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1 Commits

Author SHA1 Message Date
Paul Masurel
61422d7cd5 Change in the default fast field tokenizer manager.
`{ fast: true }` now results in the use of a the default fast field tokenizer. (instead of no tokenizer)
The default tokenizer lowercases.

Fast field gets a different default tokenizer manager than the normal tokenizer.

The serialization of the fast field options is unchanged.
2023-07-18 19:20:10 +09:00
222 changed files with 4468 additions and 13801 deletions

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@@ -3,6 +3,8 @@ name: Coverage
on:
push:
branches: [main]
pull_request:
branches: [main]
# Ensures that we cancel running jobs for the same PR / same workflow.
concurrency:
@@ -13,13 +15,13 @@ jobs:
coverage:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- name: Install Rust
run: rustup toolchain install nightly-2023-09-10 --profile minimal --component llvm-tools-preview
run: rustup toolchain install nightly --profile minimal --component llvm-tools-preview
- uses: Swatinem/rust-cache@v2
- uses: taiki-e/install-action@cargo-llvm-cov
- name: Generate code coverage
run: cargo +nightly-2023-09-10 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
run: cargo +nightly llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
continue-on-error: true

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@@ -19,7 +19,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- name: Install stable
uses: actions-rs/toolchain@v1
with:

View File

@@ -20,7 +20,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- name: Install nightly
uses: actions-rs/toolchain@v1
@@ -39,13 +39,6 @@ jobs:
- name: Check Formatting
run: cargo +nightly fmt --all -- --check
- name: Check Stable Compilation
run: cargo build --all-features
- name: Check Bench Compilation
run: cargo +nightly bench --no-run --profile=dev --all-features
- uses: actions-rs/clippy-check@v1
with:
@@ -67,7 +60,7 @@ jobs:
name: test-${{ matrix.features.label}}
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v3
- name: Install stable
uses: actions-rs/toolchain@v1

View File

@@ -1,36 +1,3 @@
Tantivy 0.21.1
================================
#### Bugfixes
- Range queries on fast fields with less values on that field than documents had an invalid end condition, leading to missing results. [#2226](https://github.com/quickwit-oss/tantivy/issues/2226)(@appaquet @PSeitz)
- Increase the minimum memory budget from 3MB to 15MB to avoid single doc segments (API fix). [#2176](https://github.com/quickwit-oss/tantivy/issues/2176)(@PSeitz)
Tantivy 0.21
================================
#### Bugfixes
- Fix track fast field memory consumption, which led to higher memory consumption than the budget allowed during indexing [#2148](https://github.com/quickwit-oss/tantivy/issues/2148)[#2147](https://github.com/quickwit-oss/tantivy/issues/2147)(@PSeitz)
- Fix a regression from 0.20 where sort index by date wasn't working anymore [#2124](https://github.com/quickwit-oss/tantivy/issues/2124)(@PSeitz)
- Fix getting the root facet on the `FacetCollector`. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086)(@adamreichold)
- Align numerical type priority order of columnar and query. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088)(@fmassot)
#### Breaking Changes
- Remove support for Brotli and Snappy compression [#2123](https://github.com/quickwit-oss/tantivy/issues/2123)(@adamreichold)
#### Features/Improvements
- Implement lenient query parser [#2129](https://github.com/quickwit-oss/tantivy/pull/2129)(@trinity-1686a)
- order_by_u64_field and order_by_fast_field allow sorting in ascending and descending order [#2111](https://github.com/quickwit-oss/tantivy/issues/2111)(@naveenann)
- Allow dynamic filters in text analyzer builder [#2110](https://github.com/quickwit-oss/tantivy/issues/2110)(@fulmicoton @fmassot)
- **Aggregation**
- Add missing parameter for term aggregation [#2149](https://github.com/quickwit-oss/tantivy/issues/2149)[#2103](https://github.com/quickwit-oss/tantivy/issues/2103)(@PSeitz)
- Add missing parameter for percentiles [#2157](https://github.com/quickwit-oss/tantivy/issues/2157)(@PSeitz)
- Add missing parameter for stats,min,max,count,sum,avg [#2151](https://github.com/quickwit-oss/tantivy/issues/2151)(@PSeitz)
- Improve aggregation deserialization error message [#2150](https://github.com/quickwit-oss/tantivy/issues/2150)(@PSeitz)
- Add validation for type Bytes to term_agg [#2077](https://github.com/quickwit-oss/tantivy/issues/2077)(@PSeitz)
- Alternative mixed field collection [#2135](https://github.com/quickwit-oss/tantivy/issues/2135)(@PSeitz)
- Add missing query_terms impl for TermSetQuery. [#2120](https://github.com/quickwit-oss/tantivy/issues/2120)(@adamreichold)
- Minor improvements to OwnedBytes [#2134](https://github.com/quickwit-oss/tantivy/issues/2134)(@adamreichold)
- Remove allocations in split compound words [#2080](https://github.com/quickwit-oss/tantivy/issues/2080)(@PSeitz)
- Ngram tokenizer now returns an error with invalid arguments [#2102](https://github.com/quickwit-oss/tantivy/issues/2102)(@fmassot)
- Make TextAnalyzerBuilder public [#2097](https://github.com/quickwit-oss/tantivy/issues/2097)(@adamreichold)
- Return an error when tokenizer is not found while indexing [#2093](https://github.com/quickwit-oss/tantivy/issues/2093)(@naveenann)
- Delayed column opening during merge [#2132](https://github.com/quickwit-oss/tantivy/issues/2132)(@PSeitz)
Tantivy 0.20.2
================================

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy"
version = "0.22.0-dev"
version = "0.20.2"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -22,46 +22,47 @@ 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"
memmap2 = { version = "0.9.0", optional = true }
tantivy-fst = "0.4.0"
memmap2 = { version = "0.7.1", optional = true }
lz4_flex = { version = "0.11", default-features = false, optional = true }
zstd = { version = "0.13", optional = true, default-features = false }
zstd = { version = "0.12", optional = true, default-features = false }
tempfile = { version = "3.3.0", optional = true }
log = "0.4.16"
serde = { version = "1.0.136", features = ["derive"] }
serde_json = "1.0.79"
num_cpus = "1.13.1"
fs4 = { version = "0.7.0", optional = true }
fs4 = { version = "0.6.3", 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"] }
bitpacking = { version = "0.8.4", 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"
lru = "0.11.0"
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" }
sstable = { version= "0.2", path="./sstable", package ="tantivy-sstable", optional = true }
stacker = { version= "0.2", path="./stacker", package ="tantivy-stacker" }
query-grammar = { version= "0.21.0", path="./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version= "0.5", path="./bitpacker" }
common = { version= "0.6", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version= "0.2", path="./tokenizer-api", package="tantivy-tokenizer-api" }
columnar = { version= "0.1", path="./columnar", package ="tantivy-columnar" }
sstable = { version= "0.1", path="./sstable", package ="tantivy-sstable", optional = true }
stacker = { version= "0.1", path="./stacker", package ="tantivy-stacker" }
query-grammar = { version= "0.20.0", path="./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version= "0.4", path="./bitpacker" }
common = { version= "0.5", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version= "0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
sketches-ddsketch = { version = "0.2.1", features = ["use_serde"] }
futures-util = { version = "0.3.28", optional = true }
fnv = "1.0.7"
[target.'cfg(windows)'.dependencies]
winapi = "0.3.9"
@@ -72,15 +73,15 @@ maplit = "1.0.2"
matches = "0.1.9"
pretty_assertions = "1.2.1"
proptest = "1.0.0"
criterion = "0.5"
test-log = "0.2.10"
env_logger = "0.10.0"
pprof = { git = "https://github.com/PSeitz/pprof-rs/", rev = "53af24b", features = ["flamegraph", "criterion"] } # temp fork that works with criterion 0.5
futures = "0.3.21"
paste = "1.0.11"
more-asserts = "0.3.1"
rand_distr = "0.4.3"
[target.'cfg(not(windows))'.dev-dependencies]
criterion = { version = "0.5", default-features = false }
[dev-dependencies.fail]
version = "0.5.0"
features = ["failpoints"]
@@ -112,11 +113,6 @@ unstable = [] # useful for benches.
quickwit = ["sstable", "futures-util"]
# Compares only the hash of a string when indexing data.
# Increases indexing speed, but may lead to extremely rare missing terms, when there's a hash collision.
# Uses 64bit ahash.
compare_hash_only = ["stacker/compare_hash_only"]
[workspace]
members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sstable", "tokenizer-api", "columnar"]
@@ -130,7 +126,7 @@ members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sst
[[test]]
name = "failpoints"
path = "tests/failpoints/mod.rs"
required-features = ["failpoints"]
required-features = ["fail/failpoints"]
[[bench]]
name = "analyzer"

View File

@@ -1,99 +1,14 @@
use criterion::{criterion_group, criterion_main, BatchSize, Bencher, Criterion, Throughput};
use tantivy::schema::{TantivyDocument, FAST, INDEXED, STORED, STRING, TEXT};
use tantivy::{tokenizer, Index, IndexWriter};
use criterion::{criterion_group, criterion_main, Criterion, Throughput};
use pprof::criterion::{Output, PProfProfiler};
use tantivy::schema::{FAST, INDEXED, STORED, STRING, TEXT};
use tantivy::Index;
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 +28,74 @@ 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 = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
}
}
})
});
group.bench_function("index-hdfs-with-commit", |b| {
let lines = get_lines(HDFS_LOGS);
b.iter(|| {
let index = Index::create_in_ram(schema.clone());
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
index_writer.commit().unwrap();
})
});
group.bench_function("index-hdfs-no-commit-with-docstore", |b| {
let lines = get_lines(HDFS_LOGS);
b.iter(|| {
let index = Index::create_in_ram(schema_with_store.clone());
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
})
});
group.bench_function("index-hdfs-with-commit-with-docstore", |b| {
let lines = get_lines(HDFS_LOGS);
b.iter(|| {
let index = Index::create_in_ram(schema_with_store.clone());
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let doc = schema.parse_document(doc_json).unwrap();
index_writer.add_document(doc).unwrap();
}
index_writer.commit().unwrap();
})
});
group.bench_function("index-hdfs-no-commit-json-without-docstore", |b| {
let lines = get_lines(HDFS_LOGS);
b.iter(|| {
let index = Index::create_in_ram(dynamic_schema.clone());
let json_field = dynamic_schema.get_field("json").unwrap();
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
for doc_json in &lines {
let json_val: serde_json::Map<String, serde_json::Value> =
serde_json::from_str(doc_json).unwrap();
let doc = tantivy::doc!(json_field=>json_val);
index_writer.add_document(doc).unwrap();
}
index_writer.commit().unwrap();
})
});
}
pub fn gh_index_benchmark(c: &mut Criterion) {
@@ -161,24 +104,38 @@ 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 = 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 = 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 +150,33 @@ 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 = 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 = 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 +187,12 @@ 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);

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-bitpacker"
version = "0.5.0"
version = "0.4.0"
edition = "2021"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
@@ -15,7 +15,7 @@ homepage = "https://github.com/quickwit-oss/tantivy"
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
[dependencies]
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker1x"] }
bitpacking = {version="0.8", default-features=false, features = ["bitpacker1x"]}
[dev-dependencies]
rand = "0.8"

View File

@@ -367,7 +367,7 @@ mod test {
let mut output: Vec<u32> = Vec::new();
for len in [0, 1, 2, 32, 33, 34, 64] {
for start_idx in 0u32..32u32 {
output.resize(len, 0);
output.resize(len as usize, 0);
bitunpacker.get_batch_u32s(start_idx, &buffer, &mut output);
for i in 0..len {
let expected = (start_idx + i as u32) & mask;

View File

@@ -64,8 +64,10 @@ fn mem_usage<T>(items: &Vec<T>) -> usize {
impl BlockedBitpacker {
pub fn new() -> Self {
let mut compressed_blocks = vec![];
compressed_blocks.resize(8, 0);
Self {
compressed_blocks: vec![0; 8],
compressed_blocks,
buffer: vec![],
offset_and_bits: vec![],
}

View File

@@ -32,7 +32,6 @@ postprocessors = [
{ pattern = 'Michael Kleen', replace = "mkleen"}, # replace with github user
{ pattern = 'Adrien Guillo', replace = "guilload"}, # replace with github user
{ pattern = 'François Massot', replace = "fmassot"}, # replace with github user
{ pattern = 'Naveen Aiathurai', replace = "naveenann"}, # replace with github user
{ pattern = '', replace = ""}, # replace with github user
]

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-columnar"
version = "0.2.0"
version = "0.1.0"
edition = "2021"
license = "MIT"
homepage = "https://github.com/quickwit-oss/tantivy"
@@ -9,13 +9,14 @@ 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"}
sstable = { version= "0.2", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.6", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.5", path = "../bitpacker/" }
stacker = { version= "0.1", path = "../stacker", package="tantivy-stacker"}
sstable = { version= "0.1", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.5", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.4", path = "../bitpacker/" }
serde = "1.0.152"
[dev-dependencies]

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

@@ -1,12 +1,9 @@
use std::cmp::Ordering;
use crate::{Column, DocId, RowId};
#[derive(Debug, Default, Clone)]
pub struct ColumnBlockAccessor<T> {
val_cache: Vec<T>,
docid_cache: Vec<DocId>,
missing_docids_cache: Vec<DocId>,
row_id_cache: Vec<RowId>,
}
@@ -23,20 +20,6 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
.values
.get_vals(&self.row_id_cache, &mut self.val_cache);
}
#[inline]
pub fn fetch_block_with_missing(&mut self, docs: &[u32], accessor: &Column<T>, missing: T) {
self.fetch_block(docs, accessor);
// We can compare docid_cache with docs to find missing docs
if docs.len() != self.docid_cache.len() || accessor.index.is_multivalue() {
self.missing_docids_cache.clear();
find_missing_docs(docs, &self.docid_cache, |doc| {
self.missing_docids_cache.push(doc);
self.val_cache.push(missing);
});
self.docid_cache
.extend_from_slice(&self.missing_docids_cache);
}
}
#[inline]
pub fn iter_vals(&self) -> impl Iterator<Item = T> + '_ {
@@ -51,82 +34,3 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
.zip(self.val_cache.iter().cloned())
}
}
/// Given two sorted lists of docids `docs` and `hits`, hits is a subset of `docs`.
/// Return all docs that are not in `hits`.
fn find_missing_docs<F>(docs: &[u32], hits: &[u32], mut callback: F)
where F: FnMut(u32) {
let mut docs_iter = docs.iter();
let mut hits_iter = hits.iter();
let mut doc = docs_iter.next();
let mut hit = hits_iter.next();
while let (Some(&current_doc), Some(&current_hit)) = (doc, hit) {
match current_doc.cmp(&current_hit) {
Ordering::Less => {
callback(current_doc);
doc = docs_iter.next();
}
Ordering::Equal => {
doc = docs_iter.next();
hit = hits_iter.next();
}
Ordering::Greater => {
hit = hits_iter.next();
}
}
}
while let Some(&current_doc) = doc {
callback(current_doc);
doc = docs_iter.next();
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_find_missing_docs() {
let docs: Vec<u32> = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
let mut missing_docs: Vec<u32> = Vec::new();
find_missing_docs(&docs, &hits, |missing_doc| {
missing_docs.push(missing_doc);
});
assert_eq!(missing_docs, vec![1, 3, 5, 7, 9]);
}
#[test]
fn test_find_missing_docs_empty() {
let docs: Vec<u32> = Vec::new();
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
let mut missing_docs: Vec<u32> = Vec::new();
find_missing_docs(&docs, &hits, |missing_doc| {
missing_docs.push(missing_doc);
});
assert_eq!(missing_docs, vec![]);
}
#[test]
fn test_find_missing_docs_all_missing() {
let docs: Vec<u32> = vec![1, 2, 3, 4, 5];
let hits: Vec<u32> = Vec::new();
let mut missing_docs: Vec<u32> = Vec::new();
find_missing_docs(&docs, &hits, |missing_doc| {
missing_docs.push(missing_doc);
});
assert_eq!(missing_docs, vec![1, 2, 3, 4, 5]);
}
}

View File

@@ -30,13 +30,6 @@ impl fmt::Debug for BytesColumn {
}
impl BytesColumn {
pub fn empty(num_docs: u32) -> BytesColumn {
BytesColumn {
dictionary: Arc::new(Dictionary::empty()),
term_ord_column: Column::build_empty_column(num_docs),
}
}
/// Fills the given `output` buffer with the term associated to the ordinal `ord`.
///
/// Returns `false` if the term does not exist (e.g. `term_ord` is greater or equal to the
@@ -84,7 +77,7 @@ impl From<StrColumn> for BytesColumn {
}
impl StrColumn {
pub fn wrap(bytes_column: BytesColumn) -> StrColumn {
pub(crate) fn wrap(bytes_column: BytesColumn) -> StrColumn {
StrColumn(bytes_column)
}

View File

@@ -130,7 +130,7 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
.select_batch_in_place(selected_docid_range.start, doc_ids);
}
/// Fills the output vector with the (possibly multiple values that are associated_with
/// Fils the output vector with the (possibly multiple values that are associated_with
/// `row_id`.
///
/// This method clears the `output` vector.

View File

@@ -1,8 +1,3 @@
//! # `column_index`
//!
//! `column_index` provides rank and select operations to associate positions when not all
//! documents have exactly one element.
mod merge;
mod multivalued_index;
mod optional_index;
@@ -42,14 +37,10 @@ impl From<MultiValueIndex> for ColumnIndex {
}
impl ColumnIndex {
#[inline]
pub fn is_multivalue(&self) -> bool {
matches!(self, ColumnIndex::Multivalued(_))
}
/// Returns the cardinality of the column index.
///
/// By convention, if the column contains no docs, we consider that it is
/// full.
// Returns the cardinality of the column index.
//
// By convention, if the column contains no docs, we consider that it is
// full.
#[inline]
pub fn get_cardinality(&self) -> Cardinality {
match self {

View File

@@ -215,12 +215,12 @@ mod bench {
let vals: Vec<RowId> = (0..TOTAL_NUM_VALUES)
.map(|_| rng.gen_bool(fill_ratio))
.enumerate()
.filter(|(_pos, val)| *val)
.filter(|(pos, val)| *val)
.map(|(pos, _)| pos as RowId)
.collect();
serialize_optional_index(&&vals[..], TOTAL_NUM_VALUES, &mut out).unwrap();
open_optional_index(OwnedBytes::new(out)).unwrap()
let codec = open_optional_index(OwnedBytes::new(out)).unwrap();
codec
}
fn random_range_iterator(
@@ -242,7 +242,7 @@ mod bench {
}
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
let ratio = percent / 100.0;
let ratio = percent as f32 / 100.0;
let step_size = (1f32 / ratio) as u32;
let deviation = step_size - 1;
random_range_iterator(0, num_values, step_size, deviation)

View File

@@ -30,7 +30,6 @@ impl<'a> SerializableColumnIndex<'a> {
}
}
/// Serialize a column index.
pub fn serialize_column_index(
column_index: SerializableColumnIndex,
output: &mut impl Write,
@@ -52,7 +51,6 @@ pub fn serialize_column_index(
Ok(column_index_num_bytes)
}
/// Open a serialized column index.
pub fn open_column_index(mut bytes: OwnedBytes) -> io::Result<ColumnIndex> {
if bytes.is_empty() {
return Err(io::Error::new(

View File

@@ -38,6 +38,6 @@ impl Ord for BlankRange {
}
impl PartialOrd for BlankRange {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
Some(self.blank_size().cmp(&other.blank_size()))
}
}

View File

@@ -2,7 +2,7 @@ mod merge_dict_column;
mod merge_mapping;
mod term_merger;
use std::collections::{BTreeMap, HashSet};
use std::collections::{BTreeMap, HashMap, HashSet};
use std::io;
use std::net::Ipv6Addr;
use std::sync::Arc;
@@ -18,8 +18,7 @@ use crate::columnar::writer::CompatibleNumericalTypes;
use crate::columnar::ColumnarReader;
use crate::dynamic_column::DynamicColumn;
use crate::{
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, DynamicColumnHandle, NumericalType,
NumericalValue,
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, NumericalType, NumericalValue,
};
/// Column types are grouped into different categories.
@@ -29,16 +28,14 @@ use crate::{
/// In practise, today, only Numerical colummns are coerced into one type today.
///
/// See also [README.md].
///
/// The ordering has to match the ordering of the variants in [ColumnType].
#[derive(Copy, Clone, Eq, PartialOrd, Ord, PartialEq, Hash, Debug)]
#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug)]
pub(crate) enum ColumnTypeCategory {
Numerical,
Bytes,
Str,
Bool,
IpAddr,
Str,
Numerical,
DateTime,
Bytes,
IpAddr,
}
impl From<ColumnType> for ColumnTypeCategory {
@@ -86,20 +83,9 @@ pub fn merge_columnar(
.iter()
.map(|reader| reader.num_rows())
.collect::<Vec<u32>>();
let columns_to_merge =
group_columns_for_merge(columnar_readers, required_columns, &merge_row_order)?;
for res in columns_to_merge {
let ((column_name, _column_type_category), grouped_columns) = res;
let grouped_columns = grouped_columns.open(&merge_row_order)?;
if grouped_columns.is_empty() {
continue;
}
let column_type = grouped_columns.column_type_after_merge();
let mut columns = grouped_columns.columns;
coerce_columns(column_type, &mut columns)?;
for ((column_name, column_type), columns) in columns_to_merge {
let mut column_serializer =
serializer.start_serialize_column(column_name.as_bytes(), column_type);
merge_column(
@@ -111,7 +97,6 @@ pub fn merge_columnar(
)?;
column_serializer.finalize()?;
}
serializer.finalize(merge_row_order.num_rows())?;
Ok(())
}
@@ -225,12 +210,40 @@ fn merge_column(
struct GroupedColumns {
required_column_type: Option<ColumnType>,
columns: Vec<Option<DynamicColumn>>,
column_category: ColumnTypeCategory,
}
impl GroupedColumns {
/// Check is column group can be skipped during serialization.
fn is_empty(&self) -> bool {
self.required_column_type.is_none() && self.columns.iter().all(Option::is_none)
fn for_category(column_category: ColumnTypeCategory, num_columnars: usize) -> Self {
GroupedColumns {
required_column_type: None,
columns: vec![None; num_columnars],
column_category,
}
}
/// Set the dynamic column for a given columnar.
fn set_column(&mut self, columnar_id: usize, column: DynamicColumn) {
self.columns[columnar_id] = Some(column);
}
/// Force the existence of a column, as well as its type.
fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
if let Some(existing_required_type) = self.required_column_type {
if existing_required_type == required_type {
// This was just a duplicate in the `required_columns`.
// Nothing to do.
return Ok(());
} else {
return Err(io::Error::new(
io::ErrorKind::InvalidInput,
"Required column conflicts with another required column of the same type \
category.",
));
}
}
self.required_column_type = Some(required_type);
Ok(())
}
/// Returns the column type after merge.
@@ -252,76 +265,11 @@ impl GroupedColumns {
}
// At the moment, only the numerical categorical column type has more than one possible
// column type.
assert!(self
.columns
.iter()
.flatten()
.all(|el| ColumnTypeCategory::from(el.column_type()) == ColumnTypeCategory::Numerical));
assert_eq!(self.column_category, ColumnTypeCategory::Numerical);
merged_numerical_columns_type(self.columns.iter().flatten()).into()
}
}
struct GroupedColumnsHandle {
required_column_type: Option<ColumnType>,
columns: Vec<Option<DynamicColumnHandle>>,
}
impl GroupedColumnsHandle {
fn new(num_columnars: usize) -> Self {
GroupedColumnsHandle {
required_column_type: None,
columns: vec![None; num_columnars],
}
}
fn open(self, merge_row_order: &MergeRowOrder) -> io::Result<GroupedColumns> {
let mut columns: Vec<Option<DynamicColumn>> = Vec::new();
for (columnar_id, column) in self.columns.iter().enumerate() {
if let Some(column) = column {
let column = column.open()?;
// We skip columns that end up with 0 documents.
// That way, we make sure they don't end up influencing the merge type or
// creating empty columns.
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
columns.push(None);
} else {
columns.push(Some(column));
}
} else {
columns.push(None);
}
}
Ok(GroupedColumns {
required_column_type: self.required_column_type,
columns,
})
}
/// Set the dynamic column for a given columnar.
fn set_column(&mut self, columnar_id: usize, column: DynamicColumnHandle) {
self.columns[columnar_id] = Some(column);
}
/// Force the existence of a column, as well as its type.
fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
if let Some(existing_required_type) = self.required_column_type {
if existing_required_type == required_type {
// This was just a duplicate in the `required_columns`.
// Nothing to do.
return Ok(());
} else {
return Err(io::Error::new(
io::ErrorKind::InvalidInput,
"Required column conflicts with another required column of the same type \
category.",
));
}
}
self.required_column_type = Some(required_type);
Ok(())
}
}
/// Returns the type of the merged numerical column.
///
/// This function picks the first numerical type out of i64, u64, f64 (order matters
@@ -345,7 +293,7 @@ fn merged_numerical_columns_type<'a>(
fn is_empty_after_merge(
merge_row_order: &MergeRowOrder,
column: &DynamicColumn,
columnar_ord: usize,
columnar_id: usize,
) -> bool {
if column.num_values() == 0u32 {
// It was empty before the merge.
@@ -357,7 +305,7 @@ fn is_empty_after_merge(
false
}
MergeRowOrder::Shuffled(shuffled) => {
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_ord] {
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_id] {
let column_index = column.column_index();
match column_index {
ColumnIndex::Empty { .. } => true,
@@ -400,34 +348,56 @@ fn is_empty_after_merge(
}
}
/// Iterates over the columns of the columnar readers, grouped by column name.
/// Key functionality is that `open` of the Columns is done lazy per group.
fn group_columns_for_merge<'a>(
columnar_readers: &'a [&'a ColumnarReader],
required_columns: &'a [(String, ColumnType)],
_merge_row_order: &'a MergeRowOrder,
) -> io::Result<BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle>> {
let mut columns: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> = BTreeMap::new();
#[allow(clippy::type_complexity)]
fn group_columns_for_merge(
columnar_readers: &[&ColumnarReader],
required_columns: &[(String, ColumnType)],
merge_row_order: &MergeRowOrder,
) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
// Each column name may have multiple types of column associated.
// For merging we are interested in the same column type category since they can be merged.
let mut columns_grouped: HashMap<(String, ColumnTypeCategory), GroupedColumns> = HashMap::new();
for &(ref column_name, column_type) in required_columns {
columns
columns_grouped
.entry((column_name.clone(), column_type.into()))
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
.or_insert_with(|| {
GroupedColumns::for_category(column_type.into(), columnar_readers.len())
})
.require_type(column_type)?;
}
for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
let column_name_and_handle = columnar_reader.iter_columns()?;
let column_name_and_handle = columnar_reader.list_columns()?;
// We skip columns that end up with 0 documents.
// That way, we make sure they don't end up influencing the merge type or
// creating empty columns.
for (column_name, handle) in column_name_and_handle {
let column_category: ColumnTypeCategory = handle.column_type().into();
columns
let column = handle.open()?;
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
continue;
}
columns_grouped
.entry((column_name, column_category))
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
.set_column(columnar_id, handle);
.or_insert_with(|| {
GroupedColumns::for_category(column_category, columnar_readers.len())
})
.set_column(columnar_id, column);
}
}
Ok(columns)
let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
Default::default();
for ((column_name, _), mut grouped_columns) in columns_grouped {
let column_type = grouped_columns.column_type_after_merge();
coerce_columns(column_type, &mut grouped_columns.columns)?;
merge_columns.insert((column_name, column_type), grouped_columns.columns);
}
Ok(merge_columns)
}
fn coerce_columns(

View File

@@ -1,5 +1,3 @@
use std::collections::BTreeMap;
use itertools::Itertools;
use super::*;
@@ -29,10 +27,22 @@ fn test_column_coercion_to_u64() {
let columnar2 = make_columnar("numbers", &[u64::MAX]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
}
#[test]
fn test_column_no_coercion_if_all_the_same() {
let columnar1 = make_columnar("numbers", &[1u64]);
let columnar2 = make_columnar("numbers", &[2u64]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
}
#[test]
@@ -41,24 +51,24 @@ fn test_column_coercion_to_i64() {
let columnar2 = make_columnar("numbers", &[2u64]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
}
//#[test]
// fn test_impossible_coercion_returns_an_error() {
// let columnar1 = make_columnar("numbers", &[u64::MAX]);
// let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
// let group_error = group_columns_for_merge_iter(
//&[&columnar1],
//&[("numbers".to_string(), ColumnType::I64)],
//&merge_order,
//)
//.unwrap_err();
// assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
//}
#[test]
fn test_impossible_coercion_returns_an_error() {
let columnar1 = make_columnar("numbers", &[u64::MAX]);
let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
let group_error = group_columns_for_merge(
&[&columnar1],
&[("numbers".to_string(), ColumnType::I64)],
&merge_order,
)
.unwrap_err();
assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
}
#[test]
fn test_group_columns_with_required_column() {
@@ -66,7 +76,7 @@ fn test_group_columns_with_required_column() {
let columnar2 = make_columnar("numbers", &[2u64]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(
&[&columnar1, &columnar2],
&[("numbers".to_string(), ColumnType::U64)],
@@ -74,7 +84,7 @@ fn test_group_columns_with_required_column() {
)
.unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
}
#[test]
@@ -83,17 +93,17 @@ fn test_group_columns_required_column_with_no_existing_columns() {
let columnar2 = make_columnar("numbers", &[2u64]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<_, _> = group_columns_for_merge(
columnars,
&[("required_col".to_string(), ColumnType::Str)],
&merge_order,
)
.unwrap();
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(
columnars,
&[("required_col".to_string(), ColumnType::Str)],
&merge_order,
)
.unwrap();
assert_eq!(column_map.len(), 2);
let columns = &column_map
.get(&("required_col".to_string(), ColumnTypeCategory::Str))
.unwrap()
.columns;
let columns = column_map
.get(&("required_col".to_string(), ColumnType::Str))
.unwrap();
assert_eq!(columns.len(), 2);
assert!(columns[0].is_none());
assert!(columns[1].is_none());
@@ -105,7 +115,7 @@ fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_ru
let columnar2 = make_columnar("numbers", &[2i64]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(
columnars,
&[("numbers".to_string(), ColumnType::U64)],
@@ -113,7 +123,7 @@ fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_ru
)
.unwrap();
assert_eq!(column_map.len(), 1);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
}
#[test]
@@ -122,23 +132,21 @@ fn test_missing_column() {
let columnar2 = make_columnar("numbers2", &[2u64]);
let columnars = &[&columnar1, &columnar2];
let merge_order = StackMergeOrder::stack(columnars).into();
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
assert_eq!(column_map.len(), 2);
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
{
let columns = &column_map
.get(&("numbers".to_string(), ColumnTypeCategory::Numerical))
.unwrap()
.columns;
let columns = column_map
.get(&("numbers".to_string(), ColumnType::I64))
.unwrap();
assert!(columns[0].is_some());
assert!(columns[1].is_none());
}
{
let columns = &column_map
.get(&("numbers2".to_string(), ColumnTypeCategory::Numerical))
.unwrap()
.columns;
let columns = column_map
.get(&("numbers2".to_string(), ColumnType::U64))
.unwrap();
assert!(columns[0].is_none());
assert!(columns[1].is_some());
}

View File

@@ -102,41 +102,30 @@ impl ColumnarReader {
pub fn num_rows(&self) -> RowId {
self.num_rows
}
// Iterate over the columns in a sorted way
pub fn iter_columns(
&self,
) -> io::Result<impl Iterator<Item = (String, DynamicColumnHandle)> + '_> {
let mut stream = self.column_dictionary.stream()?;
Ok(std::iter::from_fn(move || {
if stream.advance() {
let key_bytes: &[u8] = stream.key();
let column_code: u8 = key_bytes.last().cloned().unwrap();
// TODO Error Handling. The API gets quite ugly when returning the error here, so
// instead we could just check the first N columns upfront.
let column_type: ColumnType = ColumnType::try_from_code(column_code)
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))
.unwrap();
let range = stream.value().clone();
let column_name =
// The last two bytes are respectively the 0u8 separator and the column_type.
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
let file_slice = self
.column_data
.slice(range.start as usize..range.end as usize);
let column_handle = DynamicColumnHandle {
file_slice,
column_type,
};
Some((column_name, column_handle))
} else {
None
}
}))
}
// TODO Add unit tests
pub fn list_columns(&self) -> io::Result<Vec<(String, DynamicColumnHandle)>> {
Ok(self.iter_columns()?.collect())
let mut stream = self.column_dictionary.stream()?;
let mut results = Vec::new();
while stream.advance() {
let key_bytes: &[u8] = stream.key();
let column_code: u8 = key_bytes.last().cloned().unwrap();
let column_type: ColumnType = ColumnType::try_from_code(column_code)
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
let range = stream.value().clone();
let column_name =
// The last two bytes are respectively the 0u8 separator and the column_type.
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
let file_slice = self
.column_data
.slice(range.start as usize..range.end as usize);
let column_handle = DynamicColumnHandle {
file_slice,
column_type,
};
results.push((column_name, column_handle));
}
Ok(results)
}
fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {

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

@@ -79,6 +79,7 @@ fn mutate_or_create_column<V, TMutator>(
impl ColumnarWriter {
pub fn mem_usage(&self) -> usize {
// TODO add dictionary builders.
self.arena.mem_usage()
+ self.numerical_field_hash_map.mem_usage()
+ self.bool_field_hash_map.mem_usage()
@@ -86,11 +87,6 @@ impl ColumnarWriter {
+ self.str_field_hash_map.mem_usage()
+ self.ip_addr_field_hash_map.mem_usage()
+ self.datetime_field_hash_map.mem_usage()
+ self
.dictionaries
.iter()
.map(|dict| dict.mem_usage())
.sum::<usize>()
}
/// Returns the list of doc ids from 0..num_docs sorted by the `sort_field`
@@ -105,10 +101,6 @@ impl ColumnarWriter {
let Some(numerical_col_writer) = self
.numerical_field_hash_map
.get::<NumericalColumnWriter>(sort_field.as_bytes())
.or_else(|| {
self.datetime_field_hash_map
.get::<NumericalColumnWriter>(sort_field.as_bytes())
})
else {
return Vec::new();
};
@@ -338,7 +330,7 @@ impl ColumnarWriter {
let mut columns: Vec<(&[u8], ColumnType, Addr)> = self
.numerical_field_hash_map
.iter()
.map(|(column_name, addr)| {
.map(|(column_name, addr, _)| {
let numerical_column_writer: NumericalColumnWriter =
self.numerical_field_hash_map.read(addr);
let column_type = numerical_column_writer.numerical_type().into();
@@ -348,27 +340,27 @@ impl ColumnarWriter {
columns.extend(
self.bytes_field_hash_map
.iter()
.map(|(term, addr)| (term, ColumnType::Bytes, addr)),
.map(|(term, addr, _)| (term, ColumnType::Bytes, addr)),
);
columns.extend(
self.str_field_hash_map
.iter()
.map(|(column_name, addr)| (column_name, ColumnType::Str, addr)),
.map(|(column_name, addr, _)| (column_name, ColumnType::Str, addr)),
);
columns.extend(
self.bool_field_hash_map
.iter()
.map(|(column_name, addr)| (column_name, ColumnType::Bool, addr)),
.map(|(column_name, addr, _)| (column_name, ColumnType::Bool, addr)),
);
columns.extend(
self.ip_addr_field_hash_map
.iter()
.map(|(column_name, addr)| (column_name, ColumnType::IpAddr, addr)),
.map(|(column_name, addr, _)| (column_name, ColumnType::IpAddr, addr)),
);
columns.extend(
self.datetime_field_hash_map
.iter()
.map(|(column_name, addr)| (column_name, ColumnType::DateTime, addr)),
.map(|(column_name, addr, _)| (column_name, ColumnType::DateTime, addr)),
);
columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
@@ -437,7 +429,6 @@ impl ColumnarWriter {
&mut symbol_byte_buffer,
),
buffers,
&self.arena,
&mut column_serializer,
)?;
column_serializer.finalize()?;
@@ -491,7 +482,6 @@ 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 +489,6 @@ 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 +497,7 @@ 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 +31,26 @@ pub struct OrderedId(pub u32);
/// mapping.
#[derive(Default)]
pub(crate) struct DictionaryBuilder {
dict: SharedArenaHashMap,
dict: FnvHashMap<Vec<u8>, UnorderedId>,
}
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);
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()];
@@ -75,10 +63,6 @@ impl DictionaryBuilder {
sstable_builder.finish()?;
Ok(TermIdMapping { unordered_to_ord })
}
pub(crate) fn mem_usage(&self) -> usize {
self.dict.mem_usage()
}
}
#[cfg(test)]
@@ -87,13 +71,12 @@ 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

@@ -228,7 +228,7 @@ static_dynamic_conversions!(StrColumn, Str);
static_dynamic_conversions!(BytesColumn, Bytes);
static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
#[derive(Clone, Debug)]
#[derive(Clone)]
pub struct DynamicColumnHandle {
pub(crate) file_slice: FileSlice,
pub(crate) column_type: ColumnType,
@@ -247,7 +247,7 @@ impl DynamicColumnHandle {
}
/// Returns the `u64` fast field reader reader associated with `fields` of types
/// Str, u64, i64, f64, bool, or datetime.
/// Str, u64, i64, f64, or datetime.
///
/// If not, the fastfield reader will returns the u64-value associated with the original
/// FastValue.
@@ -258,12 +258,9 @@ impl DynamicColumnHandle {
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
Ok(Some(column.term_ord_column))
}
ColumnType::Bool => Ok(None),
ColumnType::IpAddr => Ok(None),
ColumnType::Bool
| ColumnType::I64
| ColumnType::U64
| ColumnType::F64
| ColumnType::DateTime => {
ColumnType::I64 | ColumnType::U64 | ColumnType::F64 | ColumnType::DateTime => {
let column = crate::column::open_column_u64::<u64>(column_bytes)?;
Ok(Some(column))
}

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)]
@@ -31,7 +12,7 @@ use std::io;
mod block_accessor;
mod column;
pub mod column_index;
mod column_index;
pub mod column_values;
mod columnar;
mod dictionary;

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(), 87);
}
#[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(), 87);
}
#[test]
@@ -330,9 +330,9 @@ fn bytes_strategy() -> impl Strategy<Value = &'static [u8]> {
// A random column value
fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
prop_oneof![
10 => string_strategy().prop_map(ColumnValue::Str),
1 => bytes_strategy().prop_map(ColumnValue::Bytes),
40 => num_strategy().prop_map(ColumnValue::Numerical),
10 => string_strategy().prop_map(|s| ColumnValue::Str(s)),
1 => bytes_strategy().prop_map(|b| ColumnValue::Bytes(b)),
40 => num_strategy().prop_map(|n| ColumnValue::Numerical(n)),
1 => (1u16..3u16).prop_map(|ip_addr_byte| ColumnValue::IpAddr(Ipv6Addr::new(
127,
0,
@@ -343,7 +343,7 @@ fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
0,
ip_addr_byte
))),
1 => any::<bool>().prop_map(ColumnValue::Bool),
1 => any::<bool>().prop_map(|b| ColumnValue::Bool(b)),
1 => (0_679_723_993i64..1_679_723_995i64)
.prop_map(|val| { ColumnValue::DateTime(DateTime::from_timestamp_secs(val)) })
]
@@ -419,8 +419,8 @@ fn build_columnar_with_mapping(
columnar_writer
.serialize(num_docs, old_to_new_row_ids_opt, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
let columnar_reader = ColumnarReader::open(buffer).unwrap();
columnar_reader
}
fn build_columnar(docs: &[Vec<(&'static str, ColumnValue)>]) -> ColumnarReader {
@@ -746,7 +746,7 @@ proptest! {
let stack_merge_order = StackMergeOrder::stack(&columnar_readers_arr[..]).into();
crate::merge_columnar(&columnar_readers_arr[..], &[], stack_merge_order, &mut output).unwrap();
let merged_columnar = ColumnarReader::open(output).unwrap();
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().flatten().cloned().collect();
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().cloned().flatten().collect();
let expected_merged_columnar = build_columnar(&concat_rows[..]);
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
}
@@ -772,7 +772,7 @@ fn test_columnar_merging_empty_columnar() {
.unwrap();
let merged_columnar = ColumnarReader::open(output).unwrap();
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
columnar_docs.iter().flatten().cloned().collect();
columnar_docs.iter().cloned().flatten().collect();
let expected_merged_columnar = build_columnar(&concat_rows[..]);
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
}
@@ -809,7 +809,7 @@ fn test_columnar_merging_number_columns() {
.unwrap();
let merged_columnar = ColumnarReader::open(output).unwrap();
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
columnar_docs.iter().flatten().cloned().collect();
columnar_docs.iter().cloned().flatten().collect();
let expected_merged_columnar = build_columnar(&concat_rows[..]);
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
}

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-common"
version = "0.6.0"
version = "0.5.0"
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
license = "MIT"
edition = "2021"
@@ -14,7 +14,7 @@ repository = "https://github.com/quickwit-oss/tantivy"
[dependencies]
byteorder = "1.4.3"
ownedbytes = { version= "0.6", path="../ownedbytes" }
ownedbytes = { version= "0.5", path="../ownedbytes" }
async-trait = "0.1"
time = { version = "0.3.10", features = ["serde-well-known"] }
serde = { version = "1.0.136", features = ["derive"] }

View File

@@ -1,14 +1,11 @@
#![allow(deprecated)]
use std::fmt;
use std::io::{Read, Write};
use serde::{Deserialize, Serialize};
use time::format_description::well_known::Rfc3339;
use time::{OffsetDateTime, PrimitiveDateTime, UtcOffset};
use crate::BinarySerializable;
/// Precision with which datetimes are truncated when stored in fast fields. This setting is only
/// relevant for fast fields. In the docstore, datetimes are always saved with nanosecond precision.
#[derive(
@@ -167,15 +164,3 @@ impl fmt::Debug for DateTime {
f.write_str(&utc_rfc3339)
}
}
impl BinarySerializable for DateTime {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
let timestamp_micros = self.into_timestamp_micros();
<i64 as BinarySerializable>::serialize(&timestamp_micros, writer)
}
fn deserialize<R: Read>(reader: &mut R) -> std::io::Result<Self> {
let timestamp_micros = <i64 as BinarySerializable>::deserialize(reader)?;
Ok(Self::from_timestamp_micros(timestamp_micros))
}
}

View File

@@ -1,4 +1,3 @@
use std::fs::File;
use std::ops::{Deref, Range, RangeBounds};
use std::sync::Arc;
use std::{fmt, io};
@@ -33,62 +32,6 @@ pub trait FileHandle: 'static + Send + Sync + HasLen + fmt::Debug {
}
}
#[derive(Debug)]
/// A File with it's length included.
pub struct WrapFile {
file: File,
len: usize,
}
impl WrapFile {
/// Creates a new WrapFile and stores its length.
pub fn new(file: File) -> io::Result<Self> {
let len = file.metadata()?.len() as usize;
Ok(WrapFile { file, len })
}
}
#[async_trait]
impl FileHandle for WrapFile {
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
let file_len = self.len();
// Calculate the actual range to read, ensuring it stays within file boundaries
let start = range.start;
let end = range.end.min(file_len);
// Ensure the start is before the end of the range
if start >= end {
return Err(io::Error::new(io::ErrorKind::InvalidInput, "Invalid range"));
}
let mut buffer = vec![0; end - start];
#[cfg(unix)]
{
use std::os::unix::prelude::FileExt;
self.file.read_exact_at(&mut buffer, start as u64)?;
}
#[cfg(not(unix))]
{
use std::io::{Read, Seek};
let mut file = self.file.try_clone()?; // Clone the file to read from it separately
// Seek to the start position in the file
file.seek(io::SeekFrom::Start(start as u64))?;
// Read the data into the buffer
file.read_exact(&mut buffer)?;
}
Ok(OwnedBytes::new(buffer))
}
// todo implement async
}
impl HasLen for WrapFile {
fn len(&self) -> usize {
self.len
}
}
#[async_trait]
impl FileHandle for &'static [u8] {
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
@@ -124,30 +67,6 @@ impl fmt::Debug for FileSlice {
}
}
impl FileSlice {
pub fn stream_file_chunks(&self) -> impl Iterator<Item = io::Result<OwnedBytes>> + '_ {
let len = self.range.end;
let mut start = self.range.start;
std::iter::from_fn(move || {
/// Returns chunks of 1MB of data from the FileHandle.
const CHUNK_SIZE: usize = 1024 * 1024; // 1MB
if start < len {
let end = (start + CHUNK_SIZE).min(len);
let range = start..end;
let chunk = self.data.read_bytes(range);
start += CHUNK_SIZE;
match chunk {
Ok(chunk) => Some(Ok(chunk)),
Err(e) => Some(Err(e)),
}
} else {
None
}
})
}
}
/// Takes a range, a `RangeBounds` object, and returns
/// a `Range` that corresponds to the relative application of the
/// `RangeBounds` object to the original `Range`.

View File

@@ -27,15 +27,15 @@ pub trait GroupByIteratorExtended: Iterator {
where
Self: Sized,
F: FnMut(&Self::Item) -> K,
K: PartialEq + Clone,
Self::Item: Clone,
K: PartialEq + Copy,
Self::Item: Copy,
{
GroupByIterator::new(self, key)
}
}
impl<I: Iterator> GroupByIteratorExtended for I {}
pub struct GroupByIterator<I, F, K: Clone>
pub struct GroupByIterator<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
@@ -50,7 +50,7 @@ where
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
}
struct GroupByShared<I, F, K: Clone>
struct GroupByShared<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
@@ -63,7 +63,7 @@ impl<I, F, K> GroupByIterator<I, F, K>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
K: Clone,
K: Copy,
{
fn new(inner: I, group_by_fn: F) -> Self {
let inner = GroupByShared {
@@ -80,28 +80,28 @@ where
impl<I, F, K> Iterator for GroupByIterator<I, F, K>
where
I: Iterator,
I::Item: Clone,
I::Item: Copy,
F: FnMut(&I::Item) -> K,
K: Clone,
K: Copy,
{
type Item = (K, GroupIterator<I, F, K>);
fn next(&mut self) -> Option<Self::Item> {
let mut inner = self.inner.borrow_mut();
let value = inner.iter.peek()?.clone();
let value = *inner.iter.peek()?;
let key = (inner.group_by_fn)(&value);
let inner = self.inner.clone();
let group_iter = GroupIterator {
inner,
group_key: key.clone(),
group_key: key,
};
Some((key, group_iter))
}
}
pub struct GroupIterator<I, F, K: Clone>
pub struct GroupIterator<I, F, K: Copy>
where
I: Iterator,
F: FnMut(&I::Item) -> K,
@@ -110,10 +110,10 @@ where
group_key: K,
}
impl<I, F, K: PartialEq + Clone> Iterator for GroupIterator<I, F, K>
impl<I, F, K: PartialEq + Copy> Iterator for GroupIterator<I, F, K>
where
I: Iterator,
I::Item: Clone,
I::Item: Copy,
F: FnMut(&I::Item) -> K,
{
type Item = I::Item;
@@ -121,7 +121,7 @@ where
fn next(&mut self) -> Option<Self::Item> {
let mut inner = self.inner.borrow_mut();
// peek if next value is in group
let peek_val = inner.iter.peek()?.clone();
let peek_val = *inner.iter.peek()?;
if (inner.group_by_fn)(&peek_val) == self.group_key {
inner.iter.next()
} else {

View File

@@ -1,112 +0,0 @@
use crate::replace_in_place;
/// Separates the different segments of a json path.
pub const JSON_PATH_SEGMENT_SEP: u8 = 1u8;
pub const JSON_PATH_SEGMENT_SEP_STR: &str =
unsafe { std::str::from_utf8_unchecked(&[JSON_PATH_SEGMENT_SEP]) };
/// Create a new JsonPathWriter, that creates flattened json paths for tantivy.
#[derive(Clone, Debug, Default)]
pub struct JsonPathWriter {
path: String,
indices: Vec<usize>,
expand_dots: bool,
}
impl JsonPathWriter {
pub fn new() -> Self {
JsonPathWriter {
path: String::new(),
indices: Vec::new(),
expand_dots: false,
}
}
/// When expand_dots is enabled, json object like
/// `{"k8s.node.id": 5}` is processed as if it was
/// `{"k8s": {"node": {"id": 5}}}`.
/// This option has the merit of allowing users to
/// write queries like `k8s.node.id:5`.
/// On the other, enabling that feature can lead to
/// ambiguity.
#[inline]
pub fn set_expand_dots(&mut self, expand_dots: bool) {
self.expand_dots = expand_dots;
}
/// Push a new segment to the path.
#[inline]
pub fn push(&mut self, segment: &str) {
let len_path = self.path.len();
self.indices.push(len_path);
if !self.path.is_empty() {
self.path.push_str(JSON_PATH_SEGMENT_SEP_STR);
}
self.path.push_str(segment);
if self.expand_dots {
// This might include the separation byte, which is ok because it is not a dot.
let appended_segment = &mut self.path[len_path..];
// The unsafe below is safe as long as b'.' and JSON_PATH_SEGMENT_SEP are
// valid single byte ut8 strings.
// By utf-8 design, they cannot be part of another codepoint.
unsafe {
replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, appended_segment.as_bytes_mut())
};
}
}
/// Remove the last segment. Does nothing if the path is empty.
#[inline]
pub fn pop(&mut self) {
if let Some(last_idx) = self.indices.pop() {
self.path.truncate(last_idx);
}
}
/// Clear the path.
#[inline]
pub fn clear(&mut self) {
self.path.clear();
self.indices.clear();
}
/// Get the current path.
#[inline]
pub fn as_str(&self) -> &str {
&self.path
}
}
impl From<JsonPathWriter> for String {
#[inline]
fn from(value: JsonPathWriter) -> Self {
value.path
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn json_path_writer_test() {
let mut writer = JsonPathWriter::new();
writer.push("root");
assert_eq!(writer.as_str(), "root");
writer.push("child");
assert_eq!(writer.as_str(), "root\u{1}child");
writer.pop();
assert_eq!(writer.as_str(), "root");
writer.push("k8s.node.id");
assert_eq!(writer.as_str(), "root\u{1}k8s.node.id");
writer.set_expand_dots(true);
writer.pop();
writer.push("k8s.node.id");
assert_eq!(writer.as_str(), "root\u{1}k8s\u{1}node\u{1}id");
}
}

View File

@@ -9,7 +9,6 @@ mod byte_count;
mod datetime;
pub mod file_slice;
mod group_by;
mod json_path_writer;
mod serialize;
mod vint;
mod writer;
@@ -19,7 +18,6 @@ pub use byte_count::ByteCount;
pub use datetime::DatePrecision;
pub use datetime::{DateTime, DateTimePrecision};
pub use group_by::GroupByIteratorExtended;
pub use json_path_writer::JsonPathWriter;
pub use ownedbytes::{OwnedBytes, StableDeref};
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
pub use vint::{
@@ -118,7 +116,6 @@ pub fn u64_to_f64(val: u64) -> f64 {
///
/// This function assumes that the needle is rarely contained in the bytes string
/// and offers a fast path if the needle is not present.
#[inline]
pub fn replace_in_place(needle: u8, replacement: u8, bytes: &mut [u8]) {
if !bytes.contains(&needle) {
return;

View File

@@ -1,4 +1,3 @@
use std::borrow::Cow;
use std::io::{Read, Write};
use std::{fmt, io};
@@ -250,43 +249,6 @@ impl BinarySerializable for String {
}
}
impl<'a> BinarySerializable for Cow<'a, str> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
let data: &[u8] = self.as_bytes();
VInt(data.len() as u64).serialize(writer)?;
writer.write_all(data)
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Cow<'a, str>> {
let string_length = VInt::deserialize(reader)?.val() as usize;
let mut result = String::with_capacity(string_length);
reader
.take(string_length as u64)
.read_to_string(&mut result)?;
Ok(Cow::Owned(result))
}
}
impl<'a> BinarySerializable for Cow<'a, [u8]> {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
VInt(self.len() as u64).serialize(writer)?;
for it in self.iter() {
it.serialize(writer)?;
}
Ok(())
}
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Cow<'a, [u8]>> {
let num_items = VInt::deserialize(reader)?.val();
let mut items: Vec<u8> = Vec::with_capacity(num_items as usize);
for _ in 0..num_items {
let item = u8::deserialize(reader)?;
items.push(item);
}
Ok(Cow::Owned(items))
}
}
#[cfg(test)]
pub mod test {

View File

@@ -12,7 +12,7 @@ use tantivy::aggregation::agg_result::AggregationResults;
use tantivy::aggregation::AggregationCollector;
use tantivy::query::AllQuery;
use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing, FAST};
use tantivy::{Index, IndexWriter, TantivyDocument};
use tantivy::Index;
fn main() -> tantivy::Result<()> {
// # Create Schema
@@ -37,7 +37,7 @@ fn main() -> tantivy::Result<()> {
.set_index_option(IndexRecordOption::WithFreqs)
.set_tokenizer("raw"),
)
.set_fast(None)
.set_fast("default")
.set_stored();
schema_builder.add_text_field("category", text_fieldtype);
schema_builder.add_f64_field("stock", FAST);
@@ -132,10 +132,10 @@ fn main() -> tantivy::Result<()> {
let stream = Deserializer::from_str(data).into_iter::<Value>();
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
let mut num_indexed = 0;
for value in stream {
let doc = TantivyDocument::parse_json(&schema, &serde_json::to_string(&value.unwrap())?)?;
let doc = schema.parse_document(&serde_json::to_string(&value.unwrap())?)?;
index_writer.add_document(doc)?;
num_indexed += 1;
if num_indexed > 4 {

View File

@@ -15,7 +15,7 @@
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::*;
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
use tantivy::{doc, Index, ReloadPolicy};
use tempfile::TempDir;
fn main() -> tantivy::Result<()> {
@@ -75,7 +75,7 @@ fn main() -> tantivy::Result<()> {
// Here we give tantivy a budget of `50MB`.
// Using a bigger memory_arena for the indexer may increase
// throughput, but 50 MB is already plenty.
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// Let's index our documents!
// We first need a handle on the title and the body field.
@@ -87,7 +87,7 @@ fn main() -> tantivy::Result<()> {
let title = schema.get_field("title").unwrap();
let body = schema.get_field("body").unwrap();
let mut old_man_doc = TantivyDocument::default();
let mut old_man_doc = Document::default();
old_man_doc.add_text(title, "The Old Man and the Sea");
old_man_doc.add_text(
body,
@@ -164,7 +164,7 @@ fn main() -> tantivy::Result<()> {
// will reload the index automatically after each commit.
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()?;
// We now need to acquire a searcher.
@@ -217,23 +217,9 @@ fn main() -> tantivy::Result<()> {
// the document returned will only contain
// a title.
for (_score, doc_address) in top_docs {
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
println!("{}", retrieved_doc.to_json(&schema));
let retrieved_doc = searcher.doc(doc_address)?;
println!("{}", schema.to_json(&retrieved_doc));
}
// We can also get an explanation to understand
// how a found document got its score.
let query = query_parser.parse_query("title:sea^20 body:whale^70")?;
let (_score, doc_address) = searcher
.search(&query, &TopDocs::with_limit(1))?
.into_iter()
.next()
.unwrap();
let explanation = query.explain(&searcher, doc_address)?;
println!("{}", explanation.to_pretty_json());
Ok(())
}

View File

@@ -13,7 +13,7 @@ use columnar::Column;
use tantivy::collector::{Collector, SegmentCollector};
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index, IndexWriter, Score, SegmentReader};
use tantivy::{doc, Index, Score, SegmentReader};
#[derive(Default)]
struct Stats {
@@ -142,7 +142,7 @@ fn main() -> tantivy::Result<()> {
// this example.
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
index_writer.add_document(doc!(
product_name => "Super Broom 2000",
product_description => "While it is ok for short distance travel, this broom \

View File

@@ -6,7 +6,7 @@ use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::*;
use tantivy::tokenizer::NgramTokenizer;
use tantivy::{doc, Index, IndexWriter};
use tantivy::{doc, Index};
fn main() -> tantivy::Result<()> {
// # Defining the schema
@@ -62,7 +62,7 @@ fn main() -> tantivy::Result<()> {
//
// Here we use a buffer of 50MB per thread. Using a bigger
// memory arena for the indexer can increase its throughput.
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
index_writer.add_document(doc!(
title => "The Old Man and the Sea",
body => "He was an old man who fished alone in a skiff in the Gulf Stream and \
@@ -103,8 +103,8 @@ fn main() -> tantivy::Result<()> {
let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
for (_, doc_address) in top_docs {
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
println!("{}", retrieved_doc.to_json(&schema));
let retrieved_doc = searcher.doc(doc_address)?;
println!("{}", schema.to_json(&retrieved_doc));
}
Ok(())

View File

@@ -4,8 +4,8 @@
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{DateOptions, Document, OwnedValue, Schema, INDEXED, STORED, STRING};
use tantivy::{Index, IndexWriter, TantivyDocument};
use tantivy::schema::{DateOptions, Schema, Value, INDEXED, STORED, STRING};
use tantivy::Index;
fn main() -> tantivy::Result<()> {
// # Defining the schema
@@ -22,18 +22,16 @@ fn main() -> tantivy::Result<()> {
// # Indexing documents
let index = Index::create_in_ram(schema.clone());
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// The dates are passed as string in the RFC3339 format
let doc = TantivyDocument::parse_json(
&schema,
let doc = schema.parse_document(
r#"{
"occurred_at": "2022-06-22T12:53:50.53Z",
"event": "pull-request"
}"#,
)?;
index_writer.add_document(doc)?;
let doc = TantivyDocument::parse_json(
&schema,
let doc = schema.parse_document(
r#"{
"occurred_at": "2022-06-22T13:00:00.22Z",
"event": "comment"
@@ -60,13 +58,13 @@ fn main() -> tantivy::Result<()> {
let count_docs = searcher.search(&*query, &TopDocs::with_limit(4))?;
assert_eq!(count_docs.len(), 1);
for (_score, doc_address) in count_docs {
let retrieved_doc = searcher.doc::<TantivyDocument>(doc_address)?;
let retrieved_doc = searcher.doc(doc_address)?;
assert!(matches!(
retrieved_doc.get_first(occurred_at),
Some(OwnedValue::Date(_))
Some(Value::Date(_))
));
assert_eq!(
retrieved_doc.to_json(&schema),
schema.to_json(&retrieved_doc),
r#"{"event":["comment"],"occurred_at":["2022-06-22T13:00:00.22Z"]}"#
);
}

View File

@@ -11,7 +11,7 @@
use tantivy::collector::TopDocs;
use tantivy::query::TermQuery;
use tantivy::schema::*;
use tantivy::{doc, Index, IndexReader, IndexWriter};
use tantivy::{doc, Index, IndexReader};
// A simple helper function to fetch a single document
// given its id from our index.
@@ -19,7 +19,7 @@ use tantivy::{doc, Index, IndexReader, IndexWriter};
fn extract_doc_given_isbn(
reader: &IndexReader,
isbn_term: &Term,
) -> tantivy::Result<Option<TantivyDocument>> {
) -> tantivy::Result<Option<Document>> {
let searcher = reader.searcher();
// This is the simplest query you can think of.
@@ -69,10 +69,10 @@ fn main() -> tantivy::Result<()> {
let index = Index::create_in_ram(schema.clone());
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// Let's add a couple of documents, for the sake of the example.
let mut old_man_doc = TantivyDocument::default();
let mut old_man_doc = Document::default();
old_man_doc.add_text(title, "The Old Man and the Sea");
index_writer.add_document(doc!(
isbn => "978-0099908401",
@@ -94,7 +94,7 @@ fn main() -> tantivy::Result<()> {
// Oops our frankenstein doc seems misspelled
let frankenstein_doc_misspelled = extract_doc_given_isbn(&reader, &frankenstein_isbn)?.unwrap();
assert_eq!(
frankenstein_doc_misspelled.to_json(&schema),
schema.to_json(&frankenstein_doc_misspelled),
r#"{"isbn":["978-9176370711"],"title":["Frankentein"]}"#,
);
@@ -136,7 +136,7 @@ fn main() -> tantivy::Result<()> {
// No more typo!
let frankenstein_new_doc = extract_doc_given_isbn(&reader, &frankenstein_isbn)?.unwrap();
assert_eq!(
frankenstein_new_doc.to_json(&schema),
schema.to_json(&frankenstein_new_doc),
r#"{"isbn":["978-9176370711"],"title":["Frankenstein"]}"#,
);

View File

@@ -17,7 +17,7 @@
use tantivy::collector::FacetCollector;
use tantivy::query::{AllQuery, TermQuery};
use tantivy::schema::*;
use tantivy::{doc, Index, IndexWriter};
use tantivy::{doc, Index};
fn main() -> tantivy::Result<()> {
// Let's create a temporary directory for the sake of this example
@@ -30,7 +30,7 @@ fn main() -> tantivy::Result<()> {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer(30_000_000)?;
let mut index_writer = index.writer(30_000_000)?;
// For convenience, tantivy also comes with a macro to
// reduce the boilerplate above.

View File

@@ -12,7 +12,7 @@ use std::collections::HashSet;
use tantivy::collector::TopDocs;
use tantivy::query::BooleanQuery;
use tantivy::schema::*;
use tantivy::{doc, DocId, Index, IndexWriter, Score, SegmentReader};
use tantivy::{doc, DocId, Index, Score, SegmentReader};
fn main() -> tantivy::Result<()> {
let mut schema_builder = Schema::builder();
@@ -23,7 +23,7 @@ fn main() -> tantivy::Result<()> {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer(30_000_000)?;
let mut index_writer = index.writer(30_000_000)?;
index_writer.add_document(doc!(
title => "Fried egg",
@@ -91,10 +91,11 @@ fn main() -> tantivy::Result<()> {
.iter()
.map(|(_, doc_id)| {
searcher
.doc::<TantivyDocument>(*doc_id)
.doc(*doc_id)
.unwrap()
.get_first(title)
.and_then(|v| v.as_str())
.unwrap()
.as_text()
.unwrap()
.to_owned()
})

View File

@@ -14,7 +14,7 @@
use tantivy::collector::{Count, TopDocs};
use tantivy::query::FuzzyTermQuery;
use tantivy::schema::*;
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
use tantivy::{doc, Index, ReloadPolicy};
use tempfile::TempDir;
fn main() -> tantivy::Result<()> {
@@ -66,7 +66,7 @@ fn main() -> tantivy::Result<()> {
// Here we give tantivy a budget of `50MB`.
// Using a bigger memory_arena for the indexer may increase
// throughput, but 50 MB is already plenty.
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// Let's index our documents!
// We first need a handle on the title and the body field.
@@ -123,7 +123,7 @@ fn main() -> tantivy::Result<()> {
// will reload the index automatically after each commit.
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()?;
// We now need to acquire a searcher.
@@ -151,10 +151,10 @@ fn main() -> tantivy::Result<()> {
assert_eq!(count, 3);
assert_eq!(top_docs.len(), 3);
for (score, doc_address) in top_docs {
let retrieved_doc = searcher.doc(doc_address)?;
// Note that the score is not lower for the fuzzy hit.
// There's an issue open for that: https://github.com/quickwit-oss/tantivy/issues/563
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
println!("score {score:?} doc {}", retrieved_doc.to_json(&schema));
println!("score {score:?} doc {}", schema.to_json(&retrieved_doc));
// score 1.0 doc {"title":["The Diary of Muadib"]}
//
// score 1.0 doc {"title":["The Diary of a Young Girl"]}

View File

@@ -21,7 +21,7 @@ fn main() -> tantivy::Result<()> {
}"#;
// We can parse our document
let _mice_and_men_doc = TantivyDocument::parse_json(&schema, mice_and_men_doc_json)?;
let _mice_and_men_doc = schema.parse_document(mice_and_men_doc_json)?;
// Multi-valued field are allowed, they are
// expressed in JSON by an array.
@@ -30,7 +30,7 @@ fn main() -> tantivy::Result<()> {
"title": ["Frankenstein", "The Modern Prometheus"],
"year": 1818
}"#;
let _frankenstein_doc = TantivyDocument::parse_json(&schema, frankenstein_json)?;
let _frankenstein_doc = schema.parse_document(frankenstein_json)?;
// Note that the schema is saved in your index directory.
//

View File

@@ -5,7 +5,7 @@
use tantivy::collector::Count;
use tantivy::query::RangeQuery;
use tantivy::schema::{Schema, INDEXED};
use tantivy::{doc, Index, IndexWriter, Result};
use tantivy::{doc, Index, Result};
fn main() -> Result<()> {
// For the sake of simplicity, this schema will only have 1 field
@@ -17,7 +17,7 @@ fn main() -> Result<()> {
let index = Index::create_in_ram(schema);
let reader = index.reader()?;
{
let mut index_writer: IndexWriter = index.writer_with_num_threads(1, 6_000_000)?;
let mut index_writer = index.writer_with_num_threads(1, 6_000_000)?;
for year in 1950u64..2019u64 {
index_writer.add_document(doc!(year_field => year))?;
}

View File

@@ -6,7 +6,7 @@
use tantivy::collector::{Count, TopDocs};
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, INDEXED, STORED, STRING};
use tantivy::{Index, IndexWriter, TantivyDocument};
use tantivy::Index;
fn main() -> tantivy::Result<()> {
// # Defining the schema
@@ -22,22 +22,20 @@ fn main() -> tantivy::Result<()> {
// # Indexing documents
let index = Index::create_in_ram(schema.clone());
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// ### IPv4
// Adding documents that contain an IPv4 address. Notice that the IP addresses are passed as
// `String`. Since the field is of type ip, we parse the IP address from the string and store it
// internally as IPv6.
let doc = TantivyDocument::parse_json(
&schema,
let doc = schema.parse_document(
r#"{
"ip": "192.168.0.33",
"event_type": "login"
}"#,
)?;
index_writer.add_document(doc)?;
let doc = TantivyDocument::parse_json(
&schema,
let doc = schema.parse_document(
r#"{
"ip": "192.168.0.80",
"event_type": "checkout"
@@ -46,8 +44,7 @@ fn main() -> tantivy::Result<()> {
index_writer.add_document(doc)?;
// ### IPv6
// Adding a document that contains an IPv6 address.
let doc = TantivyDocument::parse_json(
&schema,
let doc = schema.parse_document(
r#"{
"ip": "2001:0db8:85a3:0000:0000:8a2e:0370:7334",
"event_type": "checkout"

View File

@@ -10,7 +10,7 @@
// ---
// Importing tantivy...
use tantivy::schema::*;
use tantivy::{doc, DocSet, Index, IndexWriter, Postings, TERMINATED};
use tantivy::{doc, DocSet, Index, Postings, TERMINATED};
fn main() -> tantivy::Result<()> {
// We first create a schema for the sake of the
@@ -24,7 +24,7 @@ fn main() -> tantivy::Result<()> {
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_with_num_threads(1, 50_000_000)?;
let mut index_writer = index.writer_with_num_threads(1, 50_000_000)?;
index_writer.add_document(doc!(title => "The Old Man and the Sea"))?;
index_writer.add_document(doc!(title => "Of Mice and Men"))?;
index_writer.add_document(doc!(title => "The modern Promotheus"))?;

View File

@@ -7,7 +7,7 @@
use tantivy::collector::{Count, TopDocs};
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, STORED, STRING, TEXT};
use tantivy::{Index, IndexWriter, TantivyDocument};
use tantivy::Index;
fn main() -> tantivy::Result<()> {
// # Defining the schema
@@ -20,9 +20,8 @@ fn main() -> tantivy::Result<()> {
// # Indexing documents
let index = Index::create_in_ram(schema.clone());
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let doc = TantivyDocument::parse_json(
&schema,
let mut index_writer = index.writer(50_000_000)?;
let doc = schema.parse_document(
r#"{
"timestamp": "2022-02-22T23:20:50.53Z",
"event_type": "click",
@@ -34,8 +33,7 @@ fn main() -> tantivy::Result<()> {
}"#,
)?;
index_writer.add_document(doc)?;
let doc = TantivyDocument::parse_json(
&schema,
let doc = schema.parse_document(
r#"{
"timestamp": "2022-02-22T23:20:51.53Z",
"event_type": "click",

View File

@@ -1,7 +1,7 @@
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::*;
use tantivy::{doc, Index, IndexWriter, ReloadPolicy, Result};
use tantivy::{doc, Index, ReloadPolicy, Result};
use tempfile::TempDir;
fn main() -> Result<()> {
@@ -17,7 +17,7 @@ fn main() -> Result<()> {
let index = Index::create_in_dir(&index_path, schema)?;
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
index_writer.add_document(doc!(
title => "The Old Man and the Sea",
@@ -51,7 +51,7 @@ fn main() -> Result<()> {
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()?;
let searcher = reader.searcher();
@@ -67,12 +67,8 @@ fn main() -> Result<()> {
let mut titles = top_docs
.into_iter()
.map(|(_score, doc_address)| {
let doc = searcher.doc::<TantivyDocument>(doc_address)?;
let title = doc
.get_first(title)
.and_then(|v| v.as_str())
.unwrap()
.to_owned();
let doc = searcher.doc(doc_address)?;
let title = doc.get_first(title).unwrap().as_text().unwrap().to_owned();
Ok(title)
})
.collect::<Result<Vec<_>>>()?;

View File

@@ -13,7 +13,7 @@ use tantivy::collector::{Count, TopDocs};
use tantivy::query::TermQuery;
use tantivy::schema::*;
use tantivy::tokenizer::{PreTokenizedString, SimpleTokenizer, Token, TokenStream, Tokenizer};
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
use tantivy::{doc, Index, ReloadPolicy};
use tempfile::TempDir;
fn pre_tokenize_text(text: &str) -> Vec<Token> {
@@ -38,7 +38,7 @@ fn main() -> tantivy::Result<()> {
let index = Index::create_in_dir(&index_path, schema.clone())?;
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// We can create a document manually, by setting the fields
// one by one in a Document object.
@@ -83,7 +83,7 @@ fn main() -> tantivy::Result<()> {
}]
}"#;
let short_man_doc = TantivyDocument::parse_json(&schema, short_man_json)?;
let short_man_doc = schema.parse_document(short_man_json)?;
index_writer.add_document(short_man_doc)?;
@@ -94,7 +94,7 @@ fn main() -> tantivy::Result<()> {
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()?;
let searcher = reader.searcher();
@@ -115,8 +115,8 @@ fn main() -> tantivy::Result<()> {
// Note that the tokens are not stored along with the original text
// in the document store
for (_score, doc_address) in top_docs {
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
println!("{}", retrieved_doc.to_json(&schema));
let retrieved_doc = searcher.doc(doc_address)?;
println!("Document: {}", schema.to_json(&retrieved_doc));
}
// In contrary to the previous query, when we search for the "man" term we

View File

@@ -10,8 +10,7 @@
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::*;
use tantivy::snippet::{Snippet, SnippetGenerator};
use tantivy::{doc, Index, IndexWriter};
use tantivy::{doc, Index, Snippet, SnippetGenerator};
use tempfile::TempDir;
fn main() -> tantivy::Result<()> {
@@ -28,7 +27,7 @@ fn main() -> tantivy::Result<()> {
// # Indexing documents
let index = Index::create_in_dir(&index_path, schema)?;
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
// we'll only need one doc for this example.
index_writer.add_document(doc!(
@@ -55,10 +54,13 @@ fn main() -> tantivy::Result<()> {
let snippet_generator = SnippetGenerator::create(&searcher, &*query, body)?;
for (score, doc_address) in top_docs {
let doc = searcher.doc::<TantivyDocument>(doc_address)?;
let doc = searcher.doc(doc_address)?;
let snippet = snippet_generator.snippet_from_doc(&doc);
println!("Document score {score}:");
println!("title: {}", doc.get_first(title).unwrap().as_str().unwrap());
println!(
"title: {}",
doc.get_first(title).unwrap().as_text().unwrap()
);
println!("snippet: {}", snippet.to_html());
println!("custom highlighting: {}", highlight(snippet));
}

View File

@@ -15,7 +15,7 @@ use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::*;
use tantivy::tokenizer::*;
use tantivy::{doc, Index, IndexWriter};
use tantivy::{doc, Index};
fn main() -> tantivy::Result<()> {
// this example assumes you understand the content in `basic_search`
@@ -60,7 +60,7 @@ fn main() -> tantivy::Result<()> {
index.tokenizers().register("stoppy", tokenizer);
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
let mut index_writer = index.writer(50_000_000)?;
let title = schema.get_field("title").unwrap();
let body = schema.get_field("body").unwrap();
@@ -105,9 +105,9 @@ fn main() -> tantivy::Result<()> {
let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
for (score, doc_address) in top_docs {
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
let retrieved_doc = searcher.doc(doc_address)?;
println!("\n==\nDocument score {score}:");
println!("{}", retrieved_doc.to_json(&schema));
println!("{}", schema.to_json(&retrieved_doc));
}
Ok(())

View File

@@ -6,8 +6,8 @@ use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, TEXT};
use tantivy::{
doc, DocAddress, DocId, Index, IndexWriter, Opstamp, Searcher, SearcherGeneration, SegmentId,
SegmentReader, Warmer,
doc, DocAddress, DocId, Index, Opstamp, Searcher, SearcherGeneration, SegmentId, SegmentReader,
Warmer,
};
// This example shows how warmers can be used to
@@ -143,7 +143,7 @@ fn main() -> tantivy::Result<()> {
const SNEAKERS: ProductId = 23222;
let index = Index::create_in_ram(schema);
let mut writer: IndexWriter = index.writer_with_num_threads(1, 15_000_000)?;
let mut writer = index.writer_with_num_threads(1, 10_000_000)?;
writer.add_document(doc!(product_id=>OLIVE_OIL, text=>"cooking olive oil from greece"))?;
writer.add_document(doc!(product_id=>GLOVES, text=>"kitchen gloves, perfect for cooking"))?;
writer.add_document(doc!(product_id=>SNEAKERS, text=>"uber sweet sneakers"))?;

View File

@@ -1,7 +1,7 @@
[package]
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
name = "ownedbytes"
version = "0.6.0"
version = "0.5.0"
edition = "2021"
description = "Expose data as static slice"
license = "MIT"

View File

@@ -1,7 +1,7 @@
use std::convert::TryInto;
use std::ops::{Deref, Range};
use std::sync::Arc;
use std::{fmt, io};
use std::{fmt, io, mem};
pub use stable_deref_trait::StableDeref;
@@ -26,8 +26,8 @@ impl OwnedBytes {
data_holder: T,
) -> OwnedBytes {
let box_stable_deref = Arc::new(data_holder);
let bytes: &[u8] = box_stable_deref.deref();
let data = unsafe { &*(bytes as *const [u8]) };
let bytes: &[u8] = box_stable_deref.as_ref();
let data = unsafe { mem::transmute::<_, &'static [u8]>(bytes.deref()) };
OwnedBytes {
data,
box_stable_deref,
@@ -57,12 +57,6 @@ impl OwnedBytes {
self.data.len()
}
/// Returns true iff this `OwnedBytes` is empty.
#[inline]
pub fn is_empty(&self) -> bool {
self.data.is_empty()
}
/// Splits the OwnedBytes into two OwnedBytes `(left, right)`.
///
/// Left will hold `split_len` bytes.
@@ -74,14 +68,13 @@ impl OwnedBytes {
#[inline]
#[must_use]
pub fn split(self, split_len: usize) -> (OwnedBytes, OwnedBytes) {
let (left_data, right_data) = self.data.split_at(split_len);
let right_box_stable_deref = self.box_stable_deref.clone();
let left = OwnedBytes {
data: left_data,
data: &self.data[..split_len],
box_stable_deref: self.box_stable_deref,
};
let right = OwnedBytes {
data: right_data,
data: &self.data[split_len..],
box_stable_deref: right_box_stable_deref,
};
(left, right)
@@ -106,45 +99,55 @@ impl OwnedBytes {
///
/// `self` is truncated to `split_len`, left with the remaining bytes.
pub fn split_off(&mut self, split_len: usize) -> OwnedBytes {
let (left, right) = self.data.split_at(split_len);
let right_box_stable_deref = self.box_stable_deref.clone();
let right_piece = OwnedBytes {
data: right,
data: &self.data[split_len..],
box_stable_deref: right_box_stable_deref,
};
self.data = left;
self.data = &self.data[..split_len];
right_piece
}
/// Returns true iff this `OwnedBytes` is empty.
#[inline]
pub fn is_empty(&self) -> bool {
self.as_slice().is_empty()
}
/// Drops the left most `advance_len` bytes.
#[inline]
pub fn advance(&mut self, advance_len: usize) -> &[u8] {
let (data, rest) = self.data.split_at(advance_len);
self.data = rest;
data
pub fn advance(&mut self, advance_len: usize) {
self.data = &self.data[advance_len..]
}
/// Reads an `u8` from the `OwnedBytes` and advance by one byte.
#[inline]
pub fn read_u8(&mut self) -> u8 {
self.advance(1)[0]
}
assert!(!self.is_empty());
#[inline]
fn read_n<const N: usize>(&mut self) -> [u8; N] {
self.advance(N).try_into().unwrap()
}
/// Reads an `u32` encoded as little-endian from the `OwnedBytes` and advance by 4 bytes.
#[inline]
pub fn read_u32(&mut self) -> u32 {
u32::from_le_bytes(self.read_n())
let byte = self.as_slice()[0];
self.advance(1);
byte
}
/// Reads an `u64` encoded as little-endian from the `OwnedBytes` and advance by 8 bytes.
#[inline]
pub fn read_u64(&mut self) -> u64 {
u64::from_le_bytes(self.read_n())
assert!(self.len() > 7);
let octlet: [u8; 8] = self.as_slice()[..8].try_into().unwrap();
self.advance(8);
u64::from_le_bytes(octlet)
}
/// Reads an `u32` encoded as little-endian from the `OwnedBytes` and advance by 4 bytes.
#[inline]
pub fn read_u32(&mut self) -> u32 {
assert!(self.len() > 3);
let quad: [u8; 4] = self.as_slice()[..4].try_into().unwrap();
self.advance(4);
u32::from_le_bytes(quad)
}
}
@@ -198,33 +201,32 @@ impl Deref for OwnedBytes {
}
}
impl AsRef<[u8]> for OwnedBytes {
#[inline]
fn as_ref(&self) -> &[u8] {
self.as_slice()
}
}
impl io::Read for OwnedBytes {
#[inline]
fn read(&mut self, buf: &mut [u8]) -> io::Result<usize> {
let data_len = self.data.len();
let buf_len = buf.len();
if data_len >= buf_len {
let data = self.advance(buf_len);
buf.copy_from_slice(data);
Ok(buf_len)
} else {
buf[..data_len].copy_from_slice(self.data);
self.data = &[];
Ok(data_len)
}
let read_len = {
let data = self.as_slice();
if data.len() >= buf.len() {
let buf_len = buf.len();
buf.copy_from_slice(&data[..buf_len]);
buf.len()
} else {
let data_len = data.len();
buf[..data_len].copy_from_slice(data);
data_len
}
};
self.advance(read_len);
Ok(read_len)
}
#[inline]
fn read_to_end(&mut self, buf: &mut Vec<u8>) -> io::Result<usize> {
buf.extend(self.data);
let read_len = self.data.len();
self.data = &[];
let read_len = {
let data = self.as_slice();
buf.extend(data);
data.len()
};
self.advance(read_len);
Ok(read_len)
}
#[inline]
@@ -240,6 +242,13 @@ impl io::Read for OwnedBytes {
}
}
impl AsRef<[u8]> for OwnedBytes {
#[inline]
fn as_ref(&self) -> &[u8] {
self.as_slice()
}
}
#[cfg(test)]
mod tests {
use std::io::{self, Read};

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-query-grammar"
version = "0.21.0"
version = "0.20.0"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -12,4 +12,6 @@ keywords = ["search", "information", "retrieval"]
edition = "2021"
[dependencies]
nom = "7"
combine = {version="4", default-features=false, features=[] }
once_cell = "1.7.2"
regex ={ version = "1.5.4", default-features = false, features = ["std", "unicode"] }

View File

@@ -1,353 +0,0 @@
//! nom combinators for infallible operations
use std::convert::Infallible;
use nom::{AsChar, IResult, InputLength, InputTakeAtPosition};
pub(crate) type ErrorList = Vec<LenientErrorInternal>;
pub(crate) type JResult<I, O> = IResult<I, (O, ErrorList), Infallible>;
/// An error, with an end-of-string based offset
#[derive(Debug)]
pub(crate) struct LenientErrorInternal {
pub pos: usize,
pub message: String,
}
/// A recoverable error and the position it happened at
#[derive(Debug, PartialEq)]
pub struct LenientError {
pub pos: usize,
pub message: String,
}
impl LenientError {
pub(crate) fn from_internal(internal: LenientErrorInternal, str_len: usize) -> LenientError {
LenientError {
pos: str_len - internal.pos,
message: internal.message,
}
}
}
fn unwrap_infallible<T>(res: Result<T, nom::Err<Infallible>>) -> T {
match res {
Ok(val) => val,
Err(_) => unreachable!(),
}
}
// when rfcs#1733 get stabilized, this can make things clearer
// trait InfallibleParser<I, O> = nom::Parser<I, (O, ErrorList), std::convert::Infallible>;
/// A variant of the classical `opt` parser, except it returns an infallible error type.
///
/// It's less generic than the original to ease type resolution in the rest of the code.
pub(crate) fn opt_i<I: Clone, O, F>(mut f: F) -> impl FnMut(I) -> JResult<I, Option<O>>
where F: nom::Parser<I, O, nom::error::Error<I>> {
move |input: I| {
let i = input.clone();
match f.parse(input) {
Ok((i, o)) => Ok((i, (Some(o), Vec::new()))),
Err(_) => Ok((i, (None, Vec::new()))),
}
}
}
pub(crate) fn opt_i_err<'a, I: Clone + InputLength, O, F>(
mut f: F,
message: impl ToString + 'a,
) -> impl FnMut(I) -> JResult<I, Option<O>> + 'a
where
F: nom::Parser<I, O, nom::error::Error<I>> + 'a,
{
move |input: I| {
let i = input.clone();
match f.parse(input) {
Ok((i, o)) => Ok((i, (Some(o), Vec::new()))),
Err(_) => {
let errs = vec![LenientErrorInternal {
pos: i.input_len(),
message: message.to_string(),
}];
Ok((i, (None, errs)))
}
}
}
}
pub(crate) fn space0_infallible<T>(input: T) -> JResult<T, T>
where
T: InputTakeAtPosition + Clone,
<T as InputTakeAtPosition>::Item: AsChar + Clone,
{
opt_i(nom::character::complete::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>>
where
T: InputTakeAtPosition + Clone + InputLength,
<T as InputTakeAtPosition>::Item: AsChar + Clone,
{
opt_i(nom::character::complete::space1)(input).map(|(left, (spaces, mut errors))| {
if spaces.is_none() {
errors.push(LenientErrorInternal {
pos: left.input_len(),
message: "missing space".to_string(),
})
}
(left, (spaces, errors))
})
}
pub(crate) fn fallible<I, O, E: nom::error::ParseError<I>, F>(
mut f: F,
) -> impl FnMut(I) -> IResult<I, O, E>
where F: nom::Parser<I, (O, ErrorList), Infallible> {
use nom::Err;
move |input: I| match f.parse(input) {
Ok((input, (output, _err))) => Ok((input, output)),
Err(Err::Incomplete(needed)) => Err(Err::Incomplete(needed)),
Err(Err::Error(val)) | Err(Err::Failure(val)) => match val {},
}
}
pub(crate) fn delimited_infallible<I, O1, O2, O3, F, G, H>(
mut first: F,
mut second: G,
mut third: H,
) -> impl FnMut(I) -> JResult<I, O2>
where
F: nom::Parser<I, (O1, ErrorList), Infallible>,
G: nom::Parser<I, (O2, ErrorList), Infallible>,
H: nom::Parser<I, (O3, ErrorList), Infallible>,
{
move |input: I| {
let (input, (_, mut err)) = first.parse(input)?;
let (input, (o2, mut err2)) = second.parse(input)?;
err.append(&mut err2);
let (input, (_, mut err3)) = third.parse(input)?;
err.append(&mut err3);
Ok((input, (o2, err)))
}
}
// Parse nothing. Just a lazy way to not implement terminated/preceded and use delimited instead
pub(crate) fn nothing(i: &str) -> JResult<&str, ()> {
Ok((i, ((), Vec::new())))
}
pub(crate) trait TupleInfallible<I, O> {
/// Parses the input and returns a tuple of results of each parser.
fn parse(&mut self, input: I) -> JResult<I, O>;
}
impl<Input, Output, F: nom::Parser<Input, (Output, ErrorList), Infallible>>
TupleInfallible<Input, (Output,)> for (F,)
{
fn parse(&mut self, input: Input) -> JResult<Input, (Output,)> {
self.0.parse(input).map(|(i, (o, e))| (i, ((o,), e)))
}
}
// these macros are heavily copied from nom, with some minor adaptations for our type
macro_rules! tuple_trait(
($name1:ident $ty1:ident, $name2: ident $ty2:ident, $($name:ident $ty:ident),*) => (
tuple_trait!(__impl $name1 $ty1, $name2 $ty2; $($name $ty),*);
);
(__impl $($name:ident $ty: ident),+; $name1:ident $ty1:ident, $($name2:ident $ty2:ident),*) => (
tuple_trait_impl!($($name $ty),+);
tuple_trait!(__impl $($name $ty),+ , $name1 $ty1; $($name2 $ty2),*);
);
(__impl $($name:ident $ty: ident),+; $name1:ident $ty1:ident) => (
tuple_trait_impl!($($name $ty),+);
tuple_trait_impl!($($name $ty),+, $name1 $ty1);
);
);
macro_rules! tuple_trait_impl(
($($name:ident $ty: ident),+) => (
impl<
Input: Clone, $($ty),+ ,
$($name: nom::Parser<Input, ($ty, ErrorList), Infallible>),+
> TupleInfallible<Input, ( $($ty),+ )> for ( $($name),+ ) {
fn parse(&mut self, input: Input) -> JResult<Input, ( $($ty),+ )> {
let mut error_list = Vec::new();
tuple_trait_inner!(0, self, input, (), error_list, $($name)+)
}
}
);
);
macro_rules! tuple_trait_inner(
($it:tt, $self:expr, $input:expr, (), $error_list:expr, $head:ident $($id:ident)+) => ({
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
$error_list.append(&mut err);
succ!($it, tuple_trait_inner!($self, i, ( o ), $error_list, $($id)+))
});
($it:tt, $self:expr, $input:expr, ($($parsed:tt)*), $error_list:expr, $head:ident $($id:ident)+) => ({
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
$error_list.append(&mut err);
succ!($it, tuple_trait_inner!($self, i, ($($parsed)* , o), $error_list, $($id)+))
});
($it:tt, $self:expr, $input:expr, ($($parsed:tt)*), $error_list:expr, $head:ident) => ({
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
$error_list.append(&mut err);
Ok((i, (($($parsed)* , o), $error_list)))
});
);
macro_rules! succ (
(0, $submac:ident ! ($($rest:tt)*)) => ($submac!(1, $($rest)*));
(1, $submac:ident ! ($($rest:tt)*)) => ($submac!(2, $($rest)*));
(2, $submac:ident ! ($($rest:tt)*)) => ($submac!(3, $($rest)*));
(3, $submac:ident ! ($($rest:tt)*)) => ($submac!(4, $($rest)*));
(4, $submac:ident ! ($($rest:tt)*)) => ($submac!(5, $($rest)*));
(5, $submac:ident ! ($($rest:tt)*)) => ($submac!(6, $($rest)*));
(6, $submac:ident ! ($($rest:tt)*)) => ($submac!(7, $($rest)*));
(7, $submac:ident ! ($($rest:tt)*)) => ($submac!(8, $($rest)*));
(8, $submac:ident ! ($($rest:tt)*)) => ($submac!(9, $($rest)*));
(9, $submac:ident ! ($($rest:tt)*)) => ($submac!(10, $($rest)*));
(10, $submac:ident ! ($($rest:tt)*)) => ($submac!(11, $($rest)*));
(11, $submac:ident ! ($($rest:tt)*)) => ($submac!(12, $($rest)*));
(12, $submac:ident ! ($($rest:tt)*)) => ($submac!(13, $($rest)*));
(13, $submac:ident ! ($($rest:tt)*)) => ($submac!(14, $($rest)*));
(14, $submac:ident ! ($($rest:tt)*)) => ($submac!(15, $($rest)*));
(15, $submac:ident ! ($($rest:tt)*)) => ($submac!(16, $($rest)*));
(16, $submac:ident ! ($($rest:tt)*)) => ($submac!(17, $($rest)*));
(17, $submac:ident ! ($($rest:tt)*)) => ($submac!(18, $($rest)*));
(18, $submac:ident ! ($($rest:tt)*)) => ($submac!(19, $($rest)*));
(19, $submac:ident ! ($($rest:tt)*)) => ($submac!(20, $($rest)*));
(20, $submac:ident ! ($($rest:tt)*)) => ($submac!(21, $($rest)*));
);
tuple_trait!(FnA A, FnB B, FnC C, FnD D, FnE E, FnF F, FnG G, FnH H, FnI I, FnJ J, FnK K, FnL L,
FnM M, FnN N, FnO O, FnP P, FnQ Q, FnR R, FnS S, FnT T, FnU U);
// Special case: implement `TupleInfallible` for `()`, the unit type.
// This can come up in macros which accept a variable number of arguments.
// Literally, `()` is an empty tuple, so it should simply parse nothing.
impl<I> TupleInfallible<I, ()> for () {
fn parse(&mut self, input: I) -> JResult<I, ()> {
Ok((input, ((), Vec::new())))
}
}
pub(crate) fn tuple_infallible<I, O, List: TupleInfallible<I, O>>(
mut l: List,
) -> impl FnMut(I) -> JResult<I, O> {
move |i: I| l.parse(i)
}
pub(crate) fn separated_list_infallible<I, O, O2, F, G>(
mut sep: G,
mut f: F,
) -> impl FnMut(I) -> JResult<I, Vec<O>>
where
I: Clone + InputLength,
F: nom::Parser<I, (O, ErrorList), Infallible>,
G: nom::Parser<I, (O2, ErrorList), Infallible>,
{
move |i: I| {
let mut res: Vec<O> = Vec::new();
let mut errors: ErrorList = Vec::new();
let (mut i, (o, mut err)) = unwrap_infallible(f.parse(i.clone()));
errors.append(&mut err);
res.push(o);
loop {
let (i_sep_parsed, (_, mut err_sep)) = unwrap_infallible(sep.parse(i.clone()));
let len_before = i_sep_parsed.input_len();
let (i_elem_parsed, (o, mut err_elem)) =
unwrap_infallible(f.parse(i_sep_parsed.clone()));
// infinite loop check: the parser must always consume
// if we consumed nothing here, don't produce an element.
if i_elem_parsed.input_len() == len_before {
return Ok((i, (res, errors)));
}
res.push(o);
errors.append(&mut err_sep);
errors.append(&mut err_elem);
i = i_elem_parsed;
}
}
}
pub(crate) trait Alt<I, O> {
/// Tests each parser in the tuple and returns the result of the first one that succeeds
fn choice(&mut self, input: I) -> Option<JResult<I, O>>;
}
macro_rules! alt_trait(
($first_cond:ident $first:ident, $($id_cond:ident $id: ident),+) => (
alt_trait!(__impl $first_cond $first; $($id_cond $id),+);
);
(__impl $($current_cond:ident $current:ident),*; $head_cond:ident $head:ident, $($id_cond:ident $id:ident),+) => (
alt_trait_impl!($($current_cond $current),*);
alt_trait!(__impl $($current_cond $current,)* $head_cond $head; $($id_cond $id),+);
);
(__impl $($current_cond:ident $current:ident),*; $head_cond:ident $head:ident) => (
alt_trait_impl!($($current_cond $current),*);
alt_trait_impl!($($current_cond $current,)* $head_cond $head);
);
);
macro_rules! alt_trait_impl(
($($id_cond:ident $id:ident),+) => (
impl<
Input: Clone, Output,
$(
// () are to make things easier on me, but I'm not entirely sure whether we can do better
// with rule E0207
$id_cond: nom::Parser<Input, (), ()>,
$id: nom::Parser<Input, (Output, ErrorList), Infallible>
),+
> Alt<Input, Output> for ( $(($id_cond, $id),)+ ) {
fn choice(&mut self, input: Input) -> Option<JResult<Input, Output>> {
match self.0.0.parse(input.clone()) {
Err(_) => alt_trait_inner!(1, self, input, $($id_cond $id),+),
Ok((input_left, _)) => Some(self.0.1.parse(input_left)),
}
}
}
);
);
macro_rules! alt_trait_inner(
($it:tt, $self:expr, $input:expr, $head_cond:ident $head:ident, $($id_cond:ident $id:ident),+) => (
match $self.$it.0.parse($input.clone()) {
Err(_) => succ!($it, alt_trait_inner!($self, $input, $($id_cond $id),+)),
Ok((input_left, _)) => Some($self.$it.1.parse(input_left)),
}
);
($it:tt, $self:expr, $input:expr, $head_cond:ident $head:ident) => (
None
);
);
alt_trait!(A1 A, B1 B, C1 C, D1 D, E1 E, F1 F, G1 G, H1 H, I1 I, J1 J, K1 K,
L1 L, M1 M, N1 N, O1 O, P1 P, Q1 Q, R1 R, S1 S, T1 T, U1 U);
/// An alt() like combinator. For each branch, it first tries a fallible parser, which commits to
/// this branch, or tells to check next branch, and the execute the infallible parser which follow.
///
/// In case no branch match, the default (fallible) parser is executed.
pub(crate) fn alt_infallible<I: Clone, O, F, List: Alt<I, O>>(
mut l: List,
mut default: F,
) -> impl FnMut(I) -> JResult<I, O>
where
F: nom::Parser<I, (O, ErrorList), Infallible>,
{
move |i: I| l.choice(i.clone()).unwrap_or_else(|| default.parse(i))
}

View File

@@ -1,26 +1,19 @@
#![allow(clippy::derive_partial_eq_without_eq)]
mod infallible;
mod occur;
mod query_grammar;
mod user_input_ast;
use combine::parser::Parser;
pub use crate::infallible::LenientError;
pub use crate::occur::Occur;
use crate::query_grammar::{parse_to_ast, parse_to_ast_lenient};
use crate::query_grammar::parse_to_ast;
pub use crate::user_input_ast::{
Delimiter, UserInputAst, UserInputBound, UserInputLeaf, UserInputLiteral,
};
pub struct Error;
/// Parse a query
pub fn parse_query(query: &str) -> Result<UserInputAst, Error> {
let (_remaining, user_input_ast) = parse_to_ast(query).map_err(|_| Error)?;
let (user_input_ast, _remaining) = parse_to_ast().parse(query).map_err(|_| Error)?;
Ok(user_input_ast)
}
/// Parse a query, trying to recover from syntax errors, and giving hints toward fixing errors.
pub fn parse_query_lenient(query: &str) -> (UserInputAst, Vec<LenientError>) {
parse_to_ast_lenient(query)
}

File diff suppressed because it is too large Load Diff

View File

@@ -3,7 +3,7 @@ use std::fmt::{Debug, Formatter};
use crate::Occur;
#[derive(PartialEq, Clone)]
#[derive(PartialEq)]
pub enum UserInputLeaf {
Literal(UserInputLiteral),
All,
@@ -16,34 +16,6 @@ pub enum UserInputLeaf {
field: Option<String>,
elements: Vec<String>,
},
Exists {
field: String,
},
}
impl UserInputLeaf {
pub(crate) fn set_field(self, field: Option<String>) -> Self {
match self {
UserInputLeaf::Literal(mut literal) => {
literal.field_name = field;
UserInputLeaf::Literal(literal)
}
UserInputLeaf::All => UserInputLeaf::All,
UserInputLeaf::Range {
field: _,
lower,
upper,
} => UserInputLeaf::Range {
field,
lower,
upper,
},
UserInputLeaf::Set { field: _, elements } => UserInputLeaf::Set { field, elements },
UserInputLeaf::Exists { field: _ } => UserInputLeaf::Exists {
field: field.expect("Exist query without a field isn't allowed"),
},
}
}
}
impl Debug for UserInputLeaf {
@@ -56,7 +28,6 @@ impl Debug for UserInputLeaf {
ref upper,
} => {
if let Some(ref field) = field {
// TODO properly escape field (in case of \")
write!(formatter, "\"{field}\":")?;
}
lower.display_lower(formatter)?;
@@ -66,7 +37,6 @@ impl Debug for UserInputLeaf {
}
UserInputLeaf::Set { field, elements } => {
if let Some(ref field) = field {
// TODO properly escape field (in case of \")
write!(formatter, "\"{field}\": ")?;
}
write!(formatter, "IN [")?;
@@ -74,15 +44,11 @@ impl Debug for UserInputLeaf {
if i != 0 {
write!(formatter, " ")?;
}
// TODO properly escape element
write!(formatter, "\"{text}\"")?;
}
write!(formatter, "]")
}
UserInputLeaf::All => write!(formatter, "*"),
UserInputLeaf::Exists { field } => {
write!(formatter, "\"{field}\":*")
}
}
}
}
@@ -94,7 +60,7 @@ pub enum Delimiter {
None,
}
#[derive(PartialEq, Clone)]
#[derive(PartialEq)]
pub struct UserInputLiteral {
pub field_name: Option<String>,
pub phrase: String,
@@ -106,20 +72,16 @@ pub struct UserInputLiteral {
impl fmt::Debug for UserInputLiteral {
fn fmt(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
if let Some(ref field) = self.field_name {
// TODO properly escape field (in case of \")
write!(formatter, "\"{field}\":")?;
}
match self.delimiter {
Delimiter::SingleQuotes => {
// TODO properly escape element (in case of \')
write!(formatter, "'{}'", self.phrase)?;
}
Delimiter::DoubleQuotes => {
// TODO properly escape element (in case of \")
write!(formatter, "\"{}\"", self.phrase)?;
}
Delimiter::None => {
// TODO properly escape element
write!(formatter, "{}", self.phrase)?;
}
}
@@ -132,7 +94,7 @@ impl fmt::Debug for UserInputLiteral {
}
}
#[derive(PartialEq, Debug, Clone)]
#[derive(PartialEq)]
pub enum UserInputBound {
Inclusive(String),
Exclusive(String),
@@ -142,7 +104,6 @@ pub enum UserInputBound {
impl UserInputBound {
fn display_lower(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
match *self {
// TODO properly escape word if required
UserInputBound::Inclusive(ref word) => write!(formatter, "[\"{word}\""),
UserInputBound::Exclusive(ref word) => write!(formatter, "{{\"{word}\""),
UserInputBound::Unbounded => write!(formatter, "{{\"*\""),
@@ -151,7 +112,6 @@ impl UserInputBound {
fn display_upper(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
match *self {
// TODO properly escape word if required
UserInputBound::Inclusive(ref word) => write!(formatter, "\"{word}\"]"),
UserInputBound::Exclusive(ref word) => write!(formatter, "\"{word}\"}}"),
UserInputBound::Unbounded => write!(formatter, "\"*\"}}"),
@@ -167,7 +127,6 @@ impl UserInputBound {
}
}
#[derive(PartialEq, Clone)]
pub enum UserInputAst {
Clause(Vec<(Option<Occur>, UserInputAst)>),
Leaf(Box<UserInputLeaf>),
@@ -237,7 +196,6 @@ impl fmt::Debug for UserInputAst {
match *self {
UserInputAst::Clause(ref subqueries) => {
if subqueries.is_empty() {
// TODO this will break ast reserialization, is writing "( )" enought?
write!(formatter, "<emptyclause>")?;
} else {
write!(formatter, "(")?;

View File

@@ -48,7 +48,7 @@ mod bench {
let score_field_f64 = schema_builder.add_f64_field("score_f64", score_fieldtype.clone());
let score_field_i64 = schema_builder.add_i64_field("score_i64", score_fieldtype);
let index = Index::create_from_tempdir(schema_builder.build())?;
let few_terms_data = ["INFO", "ERROR", "WARN", "DEBUG"];
let few_terms_data = vec!["INFO", "ERROR", "WARN", "DEBUG"];
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
@@ -85,7 +85,7 @@ mod bench {
if cardinality == Cardinality::Sparse {
doc_with_value /= 20;
}
let _val_max = 1_000_000.0;
let val_max = 1_000_000.0;
for _ in 0..doc_with_value {
let val: f64 = rng.gen_range(0.0..1_000_000.0);
let json = if rng.gen_bool(0.1) {

View File

@@ -73,9 +73,9 @@ impl AggregationLimits {
/// Create a new ResourceLimitGuard, that will release the memory when dropped.
pub fn new_guard(&self) -> ResourceLimitGuard {
ResourceLimitGuard {
// The counter which is shared between the aggregations for one request.
/// The counter which is shared between the aggregations for one request.
memory_consumption: Arc::clone(&self.memory_consumption),
// The memory_limit in bytes
/// The memory_limit in bytes
memory_limit: self.memory_limit,
allocated_with_the_guard: 0,
}
@@ -134,142 +134,3 @@ impl Drop for ResourceLimitGuard {
.fetch_sub(self.allocated_with_the_guard, Ordering::Relaxed);
}
}
#[cfg(test)]
mod tests {
use crate::aggregation::tests::exec_request_with_query;
// https://github.com/quickwit-oss/quickwit/issues/3837
#[test]
fn test_agg_limits_with_empty_merge() {
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::bucket::tests::get_test_index_from_docs;
let docs = vec![
vec![r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb", "text2": "bbb" }"#],
vec![r#"{ "text": "aaa", "text2": "bbb" }"#],
];
let index = get_test_index_from_docs(false, &docs).unwrap();
{
let elasticsearch_compatible_json = json!(
{
"1": {
"terms": {"field": "text2", "min_doc_count": 0},
"aggs": {
"2":{
"date_histogram": {
"field": "date",
"fixed_interval": "1d",
"extended_bounds": {
"min": "2015-01-01T00:00:00Z",
"max": "2015-01-10T00:00:00Z"
}
}
}
}
}
}
);
let agg_req: Aggregations = serde_json::from_str(
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
)
.unwrap();
let res = exec_request_with_query(agg_req, &index, Some(("text", "bbb"))).unwrap();
let expected_res = json!({
"1": {
"buckets": [
{
"2": {
"buckets": [
{ "doc_count": 0, "key": 1420070400000.0, "key_as_string": "2015-01-01T00:00:00Z" },
{ "doc_count": 1, "key": 1420156800000.0, "key_as_string": "2015-01-02T00:00:00Z" },
{ "doc_count": 0, "key": 1420243200000.0, "key_as_string": "2015-01-03T00:00:00Z" },
{ "doc_count": 0, "key": 1420329600000.0, "key_as_string": "2015-01-04T00:00:00Z" },
{ "doc_count": 0, "key": 1420416000000.0, "key_as_string": "2015-01-05T00:00:00Z" },
{ "doc_count": 0, "key": 1420502400000.0, "key_as_string": "2015-01-06T00:00:00Z" },
{ "doc_count": 0, "key": 1420588800000.0, "key_as_string": "2015-01-07T00:00:00Z" },
{ "doc_count": 0, "key": 1420675200000.0, "key_as_string": "2015-01-08T00:00:00Z" },
{ "doc_count": 0, "key": 1420761600000.0, "key_as_string": "2015-01-09T00:00:00Z" },
{ "doc_count": 0, "key": 1420848000000.0, "key_as_string": "2015-01-10T00:00:00Z" }
]
},
"doc_count": 1,
"key": "bbb"
}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
}
});
assert_eq!(res, expected_res);
}
}
// https://github.com/quickwit-oss/quickwit/issues/3837
#[test]
fn test_agg_limits_with_empty_data() {
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::bucket::tests::get_test_index_from_docs;
let docs = vec![vec![r#"{ "text": "aaa", "text2": "bbb" }"#]];
let index = get_test_index_from_docs(false, &docs).unwrap();
{
// Empty result since there is no doc with dates
let elasticsearch_compatible_json = json!(
{
"1": {
"terms": {"field": "text2", "min_doc_count": 0},
"aggs": {
"2":{
"date_histogram": {
"field": "date",
"fixed_interval": "1d",
"extended_bounds": {
"min": "2015-01-01T00:00:00Z",
"max": "2015-01-10T00:00:00Z"
}
}
}
}
}
}
);
let agg_req: Aggregations = serde_json::from_str(
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
)
.unwrap();
let res = exec_request_with_query(agg_req, &index, Some(("text", "bbb"))).unwrap();
let expected_res = json!({
"1": {
"buckets": [
{
"2": {
"buckets": [
{ "doc_count": 0, "key": 1420070400000.0, "key_as_string": "2015-01-01T00:00:00Z" },
{ "doc_count": 0, "key": 1420156800000.0, "key_as_string": "2015-01-02T00:00:00Z" },
{ "doc_count": 0, "key": 1420243200000.0, "key_as_string": "2015-01-03T00:00:00Z" },
{ "doc_count": 0, "key": 1420329600000.0, "key_as_string": "2015-01-04T00:00:00Z" },
{ "doc_count": 0, "key": 1420416000000.0, "key_as_string": "2015-01-05T00:00:00Z" },
{ "doc_count": 0, "key": 1420502400000.0, "key_as_string": "2015-01-06T00:00:00Z" },
{ "doc_count": 0, "key": 1420588800000.0, "key_as_string": "2015-01-07T00:00:00Z" },
{ "doc_count": 0, "key": 1420675200000.0, "key_as_string": "2015-01-08T00:00:00Z" },
{ "doc_count": 0, "key": 1420761600000.0, "key_as_string": "2015-01-09T00:00:00Z" },
{ "doc_count": 0, "key": 1420848000000.0, "key_as_string": "2015-01-10T00:00:00Z" }
]
},
"doc_count": 0,
"key": "bbb"
}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
}
});
assert_eq!(res, expected_res);
}
}
}

View File

@@ -44,49 +44,22 @@ use super::metric::{
/// The key is the user defined name of the aggregation.
pub type Aggregations = HashMap<String, Aggregation>;
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
/// Aggregation request.
///
/// An aggregation is either a bucket or a metric.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
#[serde(try_from = "AggregationForDeserialization")]
pub struct Aggregation {
/// The aggregation variant, which can be either a bucket or a metric.
#[serde(flatten)]
pub agg: AggregationVariants,
/// The sub_aggregations, only valid for bucket type aggregations. Each bucket will aggregate
/// on the document set in the bucket.
#[serde(rename = "aggs")]
#[serde(default)]
#[serde(skip_serializing_if = "Aggregations::is_empty")]
pub sub_aggregation: Aggregations,
}
/// In order to display proper error message, we cannot rely on flattening
/// the json enum. Instead we introduce an intermediary struct to separate
/// the aggregation from the subaggregation.
#[derive(Deserialize)]
struct AggregationForDeserialization {
#[serde(flatten)]
pub aggs_remaining_json: serde_json::Value,
#[serde(rename = "aggs")]
#[serde(default)]
pub sub_aggregation: Aggregations,
}
impl TryFrom<AggregationForDeserialization> for Aggregation {
type Error = serde_json::Error;
fn try_from(value: AggregationForDeserialization) -> serde_json::Result<Self> {
let AggregationForDeserialization {
aggs_remaining_json,
sub_aggregation,
} = value;
let agg: AggregationVariants = serde_json::from_value(aggs_remaining_json)?;
Ok(Aggregation {
agg,
sub_aggregation,
})
}
}
impl Aggregation {
pub(crate) fn sub_aggregation(&self) -> &Aggregations {
&self.sub_aggregation
@@ -150,8 +123,7 @@ pub enum AggregationVariants {
}
impl AggregationVariants {
/// Returns the name of the field used by the aggregation.
pub fn get_fast_field_name(&self) -> &str {
fn get_fast_field_name(&self) -> &str {
match self {
AggregationVariants::Terms(terms) => terms.field.as_str(),
AggregationVariants::Range(range) => range.field.as_str(),

View File

@@ -13,7 +13,6 @@ use super::metric::{
};
use super::segment_agg_result::AggregationLimits;
use super::VecWithNames;
use crate::aggregation::{f64_to_fastfield_u64, Key};
use crate::SegmentReader;
#[derive(Default)]
@@ -36,242 +35,96 @@ pub struct AggregationWithAccessor {
/// based on search terms. That is not that case currently, but eventually this needs to be
/// Option or moved.
pub(crate) accessor: Column<u64>,
/// Load insert u64 for missing use case
pub(crate) missing_value_for_accessor: Option<u64>,
pub(crate) str_dict_column: Option<StrColumn>,
pub(crate) field_type: ColumnType,
/// In case there are multiple types of fast fields, e.g. string and numeric.
/// Only used for term aggregations currently.
pub(crate) accessor2: Option<(Column<u64>, ColumnType)>,
pub(crate) sub_aggregation: AggregationsWithAccessor,
pub(crate) limits: ResourceLimitGuard,
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
/// Used for missing term aggregation, which checks all columns for existence.
/// 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.
pub(crate) accessors: Vec<Column<u64>>,
pub(crate) agg: Aggregation,
}
impl AggregationWithAccessor {
/// May return multiple accessors if the aggregation is e.g. on mixed field types.
fn try_from_agg(
agg: &Aggregation,
sub_aggregation: &Aggregations,
reader: &SegmentReader,
limits: AggregationLimits,
) -> crate::Result<Vec<AggregationWithAccessor>> {
let add_agg_with_accessor = |accessor: Column<u64>,
column_type: ColumnType,
aggs: &mut Vec<AggregationWithAccessor>|
-> crate::Result<()> {
let res = AggregationWithAccessor {
accessor,
accessors: Vec::new(),
field_type: column_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
sub_aggregation,
reader,
&limits,
)?,
agg: agg.clone(),
limits: limits.new_guard(),
missing_value_for_accessor: None,
str_dict_column: None,
column_block_accessor: Default::default(),
};
aggs.push(res);
Ok(())
};
let mut res: Vec<AggregationWithAccessor> = Vec::new();
) -> crate::Result<AggregationWithAccessor> {
let mut str_dict_column = None;
let mut accessor2 = None;
use AggregationVariants::*;
match &agg.agg {
let (accessor, field_type) = match &agg.agg {
Range(RangeAggregation {
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
}) => get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?,
Histogram(HistogramAggregation {
field: field_name, ..
}) => {
let (accessor, column_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
}
}) => get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?,
DateHistogram(DateHistogramAggregationReq {
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(accessor, column_type, &mut res)?;
}
}) => get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?,
Terms(TermsAggregation {
field: field_name,
missing,
..
field: field_name, ..
}) => {
let str_dict_column = reader.fast_fields().str(field_name)?;
str_dict_column = reader.fast_fields().str(field_name)?;
let allowed_column_types = [
ColumnType::I64,
ColumnType::U64,
ColumnType::F64,
ColumnType::Str,
ColumnType::DateTime,
// ColumnType::Bytes Unsupported
// ColumnType::Bool Unsupported
// ColumnType::IpAddr Unsupported
// ColumnType::DateTime Unsupported
];
// In case the column is empty we want the shim column to match the missing type
let fallback_type = missing
.as_ref()
.map(|missing| match missing {
Key::Str(_) => ColumnType::Str,
Key::F64(_) => ColumnType::F64,
})
.unwrap_or(ColumnType::U64);
let column_and_types = get_all_ff_reader_or_empty(
reader,
field_name,
Some(&allowed_column_types),
fallback_type,
)?;
let missing_and_more_than_one_col = column_and_types.len() > 1 && missing.is_some();
let text_on_non_text_col = column_and_types.len() == 1
&& column_and_types[0].1.numerical_type().is_some()
&& missing
.as_ref()
.map(|m| matches!(m, Key::Str(_)))
.unwrap_or(false);
// Actually we could convert the text to a number and have the fast path, if it is
// provided in Rfc3339 format. But this use case is probably common
// enough to justify the effort.
let text_on_date_col = column_and_types.len() == 1
&& column_and_types[0].1 == ColumnType::DateTime
&& missing
.as_ref()
.map(|m| matches!(m, Key::Str(_)))
.unwrap_or(false);
let use_special_missing_agg =
missing_and_more_than_one_col || text_on_non_text_col || text_on_date_col;
if use_special_missing_agg {
let column_and_types =
get_all_ff_reader_or_empty(reader, field_name, None, fallback_type)?;
let accessors: 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 {
let missing_value_term_agg = if use_special_missing_agg {
None
} else {
missing.clone()
};
let missing_value_for_accessor =
if let Some(missing) = missing_value_term_agg.as_ref() {
get_missing_val(column_type, missing, agg.agg.get_fast_field_name())?
} else {
None
};
let agg = AggregationWithAccessor {
missing_value_for_accessor,
accessor,
accessors: Vec::new(),
field_type: column_type,
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);
}
let mut columns =
get_all_ff_reader_or_empty(reader, field_name, Some(&allowed_column_types))?;
let first = columns.pop().unwrap();
accessor2 = columns.pop();
first
}
Average(AverageAggregation {
field: field_name, ..
})
| Count(CountAggregation {
field: field_name, ..
})
| Max(MaxAggregation {
field: field_name, ..
})
| Min(MinAggregation {
field: field_name, ..
})
| Stats(StatsAggregation {
field: field_name, ..
})
| Sum(SumAggregation {
field: field_name, ..
}) => {
let (accessor, column_type) =
Average(AverageAggregation { field: field_name })
| Count(CountAggregation { field: field_name })
| Max(MaxAggregation { field: field_name })
| Min(MinAggregation { field: field_name })
| Stats(StatsAggregation { field: field_name })
| Sum(SumAggregation { field: field_name }) => {
let (accessor, field_type) =
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
(accessor, field_type)
}
Percentiles(percentiles) => {
let (accessor, column_type) = get_ff_reader(
let (accessor, field_type) = get_ff_reader(
reader,
percentiles.field_name(),
Some(get_numeric_or_date_column_types()),
)?;
add_agg_with_accessor(accessor, column_type, &mut res)?;
(accessor, field_type)
}
};
Ok(res)
let sub_aggregation = sub_aggregation.clone();
Ok(AggregationWithAccessor {
accessor,
accessor2,
field_type,
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
&sub_aggregation,
reader,
&limits,
)?,
agg: agg.clone(),
str_dict_column,
limits: limits.new_guard(),
column_block_accessor: Default::default(),
})
}
}
fn get_missing_val(
column_type: ColumnType,
missing: &Key,
field_name: &str,
) -> crate::Result<Option<u64>> {
let missing_val = match missing {
Key::Str(_) if column_type == ColumnType::Str => Some(u64::MAX),
// Allow fallback to number on text fields
Key::F64(_) if column_type == ColumnType::Str => Some(u64::MAX),
Key::F64(val) if column_type.numerical_type().is_some() => {
f64_to_fastfield_u64(*val, &column_type)
}
_ => {
return Err(crate::TantivyError::InvalidArgument(format!(
"Missing value {:?} for field {} is not supported for column type {:?}",
missing, field_name, column_type
)));
}
};
Ok(missing_val)
}
fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
&[
ColumnType::F64,
@@ -288,15 +141,15 @@ pub(crate) fn get_aggs_with_segment_accessor_and_validate(
) -> crate::Result<AggregationsWithAccessor> {
let mut aggss = Vec::new();
for (key, agg) in aggs.iter() {
let aggs = AggregationWithAccessor::try_from_agg(
agg,
agg.sub_aggregation(),
reader,
limits.clone(),
)?;
for agg in aggs {
aggss.push((key.to_string(), agg));
}
aggss.push((
key.to_string(),
AggregationWithAccessor::try_from_agg(
agg,
agg.sub_aggregation(),
reader,
limits.clone(),
)?,
));
}
Ok(AggregationsWithAccessor::from_data(
VecWithNames::from_entries(aggss),
@@ -328,13 +181,15 @@ fn get_all_ff_reader_or_empty(
reader: &SegmentReader,
field_name: &str,
allowed_column_types: Option<&[ColumnType]>,
fallback_type: ColumnType,
) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
let ff_fields = reader.fast_fields();
let mut ff_field_with_type =
ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
if ff_field_with_type.is_empty() {
ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
ff_field_with_type.push((
Column::build_empty_column(reader.num_docs()),
ColumnType::U64,
));
}
Ok(ff_field_with_type)
}

View File

@@ -9,7 +9,7 @@ use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_v
use crate::aggregation::DistributedAggregationCollector;
use crate::query::{AllQuery, TermQuery};
use crate::schema::{IndexRecordOption, Schema, FAST};
use crate::{Index, IndexWriter, Term};
use crate::{Index, Term};
fn get_avg_req(field_name: &str) -> Aggregation {
serde_json::from_value(json!({
@@ -558,10 +558,10 @@ fn test_aggregation_invalid_requests() -> crate::Result<()> {
assert_eq!(agg_req_1.is_err(), true);
// TODO: This should list valid values
assert!(agg_req_1
.unwrap_err()
.to_string()
.contains("unknown variant `doesnotmatchanyagg`, expected one of"));
assert_eq!(
agg_req_1.unwrap_err().to_string(),
"no variant of enum AggregationVariants found in flattened data"
);
// TODO: This should return an error
// let agg_res = avg_on_field("not_exist_field").unwrap_err();
@@ -586,7 +586,7 @@ fn test_aggregation_on_json_object() {
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
index_writer
.add_document(doc!(json => json!({"color": "red"})))
.unwrap();
@@ -624,72 +624,13 @@ fn test_aggregation_on_json_object() {
);
}
#[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.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": 1, "key": "blue"},
{"doc_count": 1, "key": "red"}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
},
"jsonagg2": {
"buckets": [
{"doc_count": 1, "key": "blue"},
{"doc_count": 1, "key": "red"}
],
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0
}
})
);
}
#[test]
fn test_aggregation_on_json_object_empty_columns() {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
// => Empty column when accessing color
index_writer
.add_document(doc!(json => json!({"price": 10.0})))
@@ -807,7 +748,7 @@ fn test_aggregation_on_json_object_mixed_types() {
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(json => json!({"mixed_type": 10.0})))

View File

@@ -132,7 +132,6 @@ impl DateHistogramAggregationReq {
hard_bounds: self.hard_bounds,
extended_bounds: self.extended_bounds,
keyed: self.keyed,
is_normalized_to_ns: false,
})
}
@@ -244,15 +243,15 @@ fn parse_into_milliseconds(input: &str) -> Result<i64, AggregationError> {
}
#[cfg(test)]
pub mod tests {
mod tests {
use pretty_assertions::assert_eq;
use super::*;
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::tests::exec_request;
use crate::indexer::NoMergePolicy;
use crate::schema::{Schema, FAST, STRING};
use crate::{Index, IndexWriter, TantivyDocument};
use crate::schema::{Schema, FAST};
use crate::Index;
#[test]
fn test_parse_into_millisecs() {
@@ -307,8 +306,7 @@ pub mod tests {
) -> crate::Result<Index> {
let mut schema_builder = Schema::builder();
schema_builder.add_date_field("date", FAST);
schema_builder.add_text_field("text", FAST | STRING);
schema_builder.add_text_field("text2", FAST | STRING);
schema_builder.add_text_field("text", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
{
@@ -316,7 +314,7 @@ pub mod tests {
index_writer.set_merge_policy(Box::new(NoMergePolicy));
for values in segment_and_docs {
for doc_str in values {
let doc = TantivyDocument::parse_json(&schema, doc_str)?;
let doc = schema.parse_document(doc_str)?;
index_writer.add_document(doc)?;
}
// writing the segment
@@ -328,7 +326,7 @@ pub mod tests {
.searchable_segment_ids()
.expect("Searchable segments failed.");
if segment_ids.len() > 1 {
let mut index_writer: IndexWriter = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests()?;
index_writer.merge(&segment_ids).wait()?;
index_writer.wait_merging_threads()?;
}

View File

@@ -122,14 +122,11 @@ pub struct HistogramAggregation {
/// Whether to return the buckets as a hash map
#[serde(default)]
pub keyed: bool,
/// Whether the values are normalized to ns for date time values. Defaults to false.
#[serde(default)]
pub is_normalized_to_ns: bool,
}
impl HistogramAggregation {
pub(crate) fn normalize_date_time(&mut self) {
if !self.is_normalized_to_ns {
pub(crate) fn normalize(&mut self, column_type: ColumnType) {
if column_type.is_date_time() {
// values are provided in ms, but the fastfield is in nano seconds
self.interval *= 1_000_000.0;
self.offset = self.offset.map(|off| off * 1_000_000.0);
@@ -141,7 +138,6 @@ impl HistogramAggregation {
min: bounds.min * 1_000_000.0,
max: bounds.max * 1_000_000.0,
});
self.is_normalized_to_ns = true;
}
}
@@ -355,7 +351,6 @@ impl SegmentHistogramCollector {
let buckets_mem = self.buckets.memory_consumption();
self_mem + sub_aggs_mem + buckets_mem
}
/// Converts the collector result into a intermediate bucket result.
pub fn into_intermediate_bucket_result(
self,
agg_with_accessor: &AggregationWithAccessor,
@@ -374,7 +369,7 @@ impl SegmentHistogramCollector {
Ok(IntermediateBucketResult::Histogram {
buckets,
is_date_agg: self.column_type == ColumnType::DateTime,
column_type: Some(self.column_type),
})
}
@@ -385,9 +380,7 @@ impl SegmentHistogramCollector {
accessor_idx: usize,
) -> crate::Result<Self> {
req.validate()?;
if field_type == ColumnType::DateTime {
req.normalize_date_time();
}
req.normalize(field_type);
let sub_aggregation_blueprint = if sub_aggregation.is_empty() {
None
@@ -445,7 +438,6 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
// memory check upfront
let (_, first_bucket_num, last_bucket_num) =
generate_bucket_pos_with_opt_minmax(histogram_req, min_max);
// It's based on user input, so we need to account for overflows
let added_buckets = ((last_bucket_num.saturating_sub(first_bucket_num)).max(0) as u64)
.saturating_sub(buckets.len() as u64);
@@ -461,12 +453,15 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
let final_buckets: Vec<BucketEntry> = buckets
.into_iter()
.merge_join_by(fill_gaps_buckets, |existing_bucket, fill_gaps_bucket| {
existing_bucket
.key
.partial_cmp(fill_gaps_bucket)
.unwrap_or(Ordering::Equal)
})
.merge_join_by(
fill_gaps_buckets.into_iter(),
|existing_bucket, fill_gaps_bucket| {
existing_bucket
.key
.partial_cmp(fill_gaps_bucket)
.unwrap_or(Ordering::Equal)
},
)
.map(|either| match either {
// Ignore the generated bucket
itertools::EitherOrBoth::Both(existing, _) => existing,
@@ -489,7 +484,7 @@ fn intermediate_buckets_to_final_buckets_fill_gaps(
// Convert to BucketEntry
pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
buckets: Vec<IntermediateHistogramBucketEntry>,
is_date_agg: bool,
column_type: Option<ColumnType>,
histogram_req: &HistogramAggregation,
sub_aggregation: &Aggregations,
limits: &AggregationLimits,
@@ -498,8 +493,8 @@ pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
// The request used in the the call to final is not yet be normalized.
// Normalization is changing the precision from milliseconds to nanoseconds.
let mut histogram_req = histogram_req.clone();
if is_date_agg {
histogram_req.normalize_date_time();
if let Some(column_type) = column_type {
histogram_req.normalize(column_type);
}
let mut buckets = if histogram_req.min_doc_count() == 0 {
// With min_doc_count != 0, we may need to add buckets, so that there are no
@@ -523,7 +518,7 @@ pub(crate) fn intermediate_histogram_buckets_to_final_buckets(
// If we have a date type on the histogram buckets, we add the `key_as_string` field as rfc339
// and normalize from nanoseconds to milliseconds
if is_date_agg {
if column_type == Some(ColumnType::DateTime) {
for bucket in buckets.iter_mut() {
if let crate::aggregation::Key::F64(ref mut val) = bucket.key {
let key_as_string = format_date(*val as i64)?;

View File

@@ -25,15 +25,15 @@
mod histogram;
mod range;
mod term_agg;
mod term_missing_agg;
use std::collections::HashMap;
pub(crate) use histogram::SegmentHistogramCollector;
pub use histogram::*;
pub(crate) use range::SegmentRangeCollector;
pub use range::*;
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
pub use term_agg::*;
pub use term_missing_agg::*;
/// Order for buckets in a bucket aggregation.
#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize, Default)]

View File

@@ -262,7 +262,7 @@ impl SegmentRangeCollector {
pub(crate) fn from_req_and_validate(
req: &RangeAggregation,
sub_aggregation: &mut AggregationsWithAccessor,
limits: &ResourceLimitGuard,
limits: &mut ResourceLimitGuard,
field_type: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
@@ -465,7 +465,7 @@ mod tests {
SegmentRangeCollector::from_req_and_validate(
&req,
&mut Default::default(),
&AggregationLimits::default().new_guard(),
&mut AggregationLimits::default().new_guard(),
field_type,
0,
)

View File

@@ -1,6 +1,6 @@
use std::fmt::Debug;
use columnar::{BytesColumn, ColumnType, MonotonicallyMappableToU64, StrColumn};
use columnar::ColumnType;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
@@ -9,6 +9,7 @@ use crate::aggregation::agg_limits::MemoryConsumption;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::f64_from_fastfield_u64;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
@@ -16,7 +17,6 @@ use crate::aggregation::intermediate_agg_result::{
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
use crate::aggregation::{f64_from_fastfield_u64, format_date, Key};
use crate::error::DataCorruption;
use crate::TantivyError;
@@ -146,28 +146,6 @@ pub struct TermsAggregation {
/// { "average_price": "asc" }
#[serde(skip_serializing_if = "Option::is_none", default)]
pub order: Option<CustomOrder>,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "missing": "NO_DATA" }
///
/// # Internal
///
/// Internally, `missing` requires some specialized handling in some scenarios.
///
/// Simple Case:
/// In the simplest case, we can just put the missing value in the termmap use that. In case of
/// text we put a special u64::MAX and replace it at the end with the actual missing value,
/// when loading the text.
/// Special Case 1:
/// If we have multiple columns on one field, we need to have a union on the indices on both
/// columns, to find docids without a value. That requires a special missing aggreggation.
/// Special Case 2: if the key is of type text and the column is numerical, we also need to use
/// the special missing aggregation, since there is no mechanism in the numerical column to
/// add text.
#[serde(skip_serializing_if = "Option::is_none", default)]
pub missing: Option<Key>,
}
/// Same as TermsAggregation, but with populated defaults.
@@ -198,7 +176,6 @@ pub(crate) struct TermsAggregationInternal {
pub min_doc_count: u64,
pub order: CustomOrder,
pub missing: Option<Key>,
}
impl TermsAggregationInternal {
@@ -218,7 +195,6 @@ impl TermsAggregationInternal {
.unwrap_or_else(|| order == CustomOrder::default()),
min_doc_count: req.min_doc_count.unwrap_or(1),
order,
missing: req.missing.clone(),
}
}
}
@@ -248,6 +224,110 @@ impl TermBuckets {
}
}
/// The composite collector is used, when we have different types under one field, to support a term
/// aggregation on both.
#[derive(Clone, Debug)]
pub struct SegmentTermCollectorComposite {
term_agg1: SegmentTermCollector, // field type 1, e.g. strings
term_agg2: SegmentTermCollector, // field type 2, e.g. u64
accessor_idx: usize,
}
impl SegmentAggregationCollector for SegmentTermCollectorComposite {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
let bucket = self
.term_agg1
.into_intermediate_bucket_result(agg_with_accessor)?;
results.push(
name.to_string(),
IntermediateAggregationResult::Bucket(bucket),
)?;
let bucket = self
.term_agg2
.into_intermediate_bucket_result(agg_with_accessor)?;
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
}
#[inline]
fn collect(
&mut self,
doc: crate::DocId,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.term_agg1.collect_block(&[doc], agg_with_accessor)?;
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
self.term_agg2.collect_block(&[doc], agg_with_accessor)?;
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
Ok(())
}
#[inline]
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
self.term_agg1.collect_block(docs, agg_with_accessor)?;
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
self.term_agg2.collect_block(docs, agg_with_accessor)?;
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
Ok(())
}
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
self.term_agg1.flush(agg_with_accessor)?;
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
self.term_agg2.flush(agg_with_accessor)?;
self.swap_accessor(&mut agg_with_accessor.aggs.values[self.accessor_idx]);
Ok(())
}
}
impl SegmentTermCollectorComposite {
/// Swaps the accessor and field type with the second accessor and field type.
/// This way we can use the same code for both aggregations.
fn swap_accessor(&self, aggregations: &mut AggregationWithAccessor) {
if let Some(accessor) = aggregations.accessor2.as_mut() {
std::mem::swap(&mut accessor.0, &mut aggregations.accessor);
std::mem::swap(&mut accessor.1, &mut aggregations.field_type);
}
}
pub(crate) fn from_req_and_validate(
req: &TermsAggregation,
sub_aggregations: &mut AggregationsWithAccessor,
field_type: ColumnType,
field_type2: ColumnType,
accessor_idx: usize,
) -> crate::Result<Self> {
Ok(Self {
term_agg1: SegmentTermCollector::from_req_and_validate(
req,
sub_aggregations,
field_type,
accessor_idx,
)?,
term_agg2: SegmentTermCollector::from_req_and_validate(
req,
sub_aggregations,
field_type2,
accessor_idx,
)?,
accessor_idx,
})
}
}
/// The collector puts values from the fast field into the correct buckets and does a conversion to
/// the correct datatype.
#[derive(Clone, Debug)]
@@ -299,16 +379,9 @@ impl SegmentAggregationCollector for SegmentTermCollector {
let mem_pre = self.get_memory_consumption();
if let Some(missing) = bucket_agg_accessor.missing_value_for_accessor {
bucket_agg_accessor
.column_block_accessor
.fetch_block_with_missing(docs, &bucket_agg_accessor.accessor, missing);
} else {
bucket_agg_accessor
.column_block_accessor
.fetch_block(docs, &bucket_agg_accessor.accessor);
}
bucket_agg_accessor
.column_block_accessor
.fetch_block(docs, &bucket_agg_accessor.accessor);
for term_id in bucket_agg_accessor.column_block_accessor.iter_vals() {
let entry = self.term_buckets.entries.entry(term_id).or_default();
*entry += 1;
@@ -470,42 +543,19 @@ impl SegmentTermCollector {
let term_dict = agg_with_accessor
.str_dict_column
.as_ref()
.cloned()
.unwrap_or_else(|| {
StrColumn::wrap(BytesColumn::empty(agg_with_accessor.accessor.num_docs()))
});
.expect("internal error: term dictionary not found for term aggregation");
let mut buffer = String::new();
for (term_id, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(term_id, doc_count)?;
// Special case for missing key
if term_id == u64::MAX {
let missing_key = self
.req
.missing
.as_ref()
.expect("Found placeholder term_id but `missing` is None");
match missing_key {
Key::Str(missing) => {
buffer.clear();
buffer.push_str(missing);
dict.insert(
IntermediateKey::Str(buffer.to_string()),
intermediate_entry,
);
}
Key::F64(val) => {
buffer.push_str(&val.to_string());
dict.insert(IntermediateKey::F64(*val), intermediate_entry);
}
}
} else {
if !term_dict.ord_to_str(term_id, &mut buffer)? {
return Err(TantivyError::InternalError(format!(
"Couldn't find term_id {term_id} in dict"
)));
}
dict.insert(IntermediateKey::Str(buffer.to_string()), intermediate_entry);
if !term_dict.ord_to_str(term_id, &mut buffer)? {
return Err(TantivyError::InternalError(format!(
"Couldn't find term_id {term_id} in dict"
)));
}
let intermediate_entry = into_intermediate_bucket_entry(term_id, doc_count)?;
dict.insert(IntermediateKey::Str(buffer.to_string()), intermediate_entry);
}
if self.req.min_doc_count == 0 {
// TODO: Handle rev streaming for descending sorting by keys
@@ -531,13 +581,6 @@ impl SegmentTermCollector {
});
}
}
} 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 {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
@@ -590,9 +633,6 @@ pub(crate) fn cut_off_buckets<T: GetDocCount + Debug>(
#[cfg(test)]
mod tests {
use common::DateTime;
use time::{Date, Month};
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::tests::{
exec_request, exec_request_with_query, exec_request_with_query_and_memory_limit,
@@ -601,7 +641,7 @@ mod tests {
use crate::aggregation::AggregationLimits;
use crate::indexer::NoMergePolicy;
use crate::schema::{Schema, FAST, STRING};
use crate::{Index, IndexWriter};
use crate::Index;
#[test]
fn terms_aggregation_test_single_segment() -> crate::Result<()> {
@@ -1253,13 +1293,13 @@ mod tests {
// searching for terma, but min_doc_count will return all terms
let res = exec_request_with_query(agg_req, &index, Some(("string2", "hit")))?;
assert_eq!(res["my_texts"]["buckets"][0]["key"], "A");
assert_eq!(res["my_texts"]["buckets"][0]["key"], "a");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 2);
assert_eq!(
res["my_texts"]["buckets"][0]["elhistogram"]["buckets"],
json!([{ "doc_count": 1, "key": 1.0 }, { "doc_count": 1, "key": 2.0 } ])
);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "B");
assert_eq!(res["my_texts"]["buckets"][1]["key"], "b");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 1);
assert_eq!(
res["my_texts"]["buckets"][1]["elhistogram"]["buckets"],
@@ -1281,7 +1321,6 @@ mod tests {
];
let index = get_test_index_from_terms(false, &terms_per_segment)?;
assert_eq!(index.searchable_segments().unwrap().len(), 2);
let agg_req: Aggregations = serde_json::from_value(json!({
"my_texts": {
@@ -1382,10 +1421,10 @@ mod tests {
let res = exec_request_with_query(agg_req, &index, None).unwrap();
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]["key"], "hallo hallo");
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]["key"], "hello hello");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 1);
Ok(())
@@ -1467,47 +1506,6 @@ mod tests {
Ok(())
}
#[test]
fn terms_empty_json() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with empty json
index_writer.add_document(doc!()).unwrap();
index_writer.commit().unwrap();
// => Segment with json, but no field partially_empty
index_writer
.add_document(doc!(json => json!({"different_field": "blue"})))
.unwrap();
index_writer.commit().unwrap();
//// => Segment with field partially_empty
index_writer
.add_document(doc!(json => json!({"partially_empty": "blue"})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"my_texts": {
"terms": {
"field": "json.partially_empty"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(res["my_texts"]["buckets"][0]["key"], "blue");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 1);
assert_eq!(res["my_texts"]["buckets"][1], serde_json::Value::Null);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_bytes() -> crate::Result<()> {
@@ -1545,353 +1543,4 @@ mod tests {
Ok(())
}
#[test]
fn terms_aggregation_missing_multi_value() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", FAST);
let id_field = schema_builder.add_u64_field("id", FAST);
let index = Index::create_in_ram(schema_builder.build());
{
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
index_writer.set_merge_policy(Box::new(NoMergePolicy));
index_writer.add_document(doc!(
text_field => "Hello Hello",
text_field => "Hello Hello",
id_field => 1u64,
id_field => 1u64,
))?;
// Missing
index_writer.add_document(doc!())?;
index_writer.add_document(doc!(
text_field => "Hello Hello",
))?;
index_writer.add_document(doc!(
text_field => "Hello Hello",
))?;
index_writer.commit()?;
// Empty segment special case
index_writer.add_document(doc!())?;
index_writer.commit()?;
// Full segment special case
index_writer.add_document(doc!(
text_field => "Hello Hello",
id_field => 1u64,
))?;
index_writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_texts": {
"terms": {
"field": "text",
"missing": "Empty"
},
},
"my_texts2": {
"terms": {
"field": "text",
"missing": 1337
},
},
"my_ids": {
"terms": {
"field": "id",
"missing": 1337
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Hello Hello");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 5);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Empty");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
assert_eq!(
res["my_texts"]["buckets"][2]["key"],
serde_json::Value::Null
);
// text field with numner as missing fallback
assert_eq!(res["my_texts2"]["buckets"][0]["key"], "Hello Hello");
assert_eq!(res["my_texts2"]["buckets"][0]["doc_count"], 5);
assert_eq!(res["my_texts2"]["buckets"][1]["key"], 1337.0);
assert_eq!(res["my_texts2"]["buckets"][1]["doc_count"], 2);
assert_eq!(
res["my_texts2"]["buckets"][2]["key"],
serde_json::Value::Null
);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
// id field
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_ids"]["buckets"][1]["key"], 1.0);
assert_eq!(res["my_ids"]["buckets"][1]["doc_count"], 3);
assert_eq!(res["my_ids"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
#[test]
fn terms_aggregation_missing_simple_id() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let id_field = schema_builder.add_u64_field("id", FAST);
let index = Index::create_in_ram(schema_builder.build());
{
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
index_writer.set_merge_policy(Box::new(NoMergePolicy));
index_writer.add_document(doc!(
id_field => 1u64,
))?;
// Missing
index_writer.add_document(doc!())?;
index_writer.add_document(doc!())?;
index_writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_ids": {
"terms": {
"field": "id",
"missing": 1337
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// id field
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_ids"]["buckets"][1]["key"], 1.0);
assert_eq!(res["my_ids"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_ids"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
#[test]
fn terms_aggregation_missing1() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", FAST);
let id_field = schema_builder.add_u64_field("id", FAST);
let index = Index::create_in_ram(schema_builder.build());
{
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
index_writer.set_merge_policy(Box::new(NoMergePolicy));
index_writer.add_document(doc!(
text_field => "Hello Hello",
id_field => 1u64,
))?;
// Missing
index_writer.add_document(doc!())?;
index_writer.add_document(doc!(
text_field => "Hello Hello",
))?;
index_writer.add_document(doc!(
text_field => "Hello Hello",
))?;
index_writer.commit()?;
// Empty segment special case
index_writer.add_document(doc!())?;
index_writer.commit()?;
// Full segment special case
index_writer.add_document(doc!(
text_field => "Hello Hello",
id_field => 1u64,
))?;
index_writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_texts": {
"terms": {
"field": "text",
"missing": "Empty"
},
},
"my_texts2": {
"terms": {
"field": "text",
"missing": 1337
},
},
"my_ids": {
"terms": {
"field": "id",
"missing": 1337
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Hello Hello");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "Empty");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 2);
assert_eq!(
res["my_texts"]["buckets"][2]["key"],
serde_json::Value::Null
);
// text field with numner as missing fallback
assert_eq!(res["my_texts2"]["buckets"][0]["key"], "Hello Hello");
assert_eq!(res["my_texts2"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_texts2"]["buckets"][1]["key"], 1337.0);
assert_eq!(res["my_texts2"]["buckets"][1]["doc_count"], 2);
assert_eq!(
res["my_texts2"]["buckets"][2]["key"],
serde_json::Value::Null
);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
// id field
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_ids"]["buckets"][1]["key"], 1.0);
assert_eq!(res["my_ids"]["buckets"][1]["doc_count"], 2);
assert_eq!(res["my_ids"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
#[test]
fn terms_aggregation_missing_empty() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
schema_builder.add_text_field("text", FAST);
schema_builder.add_u64_field("id", FAST);
let index = Index::create_in_ram(schema_builder.build());
{
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
index_writer.set_merge_policy(Box::new(NoMergePolicy));
// Empty segment special case
index_writer.add_document(doc!())?;
index_writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_texts": {
"terms": {
"field": "text",
"missing": "Empty"
},
},
"my_texts2": {
"terms": {
"field": "text",
"missing": 1337
},
},
"my_ids": {
"terms": {
"field": "id",
"missing": 1337
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["my_texts"]["buckets"][0]["key"], "Empty");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 1);
assert_eq!(
res["my_texts"]["buckets"][1]["key"],
serde_json::Value::Null
);
// text field with number as missing fallback
assert_eq!(res["my_texts2"]["buckets"][0]["key"], 1337.0);
assert_eq!(res["my_texts2"]["buckets"][0]["doc_count"], 1);
assert_eq!(
res["my_texts2"]["buckets"][1]["key"],
serde_json::Value::Null
);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
// id field
assert_eq!(res["my_ids"]["buckets"][0]["key"], 1337.0);
assert_eq!(res["my_ids"]["buckets"][0]["doc_count"], 1);
assert_eq!(res["my_ids"]["buckets"][1]["key"], serde_json::Value::Null);
Ok(())
}
#[test]
fn terms_aggregation_date() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field("date_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1983, Month::September, 27)?.with_hms(0, 0, 0)?)))?;
writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_date": {
"terms": {
"field": "date_field"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// date_field field
assert_eq!(res["my_date"]["buckets"][0]["key"], "1982-09-17T00:00:00Z");
assert_eq!(res["my_date"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_date"]["buckets"][1]["key"], "1983-09-27T00:00:00Z");
assert_eq!(res["my_date"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_date"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
#[test]
fn terms_aggregation_date_missing() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let date_field = schema_builder.add_date_field("date_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1983, Month::September, 27)?.with_hms(0, 0, 0)?)))?;
writer.add_document(doc!())?;
writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_date": {
"terms": {
"field": "date_field",
"missing": "1982-09-17T00:00:00Z"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// date_field field
assert_eq!(res["my_date"]["buckets"][0]["key"], "1982-09-17T00:00:00Z");
assert_eq!(res["my_date"]["buckets"][0]["doc_count"], 3);
assert_eq!(res["my_date"]["buckets"][1]["key"], "1983-09-27T00:00:00Z");
assert_eq!(res["my_date"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_date"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
}

View File

@@ -1,476 +0,0 @@
use rustc_hash::FxHashMap;
use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
};
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
};
/// The specialized missing term aggregation.
#[derive(Default, Debug, Clone)]
pub struct TermMissingAgg {
missing_count: u32,
accessor_idx: usize,
sub_agg: Option<Box<dyn SegmentAggregationCollector>>,
}
impl TermMissingAgg {
pub(crate) fn new(
accessor_idx: usize,
sub_aggregations: &mut AggregationsWithAccessor,
) -> crate::Result<Self> {
let has_sub_aggregations = !sub_aggregations.is_empty();
let sub_agg = if has_sub_aggregations {
let sub_aggregation = build_segment_agg_collector(sub_aggregations)?;
Some(sub_aggregation)
} else {
None
};
Ok(Self {
accessor_idx,
sub_agg,
..Default::default()
})
}
}
impl SegmentAggregationCollector for TermMissingAgg {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_with_accessor: &AggregationsWithAccessor,
results: &mut IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
let term_agg = agg_with_accessor
.agg
.agg
.as_term()
.expect("TermMissingAgg collector must be term agg req");
let missing = term_agg
.missing
.as_ref()
.expect("TermMissingAgg collector, but no missing found in agg req")
.clone();
let mut entries: FxHashMap<IntermediateKey, IntermediateTermBucketEntry> =
Default::default();
let mut missing_entry = IntermediateTermBucketEntry {
doc_count: self.missing_count,
sub_aggregation: Default::default(),
};
if let Some(sub_agg) = self.sub_agg {
let mut res = IntermediateAggregationResults::default();
sub_agg.add_intermediate_aggregation_result(
&agg_with_accessor.sub_aggregation,
&mut res,
)?;
missing_entry.sub_aggregation = res;
}
entries.insert(missing.into(), missing_entry);
let bucket = IntermediateBucketResult::Terms(IntermediateTermBucketResult {
entries,
sum_other_doc_count: 0,
doc_count_error_upper_bound: 0,
});
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
Ok(())
}
fn collect(
&mut self,
doc: crate::DocId,
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let agg = &mut agg_with_accessor.aggs.values[self.accessor_idx];
let has_value = agg.accessors.iter().any(|acc| acc.index.has_value(doc));
if !has_value {
self.missing_count += 1;
if let Some(sub_agg) = self.sub_agg.as_mut() {
sub_agg.collect(doc, &mut agg.sub_aggregation)?;
}
}
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
for doc in docs {
self.collect(*doc, agg_with_accessor)?;
}
Ok(())
}
}
#[cfg(test)]
mod tests {
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::tests::exec_request_with_query;
use crate::schema::{Schema, FAST};
use crate::{Index, IndexWriter};
#[test]
fn terms_aggregation_missing_mixed_type_mult_seg_sub_agg() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let score = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(score => 1.0, json => json!({"mixed_type": 10.0})))
.unwrap();
index_writer.add_document(doc!(score => 5.0))?;
// index_writer.commit().unwrap();
//// => Segment with all values text
index_writer
.add_document(doc!(score => 1.0, json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer.add_document(doc!(score => 5.0))?;
// index_writer.commit().unwrap();
// => Segment with mixed values
index_writer.add_document(doc!(json => json!({"mixed_type": "red"})))?;
index_writer.add_document(doc!(json => json!({"mixed_type": -20.5})))?;
index_writer.add_document(doc!(json => json!({"mixed_type": true})))?;
index_writer.add_document(doc!(score => 5.0))?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
"aggs": {
"sum_score": {
"sum": {
"field": "score"
}
}
}
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
assert_eq!(
res["replace_null"]["buckets"][0]["sum_score"]["value"],
15.0
);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_missing_mixed_type_sub_agg_reg1() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let score = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer.add_document(doc!(score => 1.0, json => json!({"mixed_type": 10.0})))?;
index_writer.add_document(doc!(score => 5.0))?;
index_writer.add_document(doc!(score => 5.0))?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
"aggs": {
"sum_score": {
"sum": {
"field": "score"
}
}
}
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 2);
assert_eq!(
res["replace_null"]["buckets"][0]["sum_score"]["value"],
10.0
);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_missing_mult_seg_empty() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let score = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
index_writer.add_document(doc!(score => 5.0))?;
index_writer.commit().unwrap();
index_writer.add_document(doc!(score => 5.0))?;
index_writer.commit().unwrap();
index_writer.add_document(doc!(score => 5.0))?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
"aggs": {
"sum_score": {
"sum": {
"field": "score"
}
}
}
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
assert_eq!(
res["replace_null"]["buckets"][0]["sum_score"]["value"],
15.0
);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_missing_single_seg_empty() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let score = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
index_writer.add_document(doc!(score => 5.0))?;
index_writer.add_document(doc!(score => 5.0))?;
index_writer.add_document(doc!(score => 5.0))?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
"aggs": {
"sum_score": {
"sum": {
"field": "score"
}
}
}
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
assert_eq!(
res["replace_null"]["buckets"][0]["sum_score"]["value"],
15.0
);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_missing_mixed_type_mult_seg() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(json => json!({"mixed_type": 10.0})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
//// => Segment with all values text
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
// => Segment with mixed values
index_writer
.add_document(doc!(json => json!({"mixed_type": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": -20.5})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": true})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
},
"replace_num": {
"terms": {
"field": "json.mixed_type",
"missing": 1337
},
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
assert_eq!(res["replace_num"]["buckets"][0]["key"], 1337.0);
assert_eq!(res["replace_num"]["buckets"][0]["doc_count"], 3);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_missing_str_on_numeric_field() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(json => json!({"mixed_type": 10.0})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.add_document(doc!())?;
index_writer
.add_document(doc!(json => json!({"mixed_type": -20.5})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
#[test]
fn terms_aggregation_missing_mixed_type_one_seg() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(json => json!({"mixed_type": 10.0})))
.unwrap();
index_writer.add_document(doc!())?;
//// => Segment with all values text
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer.add_document(doc!())?;
// => Segment with mixed values
index_writer
.add_document(doc!(json => json!({"mixed_type": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": -20.5})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": true})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"replace_null": {
"terms": {
"field": "json.mixed_type",
"missing": "NULL"
},
},
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// text field
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
Ok(())
}
}

View File

@@ -111,6 +111,9 @@ impl IntermediateAggregationResults {
}
/// Convert intermediate result and its aggregation request to the final result.
///
/// Internal function, AggregationsInternal is used instead Aggregations, which is optimized
/// for internal processing, by splitting metric and buckets into separate groups.
pub(crate) fn into_final_result_internal(
self,
req: &Aggregations,
@@ -118,14 +121,7 @@ impl IntermediateAggregationResults {
) -> crate::Result<AggregationResults> {
let mut results: FxHashMap<String, AggregationResult> = FxHashMap::default();
for (key, agg_res) in self.aggs_res.into_iter() {
let req = req.get(key.as_str()).unwrap_or_else(|| {
panic!(
"Could not find key {:?} in request keys {:?}. This probably means that \
add_intermediate_aggregation_result passed the wrong agg object.",
key,
req.keys().collect::<Vec<_>>()
)
});
let req = req.get(key.as_str()).unwrap();
results.insert(key, agg_res.into_final_result(req, limits)?);
}
// Handle empty results
@@ -172,16 +168,10 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
Range(_) => IntermediateAggregationResult::Bucket(IntermediateBucketResult::Range(
Default::default(),
)),
Histogram(_) => {
Histogram(_) | DateHistogram(_) => {
IntermediateAggregationResult::Bucket(IntermediateBucketResult::Histogram {
buckets: Vec::new(),
is_date_agg: false,
})
}
DateHistogram(_) => {
IntermediateAggregationResult::Bucket(IntermediateBucketResult::Histogram {
buckets: Vec::new(),
is_date_agg: true,
column_type: None,
})
}
Average(_) => IntermediateAggregationResult::Metric(IntermediateMetricResult::Average(
@@ -349,8 +339,8 @@ pub enum IntermediateBucketResult {
/// This is the histogram entry for a bucket, which contains a key, count, and optionally
/// sub_aggregations.
Histogram {
/// The column_type of the underlying `Column` is DateTime
is_date_agg: bool,
/// The column_type of the underlying `Column`
column_type: Option<ColumnType>,
/// The buckets
buckets: Vec<IntermediateHistogramBucketEntry>,
},
@@ -405,7 +395,7 @@ impl IntermediateBucketResult {
Ok(BucketResult::Range { buckets })
}
IntermediateBucketResult::Histogram {
is_date_agg,
column_type,
buckets,
} => {
let histogram_req = &req
@@ -414,7 +404,7 @@ impl IntermediateBucketResult {
.expect("unexpected aggregation, expected histogram aggregation");
let buckets = intermediate_histogram_buckets_to_final_buckets(
buckets,
is_date_agg,
column_type,
histogram_req,
req.sub_aggregation(),
limits,
@@ -463,17 +453,17 @@ impl IntermediateBucketResult {
(
IntermediateBucketResult::Histogram {
buckets: buckets_left,
is_date_agg: _,
..
},
IntermediateBucketResult::Histogram {
buckets: buckets_right,
is_date_agg: _,
..
},
) => {
let buckets: Result<Vec<IntermediateHistogramBucketEntry>, TantivyError> =
buckets_left
.drain(..)
.merge_join_by(buckets_right, |left, right| {
.merge_join_by(buckets_right.into_iter(), |left, right| {
left.key.partial_cmp(&right.key).unwrap_or(Ordering::Equal)
})
.map(|either| match either {

View File

@@ -20,21 +20,12 @@ use super::{IntermediateStats, SegmentStatsCollector};
pub struct AverageAggregation {
/// The field name to compute the average on.
pub field: String,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default)]
pub missing: Option<f64>,
}
impl AverageAggregation {
/// Creates a new [`AverageAggregation`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
Self {
field: field_name,
missing: None,
}
Self { field: field_name }
}
/// Returns the field name the aggregation is computed on.
pub fn field_name(&self) -> &str {

View File

@@ -18,23 +18,14 @@ use super::{IntermediateStats, SegmentStatsCollector};
/// ```
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct CountAggregation {
/// The field name to compute the count on.
/// The field name to compute the minimum on.
pub field: String,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default)]
pub missing: Option<f64>,
}
impl CountAggregation {
/// Creates a new [`CountAggregation`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
Self {
field: field_name,
missing: None,
}
Self { field: field_name }
}
/// Returns the field name the aggregation is computed on.
pub fn field_name(&self) -> &str {
@@ -60,7 +51,7 @@ impl IntermediateCount {
pub fn merge_fruits(&mut self, other: IntermediateCount) {
self.stats.merge_fruits(other.stats);
}
/// Computes the final count value.
/// Computes the final minimum value.
pub fn finalize(&self) -> Option<f64> {
Some(self.stats.finalize().count as f64)
}

View File

@@ -20,21 +20,12 @@ use super::{IntermediateStats, SegmentStatsCollector};
pub struct MaxAggregation {
/// The field name to compute the maximum on.
pub field: String,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default)]
pub missing: Option<f64>,
}
impl MaxAggregation {
/// Creates a new [`MaxAggregation`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
Self {
field: field_name,
missing: None,
}
Self { field: field_name }
}
/// Returns the field name the aggregation is computed on.
pub fn field_name(&self) -> &str {
@@ -65,55 +56,3 @@ impl IntermediateMax {
self.stats.finalize().max
}
}
#[cfg(test)]
mod tests {
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::tests::exec_request_with_query;
use crate::schema::{Schema, FAST};
use crate::{Index, IndexWriter};
#[test]
fn test_max_agg_with_missing() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with empty json
index_writer.add_document(doc!()).unwrap();
index_writer.commit().unwrap();
// => Segment with json, but no field partially_empty
index_writer
.add_document(doc!(json => json!({"different_field": "blue"})))
.unwrap();
index_writer.commit().unwrap();
//// => Segment with field partially_empty
index_writer
.add_document(doc!(json => json!({"partially_empty": 10.0})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"my_stats": {
"max": {
"field": "json.partially_empty",
"missing": 100.0,
}
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(
res["my_stats"],
json!({
"value": 100.0,
})
);
Ok(())
}
}

View File

@@ -20,21 +20,12 @@ use super::{IntermediateStats, SegmentStatsCollector};
pub struct MinAggregation {
/// The field name to compute the minimum on.
pub field: String,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default)]
pub missing: Option<f64>,
}
impl MinAggregation {
/// Creates a new [`MinAggregation`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
Self {
field: field_name,
missing: None,
}
Self { field: field_name }
}
/// Returns the field name the aggregation is computed on.
pub fn field_name(&self) -> &str {

View File

@@ -88,7 +88,7 @@ mod tests {
use crate::aggregation::AggregationCollector;
use crate::query::AllQuery;
use crate::schema::{NumericOptions, Schema};
use crate::{Index, IndexWriter};
use crate::Index;
#[test]
fn test_metric_aggregations() {
@@ -96,7 +96,7 @@ mod tests {
let field_options = NumericOptions::default().set_fast();
let field = schema_builder.add_f64_field("price", field_options);
let index = Index::create_in_ram(schema_builder.build());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
for i in 0..3 {
index_writer

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::{f64_from_fastfield_u64, f64_to_fastfield_u64, AggregationError};
use crate::aggregation::{f64_from_fastfield_u64, AggregationError};
use crate::{DocId, TantivyError};
/// # Percentiles
@@ -80,12 +80,6 @@ pub struct PercentilesAggregationReq {
/// Whether to return the percentiles as a hash map
#[serde(default = "default_as_true")]
pub keyed: bool,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(skip_serializing_if = "Option::is_none", default)]
pub missing: Option<f64>,
}
fn default_percentiles() -> &'static [f64] {
&[1.0, 5.0, 25.0, 50.0, 75.0, 95.0, 99.0]
@@ -101,7 +95,6 @@ impl PercentilesAggregationReq {
field: field_name,
percents: None,
keyed: default_as_true(),
missing: None,
}
}
/// Returns the field name the aggregation is computed on.
@@ -134,7 +127,6 @@ pub(crate) struct SegmentPercentilesCollector {
pub(crate) percentiles: PercentilesCollector,
pub(crate) accessor_idx: usize,
val_cache: Vec<u64>,
missing: Option<u64>,
}
#[derive(Clone, Serialize, Deserialize)]
@@ -235,16 +227,11 @@ impl SegmentPercentilesCollector {
accessor_idx: usize,
) -> crate::Result<Self> {
req.validate()?;
let missing = req
.missing
.and_then(|val| f64_to_fastfield_u64(val, &field_type));
Ok(Self {
field_type,
percentiles: PercentilesCollector::new(),
accessor_idx,
val_cache: Default::default(),
missing,
})
}
#[inline]
@@ -253,17 +240,9 @@ impl SegmentPercentilesCollector {
docs: &[DocId],
agg_accessor: &mut AggregationWithAccessor,
) {
if let Some(missing) = self.missing.as_ref() {
agg_accessor.column_block_accessor.fetch_block_with_missing(
docs,
&agg_accessor.accessor,
*missing,
);
} else {
agg_accessor
.column_block_accessor
.fetch_block(docs, &agg_accessor.accessor);
}
agg_accessor
.column_block_accessor
.fetch_block(docs, &agg_accessor.accessor);
for val in agg_accessor.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
@@ -298,22 +277,9 @@ impl SegmentAggregationCollector for SegmentPercentilesCollector {
) -> crate::Result<()> {
let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
if let Some(missing) = self.missing {
let mut has_val = false;
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.percentiles.collect(val1);
has_val = true;
}
if !has_val {
self.percentiles
.collect(f64_from_fastfield_u64(missing, &self.field_type));
}
} else {
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.percentiles.collect(val1);
}
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.percentiles.collect(val1);
}
Ok(())
@@ -343,12 +309,10 @@ mod tests {
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::tests::{
exec_request_with_query, get_test_index_from_values, get_test_index_from_values_and_terms,
get_test_index_from_values, get_test_index_from_values_and_terms,
};
use crate::aggregation::AggregationCollector;
use crate::query::AllQuery;
use crate::schema::{Schema, FAST};
use crate::Index;
#[test]
fn test_aggregation_percentiles_empty_index() -> crate::Result<()> {
@@ -499,7 +463,7 @@ mod tests {
fn test_aggregation_percentiles(merge_segments: bool) -> crate::Result<()> {
use rand_distr::Distribution;
let num_values_in_segment = [100, 30_000, 8000];
let num_values_in_segment = vec![100, 30_000, 8000];
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
let mut rng = StdRng::from_seed([1u8; 32]);
@@ -581,110 +545,4 @@ mod tests {
Ok(())
}
#[test]
fn test_percentiles_missing_sub_agg() -> crate::Result<()> {
// This test verifies the `collect` method (in contrast to `collect_block`), which is
// called when the sub-aggregations are flushed.
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("texts", FAST);
let score_field_f64 = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_for_tests()?;
// writing the segment
index_writer.add_document(doc!(
score_field_f64 => 10.0f64,
text_field => "a"
))?;
index_writer.add_document(doc!(
score_field_f64 => 10.0f64,
text_field => "a"
))?;
index_writer.add_document(doc!(text_field => "a"))?;
index_writer.commit()?;
}
let agg_req: Aggregations = {
serde_json::from_value(json!({
"range_with_stats": {
"terms": {
"field": "texts"
},
"aggs": {
"percentiles": {
"percentiles": {
"field": "score",
"missing": 5.0
}
}
}
}
}))
.unwrap()
};
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(res["range_with_stats"]["buckets"][0]["doc_count"], 3);
assert_eq!(
res["range_with_stats"]["buckets"][0]["percentiles"]["values"]["1.0"],
5.0028295751107414
);
assert_eq!(
res["range_with_stats"]["buckets"][0]["percentiles"]["values"]["99.0"],
10.07469668951144
);
Ok(())
}
#[test]
fn test_percentiles_missing() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("texts", FAST);
let score_field_f64 = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_for_tests()?;
// writing the segment
index_writer.add_document(doc!(
score_field_f64 => 10.0f64,
text_field => "a"
))?;
index_writer.add_document(doc!(
score_field_f64 => 10.0f64,
text_field => "a"
))?;
index_writer.add_document(doc!(text_field => "a"))?;
index_writer.commit()?;
}
let agg_req: Aggregations = {
serde_json::from_value(json!({
"percentiles": {
"percentiles": {
"field": "score",
"missing": 5.0
}
}
}))
.unwrap()
};
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(res["percentiles"]["values"]["1.0"], 5.0028295751107414);
assert_eq!(res["percentiles"]["values"]["99.0"], 10.07469668951144);
Ok(())
}
}

View File

@@ -5,11 +5,11 @@ use super::*;
use crate::aggregation::agg_req_with_accessor::{
AggregationWithAccessor, AggregationsWithAccessor,
};
use crate::aggregation::f64_from_fastfield_u64;
use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
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
@@ -29,21 +29,12 @@ use crate::{DocId, TantivyError};
pub struct StatsAggregation {
/// The field name to compute the stats on.
pub field: String,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default)]
pub missing: Option<f64>,
}
impl StatsAggregation {
/// Creates a new [`StatsAggregation`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
StatsAggregation {
field: field_name,
missing: None,
}
StatsAggregation { field: field_name }
}
/// Returns the field name the aggregation is computed on.
pub fn field_name(&self) -> &str {
@@ -162,7 +153,6 @@ pub(crate) enum SegmentStatsType {
#[derive(Clone, Debug, PartialEq)]
pub(crate) struct SegmentStatsCollector {
missing: Option<u64>,
field_type: ColumnType,
pub(crate) collecting_for: SegmentStatsType,
pub(crate) stats: IntermediateStats,
@@ -175,15 +165,12 @@ impl SegmentStatsCollector {
field_type: ColumnType,
collecting_for: SegmentStatsType,
accessor_idx: usize,
missing: Option<f64>,
) -> Self {
let missing = missing.and_then(|val| f64_to_fastfield_u64(val, &field_type));
Self {
field_type,
collecting_for,
stats: IntermediateStats::default(),
accessor_idx,
missing,
val_cache: Default::default(),
}
}
@@ -193,17 +180,10 @@ impl SegmentStatsCollector {
docs: &[DocId],
agg_accessor: &mut AggregationWithAccessor,
) {
if let Some(missing) = self.missing.as_ref() {
agg_accessor.column_block_accessor.fetch_block_with_missing(
docs,
&agg_accessor.accessor,
*missing,
);
} else {
agg_accessor
.column_block_accessor
.fetch_block(docs, &agg_accessor.accessor);
}
agg_accessor
.column_block_accessor
.fetch_block(docs, &agg_accessor.accessor);
for val in agg_accessor.column_block_accessor.iter_vals() {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
@@ -254,22 +234,10 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
agg_with_accessor: &mut AggregationsWithAccessor,
) -> crate::Result<()> {
let field = &agg_with_accessor.aggs.values[self.accessor_idx].accessor;
if let Some(missing) = self.missing {
let mut has_val = false;
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
has_val = true;
}
if !has_val {
self.stats
.collect(f64_from_fastfield_u64(missing, &self.field_type));
}
} else {
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
}
for val in field.values_for_doc(doc) {
let val1 = f64_from_fastfield_u64(val, &self.field_type);
self.stats.collect(val1);
}
Ok(())
@@ -294,13 +262,11 @@ mod tests {
use crate::aggregation::agg_req::{Aggregation, Aggregations};
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::tests::{
exec_request_with_query, get_test_index_2_segments, get_test_index_from_values,
};
use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_values};
use crate::aggregation::AggregationCollector;
use crate::query::{AllQuery, TermQuery};
use crate::schema::{IndexRecordOption, Schema, FAST};
use crate::{Index, IndexWriter, Term};
use crate::schema::IndexRecordOption;
use crate::Term;
#[test]
fn test_aggregation_stats_empty_index() -> crate::Result<()> {
@@ -487,159 +453,4 @@ mod tests {
Ok(())
}
#[test]
fn test_stats_json() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with empty json
index_writer.add_document(doc!()).unwrap();
index_writer.commit().unwrap();
// => Segment with json, but no field partially_empty
index_writer
.add_document(doc!(json => json!({"different_field": "blue"})))
.unwrap();
index_writer.commit().unwrap();
//// => Segment with field partially_empty
index_writer
.add_document(doc!(json => json!({"partially_empty": 10.0})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
let agg_req: Aggregations = serde_json::from_value(json!({
"my_stats": {
"stats": {
"field": "json.partially_empty"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(
res["my_stats"],
json!({
"avg": 10.0,
"count": 1,
"max": 10.0,
"min": 10.0,
"sum": 10.0
})
);
Ok(())
}
#[test]
fn test_stats_json_missing() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let json = schema_builder.add_json_field("json", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with empty json
index_writer.add_document(doc!()).unwrap();
index_writer.commit().unwrap();
// => Segment with json, but no field partially_empty
index_writer
.add_document(doc!(json => json!({"different_field": "blue"})))
.unwrap();
index_writer.commit().unwrap();
//// => Segment with field partially_empty
index_writer
.add_document(doc!(json => json!({"partially_empty": 10.0})))
.unwrap();
index_writer.add_document(doc!())?;
index_writer.commit().unwrap();
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(())
}
#[test]
fn test_stats_json_missing_sub_agg() -> crate::Result<()> {
// This test verifies the `collect` method (in contrast to `collect_block`), which is
// called when the sub-aggregations are flushed.
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("texts", FAST);
let score_field_f64 = schema_builder.add_f64_field("score", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut index_writer = index.writer_for_tests()?;
// writing the segment
index_writer.add_document(doc!(
score_field_f64 => 10.0f64,
text_field => "a"
))?;
index_writer.add_document(doc!(text_field => "a"))?;
index_writer.commit()?;
}
let agg_req: Aggregations = {
serde_json::from_value(json!({
"range_with_stats": {
"terms": {
"field": "texts"
},
"aggs": {
"my_stats": {
"stats": {
"field": "score",
"missing": 0.0
}
}
}
}
}))
.unwrap()
};
let res = exec_request_with_query(agg_req, &index, None)?;
assert_eq!(
res["range_with_stats"]["buckets"][0]["my_stats"]["count"],
2
);
assert_eq!(
res["range_with_stats"]["buckets"][0]["my_stats"]["min"],
0.0
);
assert_eq!(
res["range_with_stats"]["buckets"][0]["my_stats"]["avg"],
5.0
);
Ok(())
}
}

View File

@@ -20,21 +20,12 @@ use super::{IntermediateStats, SegmentStatsCollector};
pub struct SumAggregation {
/// The field name to compute the minimum on.
pub field: String,
/// The missing parameter defines how documents that are missing a value should be treated.
/// By default they will be ignored but it is also possible to treat them as if they had a
/// value. Examples in JSON format:
/// { "field": "my_numbers", "missing": "10.0" }
#[serde(default)]
pub missing: Option<f64>,
}
impl SumAggregation {
/// Creates a new [`SumAggregation`] instance from a field name.
pub fn from_field_name(field_name: String) -> Self {
Self {
field: field_name,
missing: None,
}
Self { field: field_name }
}
/// Returns the field name the aggregation is computed on.
pub fn field_name(&self) -> &str {

View File

@@ -319,7 +319,7 @@ mod tests {
use crate::indexer::NoMergePolicy;
use crate::query::{AllQuery, TermQuery};
use crate::schema::{IndexRecordOption, Schema, TextFieldIndexing, FAST, STRING};
use crate::{Index, IndexWriter, Term};
use crate::{Index, Term};
pub fn get_test_index_with_num_docs(
merge_segments: bool,
@@ -411,7 +411,7 @@ mod tests {
.set_index_option(IndexRecordOption::Basic)
.set_fieldnorms(false),
)
.set_fast(None)
.set_fast("default")
.set_stored();
let text_field = schema_builder.add_text_field("text", text_fieldtype.clone());
let text_field_id = schema_builder.add_text_field("text_id", text_fieldtype);
@@ -451,7 +451,7 @@ mod tests {
.searchable_segment_ids()
.expect("Searchable segments failed.");
if segment_ids.len() > 1 {
let mut index_writer: IndexWriter = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests()?;
index_writer.merge(&segment_ids).wait()?;
index_writer.wait_merging_threads()?;
}
@@ -466,7 +466,7 @@ mod tests {
.set_indexing_options(
TextFieldIndexing::default().set_index_option(IndexRecordOption::WithFreqs),
)
.set_fast(None)
.set_fast("default")
.set_stored();
let text_field = schema_builder.add_text_field("text", text_fieldtype);
let date_field = schema_builder.add_date_field("date", FAST);
@@ -565,7 +565,7 @@ mod tests {
let segment_ids = index
.searchable_segment_ids()
.expect("Searchable segments failed.");
let mut index_writer: IndexWriter = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests()?;
index_writer.merge(&segment_ids).wait()?;
index_writer.wait_merging_threads()?;
}

View File

@@ -15,7 +15,7 @@ use super::metric::{
SegmentPercentilesCollector, SegmentStatsCollector, SegmentStatsType, StatsAggregation,
SumAggregation,
};
use crate::aggregation::bucket::TermMissingAgg;
use crate::aggregation::bucket::SegmentTermCollectorComposite;
pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
fn add_intermediate_aggregation_result(
@@ -82,24 +82,29 @@ pub(crate) fn build_single_agg_segment_collector(
use AggregationVariants::*;
match &req.agg.agg {
Terms(terms_req) => {
if req.accessors.is_empty() {
if let Some(acc2) = req.accessor2.as_ref() {
Ok(Box::new(
SegmentTermCollectorComposite::from_req_and_validate(
terms_req,
&mut req.sub_aggregation,
req.field_type,
acc2.1,
accessor_idx,
)?,
))
} else {
Ok(Box::new(SegmentTermCollector::from_req_and_validate(
terms_req,
&mut req.sub_aggregation,
req.field_type,
accessor_idx,
)?))
} else {
Ok(Box::new(TermMissingAgg::new(
accessor_idx,
&mut req.sub_aggregation,
)?))
}
}
Range(range_req) => Ok(Box::new(SegmentRangeCollector::from_req_and_validate(
range_req,
&mut req.sub_aggregation,
&req.limits,
&mut req.limits,
req.field_type,
accessor_idx,
)?)),
@@ -115,43 +120,35 @@ pub(crate) fn build_single_agg_segment_collector(
req.field_type,
accessor_idx,
)?)),
Average(AverageAggregation { missing, .. }) => {
Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Average,
accessor_idx,
*missing,
)))
}
Count(CountAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
Average(AverageAggregation { .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Average,
accessor_idx,
))),
Count(CountAggregation { .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Count,
accessor_idx,
*missing,
))),
Max(MaxAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
Max(MaxAggregation { .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Max,
accessor_idx,
*missing,
))),
Min(MinAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
Min(MinAggregation { .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Min,
accessor_idx,
*missing,
))),
Stats(StatsAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
Stats(StatsAggregation { .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Stats,
accessor_idx,
*missing,
))),
Sum(SumAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
Sum(SumAggregation { .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Sum,
accessor_idx,
*missing,
))),
Percentiles(percentiles_req) => Ok(Box::new(
SegmentPercentilesCollector::from_req_and_validate(

View File

@@ -16,7 +16,7 @@ use crate::{DocId, Score, SegmentOrdinal, SegmentReader};
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
///
/// let mut index_writer = index.writer(15_000_000).unwrap();
/// let mut index_writer = index.writer(3_000_000).unwrap();
/// index_writer.add_document(doc!(title => "The Name of the Wind")).unwrap();
/// index_writer.add_document(doc!(title => "The Diary of Muadib")).unwrap();
/// index_writer.add_document(doc!(title => "A Dairy Cow")).unwrap();

View File

@@ -89,7 +89,7 @@ fn facet_depth(facet_bytes: &[u8]) -> usize {
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
/// {
/// let mut index_writer = index.writer(15_000_000)?;
/// let mut index_writer = index.writer(3_000_000)?;
/// // a document can be associated with any number of facets
/// index_writer.add_document(doc!(
/// title => "The Name of the Wind",
@@ -495,8 +495,8 @@ mod tests {
use crate::collector::Count;
use crate::core::Index;
use crate::query::{AllQuery, QueryParser, TermQuery};
use crate::schema::{Facet, FacetOptions, IndexRecordOption, Schema, TantivyDocument};
use crate::{IndexWriter, Term};
use crate::schema::{Document, Facet, FacetOptions, IndexRecordOption, Schema};
use crate::Term;
fn test_collapse_mapping_aux(
facet_terms: &[&str],
@@ -559,7 +559,7 @@ mod tests {
let facet_field = schema_builder.add_facet_field("facet", FacetOptions::default());
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
index_writer
.add_document(doc!(facet_field=>Facet::from("/facet/a")))
.unwrap();
@@ -588,7 +588,7 @@ mod tests {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
let num_facets: usize = 3 * 4 * 5;
let facets: Vec<Facet> = (0..num_facets)
.map(|mut n| {
@@ -601,7 +601,7 @@ mod tests {
})
.collect();
for i in 0..num_facets * 10 {
let mut doc = TantivyDocument::new();
let mut doc = Document::new();
doc.add_facet(facet_field, facets[i % num_facets].clone());
index_writer.add_document(doc).unwrap();
}
@@ -732,25 +732,24 @@ mod tests {
let index = Index::create_in_ram(schema);
let uniform = Uniform::new_inclusive(1, 100_000);
let mut docs: Vec<TantivyDocument> =
vec![("a", 10), ("b", 100), ("c", 7), ("d", 12), ("e", 21)]
.into_iter()
.flat_map(|(c, count)| {
let facet = Facet::from(&format!("/facet/{}", c));
let doc = doc!(facet_field => facet);
iter::repeat(doc).take(count)
})
.map(|mut doc| {
doc.add_facet(
facet_field,
&format!("/facet/{}", thread_rng().sample(uniform)),
);
doc
})
.collect();
let mut docs: Vec<Document> = vec![("a", 10), ("b", 100), ("c", 7), ("d", 12), ("e", 21)]
.into_iter()
.flat_map(|(c, count)| {
let facet = Facet::from(&format!("/facet/{}", c));
let doc = doc!(facet_field => facet);
iter::repeat(doc).take(count)
})
.map(|mut doc| {
doc.add_facet(
facet_field,
&format!("/facet/{}", thread_rng().sample(uniform)),
);
doc
})
.collect();
docs[..].shuffle(&mut thread_rng());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
for doc in docs {
index_writer.add_document(doc).unwrap();
}
@@ -781,7 +780,7 @@ mod tests {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let docs: Vec<TantivyDocument> = vec![("b", 2), ("a", 2), ("c", 4)]
let docs: Vec<Document> = vec![("b", 2), ("a", 2), ("c", 4)]
.into_iter()
.flat_map(|(c, count)| {
let facet = Facet::from(&format!("/facet/{}", c));
@@ -829,7 +828,7 @@ mod bench {
use crate::collector::FacetCollector;
use crate::query::AllQuery;
use crate::schema::{Facet, Schema, INDEXED};
use crate::{Index, IndexWriter};
use crate::Index;
#[bench]
fn bench_facet_collector(b: &mut Bencher) {
@@ -848,7 +847,7 @@ mod bench {
// 40425 docs
docs[..].shuffle(&mut thread_rng());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
let mut index_writer = index.writer_for_tests().unwrap();
for doc in docs {
index_writer.add_document(doc).unwrap();
}

View File

@@ -12,7 +12,8 @@ use std::marker::PhantomData;
use columnar::{BytesColumn, Column, DynamicColumn, HasAssociatedColumnType};
use crate::collector::{Collector, SegmentCollector};
use crate::{DocId, Score, SegmentReader};
use crate::schema::Field;
use crate::{DocId, Score, SegmentReader, TantivyError};
/// The `FilterCollector` filters docs using a fast field value and a predicate.
///
@@ -37,7 +38,7 @@ use crate::{DocId, Score, SegmentReader};
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
///
/// let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// index_writer.add_document(doc!(title => "The Name of the Wind", price => 30_200u64))?;
/// index_writer.add_document(doc!(title => "The Diary of Muadib", price => 29_240u64))?;
/// index_writer.add_document(doc!(title => "A Dairy Cow", price => 21_240u64))?;
@@ -49,13 +50,13 @@ use crate::{DocId, Score, SegmentReader};
///
/// let query_parser = QueryParser::for_index(&index, vec![title]);
/// let query = query_parser.parse_query("diary")?;
/// let no_filter_collector = FilterCollector::new("price".to_string(), |value: u64| value > 20_120u64, TopDocs::with_limit(2));
/// let no_filter_collector = FilterCollector::new(price, |value: u64| value > 20_120u64, TopDocs::with_limit(2));
/// let top_docs = searcher.search(&query, &no_filter_collector)?;
///
/// assert_eq!(top_docs.len(), 1);
/// assert_eq!(top_docs[0].1, DocAddress::new(0, 1));
///
/// let filter_all_collector: FilterCollector<_, _, u64> = FilterCollector::new("price".to_string(), |value| value < 5u64, TopDocs::with_limit(2));
/// let filter_all_collector: FilterCollector<_, _, u64> = FilterCollector::new(price, |value| value < 5u64, TopDocs::with_limit(2));
/// let filtered_top_docs = searcher.search(&query, &filter_all_collector)?;
///
/// assert_eq!(filtered_top_docs.len(), 0);
@@ -69,7 +70,7 @@ use crate::{DocId, Score, SegmentReader};
pub struct FilterCollector<TCollector, TPredicate, TPredicateValue>
where TPredicate: 'static + Clone
{
field: String,
field: Field,
collector: TCollector,
predicate: TPredicate,
t_predicate_value: PhantomData<TPredicateValue>,
@@ -82,7 +83,7 @@ where
TPredicate: Fn(TPredicateValue) -> bool + Send + Sync + Clone,
{
/// Create a new `FilterCollector`.
pub fn new(field: String, predicate: TPredicate, collector: TCollector) -> Self {
pub fn new(field: Field, predicate: TPredicate, collector: TCollector) -> Self {
Self {
field,
predicate,
@@ -109,7 +110,18 @@ where
segment_local_id: u32,
segment_reader: &SegmentReader,
) -> crate::Result<Self::Child> {
let column_opt = segment_reader.fast_fields().column_opt(&self.field)?;
let schema = segment_reader.schema();
let field_entry = schema.get_field_entry(self.field);
if !field_entry.is_fast() {
return Err(TantivyError::SchemaError(format!(
"Field {:?} is not a fast field.",
field_entry.name()
)));
}
let column_opt = segment_reader
.fast_fields()
.column_opt(field_entry.name())?;
let segment_collector = self
.collector
@@ -204,7 +216,7 @@ where
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
///
/// let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// index_writer.add_document(doc!(title => "The Name of the Wind", barcode => &b"010101"[..]))?;
/// index_writer.add_document(doc!(title => "The Diary of Muadib", barcode => &b"110011"[..]))?;
/// index_writer.add_document(doc!(title => "A Dairy Cow", barcode => &b"110111"[..]))?;
@@ -217,7 +229,7 @@ where
///
/// let query_parser = QueryParser::for_index(&index, vec![title]);
/// let query = query_parser.parse_query("diary")?;
/// let filter_collector = BytesFilterCollector::new("barcode".to_string(), |bytes: &[u8]| bytes.starts_with(b"01"), TopDocs::with_limit(2));
/// let filter_collector = BytesFilterCollector::new(barcode, |bytes: &[u8]| bytes.starts_with(b"01"), TopDocs::with_limit(2));
/// let top_docs = searcher.search(&query, &filter_collector)?;
///
/// assert_eq!(top_docs.len(), 1);
@@ -228,7 +240,7 @@ where
pub struct BytesFilterCollector<TCollector, TPredicate>
where TPredicate: 'static + Clone
{
field: String,
field: Field,
collector: TCollector,
predicate: TPredicate,
}
@@ -239,7 +251,7 @@ where
TPredicate: Fn(&[u8]) -> bool + Send + Sync + Clone,
{
/// Create a new `BytesFilterCollector`.
pub fn new(field: String, predicate: TPredicate, collector: TCollector) -> Self {
pub fn new(field: Field, predicate: TPredicate, collector: TCollector) -> Self {
Self {
field,
predicate,
@@ -262,7 +274,10 @@ where
segment_local_id: u32,
segment_reader: &SegmentReader,
) -> crate::Result<Self::Child> {
let column_opt = segment_reader.fast_fields().bytes(&self.field)?;
let schema = segment_reader.schema();
let field_name = schema.get_field_name(self.field);
let column_opt = segment_reader.fast_fields().bytes(field_name)?;
let segment_collector = self
.collector

View File

@@ -233,7 +233,7 @@ mod tests {
let val_field = schema_builder.add_i64_field("val_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests()?;
let mut writer = index.writer_with_num_threads(1, 4_000_000)?;
writer.add_document(doc!(val_field=>12i64))?;
writer.add_document(doc!(val_field=>-30i64))?;
writer.add_document(doc!(val_field=>-12i64))?;
@@ -255,7 +255,7 @@ mod tests {
let val_field = schema_builder.add_i64_field("val_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests()?;
let mut writer = index.writer_with_num_threads(1, 4_000_000)?;
writer.add_document(doc!(val_field=>12i64))?;
writer.commit()?;
writer.add_document(doc!(val_field=>-30i64))?;
@@ -280,7 +280,7 @@ mod tests {
let date_field = schema_builder.add_date_field("date_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests()?;
let mut writer = index.writer_with_num_threads(1, 4_000_000)?;
writer.add_document(doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1982, Month::September, 17)?.with_hms(0, 0, 0)?)))?;
writer.add_document(
doc!(date_field=>DateTime::from_primitive(Date::from_calendar_date(1986, Month::March, 9)?.with_hms(0, 0, 0)?)),

View File

@@ -44,7 +44,7 @@
//! # let title = schema_builder.add_text_field("title", TEXT);
//! # let schema = schema_builder.build();
//! # let index = Index::create_in_ram(schema);
//! # let mut index_writer = index.writer(15_000_000)?;
//! # let mut index_writer = index.writer(3_000_000)?;
//! # index_writer.add_document(doc!(
//! # title => "The Name of the Wind",
//! # ))?;
@@ -97,7 +97,7 @@ pub use self::multi_collector::{FruitHandle, MultiCollector, MultiFruit};
mod top_collector;
mod top_score_collector;
pub use self::top_score_collector::{TopDocs, TopNComputer};
pub use self::top_score_collector::TopDocs;
mod custom_score_top_collector;
pub use self::custom_score_top_collector::{CustomScorer, CustomSegmentScorer};

View File

@@ -120,7 +120,7 @@ impl<TFruit: Fruit> FruitHandle<TFruit> {
/// let title = schema_builder.add_text_field("title", TEXT);
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
/// let mut index_writer = index.writer(15_000_000)?;
/// let mut index_writer = index.writer(3_000_000)?;
/// index_writer.add_document(doc!(title => "The Name of the Wind"))?;
/// index_writer.add_document(doc!(title => "The Diary of Muadib"))?;
/// index_writer.add_document(doc!(title => "A Dairy Cow"))?;

View File

@@ -7,9 +7,7 @@ use crate::query::{AllQuery, QueryParser};
use crate::schema::{Schema, FAST, TEXT};
use crate::time::format_description::well_known::Rfc3339;
use crate::time::OffsetDateTime;
use crate::{
doc, DateTime, DocAddress, DocId, Index, Score, Searcher, SegmentOrdinal, TantivyDocument,
};
use crate::{doc, DateTime, DocAddress, DocId, Document, Index, Score, Searcher, SegmentOrdinal};
pub const TEST_COLLECTOR_WITH_SCORE: TestCollector = TestCollector {
compute_score: true,
@@ -28,7 +26,7 @@ pub fn test_filter_collector() -> crate::Result<()> {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
index_writer.add_document(doc!(title => "The Name of the Wind", price => 30_200u64, date => DateTime::from_utc(OffsetDateTime::parse("1898-04-09T00:00:00+00:00", &Rfc3339).unwrap())))?;
index_writer.add_document(doc!(title => "The Diary of Muadib", price => 29_240u64, date => DateTime::from_utc(OffsetDateTime::parse("2020-04-09T00:00:00+00:00", &Rfc3339).unwrap())))?;
index_writer.add_document(doc!(title => "The Diary of Anne Frank", price => 18_240u64, date => DateTime::from_utc(OffsetDateTime::parse("2019-04-20T00:00:00+00:00", &Rfc3339).unwrap())))?;
@@ -42,7 +40,7 @@ pub fn test_filter_collector() -> crate::Result<()> {
let query_parser = QueryParser::for_index(&index, vec![title]);
let query = query_parser.parse_query("diary")?;
let filter_some_collector = FilterCollector::new(
"price".to_string(),
price,
&|value: u64| value > 20_120u64,
TopDocs::with_limit(2),
);
@@ -51,11 +49,8 @@ pub fn test_filter_collector() -> crate::Result<()> {
assert_eq!(top_docs.len(), 1);
assert_eq!(top_docs[0].1, DocAddress::new(0, 1));
let filter_all_collector: FilterCollector<_, _, u64> = FilterCollector::new(
"price".to_string(),
&|value| value < 5u64,
TopDocs::with_limit(2),
);
let filter_all_collector: FilterCollector<_, _, u64> =
FilterCollector::new(price, &|value| value < 5u64, TopDocs::with_limit(2));
let filtered_top_docs = searcher.search(&query, &filter_all_collector).unwrap();
assert_eq!(filtered_top_docs.len(), 0);
@@ -66,8 +61,7 @@ pub fn test_filter_collector() -> crate::Result<()> {
> 0
}
let filter_dates_collector =
FilterCollector::new("date".to_string(), &date_filter, TopDocs::with_limit(5));
let filter_dates_collector = FilterCollector::new(date, &date_filter, TopDocs::with_limit(5));
let filtered_date_docs = searcher.search(&query, &filter_dates_collector)?;
assert_eq!(filtered_date_docs.len(), 2);
@@ -286,8 +280,8 @@ fn make_test_searcher() -> crate::Result<Searcher> {
let schema = Schema::builder().build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_for_tests()?;
index_writer.add_document(TantivyDocument::default())?;
index_writer.add_document(TantivyDocument::default())?;
index_writer.add_document(Document::default())?;
index_writer.add_document(Document::default())?;
index_writer.commit()?;
Ok(index.reader()?.searcher())
}

View File

@@ -1,7 +1,7 @@
use std::cmp::Ordering;
use std::collections::BinaryHeap;
use std::marker::PhantomData;
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.
@@ -20,14 +20,6 @@ pub(crate) struct ComparableDoc<T, D> {
pub feature: T,
pub doc: D,
}
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("ComparableDoc")
.field("feature", &self.feature)
.field("doc", &self.doc)
.finish()
}
}
impl<T: PartialOrd, D: PartialOrd> PartialOrd for ComparableDoc<T, D> {
fn partial_cmp(&self, other: &Self) -> Option<Ordering> {
@@ -99,13 +91,18 @@ where T: PartialOrd + Clone
if self.limit == 0 {
return Ok(Vec::new());
}
let mut top_collector = TopNComputer::new(self.limit + self.offset);
let mut top_collector = BinaryHeap::new();
for child_fruit in children {
for (feature, doc) in child_fruit {
top_collector.push(ComparableDoc { feature, doc });
if top_collector.len() < (self.limit + self.offset) {
top_collector.push(ComparableDoc { feature, doc });
} else if let Some(mut head) = top_collector.peek_mut() {
if head.feature < feature {
*head = ComparableDoc { feature, doc };
}
}
}
}
Ok(top_collector
.into_sorted_vec()
.into_iter()
@@ -114,7 +111,7 @@ where T: PartialOrd + Clone
.collect())
}
pub(crate) fn for_segment<F: PartialOrd + Clone>(
pub(crate) fn for_segment<F: PartialOrd>(
&self,
segment_id: SegmentOrdinal,
_: &SegmentReader,
@@ -139,18 +136,20 @@ where T: PartialOrd + Clone
/// The Top Collector keeps track of the K documents
/// sorted by type `T`.
///
/// The implementation is based on a repeatedly truncating on the median after K * 2 documents
/// The implementation is based on a `BinaryHeap`.
/// The theoretical complexity for collecting the top `K` out of `n` documents
/// is `O(n + K)`.
/// is `O(n log K)`.
pub(crate) struct TopSegmentCollector<T> {
topn_computer: TopNComputer<T, DocId>,
limit: usize,
heap: BinaryHeap<ComparableDoc<T, DocId>>,
segment_ord: u32,
}
impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
impl<T: PartialOrd> TopSegmentCollector<T> {
fn new(segment_ord: SegmentOrdinal, limit: usize) -> TopSegmentCollector<T> {
TopSegmentCollector {
topn_computer: TopNComputer::new(limit),
limit,
heap: BinaryHeap::with_capacity(limit),
segment_ord,
}
}
@@ -159,7 +158,7 @@ impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
pub fn harvest(self) -> Vec<(T, DocAddress)> {
let segment_ord = self.segment_ord;
self.topn_computer
self.heap
.into_sorted_vec()
.into_iter()
.map(|comparable_doc| {
@@ -174,13 +173,33 @@ impl<T: PartialOrd + Clone> TopSegmentCollector<T> {
.collect()
}
/// Return true if more documents have been collected than the limit.
#[inline]
pub(crate) fn at_capacity(&self) -> bool {
self.heap.len() >= self.limit
}
/// Collects a document scored by the given feature
///
/// It collects documents until it has reached the max capacity. Once it reaches capacity, it
/// 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(ComparableDoc { feature, doc });
if self.at_capacity() {
// It's ok to unwrap as long as a limit of 0 is forbidden.
if let Some(limit_feature) = self.heap.peek().map(|head| head.feature.clone()) {
if limit_feature < feature {
if let Some(mut head) = self.heap.peek_mut() {
head.feature = feature;
head.doc = doc;
}
}
}
} else {
// we have not reached capacity yet, so we can just push the
// element.
self.heap.push(ComparableDoc { feature, doc });
}
}
}

View File

@@ -1,3 +1,4 @@
use std::collections::BinaryHeap;
use std::fmt;
use std::marker::PhantomData;
use std::sync::Arc;
@@ -85,15 +86,12 @@ where
/// The `TopDocs` collector keeps track of the top `K` documents
/// sorted by their score.
///
/// The implementation is based on a repeatedly truncating on the median after K * 2 documents
/// with pattern defeating QuickSort.
/// The theoretical complexity for collecting the top `K` out of `N` documents
/// is `O(N + K)`.
/// The implementation is based on a `BinaryHeap`.
/// The theoretical complexity for collecting the top `K` out of `n` documents
/// is `O(n log K)`.
///
/// This collector does not guarantee a stable sorting in case of a tie on the
/// document score, for stable sorting `PartialOrd` needs to resolve on other fields
/// like docid in case of score equality.
/// Only then, it is suitable for pagination.
/// This collector guarantees a stable sorting in case of a tie on the
/// document score. As such, it is suitable to implement pagination.
///
/// ```rust
/// use tantivy::collector::TopDocs;
@@ -107,7 +105,7 @@ where
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
///
/// let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// index_writer.add_document(doc!(title => "The Name of the Wind"))?;
/// index_writer.add_document(doc!(title => "The Diary of Muadib"))?;
/// index_writer.add_document(doc!(title => "A Dairy Cow"))?;
@@ -212,7 +210,7 @@ impl TopDocs {
/// let schema = schema_builder.build();
/// let index = Index::create_in_ram(schema);
///
/// let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// index_writer.add_document(doc!(title => "The Name of the Wind"))?;
/// index_writer.add_document(doc!(title => "The Diary of Muadib"))?;
/// index_writer.add_document(doc!(title => "A Dairy Cow"))?;
@@ -263,7 +261,7 @@ impl TopDocs {
/// # let schema = schema_builder.build();
/// #
/// # let index = Index::create_in_ram(schema);
/// # let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// # let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// # index_writer.add_document(doc!(title => "The Name of the Wind", rating => 92u64))?;
/// # index_writer.add_document(doc!(title => "The Diary of Muadib", rating => 97u64))?;
/// # index_writer.add_document(doc!(title => "A Dairy Cow", rating => 63u64))?;
@@ -351,7 +349,7 @@ impl TopDocs {
/// # let schema = schema_builder.build();
/// #
/// # let index = Index::create_in_ram(schema);
/// # let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// # let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// # index_writer.add_document(doc!(title => "MadCow Inc.", revenue => 92_000_000i64))?;
/// # index_writer.add_document(doc!(title => "Zozo Cow KKK", revenue => 119_000_000i64))?;
/// # index_writer.add_document(doc!(title => "Declining Cow", revenue => -63_000_000i64))?;
@@ -451,7 +449,7 @@ impl TopDocs {
/// fn create_index() -> tantivy::Result<Index> {
/// let schema = create_schema();
/// let index = Index::create_in_ram(schema);
/// let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// let product_name = index.schema().get_field("product_name").unwrap();
/// let popularity: Field = index.schema().get_field("popularity").unwrap();
/// index_writer.add_document(doc!(product_name => "The Diary of Muadib", popularity => 1u64))?;
@@ -558,7 +556,7 @@ impl TopDocs {
/// # fn main() -> tantivy::Result<()> {
/// # let schema = create_schema();
/// # let index = Index::create_in_ram(schema);
/// # let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
/// # let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
/// # let product_name = index.schema().get_field("product_name").unwrap();
/// #
/// let popularity: Field = index.schema().get_field("popularity").unwrap();
@@ -663,35 +661,50 @@ 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::new(heap_len);
let mut heap: BinaryHeap<ComparableDoc<Score, DocId>> = BinaryHeap::with_capacity(heap_len);
if let Some(alive_bitset) = reader.alive_bitset() {
let mut threshold = Score::MIN;
top_n.threshold = Some(threshold);
weight.for_each_pruning(Score::MIN, reader, &mut |doc, score| {
weight.for_each_pruning(threshold, reader, &mut |doc, score| {
if alive_bitset.is_deleted(doc) {
return threshold;
}
let doc = ComparableDoc {
let heap_item = ComparableDoc {
feature: score,
doc,
};
top_n.push(doc);
threshold = top_n.threshold.unwrap_or(Score::MIN);
if heap.len() < heap_len {
heap.push(heap_item);
if heap.len() == heap_len {
threshold = heap.peek().map(|el| el.feature).unwrap_or(Score::MIN);
}
return threshold;
}
*heap.peek_mut().unwrap() = heap_item;
threshold = heap.peek().map(|el| el.feature).unwrap_or(Score::MIN);
threshold
})?;
} else {
weight.for_each_pruning(Score::MIN, reader, &mut |doc, score| {
let doc = ComparableDoc {
let heap_item = ComparableDoc {
feature: score,
doc,
};
top_n.push(doc);
top_n.threshold.unwrap_or(Score::MIN)
if heap.len() < heap_len {
heap.push(heap_item);
// TODO the threshold is suboptimal for heap.len == heap_len
if heap.len() == heap_len {
return heap.peek().map(|el| el.feature).unwrap_or(Score::MIN);
} else {
return Score::MIN;
}
}
*heap.peek_mut().unwrap() = heap_item;
heap.peek().map(|el| el.feature).unwrap_or(Score::MIN)
})?;
}
let fruit = top_n
let fruit = heap
.into_sorted_vec()
.into_iter()
.map(|cid| {
@@ -723,81 +736,9 @@ impl SegmentCollector for TopScoreSegmentCollector {
}
}
/// Fast TopN Computation
///
/// For TopN == 0, it will be relative expensive.
pub struct TopNComputer<Score, DocId> {
buffer: Vec<ComparableDoc<Score, DocId>>,
top_n: usize,
pub(crate) threshold: Option<Score>,
}
impl<Score, DocId> TopNComputer<Score, DocId>
where
Score: PartialOrd + Clone,
DocId: Ord + Clone,
{
/// Create a new `TopNComputer`.
/// Internally it will allocate a buffer of size `2 * top_n`.
pub fn new(top_n: usize) -> Self {
let vec_cap = top_n.max(1) * 2;
TopNComputer {
buffer: Vec::with_capacity(vec_cap),
top_n,
threshold: None,
}
}
#[inline]
pub(crate) fn push(&mut self, doc: ComparableDoc<Score, DocId>) {
if let Some(last_median) = self.threshold.clone() {
if doc.feature < last_median {
return;
}
}
if self.buffer.len() == self.buffer.capacity() {
let median = self.truncate_top_n();
self.threshold = Some(median);
}
// This is faster since it avoids the buffer resizing to be inlined from vec.push()
// (this is in the hot path)
// TODO: Replace with `push_within_capacity` when it's stabilized
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(doc);
// This is safe because it would panic in the line above
unsafe {
self.buffer.set_len(self.buffer.len() + 1);
}
}
#[inline(never)]
fn truncate_top_n(&mut self) -> Score {
// Use select_nth_unstable to find the top nth score
let (_, median_el, _) = self.buffer.select_nth_unstable(self.top_n);
let median_score = median_el.feature.clone();
// Remove all elements below the top_n
self.buffer.truncate(self.top_n);
median_score
}
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
}
}
#[cfg(test)]
mod tests {
use super::{TopDocs, TopNComputer};
use crate::collector::top_collector::ComparableDoc;
use super::TopDocs;
use crate::collector::Collector;
use crate::query::{AllQuery, Query, QueryParser};
use crate::schema::{Field, Schema, FAST, STORED, TEXT};
@@ -811,7 +752,7 @@ mod tests {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
// writing the segment
let mut index_writer = index.writer_with_num_threads(1, 20_000_000)?;
let mut index_writer = index.writer_with_num_threads(1, 10_000_000)?;
index_writer.add_document(doc!(text_field=>"Hello happy tax payer."))?;
index_writer.add_document(doc!(text_field=>"Droopy says hello happy tax payer"))?;
index_writer.add_document(doc!(text_field=>"I like Droopy"))?;
@@ -826,78 +767,6 @@ mod tests {
}
}
#[test]
fn test_empty_topn_computer() {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(0);
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(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(),
&[
ComparableDoc {
feature: 3u32,
doc: 3u32,
},
ComparableDoc {
feature: 2u32,
doc: 2u32,
}
]
);
}
#[test]
fn test_topn_computer_no_panic() {
for top_n in 0..10 {
let mut computer: TopNComputer<u32, u32> = TopNComputer::new(top_n);
for _ in 0..1 + top_n * 2 {
computer.push(ComparableDoc {
feature: 1u32,
doc: 1u32,
});
}
let _vals = computer.into_sorted_vec();
}
}
#[test]
fn test_top_collector_not_at_capacity_without_offset() -> crate::Result<()> {
let index = make_index()?;
@@ -983,25 +852,20 @@ mod tests {
// using AllQuery to get a constant score
let searcher = index.reader().unwrap().searcher();
let page_0 = searcher.search(&AllQuery, &TopDocs::with_limit(1)).unwrap();
let page_1 = searcher.search(&AllQuery, &TopDocs::with_limit(2)).unwrap();
let page_2 = searcher.search(&AllQuery, &TopDocs::with_limit(3)).unwrap();
// precondition for the test to be meaningful: we did get documents
// with the same score
assert!(page_0.iter().all(|result| result.0 == page_1[0].0));
assert!(page_1.iter().all(|result| result.0 == page_1[0].0));
assert!(page_2.iter().all(|result| result.0 == page_2[0].0));
// sanity check since we're relying on make_index()
assert_eq!(page_0.len(), 1);
assert_eq!(page_1.len(), 2);
assert_eq!(page_2.len(), 3);
assert_eq!(page_1, &page_2[..page_1.len()]);
assert_eq!(page_0, &page_2[..page_0.len()]);
}
#[test]
@@ -1258,7 +1122,7 @@ mod tests {
mut doc_adder: impl FnMut(&mut IndexWriter),
) -> (Index, Box<dyn Query>) {
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_with_num_threads(1, 15_000_000).unwrap();
let mut index_writer = index.writer_with_num_threads(1, 10_000_000).unwrap();
doc_adder(&mut index_writer);
index_writer.commit().unwrap();
let query_parser = QueryParser::for_index(&index, vec![query_field]);

View File

@@ -16,14 +16,12 @@ use crate::directory::error::OpenReadError;
use crate::directory::MmapDirectory;
use crate::directory::{Directory, ManagedDirectory, RamDirectory, INDEX_WRITER_LOCK};
use crate::error::{DataCorruption, TantivyError};
use crate::indexer::index_writer::{MAX_NUM_THREAD, MEMORY_BUDGET_NUM_BYTES_MIN};
use crate::indexer::index_writer::{MAX_NUM_THREAD, MEMORY_ARENA_NUM_BYTES_MIN};
use crate::indexer::segment_updater::save_metas;
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::{merge_field_meta_data, FieldMetadata, SegmentReader};
use crate::IndexWriter;
fn load_metas(
directory: &dyn Directory,
@@ -122,8 +120,8 @@ impl IndexBuilder {
Self {
schema: None,
index_settings: IndexSettings::default(),
tokenizer_manager: TokenizerManager::default(),
fast_field_tokenizer_manager: TokenizerManager::default(),
tokenizer_manager: TokenizerManager::default_for_indexing(),
fast_field_tokenizer_manager: TokenizerManager::default_for_fast_fields(),
}
}
@@ -186,11 +184,11 @@ impl IndexBuilder {
///
/// It expects an originally empty directory, and will not run any GC operation.
#[doc(hidden)]
pub fn single_segment_index_writer<D: Document>(
pub fn single_segment_index_writer(
self,
dir: impl Into<Box<dyn Directory>>,
mem_budget: usize,
) -> crate::Result<SingleSegmentIndexWriter<D>> {
) -> crate::Result<SingleSegmentIndexWriter> {
let index = self.create(dir)?;
let index_simple_writer = SingleSegmentIndexWriter::new(index, mem_budget)?;
Ok(index_simple_writer)
@@ -402,8 +400,8 @@ impl Index {
settings: metas.index_settings.clone(),
directory,
schema,
tokenizers: TokenizerManager::default(),
fast_field_tokenizers: TokenizerManager::default(),
tokenizers: TokenizerManager::default_for_indexing(),
fast_field_tokenizers: TokenizerManager::default_for_fast_fields(),
executor: Arc::new(Executor::single_thread()),
inventory,
}
@@ -490,28 +488,6 @@ 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
@@ -547,19 +523,19 @@ impl Index {
/// - `num_threads` defines the number of indexing workers that
/// should work at the same time.
///
/// - `overall_memory_budget_in_bytes` sets the amount of memory
/// - `overall_memory_arena_in_bytes` sets the amount of memory
/// allocated for all indexing thread.
/// Each thread will receive a budget of `overall_memory_budget_in_bytes / num_threads`.
/// Each thread will receive a budget of `overall_memory_arena_in_bytes / num_threads`.
///
/// # Errors
/// If the lockfile already exists, returns `Error::DirectoryLockBusy` or an `Error::IoError`.
/// If the memory arena per thread is too small or too big, returns
/// `TantivyError::InvalidArgument`
pub fn writer_with_num_threads<D: Document>(
pub fn writer_with_num_threads(
&self,
num_threads: usize,
overall_memory_budget_in_bytes: usize,
) -> crate::Result<IndexWriter<D>> {
overall_memory_arena_in_bytes: usize,
) -> crate::Result<IndexWriter> {
let directory_lock = self
.directory
.acquire_lock(&INDEX_WRITER_LOCK)
@@ -574,7 +550,7 @@ impl Index {
),
)
})?;
let memory_arena_in_bytes_per_thread = overall_memory_budget_in_bytes / num_threads;
let memory_arena_in_bytes_per_thread = overall_memory_arena_in_bytes / num_threads;
IndexWriter::new(
self,
num_threads,
@@ -585,11 +561,11 @@ impl Index {
/// Helper to create an index writer for tests.
///
/// That index writer only simply has a single thread and a memory budget of 15 MB.
/// That index writer only simply has a single thread and a memory arena of 10 MB.
/// Using a single thread gives us a deterministic allocation of DocId.
#[cfg(test)]
pub fn writer_for_tests<D: Document>(&self) -> crate::Result<IndexWriter<D>> {
self.writer_with_num_threads(1, MEMORY_BUDGET_NUM_BYTES_MIN)
pub fn writer_for_tests(&self) -> crate::Result<IndexWriter> {
self.writer_with_num_threads(1, 10_000_000)
}
/// Creates a multithreaded writer
@@ -603,16 +579,13 @@ impl Index {
/// If the lockfile already exists, returns `Error::FileAlreadyExists`.
/// If the memory arena per thread is too small or too big, returns
/// `TantivyError::InvalidArgument`
pub fn writer<D: Document>(
&self,
memory_budget_in_bytes: usize,
) -> crate::Result<IndexWriter<D>> {
pub fn writer(&self, memory_arena_num_bytes: usize) -> crate::Result<IndexWriter> {
let mut num_threads = std::cmp::min(num_cpus::get(), MAX_NUM_THREAD);
let memory_budget_num_bytes_per_thread = memory_budget_in_bytes / num_threads;
if memory_budget_num_bytes_per_thread < MEMORY_BUDGET_NUM_BYTES_MIN {
num_threads = (memory_budget_in_bytes / MEMORY_BUDGET_NUM_BYTES_MIN).max(1);
let memory_arena_num_bytes_per_thread = memory_arena_num_bytes / num_threads;
if memory_arena_num_bytes_per_thread < MEMORY_ARENA_NUM_BYTES_MIN {
num_threads = (memory_arena_num_bytes / MEMORY_ARENA_NUM_BYTES_MIN).max(1);
}
self.writer_with_num_threads(num_threads, memory_budget_in_bytes)
self.writer_with_num_threads(num_threads, memory_arena_num_bytes)
}
/// Accessor to the index settings

View File

@@ -1,12 +1,11 @@
use std::io;
use common::BinarySerializable;
use fnv::FnvHashSet;
use crate::directory::FileSlice;
use crate::positions::PositionReader;
use crate::postings::{BlockSegmentPostings, SegmentPostings, TermInfo};
use crate::schema::{IndexRecordOption, Term, Type, JSON_END_OF_PATH};
use crate::schema::{IndexRecordOption, Term};
use crate::termdict::TermDictionary;
/// The inverted index reader is in charge of accessing
@@ -70,28 +69,6 @@ impl InvertedIndexReader {
&self.termdict
}
/// Return the fields and types encoded in the dictionary in lexicographic oder.
/// Only valid on JSON fields.
///
/// 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)>> {
let mut stream = self.termdict.stream()?;
let mut fields = Vec::new();
let mut fields_set = FnvHashSet::default();
while let Some((term, _term_info)) = stream.next() {
if let Some(index) = term.iter().position(|&byte| byte == JSON_END_OF_PATH) {
if !fields_set.contains(&term[..index + 2]) {
fields_set.insert(term[..index + 2].to_vec());
let typ = Type::from_code(term[index + 1]).unwrap();
fields.push((String::from_utf8_lossy(&term[..index]).to_string(), typ));
}
}
}
Ok(fields)
}
/// Resets the block segment to another position of the postings
/// file.
///

View File

@@ -1,11 +1,11 @@
use columnar::MonotonicallyMappableToU64;
use common::{replace_in_place, JsonPathWriter};
use common::replace_in_place;
use murmurhash32::murmurhash2;
use rustc_hash::FxHashMap;
use crate::fastfield::FastValue;
use crate::postings::{IndexingContext, IndexingPosition, PostingsWriter};
use crate::schema::document::{ReferenceValue, ReferenceValueLeaf, Value};
use crate::schema::term::JSON_PATH_SEGMENT_SEP;
use crate::schema::term::{JSON_PATH_SEGMENT_SEP, JSON_PATH_SEGMENT_SEP_STR};
use crate::schema::{Field, Type, DATE_TIME_PRECISION_INDEXED};
use crate::time::format_description::well_known::Rfc3339;
use crate::time::{OffsetDateTime, UtcOffset};
@@ -57,41 +57,31 @@ struct IndexingPositionsPerPath {
}
impl IndexingPositionsPerPath {
fn get_position_from_id(&mut self, id: u32) -> &mut IndexingPosition {
self.positions_per_path.entry(id).or_default()
fn get_position(&mut self, term: &Term) -> &mut IndexingPosition {
self.positions_per_path
.entry(murmurhash2(term.serialized_term()))
.or_insert_with(Default::default)
}
}
/// 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>>(
pub(crate) fn index_json_values<'a>(
doc: DocId,
json_visitors: impl Iterator<Item = crate::Result<V::ObjectIter>>,
json_values: impl Iterator<Item = crate::Result<&'a serde_json::Map<String, serde_json::Value>>>,
text_analyzer: &mut TextAnalyzer,
expand_dots_enabled: bool,
term_buffer: &mut Term,
postings_writer: &mut dyn PostingsWriter,
json_path_writer: &mut JsonPathWriter,
ctx: &mut IndexingContext,
) -> crate::Result<()> {
json_path_writer.clear();
json_path_writer.set_expand_dots(expand_dots_enabled);
let mut json_term_writer = JsonTermWriter::wrap(term_buffer, expand_dots_enabled);
let mut positions_per_path: IndexingPositionsPerPath = Default::default();
for json_visitor_res in json_visitors {
let json_visitor = json_visitor_res?;
index_json_object::<V>(
for json_value_res in json_values {
let json_value = json_value_res?;
index_json_object(
doc,
json_visitor,
json_value,
text_analyzer,
term_buffer,
json_path_writer,
&mut json_term_writer,
postings_writer,
ctx,
&mut positions_per_path,
@@ -100,154 +90,93 @@ pub(crate) fn index_json_values<'a, V: Value<'a>>(
Ok(())
}
#[allow(clippy::too_many_arguments)]
fn index_json_object<'a, V: Value<'a>>(
fn index_json_object(
doc: DocId,
json_visitor: V::ObjectIter,
json_value: &serde_json::Map<String, serde_json::Value>,
text_analyzer: &mut TextAnalyzer,
term_buffer: &mut Term,
json_path_writer: &mut JsonPathWriter,
json_term_writer: &mut JsonTermWriter,
postings_writer: &mut dyn PostingsWriter,
ctx: &mut IndexingContext,
positions_per_path: &mut IndexingPositionsPerPath,
) {
for (json_path_segment, json_value_visitor) in json_visitor {
json_path_writer.push(json_path_segment);
for (json_path_segment, json_value) in json_value {
json_term_writer.push_path_segment(json_path_segment);
index_json_value(
doc,
json_value_visitor,
json_value,
text_analyzer,
term_buffer,
json_path_writer,
json_term_writer,
postings_writer,
ctx,
positions_per_path,
);
json_path_writer.pop();
json_term_writer.pop_path_segment();
}
}
#[allow(clippy::too_many_arguments)]
fn index_json_value<'a, V: Value<'a>>(
fn index_json_value(
doc: DocId,
json_value: V,
json_value: &serde_json::Value,
text_analyzer: &mut TextAnalyzer,
term_buffer: &mut Term,
json_path_writer: &mut JsonPathWriter,
json_term_writer: &mut JsonTermWriter,
postings_writer: &mut dyn PostingsWriter,
ctx: &mut IndexingContext,
positions_per_path: &mut IndexingPositionsPerPath,
) {
let set_path_id = |term_buffer: &mut Term, unordered_id: u32| {
term_buffer.truncate_value_bytes(0);
term_buffer.append_bytes(&unordered_id.to_be_bytes());
};
let set_type = |term_buffer: &mut Term, typ: Type| {
term_buffer.append_bytes(&[typ.to_code()]);
};
match json_value.as_value() {
ReferenceValue::Leaf(leaf) => match leaf {
ReferenceValueLeaf::Null => {}
ReferenceValueLeaf::Str(val) => {
let mut token_stream = text_analyzer.token_stream(val);
let unordered_id = ctx
.path_to_unordered_id
.get_or_allocate_unordered_id(json_path_writer.as_str());
// TODO: make sure the chain position works out.
set_path_id(term_buffer, unordered_id);
set_type(term_buffer, Type::Str);
let indexing_position = positions_per_path.get_position_from_id(unordered_id);
match json_value {
serde_json::Value::Null => {}
serde_json::Value::Bool(val_bool) => {
json_term_writer.set_fast_value(*val_bool);
postings_writer.subscribe(doc, 0u32, json_term_writer.term(), ctx);
}
serde_json::Value::Number(number) => {
if let Some(number_i64) = number.as_i64() {
json_term_writer.set_fast_value(number_i64);
} else if let Some(number_u64) = number.as_u64() {
json_term_writer.set_fast_value(number_u64);
} else if let Some(number_f64) = number.as_f64() {
json_term_writer.set_fast_value(number_f64);
}
postings_writer.subscribe(doc, 0u32, json_term_writer.term(), ctx);
}
serde_json::Value::String(text) => match infer_type_from_str(text) {
TextOrDateTime::Text(text) => {
let mut token_stream = text_analyzer.token_stream(text);
// TODO make sure the chain position works out.
json_term_writer.close_path_and_set_type(Type::Str);
let indexing_position = positions_per_path.get_position(json_term_writer.term());
postings_writer.index_text(
doc,
&mut *token_stream,
term_buffer,
json_term_writer.term_buffer,
ctx,
indexing_position,
);
}
ReferenceValueLeaf::U64(val) => {
set_path_id(
term_buffer,
ctx.path_to_unordered_id
.get_or_allocate_unordered_id(json_path_writer.as_str()),
);
term_buffer.append_type_and_fast_value(val);
postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
}
ReferenceValueLeaf::I64(val) => {
set_path_id(
term_buffer,
ctx.path_to_unordered_id
.get_or_allocate_unordered_id(json_path_writer.as_str()),
);
term_buffer.append_type_and_fast_value(val);
postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
}
ReferenceValueLeaf::F64(val) => {
set_path_id(
term_buffer,
ctx.path_to_unordered_id
.get_or_allocate_unordered_id(json_path_writer.as_str()),
);
term_buffer.append_type_and_fast_value(val);
postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
}
ReferenceValueLeaf::Bool(val) => {
set_path_id(
term_buffer,
ctx.path_to_unordered_id
.get_or_allocate_unordered_id(json_path_writer.as_str()),
);
term_buffer.append_type_and_fast_value(val);
postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
}
ReferenceValueLeaf::Date(val) => {
set_path_id(
term_buffer,
ctx.path_to_unordered_id
.get_or_allocate_unordered_id(json_path_writer.as_str()),
);
term_buffer.append_type_and_fast_value(val);
postings_writer.subscribe(doc, 0u32, term_buffer, ctx);
}
ReferenceValueLeaf::PreTokStr(_) => {
unimplemented!(
"Pre-tokenized string support in dynamic fields is not yet implemented"
)
}
ReferenceValueLeaf::Bytes(_) => {
unimplemented!("Bytes support in dynamic fields is not yet implemented")
}
ReferenceValueLeaf::Facet(_) => {
unimplemented!("Facet support in dynamic fields is not yet implemented")
}
ReferenceValueLeaf::IpAddr(_) => {
unimplemented!("IP address support in dynamic fields is not yet implemented")
TextOrDateTime::DateTime(dt) => {
json_term_writer.set_fast_value(DateTime::from_utc(dt));
postings_writer.subscribe(doc, 0u32, json_term_writer.term(), ctx);
}
},
ReferenceValue::Array(elements) => {
for val in elements {
serde_json::Value::Array(arr) => {
for val in arr {
index_json_value(
doc,
val,
text_analyzer,
term_buffer,
json_path_writer,
json_term_writer,
postings_writer,
ctx,
positions_per_path,
);
}
}
ReferenceValue::Object(object) => {
index_json_object::<V>(
serde_json::Value::Object(map) => {
index_json_object(
doc,
object,
map,
text_analyzer,
term_buffer,
json_path_writer,
json_term_writer,
postings_writer,
ctx,
positions_per_path,
@@ -256,6 +185,21 @@ fn index_json_value<'a, V: Value<'a>>(
}
}
enum TextOrDateTime<'a> {
Text(&'a str),
DateTime(OffsetDateTime),
}
fn infer_type_from_str(text: &str) -> TextOrDateTime {
match OffsetDateTime::parse(text, &Rfc3339) {
Ok(dt) => {
let dt_utc = dt.to_offset(UtcOffset::UTC);
TextOrDateTime::DateTime(dt_utc)
}
Err(_) => TextOrDateTime::Text(text),
}
}
// Tries to infer a JSON type from a string.
pub fn convert_to_fast_value_and_get_term(
json_term_writer: &mut JsonTermWriter,
@@ -328,7 +272,7 @@ 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();
@@ -368,13 +312,17 @@ pub(crate) fn encode_column_name(
json_path: &str,
expand_dots_enabled: bool,
) -> String {
let mut path = JsonPathWriter::default();
path.push(field_name);
path.set_expand_dots(expand_dots_enabled);
for segment in split_json_path(json_path) {
path.push(&segment);
let mut column_key: String = String::with_capacity(field_name.len() + json_path.len() + 1);
column_key.push_str(field_name);
for mut segment in split_json_path(json_path) {
column_key.push_str(JSON_PATH_SEGMENT_SEP_STR);
if expand_dots_enabled {
// We need to replace `.` by JSON_PATH_SEGMENT_SEP.
unsafe { replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, segment.as_bytes_mut()) };
}
column_key.push_str(&segment);
}
path.into()
column_key
}
impl<'a> JsonTermWriter<'a> {
@@ -414,7 +362,6 @@ impl<'a> JsonTermWriter<'a> {
self.term_buffer.append_bytes(&[typ.to_code()]);
}
// TODO: Remove this function and use JsonPathWriter instead.
pub fn push_path_segment(&mut self, segment: &str) {
// the path stack should never be empty.
self.trim_to_end_of_path();
@@ -672,21 +619,21 @@ mod tests {
#[test]
fn test_split_json_path_escaped_dot() {
let json_path = split_json_path(r"toto\.titi");
let json_path = split_json_path(r#"toto\.titi"#);
assert_eq!(&json_path, &["toto.titi"]);
let json_path_2 = split_json_path(r"k8s\.container\.name");
let json_path_2 = split_json_path(r#"k8s\.container\.name"#);
assert_eq!(&json_path_2, &["k8s.container.name"]);
}
#[test]
fn test_split_json_path_escaped_backslash() {
let json_path = split_json_path(r"toto\\titi");
assert_eq!(&json_path, &[r"toto\titi"]);
let json_path = split_json_path(r#"toto\\titi"#);
assert_eq!(&json_path, &[r#"toto\titi"#]);
}
#[test]
fn test_split_json_path_escaped_normal_letter() {
let json_path = split_json_path(r"toto\titi");
let json_path = split_json_path(r#"toto\titi"#);
assert_eq!(&json_path, &[r#"tototiti"#]);
}
}

View File

@@ -25,7 +25,7 @@ pub use self::searcher::{Searcher, SearcherGeneration};
pub use self::segment::Segment;
pub use self::segment_component::SegmentComponent;
pub use self::segment_id::SegmentId;
pub use self::segment_reader::{merge_field_meta_data, FieldMetadata, SegmentReader};
pub use self::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

View File

@@ -5,8 +5,7 @@ use std::{fmt, io};
use crate::collector::Collector;
use crate::core::{Executor, SegmentReader};
use crate::query::{Bm25StatisticsProvider, EnableScoring, Query};
use crate::schema::document::DocumentDeserialize;
use crate::schema::{Schema, Term};
use crate::schema::{Document, Schema, Term};
use crate::space_usage::SearcherSpaceUsage;
use crate::store::{CacheStats, StoreReader};
use crate::{DocAddress, Index, Opstamp, SegmentId, TrackedObject};
@@ -84,7 +83,7 @@ impl Searcher {
///
/// The searcher uses the segment ordinal to route the
/// request to the right `Segment`.
pub fn doc<D: DocumentDeserialize>(&self, doc_address: DocAddress) -> crate::Result<D> {
pub fn doc(&self, doc_address: DocAddress) -> crate::Result<Document> {
let store_reader = &self.inner.store_readers[doc_address.segment_ord as usize];
store_reader.get(doc_address.doc_id)
}
@@ -104,10 +103,7 @@ impl Searcher {
/// Fetches a document in an asynchronous manner.
#[cfg(feature = "quickwit")]
pub async fn doc_async<D: DocumentDeserialize>(
&self,
doc_address: DocAddress,
) -> crate::Result<D> {
pub async fn doc_async(&self, doc_address: DocAddress) -> crate::Result<Document> {
let store_reader = &self.inner.store_readers[doc_address.segment_ord as usize];
store_reader.get_async(doc_address.doc_id).await
}

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::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>,
@@ -514,127 +353,9 @@ impl fmt::Debug for SegmentReader {
#[cfg(test)]
mod test {
use super::*;
use crate::core::Index;
use crate::schema::{Schema, SchemaBuilder, Term, STORED, TEXT};
use crate::{DocId, FieldMetadata, IndexWriter};
#[test]
fn test_merge_field_meta_data_same() {
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);
}
use crate::schema::{Schema, Term, STORED, TEXT};
use crate::DocId;
#[test]
fn test_num_alive() -> crate::Result<()> {
@@ -645,7 +366,7 @@ mod test {
let name = schema.get_field("name").unwrap();
{
let mut index_writer: IndexWriter = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests()?;
index_writer.add_document(doc!(name => "tantivy"))?;
index_writer.add_document(doc!(name => "horse"))?;
index_writer.add_document(doc!(name => "jockey"))?;
@@ -671,7 +392,7 @@ mod test {
let name = schema.get_field("name").unwrap();
{
let mut index_writer: IndexWriter = index.writer_for_tests()?;
let mut index_writer = index.writer_for_tests()?;
index_writer.add_document(doc!(name => "tantivy"))?;
index_writer.add_document(doc!(name => "horse"))?;
index_writer.add_document(doc!(name => "jockey"))?;
@@ -681,7 +402,7 @@ mod test {
}
{
let mut index_writer2: IndexWriter = index.writer(50_000_000)?;
let mut index_writer2 = index.writer(50_000_000)?;
index_writer2.delete_term(Term::from_field_text(name, "horse"));
index_writer2.delete_term(Term::from_field_text(name, "cap"));

View File

@@ -1,20 +1,16 @@
use std::marker::PhantomData;
use crate::indexer::operation::AddOperation;
use crate::indexer::segment_updater::save_metas;
use crate::indexer::SegmentWriter;
use crate::schema::document::Document;
use crate::{Directory, Index, IndexMeta, Opstamp, Segment, TantivyDocument};
use crate::{Directory, Document, Index, IndexMeta, Opstamp, Segment};
#[doc(hidden)]
pub struct SingleSegmentIndexWriter<D: Document = TantivyDocument> {
pub struct SingleSegmentIndexWriter {
segment_writer: SegmentWriter,
segment: Segment,
opstamp: Opstamp,
_phantom: PhantomData<D>,
}
impl<D: Document> SingleSegmentIndexWriter<D> {
impl SingleSegmentIndexWriter {
pub fn new(index: Index, mem_budget: usize) -> crate::Result<Self> {
let segment = index.new_segment();
let segment_writer = SegmentWriter::for_segment(mem_budget, segment.clone())?;
@@ -22,7 +18,6 @@ impl<D: Document> SingleSegmentIndexWriter<D> {
segment_writer,
segment,
opstamp: 0,
_phantom: PhantomData,
})
}
@@ -30,7 +25,7 @@ impl<D: Document> SingleSegmentIndexWriter<D> {
self.segment_writer.mem_usage()
}
pub fn add_document(&mut self, document: D) -> crate::Result<()> {
pub fn add_document(&mut self, document: Document) -> crate::Result<()> {
let opstamp = self.opstamp;
self.opstamp += 1;
self.segment_writer

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, Document, Index, IndexBuilder, IndexReader, IndexSettings, ReloadPolicy, SegmentId,
Term,
};
#[test]
@@ -122,7 +121,7 @@ fn test_index_on_commit_reload_policy() -> crate::Result<()> {
let index = Index::create_in_ram(schema);
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()
.unwrap();
assert_eq!(reader.searcher().num_docs(), 0);
@@ -148,7 +147,7 @@ mod mmap_specific {
let index = Index::create_in_dir(tempdir_path, schema).unwrap();
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()
.unwrap();
assert_eq!(reader.searcher().num_docs(), 0);
@@ -160,7 +159,7 @@ mod mmap_specific {
let schema = throw_away_schema();
let field = schema.get_field("num_likes").unwrap();
let mut index = Index::create_from_tempdir(schema)?;
let mut writer: IndexWriter = index.writer_for_tests()?;
let mut writer = index.writer_for_tests()?;
writer.commit()?;
let reader = index
.reader_builder()
@@ -190,7 +189,7 @@ mod mmap_specific {
let read_index = Index::open_in_dir(&tempdir_path).unwrap();
let reader = read_index
.reader_builder()
.reload_policy(ReloadPolicy::OnCommitWithDelay)
.reload_policy(ReloadPolicy::OnCommit)
.try_into()
.unwrap();
assert_eq!(reader.searcher().num_docs(), 0);
@@ -209,7 +208,7 @@ fn test_index_on_commit_reload_policy_aux(
.watch(WatchCallback::new(move || {
let _ = sender.send(());
}));
let mut writer: IndexWriter = index.writer_for_tests()?;
let mut writer = index.writer_for_tests()?;
assert_eq!(reader.searcher().num_docs(), 0);
writer.add_document(doc!(field=>1u64))?;
writer.commit().unwrap();
@@ -243,7 +242,7 @@ fn garbage_collect_works_as_intended() -> crate::Result<()> {
let field = schema.get_field("num_likes").unwrap();
let index = Index::create(directory.clone(), schema, IndexSettings::default())?;
let mut writer: IndexWriter = index.writer_with_num_threads(1, 32_000_000).unwrap();
let mut writer = index.writer_with_num_threads(1, 32_000_000).unwrap();
for _seg in 0..8 {
for i in 0u64..1_000u64 {
writer.add_document(doc!(field => i))?;
@@ -284,7 +283,7 @@ fn test_single_segment_index_writer() -> crate::Result<()> {
let directory = RamDirectory::default();
let mut single_segment_index_writer = Index::builder()
.schema(schema)
.single_segment_index_writer(directory, 15_000_000)?;
.single_segment_index_writer(directory, 10_000_000)?;
for _ in 0..10 {
let doc = doc!(text_field=>"hello");
single_segment_index_writer.add_document(doc)?;
@@ -307,7 +306,7 @@ fn test_merging_segment_update_docfreq() {
let id_field = schema_builder.add_text_field("id", STRING);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer: IndexWriter = index.writer_for_tests().unwrap();
let mut writer = index.writer_for_tests().unwrap();
writer.set_merge_policy(Box::new(NoMergePolicy));
for _ in 0..5 {
writer.add_document(doc!(text_field=>"hello")).unwrap();
@@ -318,13 +317,13 @@ fn test_merging_segment_update_docfreq() {
writer
.add_document(doc!(text_field=>"hello", id_field=>"TO_BE_DELETED"))
.unwrap();
writer.add_document(TantivyDocument::default()).unwrap();
writer.add_document(Document::default()).unwrap();
writer.commit().unwrap();
for _ in 0..7 {
writer.add_document(doc!(text_field=>"hello")).unwrap();
}
writer.add_document(TantivyDocument::default()).unwrap();
writer.add_document(TantivyDocument::default()).unwrap();
writer.add_document(Document::default()).unwrap();
writer.add_document(Document::default()).unwrap();
writer.delete_term(Term::from_field_text(id_field, "TO_BE_DELETED"));
writer.commit().unwrap();
@@ -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);
}
}

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