std::cmp::PartialEq for TopHitsCollector {
fn eq(&self, _other: &Self) -> bool {
false
}
}
impl TopHitsCollector {
fn collect(&mut self, features: ComparableDocFeatures, doc: DocAddress) {
self.top_n.push(features, doc);
}
pub(crate) fn merge_fruits(&mut self, other_fruit: Self) -> crate::Result<()> {
for doc in other_fruit.top_n.into_vec() {
self.collect(doc.feature, doc.doc);
}
Ok(())
}
/// Finalize by converting self into the final result form
pub fn finalize(self) -> TopHitsMetricResult {
let mut hits: Vec<TopHitsVecEntry> = self
.top_n
.into_sorted_vec()
.into_iter()
.map(|doc| TopHitsVecEntry {
sort: doc.feature.0.iter().map(|f| f.value).collect(),
search_results: doc.feature.1,
})
.collect();
// Remove the first `from` elements
// Truncating from end would be more efficient, but we need to truncate from the front
// because `into_sorted_vec` gives us a descending order because of the inverted
// `Ord` semantics of the heap elements.
hits.drain(..self.req.from.unwrap_or(0));
TopHitsMetricResult { hits }
}
}
#[derive(Clone)]
pub(crate) struct SegmentTopHitsCollector {
segment_ordinal: SegmentOrdinal,
accessor_idx: usize,
inner_collector: TopHitsCollector,
}
impl SegmentTopHitsCollector {
pub fn from_req(
req: &TopHitsAggregation,
accessor_idx: usize,
segment_ordinal: SegmentOrdinal,
) -> Self {
Self {
inner_collector: TopHitsCollector {
req: req.clone(),
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
},
segment_ordinal,
accessor_idx,
}
}
}
impl std::fmt::Debug for SegmentTopHitsCollector {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
f.debug_struct("SegmentTopHitsCollector")
.field("segment_id", &self.segment_ordinal)
.field("accessor_idx", &self.accessor_idx)
.field("inner_collector", &self.inner_collector)
.finish()
}
}
impl SegmentAggregationCollector for SegmentTopHitsCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_with_accessor: &crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let intermediate_result = IntermediateMetricResult::TopHits(self.inner_collector);
results.push(
name,
IntermediateAggregationResult::Metric(intermediate_result),
)
}
fn collect(
&mut self,
doc_id: crate::DocId,
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
let value_accessors = &agg_with_accessor.aggs.values[self.accessor_idx].value_accessors;
let features: Vec<ComparableDocFeature> = self
.inner_collector
.req
.sort
.iter()
.enumerate()
.map(|(idx, KeyOrder { order, .. })| {
let order = *order;
let value = accessors
.get(idx)
.expect("could not find field in accessors")
.0
.values_for_doc(doc_id)
.next();
ComparableDocFeature { value, order }
})
.collect();
let retrieval_result = self
.inner_collector
.req
.retrieval
.get_document_field_data(value_accessors, doc_id);
self.inner_collector.collect(
ComparableDocFeatures(features, retrieval_result),
DocAddress {
segment_ord: self.segment_ordinal,
doc_id,
},
);
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
// TODO: Consider getting fields with the column block accessor and refactor this.
// ---
// Would the additional complexity of getting fields with the column_block_accessor
// make sense here? Probably yes, but I want to get a first-pass review first
// before proceeding.
for doc in docs {
self.collect(*doc, agg_with_accessor)?;
}
Ok(())
}
}
#[cfg(test)]
mod tests {
use common::DateTime;
use pretty_assertions::assert_eq;
use serde_json::Value;
use time::macros::datetime;
use super::{ComparableDocFeature, ComparableDocFeatures, Order};
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::bucket::tests::get_test_index_from_docs;
use crate::aggregation::tests::get_test_index_from_values;
use crate::aggregation::AggregationCollector;
use crate::collector::ComparableDoc;
use crate::query::AllQuery;
use crate::schema::OwnedValue as SchemaValue;
fn invert_order(cmp_feature: ComparableDocFeature) -> ComparableDocFeature {
let ComparableDocFeature { value, order } = cmp_feature;
let order = match order {
Order::Asc => Order::Desc,
Order::Desc => Order::Asc,
};
ComparableDocFeature { value, order }
}
fn collector_with_capacity(capacity: usize) -> super::TopHitsCollector {
super::TopHitsCollector {
top_n: super::TopNComputer::new(capacity),
..Default::default()
}
}
fn invert_order_features(cmp_features: ComparableDocFeatures) -> ComparableDocFeatures {
let ComparableDocFeatures(cmp_features, search_results) = cmp_features;
let cmp_features = cmp_features
.into_iter()
.map(invert_order)
.collect::<Vec<_>>();
ComparableDocFeatures(cmp_features, search_results)
}
#[test]
fn test_comparable_doc_feature() -> crate::Result<()> {
let small = ComparableDocFeature {
value: Some(1),
order: Order::Asc,
};
let big = ComparableDocFeature {
value: Some(2),
order: Order::Asc,
};
let none = ComparableDocFeature {
value: None,
order: Order::Asc,
};
assert!(small < big);
assert!(none < small);
assert!(none < big);
let small = invert_order(small);
let big = invert_order(big);
let none = invert_order(none);
assert!(small > big);
assert!(none < small);
assert!(none < big);
Ok(())
}
#[test]
fn test_comparable_doc_features() -> crate::Result<()> {
let features_1 = ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(1),
order: Order::Asc,
}],
Default::default(),
);
let features_2 = ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(2),
order: Order::Asc,
}],
Default::default(),
);
assert!(features_1 < features_2);
assert!(invert_order_features(features_1.clone()) > invert_order_features(features_2));
Ok(())
}
#[test]
fn test_aggregation_top_hits_empty_index() -> crate::Result<()> {
let values = vec![];
let index = get_test_index_from_values(false, &values)?;
let d: Aggregations = serde_json::from_value(json!({
"top_hits_req": {
"top_hits": {
"size": 2,
"sort": [
{ "date": "desc" }
],
"from": 0,
}
}
}))
.unwrap();
let collector = AggregationCollector::from_aggs(d, Default::default());
let reader = index.reader()?;
let searcher = reader.searcher();
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let res: Value = serde_json::from_str(
&serde_json::to_string(&agg_res).expect("JSON serialization failed"),
)
.expect("JSON parsing failed");
assert_eq!(
res,
json!({
"top_hits_req": {
"hits": []
}
})
);
Ok(())
}
#[test]
fn test_top_hits_collector_single_feature() -> crate::Result<()> {
let docs = vec![
ComparableDoc::<_, _, false> {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 0,
},
feature: ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(1),
order: Order::Asc,
}],
Default::default(),
),
},
ComparableDoc {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 2,
},
feature: ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(3),
order: Order::Asc,
}],
Default::default(),
),
},
ComparableDoc {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 1,
},
feature: ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(5),
order: Order::Asc,
}],
Default::default(),
),
},
];
let mut collector = collector_with_capacity(3);
for doc in docs.clone() {
collector.collect(doc.feature, doc.doc);
}
let res = collector.finalize();
assert_eq!(
res,
super::TopHitsMetricResult {
hits: vec![
super::TopHitsVecEntry {
sort: vec![docs[0].feature.0[0].value],
search_results: Default::default(),
},
super::TopHitsVecEntry {
sort: vec![docs[1].feature.0[0].value],
search_results: Default::default(),
},
super::TopHitsVecEntry {
sort: vec![docs[2].feature.0[0].value],
search_results: Default::default(),
},
]
}
);
Ok(())
}
fn test_aggregation_top_hits(merge_segments: bool) -> crate::Result<()> {
let docs = vec![
vec![
r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb", "text2": "bbb", "mixed": { "dyn_arr": [1, "2"] } }"#,
r#"{ "date": "2017-06-15T00:00:00Z", "text": "ccc", "text2": "ddd", "mixed": { "dyn_arr": [3, "4"] } }"#,
],
vec![
r#"{ "text": "aaa", "text2": "bbb", "date": "2018-01-02T00:00:00Z", "mixed": { "dyn_arr": ["9", 8] } }"#,
r#"{ "text": "aaa", "text2": "bbb", "date": "2016-01-02T00:00:00Z", "mixed": { "dyn_arr": ["7", 6] } }"#,
],
];
let index = get_test_index_from_docs(merge_segments, &docs)?;
let d: Aggregations = serde_json::from_value(json!({
"top_hits_req": {
"top_hits": {
"size": 2,
"sort": [
{ "date": "desc" }
],
"from": 1,
"docvalue_fields": [
"date",
"tex*",
"mixed.*",
],
}
}
}))?;
let collector = AggregationCollector::from_aggs(d, Default::default());
let reader = index.reader()?;
let searcher = reader.searcher();
let agg_res =
serde_json::to_value(searcher.search(&AllQuery, &collector).unwrap()).unwrap();
let date_2017 = datetime!(2017-06-15 00:00:00 UTC);
let date_2016 = datetime!(2016-01-02 00:00:00 UTC);
assert_eq!(
agg_res["top_hits_req"],
json!({
"hits": [
{
"sort": [common::i64_to_u64(date_2017.unix_timestamp_nanos() as i64)],
"docvalue_fields": {
"date": [ SchemaValue::Date(DateTime::from_utc(date_2017)) ],
"text": [ "ccc" ],
"text2": [ "ddd" ],
"mixed.dyn_arr": [ 3, "4" ],
}
},
{
"sort": [common::i64_to_u64(date_2016.unix_timestamp_nanos() as i64)],
"docvalue_fields": {
"date": [ SchemaValue::Date(DateTime::from_utc(date_2016)) ],
"text": [ "aaa" ],
"text2": [ "bbb" ],
"mixed.dyn_arr": [ 6, "7" ],
}
}
]
}),
);
Ok(())
}
#[test]
fn test_aggregation_top_hits_single_segment() -> crate::Result<()> {
test_aggregation_top_hits(true)
}
#[test]
fn test_aggregation_top_hits_multi_segment() -> crate::Result<()> {
test_aggregation_top_hits(false)
}
}

View File

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

View File

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

View File

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

View File

@@ -97,7 +97,6 @@ pub use self::multi_collector::{FruitHandle, MultiCollector, MultiFruit};
mod top_collector;
mod top_score_collector;
pub use self::top_collector::ComparableDoc;
pub use self::top_score_collector::{TopDocs, TopNComputer};
mod custom_score_top_collector;

View File

@@ -2,7 +2,7 @@ use columnar::{BytesColumn, Column};
use super::*;
use crate::collector::{Count, FilterCollector, TopDocs};
use crate::index::SegmentReader;
use crate::core::SegmentReader;
use crate::query::{AllQuery, QueryParser};
use crate::schema::{Schema, FAST, TEXT};
use crate::time::format_description::well_known::Rfc3339;

View File

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

View File

@@ -3,8 +3,6 @@ use std::marker::PhantomData;
use std::sync::Arc;
use columnar::ColumnValues;
use serde::de::DeserializeOwned;
use serde::{Deserialize, Serialize};
use super::Collector;
use crate::collector::custom_score_top_collector::CustomScoreTopCollector;
@@ -311,7 +309,7 @@ impl TopDocs {
///
/// To comfortably work with `u64`s, `i64`s, `f64`s, or `date`s, please refer to
/// the [.order_by_fast_field(...)](TopDocs::order_by_fast_field) method.
pub fn order_by_u64_field(
fn order_by_u64_field(
self,
field: impl ToString,
order: Order,
@@ -665,7 +663,7 @@ impl Collector for TopDocs {
reader: &SegmentReader,
) -> crate::Result<<Self::Child as SegmentCollector>::Fruit> {
let heap_len = self.0.limit + self.0.offset;
let mut top_n: TopNComputer<_, _> = TopNComputer::new(heap_len);
let mut top_n = TopNComputer::new(heap_len);
if let Some(alive_bitset) = reader.alive_bitset() {
let mut threshold = Score::MIN;
@@ -674,13 +672,21 @@ impl Collector for TopDocs {
if alive_bitset.is_deleted(doc) {
return threshold;
}
top_n.push(score, doc);
let doc = ComparableDoc {
feature: score,
doc,
};
top_n.push(doc);
threshold = top_n.threshold.unwrap_or(Score::MIN);
threshold
})?;
} else {
weight.for_each_pruning(Score::MIN, reader, &mut |doc, score| {
top_n.push(score, doc);
let doc = ComparableDoc {
feature: score,
doc,
};
top_n.push(doc);
top_n.threshold.unwrap_or(Score::MIN)
})?;
}
@@ -719,65 +725,17 @@ impl SegmentCollector for TopScoreSegmentCollector {
/// Fast TopN Computation
///
/// Capacity of the vec is 2 * top_n.
/// The buffer is truncated to the top_n elements when it reaches the capacity of the Vec.
/// That means capacity has special meaning and should be carried over when cloning or serializing.
///
/// For TopN == 0, it will be relative expensive.
#[derive(Serialize, Deserialize)]
#[serde(from = "TopNComputerDeser<Score, D, REVERSE_ORDER>")]
pub struct TopNComputer<Score, D, const REVERSE_ORDER: bool = true> {
/// The buffer reverses sort order to get top-semantics instead of bottom-semantics
buffer: Vec<ComparableDoc<Score, D, REVERSE_ORDER>>,
pub struct TopNComputer<Score, DocId> {
buffer: Vec<ComparableDoc<Score, DocId>>,
top_n: usize,
pub(crate) threshold: Option<Score>,
}
// Intermediate struct for TopNComputer for deserialization, to keep vec capacity
#[derive(Deserialize)]
struct TopNComputerDeser<Score, D, const REVERSE_ORDER: bool> {
buffer: Vec<ComparableDoc<Score, D, REVERSE_ORDER>>,
top_n: usize,
threshold: Option<Score>,
}
// Custom clone to keep capacity
impl<Score: Clone, D: Clone, const REVERSE_ORDER: bool> Clone
for TopNComputer<Score, D, REVERSE_ORDER>
{
fn clone(&self) -> Self {
let mut buffer_clone = Vec::with_capacity(self.buffer.capacity());
buffer_clone.extend(self.buffer.iter().cloned());
TopNComputer {
buffer: buffer_clone,
top_n: self.top_n,
threshold: self.threshold.clone(),
}
}
}
impl<Score, D, const R: bool> From<TopNComputerDeser<Score, D, R>> for TopNComputer<Score, D, R> {
fn from(mut value: TopNComputerDeser<Score, D, R>) -> Self {
let expected_cap = value.top_n.max(1) * 2;
let current_cap = value.buffer.capacity();
if current_cap < expected_cap {
value.buffer.reserve_exact(expected_cap - current_cap);
} else {
value.buffer.shrink_to(expected_cap);
}
TopNComputer {
buffer: value.buffer,
top_n: value.top_n,
threshold: value.threshold,
}
}
}
impl<Score, D, const R: bool> TopNComputer<Score, D, R>
impl<Score, DocId> TopNComputer<Score, DocId>
where
Score: PartialOrd + Clone,
D: Serialize + DeserializeOwned + Ord + Clone,
DocId: Ord + Clone,
{
/// Create a new `TopNComputer`.
/// Internally it will allocate a buffer of size `2 * top_n`.
@@ -790,12 +748,10 @@ where
}
}
/// Push a new document to the top n.
/// If the document is below the current threshold, it will be ignored.
#[inline]
pub fn push(&mut self, feature: Score, doc: D) {
pub(crate) fn push(&mut self, doc: ComparableDoc<Score, DocId>) {
if let Some(last_median) = self.threshold.clone() {
if feature < last_median {
if doc.feature < last_median {
return;
}
}
@@ -810,7 +766,7 @@ where
let uninit = self.buffer.spare_capacity_mut();
// This cannot panic, because we truncate_median will at least remove one element, since
// the min capacity is 2.
uninit[0].write(ComparableDoc { doc, feature });
uninit[0].write(doc);
// This is safe because it would panic in the line above
unsafe {
self.buffer.set_len(self.buffer.len() + 1);
@@ -829,24 +785,13 @@ where
median_score
}
/// Returns the top n elements in sorted order.
pub fn into_sorted_vec(mut self) -> Vec<ComparableDoc<Score, D, R>> {
pub(crate) fn into_sorted_vec(mut self) -> Vec<ComparableDoc<Score, DocId>> {
if self.buffer.len() > self.top_n {
self.truncate_top_n();
}
self.buffer.sort_unstable();
self.buffer
}
/// Returns the top n elements in stored order.
/// Useful if you do not need the elements in sorted order,
/// for example when merging the results of multiple segments.
pub fn into_vec(mut self) -> Vec<ComparableDoc<Score, D, R>> {
if self.buffer.len() > self.top_n {
self.truncate_top_n();
}
self.buffer
}
}
#[cfg(test)]
@@ -880,44 +825,49 @@ mod tests {
crate::assert_nearly_equals!(result.0, expected.0);
}
}
#[test]
fn test_topn_computer_serde() {
let computer: TopNComputer<u32, u32> = TopNComputer::new(1);
let computer_ser = serde_json::to_string(&computer).unwrap();
let mut computer: TopNComputer<u32, u32> = serde_json::from_str(&computer_ser).unwrap();
computer.push(1u32, 5u32);
computer.push(1u32, 0u32);
computer.push(1u32, 7u32);
assert_eq!(
computer.into_sorted_vec(),
&[ComparableDoc {
feature: 1u32,
doc: 0u32,
},]
);
}
#[test]
fn test_empty_topn_computer() {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(0);
computer.push(1u32, 1u32);
computer.push(1u32, 2u32);
computer.push(1u32, 3u32);
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
computer.push(ComparableDoc {
feature: 1u32,
doc: 2u32,
});
computer.push(ComparableDoc {
feature: 1u32,
doc: 3u32,
});
assert!(computer.into_sorted_vec().is_empty());
}
#[test]
fn test_topn_computer() {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(2);
computer.push(1u32, 1u32);
computer.push(2u32, 2u32);
computer.push(3u32, 3u32);
computer.push(2u32, 4u32);
computer.push(1u32, 5u32);
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
computer.push(ComparableDoc {
feature: 2u32,
doc: 2u32,
});
computer.push(ComparableDoc {
feature: 3u32,
doc: 3u32,
});
computer.push(ComparableDoc {
feature: 2u32,
doc: 4u32,
});
computer.push(ComparableDoc {
feature: 1u32,
doc: 5u32,
});
assert_eq!(
computer.into_sorted_vec(),
&[
@@ -939,7 +889,10 @@ mod tests {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(top_n);
for _ in 0..1 + top_n * 2 {
computer.push(1u32, 1u32);
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
}
let _vals = computer.into_sorted_vec();
}

View File

@@ -6,23 +6,23 @@ use std::path::PathBuf;
use std::sync::Arc;
use super::segment::Segment;
use super::segment_reader::merge_field_meta_data;
use super::{FieldMetadata, IndexSettings};
use crate::core::{Executor, META_FILEPATH};
use super::IndexSettings;
use crate::core::single_segment_index_writer::SingleSegmentIndexWriter;
use crate::core::{
Executor, IndexMeta, SegmentId, SegmentMeta, SegmentMetaInventory, META_FILEPATH,
};
use crate::directory::error::OpenReadError;
#[cfg(feature = "mmap")]
use crate::directory::MmapDirectory;
use crate::directory::{Directory, ManagedDirectory, RamDirectory, INDEX_WRITER_LOCK};
use crate::error::{DataCorruption, TantivyError};
use crate::index::{IndexMeta, SegmentId, SegmentMeta, SegmentMetaInventory};
use crate::indexer::index_writer::{MAX_NUM_THREAD, MEMORY_BUDGET_NUM_BYTES_MIN};
use crate::indexer::segment_updater::save_metas;
use crate::indexer::{IndexWriter, SingleSegmentIndexWriter};
use crate::indexer::IndexWriter;
use crate::reader::{IndexReader, IndexReaderBuilder};
use crate::schema::document::Document;
use crate::schema::{Field, FieldType, Schema};
use crate::tokenizer::{TextAnalyzer, TokenizerManager};
use crate::SegmentReader;
fn load_metas(
directory: &dyn Directory,
@@ -322,15 +322,6 @@ impl Index {
Ok(())
}
/// Custom thread pool by a outer thread pool.
pub fn set_shared_multithread_executor(
&mut self,
shared_thread_pool: Arc<Executor>,
) -> crate::Result<()> {
self.executor = shared_thread_pool.clone();
Ok(())
}
/// Replace the default single thread search executor pool
/// by a thread pool with as many threads as there are CPUs on the system.
pub fn set_default_multithread_executor(&mut self) -> crate::Result<()> {
@@ -498,28 +489,6 @@ impl Index {
self.inventory.all()
}
/// Returns the list of fields that have been indexed in the Index.
/// The field list includes the field defined in the schema as well as the fields
/// that have been indexed as a part of a JSON field.
/// The returned field name is the full field name, including the name of the JSON field.
///
/// The returned field names can be used in queries.
///
/// Notice: If your data contains JSON fields this is **very expensive**, as it requires
/// browsing through the inverted index term dictionary and the columnar field dictionary.
///
/// Disclaimer: Some fields may not be listed here. For instance, if the schema contains a json
/// field that is not indexed nor a fast field but is stored, it is possible for the field
/// to not be listed.
pub fn fields_metadata(&self) -> crate::Result<Vec<FieldMetadata>> {
let segments = self.searchable_segments()?;
let fields_metadata: Vec<Vec<FieldMetadata>> = segments
.into_iter()
.map(|segment| SegmentReader::open(&segment)?.fields_metadata())
.collect::<Result<_, _>>()?;
Ok(merge_field_meta_data(fields_metadata, &self.schema()))
}
/// Creates a new segment_meta (Advanced user only).
///
/// As long as the `SegmentMeta` lives, the files associated with the

View File

@@ -7,7 +7,7 @@ use std::sync::Arc;
use serde::{Deserialize, Serialize};
use super::SegmentComponent;
use crate::index::SegmentId;
use crate::core::SegmentId;
use crate::schema::Schema;
use crate::store::Compressor;
use crate::{Inventory, Opstamp, TrackedObject};
@@ -19,7 +19,7 @@ struct DeleteMeta {
}
#[derive(Clone, Default)]
pub(crate) struct SegmentMetaInventory {
pub struct SegmentMetaInventory {
inventory: Inventory<InnerSegmentMeta>,
}
@@ -408,7 +408,7 @@ impl fmt::Debug for IndexMeta {
mod tests {
use super::IndexMeta;
use crate::index::index_meta::UntrackedIndexMeta;
use crate::core::index_meta::UntrackedIndexMeta;
use crate::schema::{Schema, TEXT};
use crate::store::Compressor;
#[cfg(feature = "zstd-compression")]

View File

@@ -75,7 +75,7 @@ impl InvertedIndexReader {
///
/// Notice: This requires a full scan and therefore **very expensive**.
/// TODO: Move to sstable to use the index.
pub fn list_encoded_fields(&self) -> io::Result<Vec<(String, Type)>> {
pub fn list_fields(&self) -> io::Result<Vec<(String, Type)>> {
let mut stream = self.termdict.stream()?;
let mut fields = Vec::new();
let mut fields_set = FnvHashSet::default();
@@ -266,9 +266,7 @@ impl InvertedIndexReader {
/// Warmup a block postings given a `Term`.
/// This method is for an advanced usage only.
///
/// returns a boolean, whether the term was found in the dictionary
pub async fn warm_postings(&self, term: &Term, with_positions: bool) -> io::Result<bool> {
pub async fn warm_postings(&self, term: &Term, with_positions: bool) -> io::Result<()> {
let term_info_opt: Option<TermInfo> = self.get_term_info_async(term).await?;
if let Some(term_info) = term_info_opt {
let postings = self
@@ -282,27 +280,23 @@ impl InvertedIndexReader {
} else {
postings.await?;
}
Ok(true)
} else {
Ok(false)
}
Ok(())
}
/// Warmup a block postings given a range of `Term`s.
/// This method is for an advanced usage only.
///
/// returns a boolean, whether a term matching the range was found in the dictionary
pub async fn warm_postings_range(
&self,
terms: impl std::ops::RangeBounds<Term>,
limit: Option<u64>,
with_positions: bool,
) -> io::Result<bool> {
) -> io::Result<()> {
let mut term_info = self.get_term_range_async(terms, limit).await?;
let Some(first_terminfo) = term_info.next() else {
// no key matches, nothing more to load
return Ok(false);
return Ok(());
};
let last_terminfo = term_info.last().unwrap_or_else(|| first_terminfo.clone());
@@ -322,7 +316,7 @@ impl InvertedIndexReader {
} else {
postings.await?;
}
Ok(true)
Ok(())
}
/// Warmup the block postings for all terms.

View File

@@ -62,14 +62,6 @@ impl IndexingPositionsPerPath {
}
}
/// Convert JSON_PATH_SEGMENT_SEP to a dot.
pub fn json_path_sep_to_dot(path: &mut str) {
// This is safe since we are replacing a ASCII character by another ASCII character.
unsafe {
replace_in_place(JSON_PATH_SEGMENT_SEP, b'.', path.as_bytes_mut());
}
}
#[allow(clippy::too_many_arguments)]
pub(crate) fn index_json_values<'a, V: Value<'a>>(
doc: DocId,
@@ -328,7 +320,7 @@ pub struct JsonTermWriter<'a> {
/// In other words,
/// - `k8s.node` ends up as `["k8s", "node"]`.
/// - `k8s\.node` ends up as `["k8s.node"]`.
pub fn split_json_path(json_path: &str) -> Vec<String> {
fn split_json_path(json_path: &str) -> Vec<String> {
let mut escaped_state: bool = false;
let mut json_path_segments = Vec::new();
let mut buffer = String::new();

View File

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

View File

@@ -3,8 +3,7 @@ use std::sync::Arc;
use std::{fmt, io};
use crate::collector::Collector;
use crate::core::Executor;
use crate::index::SegmentReader;
use crate::core::{Executor, SegmentReader};
use crate::query::{Bm25StatisticsProvider, EnableScoring, Query};
use crate::schema::document::DocumentDeserialize;
use crate::schema::{Schema, Term};

View File

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

View File

@@ -1,17 +1,12 @@
use std::collections::HashMap;
use std::ops::BitOrAssign;
use std::sync::{Arc, RwLock};
use std::{fmt, io};
use fnv::FnvHashMap;
use itertools::Itertools;
use crate::core::{InvertedIndexReader, Segment, SegmentComponent, SegmentId};
use crate::directory::{CompositeFile, FileSlice};
use crate::error::DataCorruption;
use crate::fastfield::{intersect_alive_bitsets, AliveBitSet, FacetReader, FastFieldReaders};
use crate::fieldnorm::{FieldNormReader, FieldNormReaders};
use crate::index::{InvertedIndexReader, Segment, SegmentComponent, SegmentId};
use crate::json_utils::json_path_sep_to_dot;
use crate::schema::{Field, IndexRecordOption, Schema, Type};
use crate::space_usage::SegmentSpaceUsage;
use crate::store::StoreReader;
@@ -285,103 +280,6 @@ impl SegmentReader {
Ok(inv_idx_reader)
}
/// Returns the list of fields that have been indexed in the segment.
/// The field list includes the field defined in the schema as well as the fields
/// that have been indexed as a part of a JSON field.
/// The returned field name is the full field name, including the name of the JSON field.
///
/// The returned field names can be used in queries.
///
/// Notice: If your data contains JSON fields this is **very expensive**, as it requires
/// browsing through the inverted index term dictionary and the columnar field dictionary.
///
/// Disclaimer: Some fields may not be listed here. For instance, if the schema contains a json
/// field that is not indexed nor a fast field but is stored, it is possible for the field
/// to not be listed.
pub fn fields_metadata(&self) -> crate::Result<Vec<FieldMetadata>> {
let mut indexed_fields: Vec<FieldMetadata> = Vec::new();
let mut map_to_canonical = FnvHashMap::default();
for (field, field_entry) in self.schema().fields() {
let field_name = field_entry.name().to_string();
let is_indexed = field_entry.is_indexed();
if is_indexed {
let is_json = field_entry.field_type().value_type() == Type::Json;
if is_json {
let inv_index = self.inverted_index(field)?;
let encoded_fields_in_index = inv_index.list_encoded_fields()?;
let mut build_path = |field_name: &str, mut json_path: String| {
// In this case we need to map the potential fast field to the field name
// accepted by the query parser.
let create_canonical =
!field_entry.is_expand_dots_enabled() && json_path.contains('.');
if create_canonical {
// Without expand dots enabled dots need to be escaped.
let escaped_json_path = json_path.replace('.', "\\.");
let full_path = format!("{}.{}", field_name, escaped_json_path);
let full_path_unescaped = format!("{}.{}", field_name, &json_path);
map_to_canonical.insert(full_path_unescaped, full_path.to_string());
full_path
} else {
// With expand dots enabled, we can use '.' instead of '\u{1}'.
json_path_sep_to_dot(&mut json_path);
format!("{}.{}", field_name, json_path)
}
};
indexed_fields.extend(
encoded_fields_in_index
.into_iter()
.map(|(name, typ)| (build_path(&field_name, name), typ))
.map(|(field_name, typ)| FieldMetadata {
indexed: true,
stored: false,
field_name,
fast: false,
typ,
}),
);
} else {
indexed_fields.push(FieldMetadata {
indexed: true,
stored: false,
field_name: field_name.to_string(),
fast: false,
typ: field_entry.field_type().value_type(),
});
}
}
}
let mut fast_fields: Vec<FieldMetadata> = self
.fast_fields()
.columnar()
.iter_columns()?
.map(|(mut field_name, handle)| {
json_path_sep_to_dot(&mut field_name);
// map to canonical path, to avoid similar but different entries.
// Eventually we should just accept '.' seperated for all cases.
let field_name = map_to_canonical
.get(&field_name)
.unwrap_or(&field_name)
.to_string();
FieldMetadata {
indexed: false,
stored: false,
field_name,
fast: true,
typ: Type::from(handle.column_type()),
}
})
.collect();
// Since the type is encoded differently in the fast field and in the inverted index,
// the order of the fields is not guaranteed to be the same. Therefore, we sort the fields.
// If we are sure that the order is the same, we can remove this sort.
indexed_fields.sort_unstable();
fast_fields.sort_unstable();
let merged = merge_field_meta_data(vec![indexed_fields, fast_fields], &self.schema);
Ok(merged)
}
/// Returns the segment id
pub fn segment_id(&self) -> SegmentId {
self.segment_id
@@ -432,65 +330,6 @@ impl SegmentReader {
}
}
#[derive(Clone, Debug, PartialEq, Eq, PartialOrd, Ord)]
/// FieldMetadata
pub struct FieldMetadata {
/// The field name
// Notice: Don't reorder the declaration of 1.field_name 2.typ, as it is used for ordering by
// field_name then typ.
pub field_name: String,
/// The field type
// Notice: Don't reorder the declaration of 1.field_name 2.typ, as it is used for ordering by
// field_name then typ.
pub typ: Type,
/// Is the field indexed for search
pub indexed: bool,
/// Is the field stored in the doc store
pub stored: bool,
/// Is the field stored in the columnar storage
pub fast: bool,
}
impl BitOrAssign for FieldMetadata {
fn bitor_assign(&mut self, rhs: Self) {
assert!(self.field_name == rhs.field_name);
assert!(self.typ == rhs.typ);
self.indexed |= rhs.indexed;
self.stored |= rhs.stored;
self.fast |= rhs.fast;
}
}
// Maybe too slow for the high cardinality case
fn is_field_stored(field_name: &str, schema: &Schema) -> bool {
schema
.find_field(field_name)
.map(|(field, _path)| schema.get_field_entry(field).is_stored())
.unwrap_or(false)
}
/// Helper to merge the field metadata from multiple segments.
pub fn merge_field_meta_data(
field_metadatas: Vec<Vec<FieldMetadata>>,
schema: &Schema,
) -> Vec<FieldMetadata> {
let mut merged_field_metadata = Vec::new();
for (_key, mut group) in &field_metadatas
.into_iter()
.kmerge_by(|left, right| left < right)
// TODO: Remove allocation
.group_by(|el| (el.field_name.to_string(), el.typ))
{
let mut merged: FieldMetadata = group.next().unwrap();
for el in group {
merged |= el;
}
// Currently is_field_stored is maybe too slow for the high cardinality case
merged.stored = is_field_stored(&merged.field_name, schema);
merged_field_metadata.push(merged);
}
merged_field_metadata
}
fn intersect_alive_bitset(
left_opt: Option<AliveBitSet>,
right_opt: Option<AliveBitSet>,
@@ -514,128 +353,10 @@ impl fmt::Debug for SegmentReader {
#[cfg(test)]
mod test {
use super::*;
use crate::index::Index;
use crate::schema::{Schema, SchemaBuilder, Term, STORED, TEXT};
use crate::core::Index;
use crate::schema::{Schema, Term, STORED, TEXT};
use crate::{DocId, IndexWriter};
#[test]
fn test_merge_field_meta_data_same() {
let schema = SchemaBuilder::new().build();
let field_metadata1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: true,
};
let field_metadata2 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: true,
};
let res = merge_field_meta_data(
vec![vec![field_metadata1.clone()], vec![field_metadata2]],
&schema,
);
assert_eq!(res, vec![field_metadata1]);
}
#[test]
fn test_merge_field_meta_data_different() {
let schema = SchemaBuilder::new().build();
let field_metadata1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: false,
stored: false,
fast: true,
};
let field_metadata2 = FieldMetadata {
field_name: "b".to_string(),
typ: crate::schema::Type::Str,
indexed: false,
stored: false,
fast: true,
};
let field_metadata3 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: false,
};
let res = merge_field_meta_data(
vec![
vec![field_metadata1.clone(), field_metadata2.clone()],
vec![field_metadata3],
],
&schema,
);
let field_metadata_expected1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: true,
};
assert_eq!(res, vec![field_metadata_expected1, field_metadata2.clone()]);
}
#[test]
fn test_merge_field_meta_data_merge() {
use pretty_assertions::assert_eq;
let get_meta_data = |name: &str, typ: Type| FieldMetadata {
field_name: name.to_string(),
typ,
indexed: false,
stored: false,
fast: true,
};
let schema = SchemaBuilder::new().build();
let mut metas = vec![get_meta_data("d", Type::Str), get_meta_data("e", Type::U64)];
metas.sort();
let res = merge_field_meta_data(vec![vec![get_meta_data("e", Type::Str)], metas], &schema);
assert_eq!(
res,
vec![
get_meta_data("d", Type::Str),
get_meta_data("e", Type::Str),
get_meta_data("e", Type::U64),
]
);
}
#[test]
fn test_merge_field_meta_data_bitxor() {
let field_metadata1 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: false,
stored: false,
fast: true,
};
let field_metadata2 = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: false,
};
let field_metadata_expected = FieldMetadata {
field_name: "a".to_string(),
typ: crate::schema::Type::Str,
indexed: true,
stored: false,
fast: true,
};
let mut res1 = field_metadata1.clone();
res1 |= field_metadata2.clone();
let mut res2 = field_metadata2.clone();
res2 |= field_metadata1;
assert_eq!(res1, field_metadata_expected);
assert_eq!(res2, field_metadata_expected);
}
#[test]
fn test_num_alive() -> crate::Result<()> {
let mut schema_builder = Schema::builder();

View File

@@ -1,13 +1,12 @@
use crate::collector::Count;
use crate::directory::{RamDirectory, WatchCallback};
use crate::indexer::{LogMergePolicy, NoMergePolicy};
use crate::json_utils::JsonTermWriter;
use crate::indexer::NoMergePolicy;
use crate::query::TermQuery;
use crate::schema::{Field, IndexRecordOption, Schema, Type, INDEXED, STRING, TEXT};
use crate::schema::{Field, IndexRecordOption, Schema, INDEXED, STRING, TEXT};
use crate::tokenizer::TokenizerManager;
use crate::{
Directory, DocSet, Index, IndexBuilder, IndexReader, IndexSettings, IndexWriter, Postings,
ReloadPolicy, SegmentId, TantivyDocument, Term,
Directory, Index, IndexBuilder, IndexReader, IndexSettings, IndexWriter, ReloadPolicy,
SegmentId, TantivyDocument, Term,
};
#[test]
@@ -345,132 +344,3 @@ fn test_merging_segment_update_docfreq() {
let term_info = inv_index.get_term_info(&term).unwrap().unwrap();
assert_eq!(term_info.doc_freq, 12);
}
// motivated by https://github.com/quickwit-oss/quickwit/issues/4130
#[test]
fn test_positions_merge_bug_non_text_json_vint() {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_json_field("dynamic", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
let mut writer: IndexWriter = index.writer_for_tests().unwrap();
let mut merge_policy = LogMergePolicy::default();
merge_policy.set_min_num_segments(2);
writer.set_merge_policy(Box::new(merge_policy));
// Here a string would work.
let doc_json = r#"{"tenant_id":75}"#;
let vals = serde_json::from_str(doc_json).unwrap();
let mut doc = TantivyDocument::default();
doc.add_object(field, vals);
writer.add_document(doc.clone()).unwrap();
writer.commit().unwrap();
writer.add_document(doc.clone()).unwrap();
writer.commit().unwrap();
writer.wait_merging_threads().unwrap();
let reader = index.reader().unwrap();
assert_eq!(reader.searcher().segment_readers().len(), 1);
}
// Same as above but with bitpacked blocks
#[test]
fn test_positions_merge_bug_non_text_json_bitpacked_block() {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_json_field("dynamic", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
let mut writer: IndexWriter = index.writer_for_tests().unwrap();
let mut merge_policy = LogMergePolicy::default();
merge_policy.set_min_num_segments(2);
writer.set_merge_policy(Box::new(merge_policy));
// Here a string would work.
let doc_json = r#"{"tenant_id":75}"#;
let vals = serde_json::from_str(doc_json).unwrap();
let mut doc = TantivyDocument::default();
doc.add_object(field, vals);
for _ in 0..128 {
writer.add_document(doc.clone()).unwrap();
}
writer.commit().unwrap();
writer.add_document(doc.clone()).unwrap();
writer.commit().unwrap();
writer.wait_merging_threads().unwrap();
let reader = index.reader().unwrap();
assert_eq!(reader.searcher().segment_readers().len(), 1);
}
#[test]
fn test_non_text_json_term_freq() {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_json_field("dynamic", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
let mut writer: IndexWriter = index.writer_for_tests().unwrap();
// Here a string would work.
let doc_json = r#"{"tenant_id":75}"#;
let vals = serde_json::from_str(doc_json).unwrap();
let mut doc = TantivyDocument::default();
doc.add_object(field, vals);
writer.add_document(doc.clone()).unwrap();
writer.commit().unwrap();
let reader = index.reader().unwrap();
assert_eq!(reader.searcher().segment_readers().len(), 1);
let searcher = reader.searcher();
let segment_reader = searcher.segment_reader(0u32);
let inv_idx = segment_reader.inverted_index(field).unwrap();
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_term_writer = JsonTermWriter::wrap(&mut term, false);
json_term_writer.push_path_segment("tenant_id");
json_term_writer.close_path_and_set_type(Type::U64);
json_term_writer.set_fast_value(75u64);
let postings = inv_idx
.read_postings(
json_term_writer.term(),
IndexRecordOption::WithFreqsAndPositions,
)
.unwrap()
.unwrap();
assert_eq!(postings.doc(), 0);
assert_eq!(postings.term_freq(), 1u32);
}
#[test]
fn test_non_text_json_term_freq_bitpacked() {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_json_field("dynamic", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
let mut writer: IndexWriter = index.writer_for_tests().unwrap();
// Here a string would work.
let doc_json = r#"{"tenant_id":75}"#;
let vals = serde_json::from_str(doc_json).unwrap();
let mut doc = TantivyDocument::default();
doc.add_object(field, vals);
let num_docs = 132;
for _ in 0..num_docs {
writer.add_document(doc.clone()).unwrap();
}
writer.commit().unwrap();
let reader = index.reader().unwrap();
assert_eq!(reader.searcher().segment_readers().len(), 1);
let searcher = reader.searcher();
let segment_reader = searcher.segment_reader(0u32);
let inv_idx = segment_reader.inverted_index(field).unwrap();
let mut term = Term::with_type_and_field(Type::Json, field);
let mut json_term_writer = JsonTermWriter::wrap(&mut term, false);
json_term_writer.push_path_segment("tenant_id");
json_term_writer.close_path_and_set_type(Type::U64);
json_term_writer.set_fast_value(75u64);
let mut postings = inv_idx
.read_postings(
json_term_writer.term(),
IndexRecordOption::WithFreqsAndPositions,
)
.unwrap()
.unwrap();
assert_eq!(postings.doc(), 0);
assert_eq!(postings.term_freq(), 1u32);
for i in 1..num_docs {
assert_eq!(postings.advance(), i);
assert_eq!(postings.term_freq(), 1u32);
}
}

View File

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

View File

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

View File

@@ -131,7 +131,7 @@ mod tests {
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 80);
assert_eq!(file.len(), 105);
let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
let column = fast_field_readers
.u64("field")
@@ -181,7 +181,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 108);
assert_eq!(file.len(), 133);
let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
let col = fast_field_readers
.u64("field")
@@ -214,7 +214,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 81);
assert_eq!(file.len(), 106);
let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
let fast_field_reader = fast_field_readers
.u64("field")
@@ -246,7 +246,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 4476);
assert_eq!(file.len(), 4501);
{
let fast_field_readers = FastFieldReaders::open(file, SCHEMA.clone()).unwrap();
let col = fast_field_readers
@@ -279,7 +279,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 252);
assert_eq!(file.len(), 277);
{
let fast_field_readers = FastFieldReaders::open(file, schema).unwrap();
@@ -773,7 +773,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 84);
assert_eq!(file.len(), 114);
let fast_field_readers = FastFieldReaders::open(file, schema).unwrap();
let bool_col = fast_field_readers.bool("field_bool").unwrap();
assert_eq!(bool_col.first(0), Some(true));
@@ -805,7 +805,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 96);
assert_eq!(file.len(), 126);
let readers = FastFieldReaders::open(file, schema).unwrap();
let bool_col = readers.bool("field_bool").unwrap();
for i in 0..25 {
@@ -830,7 +830,7 @@ mod tests {
write.terminate().unwrap();
}
let file = directory.open_read(path).unwrap();
assert_eq!(file.len(), 86);
assert_eq!(file.len(), 116);
let fastfield_readers = FastFieldReaders::open(file, schema).unwrap();
let col = fastfield_readers.bool("field_bool").unwrap();
assert_eq!(col.first(0), None);
@@ -1288,18 +1288,11 @@ mod tests {
index_writer.commit().unwrap();
let searcher = index.reader().unwrap().searcher();
let fast_field_reader = searcher.segment_reader(0u32).fast_fields();
// Supported for now, maybe dropped in the future.
let column = fast_field_reader
.column_opt::<i64>("jsonfield.attr.age")
.unwrap()
.unwrap();
let vals: Vec<i64> = column.values_for_doc(0u32).collect();
assert_eq!(&vals, &[33]);
let column = fast_field_reader
.column_opt::<i64>("jsonfield\\.attr.age")
.unwrap()
.unwrap();
let vals: Vec<i64> = column.values_for_doc(0u32).collect();
assert_eq!(&vals, &[33]);
}
}

View File

@@ -1,22 +0,0 @@
//! # Index Module
//!
//! The `index` module in Tantivy contains core components to read and write indexes.
//!
//! It contains `Index` and `Segment`, where a `Index` consists of one or more `Segment`s.
mod index;
mod index_meta;
mod inverted_index_reader;
mod segment;
mod segment_component;
mod segment_id;
mod segment_reader;
pub use self::index::{Index, IndexBuilder};
pub(crate) use self::index_meta::SegmentMetaInventory;
pub use self::index_meta::{IndexMeta, IndexSettings, IndexSortByField, Order, SegmentMeta};
pub use self::inverted_index_reader::InvertedIndexReader;
pub use self::segment::Segment;
pub use self::segment_component::SegmentComponent;
pub use self::segment_id::SegmentId;
pub use self::segment_reader::{FieldMetadata, SegmentReader};

View File

@@ -9,10 +9,10 @@ use smallvec::smallvec;
use super::operation::{AddOperation, UserOperation};
use super::segment_updater::SegmentUpdater;
use super::{AddBatch, AddBatchReceiver, AddBatchSender, PreparedCommit};
use crate::core::{Index, Segment, SegmentComponent, SegmentId, SegmentMeta, SegmentReader};
use crate::directory::{DirectoryLock, GarbageCollectionResult, TerminatingWrite};
use crate::error::TantivyError;
use crate::fastfield::write_alive_bitset;
use crate::index::{Index, Segment, SegmentComponent, SegmentId, SegmentMeta, SegmentReader};
use crate::indexer::delete_queue::{DeleteCursor, DeleteQueue};
use crate::indexer::doc_opstamp_mapping::DocToOpstampMapping;
use crate::indexer::index_writer_status::IndexWriterStatus;
@@ -1651,7 +1651,6 @@ mod tests {
force_end_merge: bool,
) -> crate::Result<Index> {
let mut schema_builder = schema::Schema::builder();
let json_field = schema_builder.add_json_field("json", FAST | TEXT | STORED);
let ip_field = schema_builder.add_ip_addr_field("ip", FAST | INDEXED | STORED);
let ips_field = schema_builder
.add_ip_addr_field("ips", IpAddrOptions::default().set_fast().set_indexed());
@@ -1730,9 +1729,7 @@ mod tests {
id_field=>id,
))?;
} else {
let json = json!({"date1": format!("2022-{id}-01T00:00:01Z"), "date2": format!("{id}-05-01T00:00:01Z"), "id": id, "ip": ip.to_string()});
index_writer.add_document(doc!(id_field=>id,
json_field=>json,
bytes_field => id.to_le_bytes().as_slice(),
id_opt_field => id,
ip_field => ip,

View File

@@ -3,7 +3,7 @@ use std::cmp;
use itertools::Itertools;
use super::merge_policy::{MergeCandidate, MergePolicy};
use crate::index::SegmentMeta;
use crate::core::SegmentMeta;
const DEFAULT_LEVEL_LOG_SIZE: f64 = 0.75;
const DEFAULT_MIN_LAYER_SIZE: u32 = 10_000;
@@ -144,7 +144,7 @@ mod tests {
use once_cell::sync::Lazy;
use super::*;
use crate::index::{SegmentId, SegmentMeta, SegmentMetaInventory};
use crate::core::{SegmentId, SegmentMeta, SegmentMetaInventory};
use crate::indexer::merge_policy::MergePolicy;
use crate::schema;
use crate::schema::INDEXED;

View File

@@ -1,7 +1,7 @@
use std::fmt::Debug;
use std::marker;
use crate::index::{SegmentId, SegmentMeta};
use crate::core::{SegmentId, SegmentMeta};
/// Set of segment suggested for a merge.
#[derive(Debug, Clone)]
@@ -39,7 +39,7 @@ impl MergePolicy for NoMergePolicy {
pub mod tests {
use super::*;
use crate::index::{SegmentId, SegmentMeta};
use crate::core::{SegmentId, SegmentMeta};
/// `MergePolicy` useful for test purposes.
///

View File

@@ -8,12 +8,12 @@ use common::ReadOnlyBitSet;
use itertools::Itertools;
use measure_time::debug_time;
use crate::core::{Segment, SegmentReader};
use crate::directory::WritePtr;
use crate::docset::{DocSet, TERMINATED};
use crate::error::DataCorruption;
use crate::fastfield::{AliveBitSet, FastFieldNotAvailableError};
use crate::fieldnorm::{FieldNormReader, FieldNormReaders, FieldNormsSerializer, FieldNormsWriter};
use crate::index::{Segment, SegmentReader};
use crate::indexer::doc_id_mapping::{MappingType, SegmentDocIdMapping};
use crate::indexer::SegmentSerializer;
use crate::postings::{InvertedIndexSerializer, Postings, SegmentPostings};
@@ -552,41 +552,7 @@ impl IndexMerger {
continue;
}
// This should never happen as we early exited for total_doc_freq == 0.
assert!(!segment_postings_containing_the_term.is_empty());
let has_term_freq = {
let has_term_freq = !segment_postings_containing_the_term[0]
.1
.block_cursor
.freqs()
.is_empty();
for (_, postings) in &segment_postings_containing_the_term[1..] {
// This may look at a strange way to test whether we have term freq or not.
// With JSON object, the schema is not sufficient to know whether a term
// has its term frequency encoded or not:
// strings may have term frequencies, while number terms never have one.
//
// Ideally, we should have burnt one bit of two in the `TermInfo`.
// However, we preferred not changing the codec too much and detect this
// instead by
// - looking at the size of the skip data for bitpacked blocks
// - observing the absence of remaining data after reading the docs for vint
// blocks.
//
// Overall the reliable way to know if we have actual frequencies loaded or not
// is to check whether the actual decoded array is empty or not.
if has_term_freq != !postings.block_cursor.freqs().is_empty() {
return Err(DataCorruption::comment_only(
"Term freqs are inconsistent across segments",
)
.into());
}
}
has_term_freq
};
field_serializer.new_term(term_bytes, total_doc_freq, has_term_freq)?;
field_serializer.new_term(term_bytes, total_doc_freq)?;
// We can now serialize this postings, by pushing each document to the
// postings serializer.
@@ -601,17 +567,8 @@ impl IndexMerger {
if let Some(remapped_doc_id) = old_to_new_doc_id[doc as usize] {
// we make sure to only write the term if
// there is at least one document.
let term_freq = if has_term_freq {
segment_postings.positions(&mut positions_buffer);
segment_postings.term_freq()
} else {
// The positions_buffer may contain positions from the previous term
// Existence of positions depend on the value type in JSON fields.
// https://github.com/quickwit-oss/tantivy/issues/2283
positions_buffer.clear();
0u32
};
let term_freq = segment_postings.term_freq();
segment_postings.positions(&mut positions_buffer);
// if doc_id_mapping exists, the doc_ids are reordered, they are
// not just stacked. The field serializer expects monotonically increasing
// doc_ids, so we collect and sort them first, before writing.
@@ -794,7 +751,7 @@ mod tests {
BytesFastFieldTestCollector, FastFieldTestCollector, TEST_COLLECTOR_WITH_SCORE,
};
use crate::collector::{Count, FacetCollector};
use crate::index::Index;
use crate::core::Index;
use crate::query::{AllQuery, BooleanQuery, EnableScoring, Scorer, TermQuery};
use crate::schema::document::Value;
use crate::schema::{

View File

@@ -1,8 +1,8 @@
#[cfg(test)]
mod tests {
use crate::collector::TopDocs;
use crate::core::Index;
use crate::fastfield::AliveBitSet;
use crate::index::Index;
use crate::query::QueryParser;
use crate::schema::document::Value;
use crate::schema::{
@@ -485,7 +485,7 @@ mod bench_sorted_index_merge {
use test::{self, Bencher};
use crate::index::Index;
use crate::core::Index;
use crate::indexer::merger::IndexMerger;
use crate::schema::{NumericOptions, Schema};
use crate::{IndexSettings, IndexSortByField, IndexWriter, Order};

View File

@@ -25,7 +25,6 @@ mod segment_register;
pub(crate) mod segment_serializer;
pub(crate) mod segment_updater;
pub(crate) mod segment_writer;
pub(crate) mod single_segment_index_writer;
mod stamper;
use crossbeam_channel as channel;
@@ -35,14 +34,13 @@ pub use self::index_writer::IndexWriter;
pub use self::log_merge_policy::LogMergePolicy;
pub use self::merge_operation::MergeOperation;
pub use self::merge_policy::{MergeCandidate, MergePolicy, NoMergePolicy};
use self::operation::AddOperation;
pub use self::operation::UserOperation;
pub use self::prepared_commit::PreparedCommit;
pub use self::segment_entry::SegmentEntry;
pub(crate) use self::segment_serializer::SegmentSerializer;
pub use self::segment_updater::{merge_filtered_segments, merge_indices};
pub use self::segment_writer::SegmentWriter;
pub use self::single_segment_index_writer::SingleSegmentIndexWriter;
use crate::indexer::operation::AddOperation;
/// Alias for the default merge policy, which is the `LogMergePolicy`.
pub type DefaultMergePolicy = LogMergePolicy;
@@ -61,13 +59,9 @@ type AddBatchReceiver<D> = channel::Receiver<AddBatch<D>>;
#[cfg(test)]
mod tests_mmap {
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::AggregationCollector;
use crate::collector::{Count, TopDocs};
use crate::index::FieldMetadata;
use crate::query::{AllQuery, QueryParser};
use crate::schema::{JsonObjectOptions, Schema, Type, FAST, INDEXED, STORED, TEXT};
use crate::collector::Count;
use crate::query::QueryParser;
use crate::schema::{JsonObjectOptions, Schema, Type, TEXT};
use crate::{Index, IndexWriter, Term};
#[test]
@@ -179,7 +173,8 @@ mod tests_mmap {
#[test]
fn test_json_field_list_fields() {
let mut schema_builder = Schema::builder();
let json_options: JsonObjectOptions = JsonObjectOptions::from(TEXT);
let json_options: JsonObjectOptions =
JsonObjectOptions::from(TEXT).set_expand_dots_enabled();
let json_field = schema_builder.add_json_field("json", json_options);
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer = index.writer_for_tests().unwrap();
@@ -198,9 +193,9 @@ mod tests_mmap {
let reader = &searcher.segment_readers()[0];
let inverted_index = reader.inverted_index(json_field).unwrap();
assert_eq!(
inverted_index.list_encoded_fields().unwrap(),
inverted_index.list_fields().unwrap(),
[
("k8s.container.name".to_string(), Type::Str),
("k8s\u{1}container\u{1}name".to_string(), Type::Str),
("sub\u{1}a".to_string(), Type::I64),
("sub\u{1}b".to_string(), Type::I64),
("suber\u{1}a".to_string(), Type::I64),
@@ -210,239 +205,4 @@ mod tests_mmap {
]
);
}
#[test]
fn test_json_fields_metadata_expanded_dots_one_segment() {
test_json_fields_metadata(true, true);
}
#[test]
fn test_json_fields_metadata_expanded_dots_multi_segment() {
test_json_fields_metadata(true, false);
}
#[test]
fn test_json_fields_metadata_no_expanded_dots_one_segment() {
test_json_fields_metadata(false, true);
}
#[test]
fn test_json_fields_metadata_no_expanded_dots_multi_segment() {
test_json_fields_metadata(false, false);
}
fn test_json_fields_metadata(expanded_dots: bool, one_segment: bool) {
use pretty_assertions::assert_eq;
let mut schema_builder = Schema::builder();
let json_options: JsonObjectOptions =
JsonObjectOptions::from(TEXT).set_fast(None).set_stored();
let json_options = if expanded_dots {
json_options.set_expand_dots_enabled()
} else {
json_options
};
schema_builder.add_json_field("json.confusing", json_options.clone());
let json_field = schema_builder.add_json_field("json.shadow", json_options.clone());
let json_field2 = schema_builder.add_json_field("json", json_options.clone());
schema_builder.add_json_field("empty_json", json_options);
let number_field = schema_builder.add_u64_field("numbers", FAST);
schema_builder.add_u64_field("empty", FAST | INDEXED | STORED);
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer = index.writer_for_tests().unwrap();
let json =
serde_json::json!({"k8s.container.name": "a", "val": "a", "sub": {"a": 1, "b": 1}});
index_writer.add_document(doc!(json_field=>json)).unwrap();
let json =
serde_json::json!({"k8s.container.name": "a", "val": "a", "suber": {"a": 1, "b": 1}});
if !one_segment {
index_writer.commit().unwrap();
}
index_writer.add_document(doc!(json_field=>json)).unwrap();
let json = serde_json::json!({"k8s.container.name": "a", "k8s.container.name": "a", "val": "a", "suber": {"a": "a", "b": 1}});
index_writer
.add_document(doc!(number_field => 50u64, json_field=>json, json_field2=>json!({"shadow": {"val": "a"}})))
.unwrap();
index_writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
assert_eq!(searcher.num_docs(), 3);
let fields_metadata = index.fields_metadata().unwrap();
assert_eq!(
fields_metadata,
[
FieldMetadata {
field_name: "empty".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::U64
},
FieldMetadata {
field_name: if expanded_dots {
"json.shadow.k8s.container.name".to_string()
} else {
"json.shadow.k8s\\.container\\.name".to_string()
},
indexed: true,
stored: true,
fast: true,
typ: Type::Str
},
FieldMetadata {
field_name: "json.shadow.sub.a".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.sub.b".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.suber.a".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.suber.a".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::Str
},
FieldMetadata {
field_name: "json.shadow.suber.b".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::I64
},
FieldMetadata {
field_name: "json.shadow.val".to_string(),
indexed: true,
stored: true,
fast: true,
typ: Type::Str
},
FieldMetadata {
field_name: "numbers".to_string(),
indexed: false,
stored: false,
fast: true,
typ: Type::U64
}
]
);
let query_parser = QueryParser::for_index(&index, vec![]);
// Test if returned field name can be queried
for indexed_field in fields_metadata.iter().filter(|meta| meta.indexed) {
let val = if indexed_field.typ == Type::Str {
"a"
} else {
"1"
};
let query_str = &format!("{}:{}", indexed_field.field_name, val);
let query = query_parser.parse_query(query_str).unwrap();
let count_docs = searcher.search(&*query, &TopDocs::with_limit(2)).unwrap();
if indexed_field.field_name.contains("empty") || indexed_field.typ == Type::Json {
assert_eq!(count_docs.len(), 0);
} else {
assert!(!count_docs.is_empty(), "{}", indexed_field.field_name);
}
}
// Test if returned field name can be used for aggregation
for fast_field in fields_metadata.iter().filter(|meta| meta.fast) {
let agg_req_str = json!(
{
"termagg": {
"terms": {
"field": fast_field.field_name,
}
}
});
let agg_req: Aggregations = serde_json::from_value(agg_req_str).unwrap();
let collector = AggregationCollector::from_aggs(agg_req, Default::default());
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let res = serde_json::to_value(agg_res).unwrap();
if !fast_field.field_name.contains("empty") && fast_field.typ != Type::Json {
assert!(
!res["termagg"]["buckets"].as_array().unwrap().is_empty(),
"{}",
fast_field.field_name
);
}
}
}
#[test]
fn test_json_field_shadowing_field_name_bug() {
/// This test is only there to display a bug on addressing a field if it gets shadowed
/// The issues only occurs if the field name that shadows contains a dot.
///
/// Happens independently of the `expand_dots` option. Since that option does not
/// affect the field name itself.
use pretty_assertions::assert_eq;
let mut schema_builder = Schema::builder();
let json_options: JsonObjectOptions =
JsonObjectOptions::from(TEXT).set_fast(None).set_stored();
// let json_options = json_options.set_expand_dots_enabled();
let json_field_shadow = schema_builder.add_json_field("json.shadow", json_options.clone());
let json_field = schema_builder.add_json_field("json", json_options.clone());
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer = index.writer_for_tests().unwrap();
index_writer
.add_document(
doc!(json_field_shadow=>json!({"val": "b"}), json_field=>json!({"shadow": {"val": "a"}})),
)
.unwrap();
index_writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
let fields_and_vals = [
("json.shadow\u{1}val".to_string(), "a"), // Succeeds
//("json.shadow.val".to_string(), "a"), // Fails
("json.shadow.val".to_string(), "b"),
];
let query_parser = QueryParser::for_index(&index, vec![]);
// Test if field name can be queried
for (indexed_field, val) in fields_and_vals.iter() {
let query_str = &format!("{}:{}", indexed_field, val);
let query = query_parser.parse_query(query_str).unwrap();
let count_docs = searcher.search(&*query, &TopDocs::with_limit(2)).unwrap();
assert!(!count_docs.is_empty(), "{}:{}", indexed_field, val);
}
// Test if field name can be used for aggregation
for (field_name, val) in fields_and_vals.iter() {
let agg_req_str = json!(
{
"termagg": {
"terms": {
"field": field_name,
}
}
});
let agg_req: Aggregations = serde_json::from_value(agg_req_str).unwrap();
let collector = AggregationCollector::from_aggs(agg_req, Default::default());
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
let res = serde_json::to_value(agg_res).unwrap();
assert_eq!(
res["termagg"]["buckets"].as_array().unwrap()[0]["key"]
.as_str()
.unwrap(),
*val,
"{}",
field_name
);
}
}
}

View File

@@ -2,7 +2,7 @@ use std::fmt;
use common::BitSet;
use crate::index::{SegmentId, SegmentMeta};
use crate::core::{SegmentId, SegmentMeta};
use crate::indexer::delete_queue::DeleteCursor;
/// A segment entry describes the state of

View File

@@ -3,8 +3,8 @@ use std::fmt::{self, Debug, Formatter};
use std::sync::{RwLock, RwLockReadGuard, RwLockWriteGuard};
use super::segment_register::SegmentRegister;
use crate::core::{SegmentId, SegmentMeta};
use crate::error::TantivyError;
use crate::index::{SegmentId, SegmentMeta};
use crate::indexer::delete_queue::DeleteCursor;
use crate::indexer::SegmentEntry;

View File

@@ -1,7 +1,7 @@
use std::collections::{HashMap, HashSet};
use std::fmt::{self, Debug, Display, Formatter};
use crate::index::{SegmentId, SegmentMeta};
use crate::core::{SegmentId, SegmentMeta};
use crate::indexer::delete_queue::DeleteCursor;
use crate::indexer::segment_entry::SegmentEntry;
@@ -103,7 +103,7 @@ impl SegmentRegister {
#[cfg(test)]
mod tests {
use super::*;
use crate::index::{SegmentId, SegmentMetaInventory};
use crate::core::{SegmentId, SegmentMetaInventory};
use crate::indexer::delete_queue::*;
fn segment_ids(segment_register: &SegmentRegister) -> Vec<SegmentId> {

View File

@@ -1,8 +1,8 @@
use common::TerminatingWrite;
use crate::core::{Segment, SegmentComponent};
use crate::directory::WritePtr;
use crate::fieldnorm::FieldNormsSerializer;
use crate::index::{Segment, SegmentComponent};
use crate::postings::InvertedIndexSerializer;
use crate::store::StoreWriter;

View File

@@ -9,10 +9,11 @@ use std::sync::{Arc, RwLock};
use rayon::{ThreadPool, ThreadPoolBuilder};
use super::segment_manager::SegmentManager;
use crate::core::META_FILEPATH;
use crate::core::{
Index, IndexMeta, IndexSettings, Segment, SegmentId, SegmentMeta, META_FILEPATH,
};
use crate::directory::{Directory, DirectoryClone, GarbageCollectionResult};
use crate::fastfield::AliveBitSet;
use crate::index::{Index, IndexMeta, IndexSettings, Segment, SegmentId, SegmentMeta};
use crate::indexer::delete_queue::DeleteCursor;
use crate::indexer::index_writer::advance_deletes;
use crate::indexer::merge_operation::MergeOperationInventory;

View File

@@ -6,9 +6,9 @@ use tokenizer_api::BoxTokenStream;
use super::doc_id_mapping::{get_doc_id_mapping_from_field, DocIdMapping};
use super::operation::AddOperation;
use crate::core::json_utils::index_json_values;
use crate::core::Segment;
use crate::fastfield::FastFieldsWriter;
use crate::fieldnorm::{FieldNormReaders, FieldNormsWriter};
use crate::index::Segment;
use crate::indexer::segment_serializer::SegmentSerializer;
use crate::postings::{
compute_table_memory_size, serialize_postings, IndexingContext, IndexingPosition,
@@ -879,31 +879,6 @@ mod tests {
assert_eq!(searcher.search(&phrase_query, &Count).unwrap(), 0);
}
#[test]
fn test_json_term_with_numeric_merge_panic_regression_bug_2283() {
// https://github.com/quickwit-oss/tantivy/issues/2283
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
let doc = json!({"field": "a"});
writer.add_document(doc!(json=>doc)).unwrap();
writer.commit().unwrap();
let doc = json!({"field": "a", "id": 1});
writer.add_document(doc!(json=>doc.clone())).unwrap();
writer.commit().unwrap();
// Force Merge
writer.wait_merging_threads().unwrap();
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let segment_ids = index
.searchable_segment_ids()
.expect("Searchable segments failed.");
index_writer.merge(&segment_ids).wait().unwrap();
assert!(index_writer.wait_merging_threads().is_ok());
}
#[test]
fn test_bug_regression_1629_position_when_array_with_a_field_value_that_does_not_contain_any_token(
) {

View File

@@ -189,7 +189,6 @@ pub mod collector;
pub mod directory;
pub mod fastfield;
pub mod fieldnorm;
pub mod index;
pub mod positions;
pub mod postings;
@@ -221,18 +220,18 @@ pub use self::docset::{DocSet, TERMINATED};
pub use self::snippet::{Snippet, SnippetGenerator};
#[doc(hidden)]
pub use crate::core::json_utils;
pub use crate::core::{Executor, Searcher, SearcherGeneration};
pub use crate::directory::Directory;
pub use crate::index::{
Index, IndexBuilder, IndexMeta, IndexSettings, IndexSortByField, InvertedIndexReader, Order,
Segment, SegmentComponent, SegmentId, SegmentMeta, SegmentReader,
pub use crate::core::{
Executor, Index, IndexBuilder, IndexMeta, IndexSettings, IndexSortByField, InvertedIndexReader,
Order, Searcher, SearcherGeneration, Segment, SegmentComponent, SegmentId, SegmentMeta,
SegmentReader, SingleSegmentIndexWriter,
};
pub use crate::directory::Directory;
pub use crate::indexer::IndexWriter;
#[deprecated(
since = "0.22.0",
note = "Will be removed in tantivy 0.23. Use export from indexer module instead"
)]
pub use crate::indexer::PreparedCommit;
pub use crate::indexer::{IndexWriter, SingleSegmentIndexWriter};
pub use crate::indexer::{merge_filtered_segments, merge_indices, PreparedCommit};
pub use crate::postings::Postings;
#[allow(deprecated)]
pub use crate::schema::DatePrecision;
@@ -339,7 +338,7 @@ impl DocAddress {
///
/// The id used for the segment is actually an ordinal
/// in the list of `Segment`s held by a `Searcher`.
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
#[derive(Debug, Clone, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub struct DocAddress {
/// The segment ordinal id that identifies the segment
/// hosting the document in the `Searcher` it is called from.
@@ -387,8 +386,8 @@ pub mod tests {
use time::OffsetDateTime;
use crate::collector::tests::TEST_COLLECTOR_WITH_SCORE;
use crate::core::SegmentReader;
use crate::docset::{DocSet, TERMINATED};
use crate::index::SegmentReader;
use crate::merge_policy::NoMergePolicy;
use crate::query::BooleanQuery;
use crate::schema::document::Value;

View File

@@ -383,8 +383,8 @@ mod tests {
use common::HasLen;
use super::BlockSegmentPostings;
use crate::core::Index;
use crate::docset::{DocSet, TERMINATED};
use crate::index::Index;
use crate::postings::compression::COMPRESSION_BLOCK_SIZE;
use crate::postings::postings::Postings;
use crate::postings::SegmentPostings;

View File

@@ -11,10 +11,6 @@ use crate::schema::{Field, Type, JSON_END_OF_PATH};
use crate::tokenizer::TokenStream;
use crate::{DocId, Term};
/// The `JsonPostingsWriter` is odd in that it relies on a hidden contract:
///
/// `subscribe` is called directly to index non-text tokens, while
/// `index_text` is used to index text.
#[derive(Default)]
pub(crate) struct JsonPostingsWriter<Rec: Recorder> {
str_posting_writer: SpecializedPostingsWriter<Rec>,

View File

@@ -42,9 +42,9 @@ pub mod tests {
use std::mem;
use super::{InvertedIndexSerializer, Postings};
use crate::core::{Index, SegmentComponent, SegmentReader};
use crate::docset::{DocSet, TERMINATED};
use crate::fieldnorm::FieldNormReader;
use crate::index::{Index, SegmentComponent, SegmentReader};
use crate::indexer::operation::AddOperation;
use crate::indexer::SegmentWriter;
use crate::query::Scorer;
@@ -63,7 +63,7 @@ pub mod tests {
let mut segment = index.new_segment();
let mut posting_serializer = InvertedIndexSerializer::open(&mut segment)?;
let mut field_serializer = posting_serializer.new_field(text_field, 120 * 4, None)?;
field_serializer.new_term("abc".as_bytes(), 12u32, true)?;
field_serializer.new_term("abc".as_bytes(), 12u32)?;
for doc_id in 0u32..120u32 {
let delta_positions = vec![1, 2, 3, 2];
field_serializer.write_doc(doc_id, 4, &delta_positions);

View File

@@ -194,7 +194,7 @@ impl<Rec: Recorder> SpecializedPostingsWriter<Rec> {
) -> io::Result<()> {
let recorder: Rec = ctx.term_index.read(addr);
let term_doc_freq = recorder.term_doc_freq().unwrap_or(0u32);
serializer.new_term(term, term_doc_freq, recorder.has_term_freq())?;
serializer.new_term(term, term_doc_freq)?;
recorder.serialize(&ctx.arena, doc_id_map, serializer, buffer_lender);
serializer.close_term()?;
Ok(())

View File

@@ -79,20 +79,24 @@ pub(crate) trait Recorder: Copy + Default + Send + Sync + 'static {
///
/// Returns `None` if not available.
fn term_doc_freq(&self) -> Option<u32>;
#[inline]
fn has_term_freq(&self) -> bool {
true
}
}
/// Only records the doc ids
#[derive(Clone, Copy, Default)]
#[derive(Clone, Copy)]
pub struct DocIdRecorder {
stack: ExpUnrolledLinkedList,
current_doc: DocId,
}
impl Default for DocIdRecorder {
fn default() -> Self {
DocIdRecorder {
stack: ExpUnrolledLinkedList::default(),
current_doc: u32::MAX,
}
}
}
impl Recorder for DocIdRecorder {
#[inline]
fn current_doc(&self) -> DocId {
@@ -101,9 +105,8 @@ impl Recorder for DocIdRecorder {
#[inline]
fn new_doc(&mut self, doc: DocId, arena: &mut MemoryArena) {
let delta = doc - self.current_doc;
self.current_doc = doc;
self.stack.writer(arena).write_u32_vint(delta);
self.stack.writer(arena).write_u32_vint(doc);
}
#[inline]
@@ -120,20 +123,21 @@ impl Recorder for DocIdRecorder {
buffer_lender: &mut BufferLender,
) {
let (buffer, doc_ids) = buffer_lender.lend_all();
// TODO avoid reading twice.
self.stack.read_to_end(arena, buffer);
// TODO avoid reading twice.
if let Some(doc_id_map) = doc_id_map {
let iter = get_sum_reader(VInt32Reader::new(&buffer[..]));
doc_ids.extend(iter.map(|old_doc_id| doc_id_map.get_new_doc_id(old_doc_id)));
doc_ids.extend(
VInt32Reader::new(&buffer[..])
.map(|old_doc_id| doc_id_map.get_new_doc_id(old_doc_id)),
);
doc_ids.sort_unstable();
for doc in doc_ids {
serializer.write_doc(*doc, 0u32, &[][..]);
}
} else {
let iter = get_sum_reader(VInt32Reader::new(&buffer[..]));
for doc_id in iter {
serializer.write_doc(doc_id, 0u32, &[][..]);
for doc in VInt32Reader::new(&buffer[..]) {
serializer.write_doc(doc, 0u32, &[][..]);
}
}
}
@@ -141,19 +145,6 @@ impl Recorder for DocIdRecorder {
fn term_doc_freq(&self) -> Option<u32> {
None
}
fn has_term_freq(&self) -> bool {
false
}
}
/// Takes an Iterator of delta encoded elements and returns an iterator
/// that yields the sum of the elements.
fn get_sum_reader(iter: impl Iterator<Item = u32>) -> impl Iterator<Item = u32> {
iter.scan(0, |state, delta| {
*state += delta;
Some(*state)
})
}
/// Recorder encoding document ids, and term frequencies
@@ -173,10 +164,9 @@ impl Recorder for TermFrequencyRecorder {
#[inline]
fn new_doc(&mut self, doc: DocId, arena: &mut MemoryArena) {
let delta = doc - self.current_doc;
self.term_doc_freq += 1;
self.current_doc = doc;
self.stack.writer(arena).write_u32_vint(delta);
self.stack.writer(arena).write_u32_vint(doc);
}
#[inline]
@@ -203,12 +193,9 @@ impl Recorder for TermFrequencyRecorder {
let mut u32_it = VInt32Reader::new(&buffer[..]);
if let Some(doc_id_map) = doc_id_map {
let mut doc_id_and_tf = vec![];
let mut prev_doc = 0;
while let Some(delta_doc_id) = u32_it.next() {
let doc_id = prev_doc + delta_doc_id;
prev_doc = doc_id;
while let Some(old_doc_id) = u32_it.next() {
let term_freq = u32_it.next().unwrap_or(self.current_tf);
doc_id_and_tf.push((doc_id_map.get_new_doc_id(doc_id), term_freq));
doc_id_and_tf.push((doc_id_map.get_new_doc_id(old_doc_id), term_freq));
}
doc_id_and_tf.sort_unstable_by_key(|&(doc_id, _)| doc_id);
@@ -216,12 +203,9 @@ impl Recorder for TermFrequencyRecorder {
serializer.write_doc(doc_id, tf, &[][..]);
}
} else {
let mut prev_doc = 0;
while let Some(delta_doc_id) = u32_it.next() {
let doc_id = prev_doc + delta_doc_id;
prev_doc = doc_id;
while let Some(doc) = u32_it.next() {
let term_freq = u32_it.next().unwrap_or(self.current_tf);
serializer.write_doc(doc_id, term_freq, &[][..]);
serializer.write_doc(doc, term_freq, &[][..]);
}
}
}
@@ -232,13 +216,23 @@ impl Recorder for TermFrequencyRecorder {
}
/// Recorder encoding term frequencies as well as positions.
#[derive(Clone, Copy, Default)]
#[derive(Clone, Copy)]
pub struct TfAndPositionRecorder {
stack: ExpUnrolledLinkedList,
current_doc: DocId,
term_doc_freq: u32,
}
impl Default for TfAndPositionRecorder {
fn default() -> Self {
TfAndPositionRecorder {
stack: ExpUnrolledLinkedList::default(),
current_doc: u32::MAX,
term_doc_freq: 0u32,
}
}
}
impl Recorder for TfAndPositionRecorder {
#[inline]
fn current_doc(&self) -> DocId {
@@ -247,10 +241,9 @@ impl Recorder for TfAndPositionRecorder {
#[inline]
fn new_doc(&mut self, doc: DocId, arena: &mut MemoryArena) {
let delta = doc - self.current_doc;
self.current_doc = doc;
self.term_doc_freq += 1u32;
self.stack.writer(arena).write_u32_vint(delta);
self.stack.writer(arena).write_u32_vint(doc);
}
#[inline]
@@ -276,10 +269,7 @@ impl Recorder for TfAndPositionRecorder {
self.stack.read_to_end(arena, buffer_u8);
let mut u32_it = VInt32Reader::new(&buffer_u8[..]);
let mut doc_id_and_positions = vec![];
let mut prev_doc = 0;
while let Some(delta_doc_id) = u32_it.next() {
let doc_id = prev_doc + delta_doc_id;
prev_doc = doc_id;
while let Some(doc) = u32_it.next() {
let mut prev_position_plus_one = 1u32;
buffer_positions.clear();
loop {
@@ -297,9 +287,9 @@ impl Recorder for TfAndPositionRecorder {
if let Some(doc_id_map) = doc_id_map {
// this simple variant to remap may consume to much memory
doc_id_and_positions
.push((doc_id_map.get_new_doc_id(doc_id), buffer_positions.to_vec()));
.push((doc_id_map.get_new_doc_id(doc), buffer_positions.to_vec()));
} else {
serializer.write_doc(doc_id, buffer_positions.len() as u32, buffer_positions);
serializer.write_doc(doc, buffer_positions.len() as u32, buffer_positions);
}
}
if doc_id_map.is_some() {

View File

@@ -71,7 +71,7 @@ impl SegmentPostings {
{
let mut postings_serializer =
PostingsSerializer::new(&mut buffer, 0.0, IndexRecordOption::Basic, None);
postings_serializer.new_term(docs.len() as u32, false);
postings_serializer.new_term(docs.len() as u32);
for &doc in docs {
postings_serializer.write_doc(doc, 1u32);
}
@@ -120,7 +120,7 @@ impl SegmentPostings {
IndexRecordOption::WithFreqs,
fieldnorm_reader,
);
postings_serializer.new_term(doc_and_tfs.len() as u32, true);
postings_serializer.new_term(doc_and_tfs.len() as u32);
for &(doc, tf) in doc_and_tfs {
postings_serializer.write_doc(doc, tf);
}
@@ -238,18 +238,14 @@ impl Postings for SegmentPostings {
}
fn positions_with_offset(&mut self, offset: u32, output: &mut Vec<u32>) {
let term_freq = self.term_freq();
let term_freq = self.term_freq() as usize;
if let Some(position_reader) = self.position_reader.as_mut() {
debug_assert!(
!self.block_cursor.freqs().is_empty(),
"No positions available"
);
let read_offset = self.block_cursor.position_offset()
+ (self.block_cursor.freqs()[..self.cur]
.iter()
.cloned()
.sum::<u32>() as u64);
output.resize(term_freq as usize, 0u32);
output.resize(term_freq, 0u32);
position_reader.read(read_offset, &mut output[..]);
let mut cum = offset;
for output_mut in output.iter_mut() {

View File

@@ -4,9 +4,9 @@ use std::io::{self, Write};
use common::{BinarySerializable, CountingWriter, VInt};
use super::TermInfo;
use crate::core::Segment;
use crate::directory::{CompositeWrite, WritePtr};
use crate::fieldnorm::FieldNormReader;
use crate::index::Segment;
use crate::positions::PositionSerializer;
use crate::postings::compression::{BlockEncoder, VIntEncoder, COMPRESSION_BLOCK_SIZE};
use crate::postings::skip::SkipSerializer;
@@ -168,12 +168,7 @@ impl<'a> FieldSerializer<'a> {
/// * term - the term. It needs to come after the previous term according to the lexicographical
/// order.
/// * term_doc_freq - return the number of document containing the term.
pub fn new_term(
&mut self,
term: &[u8],
term_doc_freq: u32,
record_term_freq: bool,
) -> io::Result<()> {
pub fn new_term(&mut self, term: &[u8], term_doc_freq: u32) -> io::Result<()> {
assert!(
!self.term_open,
"Called new_term, while the previous term was not closed."
@@ -182,8 +177,7 @@ impl<'a> FieldSerializer<'a> {
self.postings_serializer.clear();
self.current_term_info = self.current_term_info();
self.term_dictionary_builder.insert_key(term)?;
self.postings_serializer
.new_term(term_doc_freq, record_term_freq);
self.postings_serializer.new_term(term_doc_freq);
Ok(())
}
@@ -336,10 +330,10 @@ impl<W: Write> PostingsSerializer<W> {
}
}
pub fn new_term(&mut self, term_doc_freq: u32, record_term_freq: bool) {
pub fn new_term(&mut self, term_doc_freq: u32) {
self.bm25_weight = None;
self.term_has_freq = self.mode.has_freq() && record_term_freq;
self.term_has_freq = self.mode.has_freq() && term_doc_freq != 0;
if !self.term_has_freq {
return;
}
@@ -355,7 +349,7 @@ impl<W: Write> PostingsSerializer<W> {
return;
}
self.bm25_weight = Some(Bm25Weight::for_one_term_without_explain(
self.bm25_weight = Some(Bm25Weight::for_one_term(
term_doc_freq as u64,
num_docs_in_segment,
self.avg_fieldnorm,

View File

@@ -1,5 +1,5 @@
use crate::core::SegmentReader;
use crate::docset::{DocSet, BUFFER_LEN, TERMINATED};
use crate::index::SegmentReader;
use crate::query::boost_query::BoostScorer;
use crate::query::explanation::does_not_match;
use crate::query::{EnableScoring, Explanation, Query, Scorer, Weight};

View File

@@ -5,7 +5,7 @@ use common::BitSet;
use tantivy_fst::Automaton;
use super::phrase_prefix_query::prefix_end;
use crate::index::SegmentReader;
use crate::core::SegmentReader;
use crate::query::{BitSetDocSet, ConstScorer, Explanation, Scorer, Weight};
use crate::schema::{Field, IndexRecordOption};
use crate::termdict::{TermDictionary, TermStreamer};

View File

@@ -77,7 +77,7 @@ pub struct Bm25Params {
/// A struct used for computing BM25 scores.
#[derive(Clone)]
pub struct Bm25Weight {
idf_explain: Option<Explanation>,
idf_explain: Explanation,
weight: Score,
cache: [Score; 256],
average_fieldnorm: Score,
@@ -147,30 +147,11 @@ impl Bm25Weight {
idf_explain.add_const("N, total number of docs", total_num_docs as Score);
Bm25Weight::new(idf_explain, avg_fieldnorm)
}
/// Construct a [Bm25Weight] for a single term.
/// This method does not carry the [Explanation] for the idf.
pub fn for_one_term_without_explain(
term_doc_freq: u64,
total_num_docs: u64,
avg_fieldnorm: Score,
) -> Bm25Weight {
let idf = idf(term_doc_freq, total_num_docs);
Bm25Weight::new_without_explain(idf, avg_fieldnorm)
}
pub(crate) fn new(idf_explain: Explanation, average_fieldnorm: Score) -> Bm25Weight {
let weight = idf_explain.value() * (1.0 + K1);
Bm25Weight {
idf_explain: Some(idf_explain),
weight,
cache: compute_tf_cache(average_fieldnorm),
average_fieldnorm,
}
}
pub(crate) fn new_without_explain(idf: f32, average_fieldnorm: Score) -> Bm25Weight {
let weight = idf * (1.0 + K1);
Bm25Weight {
idf_explain: None,
idf_explain,
weight,
cache: compute_tf_cache(average_fieldnorm),
average_fieldnorm,
@@ -221,9 +202,7 @@ impl Bm25Weight {
let mut explanation = Explanation::new("TermQuery, product of...", score);
explanation.add_detail(Explanation::new("(K1+1)", K1 + 1.0));
if let Some(idf_explain) = &self.idf_explain {
explanation.add_detail(idf_explain.clone());
}
explanation.add_detail(self.idf_explain.clone());
explanation.add_detail(tf_explanation);
explanation
}

View File

@@ -1,7 +1,7 @@
use std::collections::HashMap;
use crate::core::SegmentReader;
use crate::docset::BUFFER_LEN;
use crate::index::SegmentReader;
use crate::postings::FreqReadingOption;
use crate::query::explanation::does_not_match;
use crate::query::score_combiner::{DoNothingCombiner, ScoreCombiner};

View File

@@ -74,8 +74,7 @@ impl Weight for BoostWeight {
fn explain(&self, reader: &SegmentReader, doc: u32) -> crate::Result<Explanation> {
let underlying_explanation = self.weight.explain(reader, doc)?;
let score = underlying_explanation.value() * self.boost;
let mut explanation =
Explanation::new_with_string(format!("Boost x{} of ...", self.boost), score);
let mut explanation = Explanation::new(format!("Boost x{} of ...", self.boost), score);
explanation.add_detail(underlying_explanation);
Ok(explanation)
}
@@ -152,7 +151,7 @@ mod tests {
let explanation = query.explain(&searcher, DocAddress::new(0, 0u32)).unwrap();
assert_eq!(
explanation.to_pretty_json(),
"{\n \"value\": 0.2,\n \"description\": \"Boost x0.2 of ...\",\n \"details\": [\n {\n \"value\": 1.0,\n \"description\": \"AllQuery\"\n }\n ]\n}"
"{\n \"value\": 0.2,\n \"description\": \"Boost x0.2 of ...\",\n \"details\": [\n {\n \"value\": 1.0,\n \"description\": \"AllQuery\",\n \"context\": []\n }\n ],\n \"context\": []\n}"
);
Ok(())
}

View File

@@ -164,9 +164,11 @@ mod tests {
"details": [
{
"value": 1.0,
"description": "AllQuery"
"description": "AllQuery",
"context": []
}
]
],
"context": []
}"#
);
Ok(())

View File

@@ -3,8 +3,8 @@ use core::fmt::Debug;
use columnar::{ColumnIndex, DynamicColumn};
use super::{ConstScorer, EmptyScorer};
use crate::core::SegmentReader;
use crate::docset::{DocSet, TERMINATED};
use crate::index::SegmentReader;
use crate::query::explanation::does_not_match;
use crate::query::{EnableScoring, Explanation, Query, Scorer, Weight};
use crate::{DocId, Score, TantivyError};

View File

@@ -1,4 +1,3 @@
use std::borrow::Cow;
use std::fmt;
use serde::Serialize;
@@ -17,12 +16,12 @@ pub(crate) fn does_not_match(doc: DocId) -> TantivyError {
#[derive(Clone, Serialize)]
pub struct Explanation {
value: Score,
description: Cow<'static, str>,
#[serde(skip_serializing_if = "Option::is_none")]
details: Option<Vec<Explanation>>,
#[serde(skip_serializing_if = "Option::is_none")]
context: Option<Vec<String>>,
description: String,
#[serde(skip_serializing_if = "Vec::is_empty")]
details: Vec<Explanation>,
context: Vec<String>,
}
impl fmt::Debug for Explanation {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
write!(f, "Explanation({})", self.to_pretty_json())
@@ -31,21 +30,12 @@ impl fmt::Debug for Explanation {
impl Explanation {
/// Creates a new explanation object.
pub fn new_with_string(description: String, value: Score) -> Explanation {
pub fn new<T: ToString>(description: T, value: Score) -> Explanation {
Explanation {
value,
description: Cow::Owned(description),
details: None,
context: None,
}
}
/// Creates a new explanation object.
pub fn new(description: &'static str, value: Score) -> Explanation {
Explanation {
value,
description: Cow::Borrowed(description),
details: None,
context: None,
description: description.to_string(),
details: vec![],
context: vec![],
}
}
@@ -58,21 +48,17 @@ impl Explanation {
///
/// Details are treated as child of the current node.
pub fn add_detail(&mut self, child_explanation: Explanation) {
self.details
.get_or_insert_with(Vec::new)
.push(child_explanation);
self.details.push(child_explanation);
}
/// Adds some extra context to the explanation.
pub fn add_context(&mut self, context: String) {
self.context.get_or_insert_with(Vec::new).push(context);
self.context.push(context);
}
/// Shortcut for `self.details.push(Explanation::new(name, value));`
pub fn add_const(&mut self, name: &'static str, value: Score) {
self.details
.get_or_insert_with(Vec::new)
.push(Explanation::new(name, value));
pub fn add_const<T: ToString>(&mut self, name: T, value: Score) {
self.details.push(Explanation::new(name, value));
}
/// Returns an indented json representation of the explanation tree for debug usage.

View File

@@ -1,6 +1,6 @@
use super::{prefix_end, PhrasePrefixScorer};
use crate::core::SegmentReader;
use crate::fieldnorm::FieldNormReader;
use crate::index::SegmentReader;
use crate::postings::SegmentPostings;
use crate::query::bm25::Bm25Weight;
use crate::query::explanation::does_not_match;
@@ -157,8 +157,8 @@ impl Weight for PhrasePrefixWeight {
#[cfg(test)]
mod tests {
use crate::core::Index;
use crate::docset::TERMINATED;
use crate::index::Index;
use crate::query::{EnableScoring, PhrasePrefixQuery, Query};
use crate::schema::{Schema, TEXT};
use crate::{DocSet, IndexWriter, Term};

View File

@@ -14,7 +14,7 @@ pub mod tests {
use super::*;
use crate::collector::tests::{TEST_COLLECTOR_WITHOUT_SCORE, TEST_COLLECTOR_WITH_SCORE};
use crate::index::Index;
use crate::core::Index;
use crate::query::{EnableScoring, QueryParser, Weight};
use crate::schema::{Schema, Term, TEXT};
use crate::{assert_nearly_equals, DocAddress, DocId, IndexWriter, TERMINATED};

View File

@@ -1,6 +1,6 @@
use super::PhraseScorer;
use crate::core::SegmentReader;
use crate::fieldnorm::FieldNormReader;
use crate::index::SegmentReader;
use crate::postings::SegmentPostings;
use crate::query::bm25::Bm25Weight;
use crate::query::explanation::does_not_match;

View File

@@ -13,7 +13,7 @@ use super::logical_ast::*;
use crate::core::json_utils::{
convert_to_fast_value_and_get_term, set_string_and_get_terms, JsonTermWriter,
};
use crate::index::Index;
use crate::core::Index;
use crate::query::range_query::{is_type_valid_for_fastfield_range_query, RangeQuery};
use crate::query::{
AllQuery, BooleanQuery, BoostQuery, EmptyQuery, FuzzyTermQuery, Occur, PhrasePrefixQuery,

View File

@@ -7,8 +7,8 @@ use common::{BinarySerializable, BitSet};
use super::map_bound;
use super::range_query_u64_fastfield::FastFieldRangeWeight;
use crate::core::SegmentReader;
use crate::error::TantivyError;
use crate::index::SegmentReader;
use crate::query::explanation::does_not_match;
use crate::query::range_query::range_query_ip_fastfield::IPFastFieldRangeWeight;
use crate::query::range_query::{is_type_valid_for_fastfield_range_query, map_bound_res};

View File

@@ -63,7 +63,7 @@ impl RegexQuery {
/// Creates a new RegexQuery from a given pattern
pub fn from_pattern(regex_pattern: &str, field: Field) -> crate::Result<Self> {
let regex = Regex::new(regex_pattern)
.map_err(|err| TantivyError::InvalidArgument(format!("RegexQueryError: {err}")))?;
.map_err(|_| TantivyError::InvalidArgument(regex_pattern.to_string()))?;
Ok(RegexQuery::from_regex(regex, field))
}
@@ -176,16 +176,4 @@ mod test {
verify_regex_query(matching_one, matching_zero, reader);
Ok(())
}
#[test]
pub fn test_pattern_error() {
let (_reader, field) = build_test_index().unwrap();
match RegexQuery::from_pattern(r"(foo", field) {
Err(crate::TantivyError::InvalidArgument(msg)) => {
assert!(msg.contains("error: unclosed group"))
}
res => panic!("unexpected result: {:?}", res),
}
}
}

View File

@@ -101,7 +101,7 @@ impl TermQuery {
..
} => Bm25Weight::for_terms(statistics_provider, &[self.term.clone()])?,
EnableScoring::Disabled { .. } => {
Bm25Weight::new(Explanation::new("<no score>", 1.0f32), 1.0f32)
Bm25Weight::new(Explanation::new("<no score>".to_string(), 1.0f32), 1.0f32)
}
};
let scoring_enabled = enable_scoring.is_scoring_enabled();

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