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Author SHA1 Message Date
Paul Masurel
e6fdba1d21 rebasing composite aggregations 2026-03-18 15:14:38 +01:00
Paul Masurel
ad5eb250fe Fix format 2026-03-16 10:41:11 +01:00
Paul Masurel
d02559a4d1 Update time deps to defensively address a vulnerability. (#2850)
Closes #2849

Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
2026-03-12 16:47:11 +01:00
Anas Limem
1922abaf33 Fixed integer overflow in segment sorting and merge policy truncation (#2846) 2026-03-12 16:44:38 +01:00
trinity-1686a
d0c5ffb0aa Merge pull request #2842 from quickwit-oss/congxie/replaceHll
Use sketches-ddsketch fork with Java-compatible binary encoding
2026-02-20 16:56:56 +01:00
cong.xie
18fedd9384 Fix nightly fmt: merge crate imports in percentiles tests
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-19 14:18:54 -05:00
cong.xie
2098fca47f Restore use_serde feature and simplify PercentilesCollector
Keep use_serde on sketches-ddsketch so DDSketch derives
Serialize/Deserialize, removing the need for custom impls
on PercentilesCollector.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-19 14:13:17 -05:00
cong.xie
1251b40c93 Drop use_serde feature; use Java binary encoding for PercentilesCollector
Replace the derived Serialize/Deserialize on PercentilesCollector with
custom impls that use DDSketch's Java-compatible binary encoding
(encode_to_java_bytes / decode_from_java_bytes). This removes the need
for the use_serde feature on sketches-ddsketch entirely.

Also restore original float test values and use assert_nearly_equals!
for all float comparisons in percentile tests, since DDSketch quantile
estimates can have minor precision differences across platforms.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-19 13:32:28 -05:00
cong.xie
09a49b872c Use assert_nearly_equals! for float comparisons in percentile test
Address review feedback: replace assert_eq! with assert_nearly_equals!
for float values that go through JSON serialization roundtrips, which
can introduce minor precision differences.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-19 13:21:48 -05:00
cong.xie
b9ace002ce Replace vendored sketches-ddsketch with git dependency
Move the vendored sketches-ddsketch crate (with Java-compatible binary
encoding) to its own repo at quickwit-oss/rust-sketches-ddsketch and
reference it via git+rev in Cargo.toml.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-19 12:22:19 -05:00
cong.xie
2dc4e9ef78 fix: resolve remaining clippy errors in ddsketch
- Replace approximate PI/E constants with non-famous value in test
- Fix reversed empty range (2048..0) → (0..2048).rev() in store test

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 15:54:27 -05:00
cong.xie
aeea65f61d refactor: rewrite encoding.rs with idiomatic Rust
- Replace bare constants with FlagType and BinEncodingMode enums
- Use const fn for flag byte construction instead of raw bit ops
- Replace if-else chain with nested match in decode_from_java_bytes
- Use split_first() in read_byte for idiomatic slice consumption
- Use split_at in read_f64_le to avoid TryInto on edition 2018
- Use u64::from(next) instead of `next as u64` casts
- Extract assert_golden, assert_quantiles_match, bytes_to_hex helpers
  to reduce duplication across golden byte tests
- Fix edition-2018 assert! format string compatibility
- Clean up is_valid_flag_byte with let-else and match

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 15:49:12 -05:00
cong.xie
4211d5a1ed fix: resolve clippy warnings in vendored sketches-ddsketch
- manual_range_contains: use !(0.0..=1.0).contains(&q)
- identity_op: simplify (0 << 2) | FLAG_TYPE to just FLAG_TYPE
- manual_clamp: use .clamp(0, 8) instead of .max(0).min(8)
- manual_repeat_n: use repeat_n() instead of repeat().take()
- cast_abs_to_unsigned: use .unsigned_abs() instead of .abs() as usize

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 13:36:06 -05:00
cong.xie
d50c7a1daf Add Java source links for cross-language alignment comments
Reference the exact Java source files in DataDog/sketches-java for
Config::new(), Config::key(), Config::value(), Config::from_gamma(),
and Store::add_count() so readers can verify the alignment.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 13:25:12 -05:00
cong.xie
cf760fd5b6 fix: remove internal reference from code comment
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 12:59:25 -05:00
cong.xie
df04c7d8f1 fix: rustfmt nightly formatting for vendored sketches-ddsketch
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 12:53:01 -05:00
cong.xie
68626bf3a1 Vendor sketches-ddsketch with Java-compatible binary encoding
Fork sketches-ddsketch as a workspace member to add native Java binary
serialization (to_java_bytes/from_java_bytes) for DDSketch. This enables
pomsky to return raw DDSketch bytes that event-query can deserialize via
DDSketchWithExactSummaryStatistics.decode().

Key changes:
- Vendor sketches-ddsketch crate with encoding.rs implementing VarEncoding,
  flag bytes, and INDEX_DELTAS_AND_COUNTS store format
- Align Config::key() to floor-based indexing matching Java's LogarithmicMapping
- Add PercentilesCollector::to_sketch_bytes() for pomsky integration
- Cross-language golden byte tests verified byte-identical with Java output

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-02-18 11:36:21 -05:00
Adrien Guillo
51f340f83d Merge pull request #2837 from quickwit-oss/congxie/replaceHll
Replace hyperloglogplus with Apache DataSketches HLL (lg_k=11)
2026-02-12 17:19:40 -05:00
cong.xie
7eca33143e Remove Datadog-specific references from comments
This is an open-source repo — replace references to Datadog's event query
with generic cross-language compatibility descriptions.
2026-02-12 11:44:42 -05:00
cong.xie
698f073f88 fix fmt 2026-02-11 15:52:39 -05:00
cong.xie
cdd24b7ee5 Replace hyperloglogplus with Apache DataSketches HLL (lg_k=11)
Switch tantivy's cardinality aggregation from the hyperloglogplus crate
(HyperLogLog++ with p=16) to the official Apache DataSketches HLL
implementation (datasketches crate v0.2.0 with lg_k=11, Hll4).

This enables returning raw HLL sketch bytes from pomsky to Datadog's
event query, where they can be properly deserialized and merged using
the same DataSketches library (Java). The previous implementation
required pomsky to fabricate fake HLL sketches from scalar cardinality
estimates, which produced incorrect results when merged.

Changes:
- Cargo.toml: hyperloglogplus 0.4.1 -> datasketches 0.2.0
- CardinalityCollector: HyperLogLogPlus<u64, BuildSaltedHasher> -> HllSketch
- Custom Serde impl using HllSketch binary format (cross-shard compat)
- New to_sketch_bytes() for external consumers (pomsky)
- Salt preserved via (salt, value) tuple hashing for column type disambiguation
- Removed BuildSaltedHasher struct
- Added 4 new unit tests (serde roundtrip, merge, binary compat, salt)
2026-02-11 08:49:46 -05:00
PSeitz
57fe659fff make serializer pub (#2835)
some changes on the posting list serializer to make it usable in
other contexts.

Improve errors

Signed-off-by: Pascal Seitz <pascal.seitz@gmail.com>
2026-02-11 14:37:42 +01:00
trinity-1686a
5562ce6037 Merge pull request #2818 from Darkheir/fix/query_grammar_regex_between_parentheses 2026-02-11 11:39:58 +01:00
Metin Dumandag
09b6ececa7 Export fields of the PercentileValuesVecEntry (#2833)
Otherwise, there is no way to access these fields when not using the
json serialized form of the aggregation results.

This simple data struct is part of the public api,
so its fields should be accessible as well.
2026-02-11 11:31:07 +01:00
Moe
8018016e46 feat: add fast field support for Bytes type (#100) (#2830)
## What

Enable range queries and TopN sorting on `Bytes` fast fields, bringing them to parity with `Str` fields.

## Why

`BytesColumn` uses the same dictionary encoding as `StrColumn` internally, but range queries and TopN sorting were explicitly disabled for `Bytes`. This prevented use cases like storing lexicographically sortable binary data (e.g., arbitrary-precision decimals) that need efficient range filtering.

## How

1. **Enable range queries for Bytes** - Changed `is_type_valid_for_fastfield_range_query()` to return `true` for `Type::Bytes`
2. **Add BytesColumn handling in scorer** - Added a branch in `FastFieldRangeWeight::scorer()` to handle bytes fields using dictionary ordinal lookup (mirrors the existing `StrColumn` logic)
3. **Add SortByBytes** - New sort key computer for TopN queries on bytes columns

## Tests

- `test_bytes_field_ff_range_query` - Tests inclusive/exclusive bounds and unbounded ranges
- `test_sort_by_bytes_asc` / `test_sort_by_bytes_desc` - Tests lexicographic ordering in both directions
2026-02-11 11:26:18 +01:00
trinity-1686a
6bf185dc3f Merge pull request #2829 from quickwit-oss/cong.xie/add-intermediate-accessors 2026-02-10 17:07:24 +01:00
cong.xie
bb141abe22 feat(aggregation): add keys() accessor to IntermediateAggregationResults 2026-02-09 15:38:35 -05:00
cong.xie
f1c29ba972 resolve conflcit 2026-02-06 14:23:11 -05:00
cong.xie
ae0554a6a5 feat(aggregation): add public accessors for intermediate aggregation results
Add accessor methods to allow external crates to read intermediate
aggregation results without accessing pub(crate) fields:

- IntermediateAggregationResults: get(), remove()
- IntermediateTermBucketResult: entries(), sum_other_doc_count(), doc_count_error_upper_bound()
- IntermediateAverage: stats()
- IntermediateStats: count(), sum()
- IntermediateKey: Display impl for string conversion
2026-02-06 11:12:20 -05:00
cong.xie
0d7abe5d23 feat(aggregation): add public accessors for intermediate aggregation results
Add accessor methods to allow external crates to read intermediate
aggregation results without accessing pub(crate) fields:

- IntermediateAggregationResults: get(), get_mut(), remove()
- IntermediateTermBucketResult: entries(), sum_other_doc_count(), doc_count_error_upper_bound()
- IntermediateAverage: stats()
- IntermediateStats: count(), sum()
- IntermediateKey: Display impl for string conversion
2026-02-06 10:28:59 -05:00
PSeitz
28db952131 Add regex search and merge segments benchmark (#2826)
* add merge_segments benchmark

* add regex search bench
2026-02-02 17:28:02 +01:00
PSeitz
98ebbf922d faster exclude queries (#2825)
* faster exclude queries

Faster exclude queries with multiple terms.

Changes `Exclude` to be able to exclude multiple DocSets, instead of
putting the docsets into a union.
Use `seek_danger` in `Exclude`.

closes #2822

* replace unwrap with match
2026-01-30 17:06:41 +01:00
Paul Masurel
4a89e74597 Fix rfc3339 typos and add Claude Code skills (#2823)
Closes #2817
2026-01-30 12:00:28 +01:00
Alex Lazar
4d99e51e50 Bump oneshot to 0.1.13 per dependabot (#2821) 2026-01-30 11:42:01 +01:00
Darkheir
a55e4069e4 feat(query-grammar): Apply PR review suggestions
Signed-off-by: Darkheir <raphael.cohen@sekoia.io>
2026-01-28 14:13:55 +01:00
Darkheir
1fd30c62be fix(query-grammar): Fix regexes between parentheses
Signed-off-by: Darkheir <raphael.cohen@sekoia.io>
2026-01-28 10:37:51 +01:00
trinity-1686a
9b619998bd Merge pull request #2816 from evance-br/fix-closing-paren-elastic-range 2026-01-27 17:00:08 +01:00
Evance Soumaoro
765c448945 uncomment commented code when testing 2026-01-27 13:19:41 +00:00
Evance Soumaoro
943594ebaa uncomment commented code when testing 2026-01-27 13:08:38 +00:00
Evance Soumaoro
df17daae0d fix closing parenthesis error on elastic range queries for lenient parser 2026-01-27 13:01:14 +00:00
Paul Masurel
0ae94baef5 Remove temp file (#2815)
Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
2026-01-27 09:22:11 +01:00
Paul Masurel
3f448ecf79 Bugfix on intersection. (#2812)
The intersection algorithm made it possible for .seek(..) with values
lower than the current doc id, breaking the DocSet contract.

The fix removes the optimization that caused left.seek(..) to be replaced
by a simpler left.advance(..).

Simply doing so lead to a performance regression.
I therefore integrated that idea within SegmentPostings.seek.

We now attempt to check the next doc systematically on seek,
PROVIDED the block is already loaded.

Closes #2811

Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
2026-01-27 09:21:09 +01:00
Paul Masurel
b86caeefe2 Major bugfix in intersection
A bug was added with the `seek_into_the_danger_zone()` optimization

(Spotted and fixed by Stu)

The contract says seek_into_the_danger_zone returns true if do is part of the docset.

The blanket implementation goes like this.

```
let current_doc = self.doc();
if current_doc < target {
     self.seek(target);
}
self.doc() == target
```

So it will return true if target is TERMINATED, where really TERMINATED does not belong to the docset.


The fix tries to clarify the contracts and fixes the intersection algorithm.
We observe a small but all over the board improvement in intersection performance.

---------

Co-authored-by: Stu Hood <stuhood@gmail.com>
Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
2026-01-23 18:44:10 +01:00
ChangRui-Ryan
abf1e64f4d add benchmark for string search and get (#2795) 2026-01-19 11:50:41 +01:00
trinity-1686a
12977bc7c4 upgrade some dependancies (#2802)
including rand, which had a few breaking changes
2026-01-14 10:19:09 +01:00
trinity-1686a
0c94eb94c3 Merge pull request #2799 from jollygreenlaser/lru 2026-01-13 22:47:35 +01:00
Paul Masurel
c92e831dde Minor refactoring in PostingsSerializer (#2801)
Removes the Write generics argument in PostingsSerializer.
This removes useless generic.
Prepares the path for codecs.
Removes one useless CountingWrite layer.
etc.

Co-authored-by: Paul Masurel <paul.masurel@datadoghq.com>
2026-01-12 13:53:43 +01:00
Alex Lazar
947c0d5f40 Bump lru to 0.16.3 per dependabot 2026-01-09 23:25:51 -08:00
142 changed files with 8162 additions and 2664 deletions

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@@ -0,0 +1,125 @@
---
name: rationalize-deps
description: Analyze Cargo.toml dependencies and attempt to remove unused features to reduce compile times and binary size
---
# Rationalize Dependencies
This skill analyzes Cargo.toml dependencies to identify and remove unused features.
## Overview
Many crates enable features by default that may not be needed. This skill:
1. Identifies dependencies with default features enabled
2. Tests if `default-features = false` works
3. Identifies which specific features are actually needed
4. Verifies compilation after changes
## Step 1: Identify the target
Ask the user which crate(s) to analyze:
- A specific crate name (e.g., "tokio", "serde")
- A specific workspace member (e.g., "quickwit-search")
- "all" to scan the entire workspace
## Step 2: Analyze current dependencies
For the workspace Cargo.toml (`quickwit/Cargo.toml`), list dependencies that:
- Do NOT have `default-features = false`
- Have default features that might be unnecessary
Run: `cargo tree -p <crate> -f "{p} {f}" --edges features` to see what features are actually used.
## Step 3: For each candidate dependency
### 3a: Check the crate's default features
Look up the crate on crates.io or check its Cargo.toml to understand:
- What features are enabled by default
- What each feature provides
Use: `cargo metadata --format-version=1 | jq '.packages[] | select(.name == "<crate>") | .features'`
### 3b: Try disabling default features
Modify the dependency in `quickwit/Cargo.toml`:
From:
```toml
some-crate = { version = "1.0" }
```
To:
```toml
some-crate = { version = "1.0", default-features = false }
```
### 3c: Run cargo check
Run: `cargo check --workspace` (or target specific packages for faster feedback)
If compilation fails:
1. Read the error messages to identify which features are needed
2. Add only the required features explicitly:
```toml
some-crate = { version = "1.0", default-features = false, features = ["needed-feature"] }
```
3. Re-run cargo check
### 3d: Binary search for minimal features
If there are many default features, use binary search:
1. Start with no features
2. If it fails, add half the default features
3. Continue until you find the minimal set
## Step 4: Document findings
For each dependency analyzed, report:
- Original configuration
- New configuration (if changed)
- Features that were removed
- Any features that are required
## Step 5: Verify full build
After all changes, run:
```bash
cargo check --workspace --all-targets
cargo test --workspace --no-run
```
## Common Patterns
### Serde
Often only needs `derive`:
```toml
serde = { version = "1.0", default-features = false, features = ["derive", "std"] }
```
### Tokio
Identify which runtime features are actually used:
```toml
tokio = { version = "1.0", default-features = false, features = ["rt-multi-thread", "macros", "sync"] }
```
### Reqwest
Often doesn't need all TLS backends:
```toml
reqwest = { version = "0.11", default-features = false, features = ["rustls-tls", "json"] }
```
## Rollback
If changes cause issues:
```bash
git checkout quickwit/Cargo.toml
cargo check --workspace
```
## Tips
- Start with large crates that have many default features (tokio, reqwest, hyper)
- Use `cargo bloat --crates` to identify large dependencies
- Check `cargo tree -d` for duplicate dependencies that might indicate feature conflicts
- Some features are needed only for tests - consider using `[dev-dependencies]` features

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@@ -0,0 +1,60 @@
---
name: simple-pr
description: Create a simple PR from staged changes with an auto-generated commit message
disable-model-invocation: true
---
# Simple PR
Follow these steps to create a simple PR from staged changes:
## Step 1: Check workspace state
Run: `git status`
Verify that all changes have been staged (no unstaged changes). If there are unstaged changes, abort and ask the user to stage their changes first with `git add`.
Also verify that we are on the `main` branch. If not, abort and ask the user to switch to main first.
## Step 2: Ensure main is up to date
Run: `git pull origin main`
This ensures we're working from the latest code.
## Step 3: Review staged changes
Run: `git diff --cached`
Review the staged changes to understand what the PR will contain.
## Step 4: Generate commit message
Based on the staged changes, generate a concise commit message (1-2 sentences) that describes the "why" rather than the "what".
Display the proposed commit message to the user and ask for confirmation before proceeding.
## Step 5: Create a new branch
Get the git username: `git config user.name | tr ' ' '-' | tr '[:upper:]' '[:lower:]'`
Create a short, descriptive branch name based on the changes (e.g., `fix-typo-in-readme`, `add-retry-logic`, `update-deps`).
Create and checkout the branch: `git checkout -b {username}/{short-descriptive-name}`
## Step 6: Commit changes
Commit with the message from step 3:
```
git commit -m "{commit-message}"
```
## Step 7: Push and open a PR
Push the branch and open a PR:
```
git push -u origin {branch-name}
gh pr create --title "{commit-message-title}" --body "{longer-description-if-needed}"
```
Report the PR URL to the user when complete.

View File

@@ -15,7 +15,7 @@ rust-version = "1.85"
exclude = ["benches/*.json", "benches/*.txt"]
[dependencies]
oneshot = "0.1.7"
oneshot = "0.1.13"
base64 = "0.22.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
@@ -27,7 +27,7 @@ regex = { version = "1.5.5", default-features = false, features = [
aho-corasick = "1.0"
tantivy-fst = "0.5"
memmap2 = { version = "0.9.0", optional = true }
lz4_flex = { version = "0.11", default-features = false, optional = true }
lz4_flex = { version = "0.12", default-features = false, optional = true }
zstd = { version = "0.13", optional = true, default-features = false }
tempfile = { version = "3.12.0", optional = true }
log = "0.4.16"
@@ -47,10 +47,10 @@ rustc-hash = "2.0.0"
thiserror = "2.0.1"
htmlescape = "0.3.1"
fail = { version = "0.5.0", optional = true }
time = { version = "0.3.35", features = ["serde-well-known"] }
time = { version = "0.3.47", features = ["serde-well-known"] }
smallvec = "1.8.0"
rayon = "1.5.2"
lru = "0.12.0"
lru = "0.16.3"
fastdivide = "0.4.0"
itertools = "0.14.0"
measure_time = "0.9.0"
@@ -64,8 +64,8 @@ query-grammar = { version = "0.25.0", path = "./query-grammar", package = "tanti
tantivy-bitpacker = { version = "0.9", path = "./bitpacker" }
common = { version = "0.10", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version = "0.6", path = "./tokenizer-api", package = "tantivy-tokenizer-api" }
sketches-ddsketch = { version = "0.3.0", features = ["use_serde"] }
hyperloglogplus = { version = "0.4.1", features = ["const-loop"] }
sketches-ddsketch = { git = "https://github.com/quickwit-oss/rust-sketches-ddsketch.git", rev = "555caf1", features = ["use_serde"] }
datasketches = "0.2.0"
futures-util = { version = "0.3.28", optional = true }
futures-channel = { version = "0.3.28", optional = true }
fnv = "1.0.7"
@@ -76,7 +76,7 @@ winapi = "0.3.9"
[dev-dependencies]
binggan = "0.14.2"
rand = "0.8.5"
rand = "0.9"
maplit = "1.0.2"
matches = "0.1.9"
pretty_assertions = "1.2.1"
@@ -85,8 +85,8 @@ test-log = "0.2.10"
futures = "0.3.21"
paste = "1.0.11"
more-asserts = "0.3.1"
rand_distr = "0.4.3"
time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
rand_distr = "0.5"
time = { version = "0.3.47", features = ["serde-well-known", "macros"] }
postcard = { version = "1.0.4", features = [
"use-std",
], default-features = false }
@@ -189,3 +189,15 @@ harness = false
[[bench]]
name = "bool_queries_with_range"
harness = false
[[bench]]
name = "str_search_and_get"
harness = false
[[bench]]
name = "merge_segments"
harness = false
[[bench]]
name = "regex_all_terms"
harness = false

View File

@@ -1,8 +1,8 @@
use binggan::plugins::PeakMemAllocPlugin;
use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
use rand::distributions::WeightedIndex;
use rand::prelude::SliceRandom;
use rand::distr::weighted::WeightedIndex;
use rand::rngs::StdRng;
use rand::seq::IndexedRandom;
use rand::{Rng, SeedableRng};
use rand_distr::Distribution;
use serde_json::json;
@@ -10,7 +10,7 @@ use tantivy::aggregation::agg_req::Aggregations;
use tantivy::aggregation::AggregationCollector;
use tantivy::query::{AllQuery, TermQuery};
use tantivy::schema::{IndexRecordOption, Schema, TextFieldIndexing, FAST, STRING};
use tantivy::{doc, Index, Term};
use tantivy::{doc, DateTime, Index, Term};
#[global_allocator]
pub static GLOBAL: &PeakMemAlloc<std::alloc::System> = &INSTRUMENTED_SYSTEM;
@@ -70,6 +70,12 @@ fn bench_agg(mut group: InputGroup<Index>) {
register!(group, terms_many_json_mixed_type_with_avg_sub_agg);
register!(group, composite_term_many_page_1000);
register!(group, composite_term_many_page_1000_with_avg_sub_agg);
register!(group, composite_term_few);
register!(group, composite_histogram);
register!(group, composite_histogram_calendar);
register!(group, cardinality_agg);
register!(group, terms_status_with_cardinality_agg);
@@ -314,6 +320,75 @@ fn terms_many_json_mixed_type_with_avg_sub_agg(index: &Index) {
execute_agg(index, agg_req);
}
fn composite_term_few(index: &Index) {
let agg_req = json!({
"my_ctf": {
"composite": {
"sources": [
{ "text_few_terms": { "terms": { "field": "text_few_terms" } } }
],
"size": 1000
}
},
});
execute_agg(index, agg_req);
}
fn composite_term_many_page_1000(index: &Index) {
let agg_req = json!({
"my_ctmp1000": {
"composite": {
"sources": [
{ "text_many_terms": { "terms": { "field": "text_many_terms" } } }
],
"size": 1000
}
},
});
execute_agg(index, agg_req);
}
fn composite_term_many_page_1000_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"my_ctmp1000wasa": {
"composite": {
"sources": [
{ "text_many_terms": { "terms": { "field": "text_many_terms" } } }
],
"size": 1000,
},
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
},
});
execute_agg(index, agg_req);
}
fn composite_histogram(index: &Index) {
let agg_req = json!({
"my_ch": {
"composite": {
"sources": [
{ "f64_histogram": { "histogram": { "field": "score_f64", "interval": 1 } } }
],
"size": 1000
}
},
});
execute_agg(index, agg_req);
}
fn composite_histogram_calendar(index: &Index) {
let agg_req = json!({
"my_chc": {
"composite": {
"sources": [
{ "time_histogram": { "date_histogram": { "field": "timestamp", "calendar_interval": "month" } } }
],
"size": 1000
}
},
});
execute_agg(index, agg_req);
}
fn execute_agg(index: &Index, agg_req: serde_json::Value) {
let agg_req: Aggregations = serde_json::from_value(agg_req).unwrap();
let collector = get_collector(agg_req);
@@ -496,6 +571,7 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
let text_field_all_unique_terms =
schema_builder.add_text_field("text_all_unique_terms", STRING | FAST);
let text_field_many_terms = schema_builder.add_text_field("text_many_terms", STRING | FAST);
let text_field_few_terms = schema_builder.add_text_field("text_few_terms", STRING | FAST);
let text_field_few_terms_status =
schema_builder.add_text_field("text_few_terms_status", STRING | FAST);
let text_field_1000_terms_zipf =
@@ -504,6 +580,7 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
let score_field = schema_builder.add_u64_field("score", score_fieldtype.clone());
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 date_field = schema_builder.add_date_field("timestamp", FAST);
// use tmp dir
let index = if reuse_index {
Index::create_in_dir("agg_bench", schema_builder.build())?
@@ -523,6 +600,7 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
let log_level_distribution =
WeightedIndex::new(status_field_data.iter().map(|item| item.1)).unwrap();
let few_terms_data = ["INFO", "ERROR", "WARN", "DEBUG"];
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
let many_terms_data = (0..150_000)
@@ -532,7 +610,7 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
// Prepare 1000 unique terms sampled using a Zipf distribution.
// Exponent ~1.1 approximates top-20 terms covering around ~20%.
let terms_1000: Vec<String> = (1..=1000).map(|i| format!("term_{i}")).collect();
let zipf_1000 = rand_distr::Zipf::new(1000, 1.1f64).unwrap();
let zipf_1000 = rand_distr::Zipf::new(1000.0, 1.1f64).unwrap();
{
let mut rng = StdRng::from_seed([1u8; 32]);
@@ -558,6 +636,8 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
text_field_all_unique_terms => "coolo",
text_field_many_terms => "cool",
text_field_many_terms => "cool",
text_field_few_terms => "cool",
text_field_few_terms => "cool",
text_field_few_terms_status => log_level_sample_a,
text_field_few_terms_status => log_level_sample_b,
text_field_1000_terms_zipf => term_1000_a.as_str(),
@@ -576,8 +656,8 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
}
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) {
let val: f64 = rng.random_range(0.0..1_000_000.0);
let json = if rng.random_bool(0.1) {
// 10% are numeric values
json!({ "mixed_type": val })
} else {
@@ -586,13 +666,15 @@ fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
index_writer.add_document(doc!(
text_field => "cool",
json_field => json,
text_field_all_unique_terms => format!("unique_term_{}", rng.gen::<u64>()),
text_field_all_unique_terms => format!("unique_term_{}", rng.random::<u64>()),
text_field_many_terms => many_terms_data.choose(&mut rng).unwrap().to_string(),
text_field_few_terms => few_terms_data.choose(&mut rng).unwrap().to_string(),
text_field_few_terms_status => status_field_data[log_level_distribution.sample(&mut rng)].0,
text_field_1000_terms_zipf => terms_1000[zipf_1000.sample(&mut rng) as usize - 1].as_str(),
score_field => val as u64,
score_field_f64 => lg_norm.sample(&mut rng),
score_field_i64 => val as i64,
date_field => DateTime::from_timestamp_millis((val * 1_000_000.) as i64),
))?;
if cardinality == Cardinality::OptionalSparse {
for _ in 0..20 {

View File

@@ -55,29 +55,29 @@ fn build_shared_indices(num_docs: usize, p_a: f32, p_b: f32, p_c: f32) -> (Bench
{
let mut writer = index.writer_with_num_threads(1, 500_000_000).unwrap();
for _ in 0..num_docs {
let has_a = rng.gen_bool(p_a as f64);
let has_b = rng.gen_bool(p_b as f64);
let has_c = rng.gen_bool(p_c as f64);
let score = rng.gen_range(0u64..100u64);
let score2 = rng.gen_range(0u64..100_000u64);
let has_a = rng.random_bool(p_a as f64);
let has_b = rng.random_bool(p_b as f64);
let has_c = rng.random_bool(p_c as f64);
let score = rng.random_range(0u64..100u64);
let score2 = rng.random_range(0u64..100_000u64);
let mut title_tokens: Vec<&str> = Vec::new();
let mut body_tokens: Vec<&str> = Vec::new();
if has_a {
if rng.gen_bool(0.1) {
if rng.random_bool(0.1) {
title_tokens.push("a");
} else {
body_tokens.push("a");
}
}
if has_b {
if rng.gen_bool(0.1) {
if rng.random_bool(0.1) {
title_tokens.push("b");
} else {
body_tokens.push("b");
}
}
if has_c {
if rng.gen_bool(0.1) {
if rng.random_bool(0.1) {
title_tokens.push("c");
} else {
body_tokens.push("c");

View File

@@ -36,13 +36,13 @@ fn build_shared_indices(num_docs: usize, p_title_a: f32, distribution: &str) ->
"dense" => {
for doc_id in 0..num_docs {
// Always add title to avoid empty documents
let title_token = if rng.gen_bool(p_title_a as f64) {
let title_token = if rng.random_bool(p_title_a as f64) {
"a"
} else {
"b"
};
let num_rand = rng.gen_range(0u64..1000u64);
let num_rand = rng.random_range(0u64..1000u64);
let num_asc = (doc_id / 10000) as u64;
@@ -60,13 +60,13 @@ fn build_shared_indices(num_docs: usize, p_title_a: f32, distribution: &str) ->
"sparse" => {
for doc_id in 0..num_docs {
// Always add title to avoid empty documents
let title_token = if rng.gen_bool(p_title_a as f64) {
let title_token = if rng.random_bool(p_title_a as f64) {
"a"
} else {
"b"
};
let num_rand = rng.gen_range(0u64..10000000u64);
let num_rand = rng.random_range(0u64..10000000u64);
let num_asc = doc_id as u64;

224
benches/merge_segments.rs Normal file
View File

@@ -0,0 +1,224 @@
// Benchmarks segment merging
//
// Notes:
// - Input segments are kept intact (no deletes / no IndexWriter merge).
// - Output is written to a `NullDirectory` that discards all files except
// fieldnorms (needed for merging).
use std::collections::HashMap;
use std::io::{self, Write};
use std::path::{Path, PathBuf};
use std::sync::{Arc, RwLock};
use binggan::{black_box, BenchRunner};
use rand::prelude::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use tantivy::directory::error::{DeleteError, OpenReadError, OpenWriteError};
use tantivy::directory::{
AntiCallToken, Directory, FileHandle, OwnedBytes, TerminatingWrite, WatchCallback, WatchHandle,
WritePtr,
};
use tantivy::indexer::{merge_filtered_segments, NoMergePolicy};
use tantivy::schema::{Schema, TEXT};
use tantivy::{doc, HasLen, Index, IndexSettings, Segment};
#[derive(Clone, Default, Debug)]
struct NullDirectory {
blobs: Arc<RwLock<HashMap<PathBuf, OwnedBytes>>>,
}
struct NullWriter;
impl Write for NullWriter {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
Ok(buf.len())
}
fn flush(&mut self) -> io::Result<()> {
Ok(())
}
}
impl TerminatingWrite for NullWriter {
fn terminate_ref(&mut self, _token: AntiCallToken) -> io::Result<()> {
Ok(())
}
}
struct InMemoryWriter {
path: PathBuf,
buffer: Vec<u8>,
blobs: Arc<RwLock<HashMap<PathBuf, OwnedBytes>>>,
}
impl Write for InMemoryWriter {
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
self.buffer.extend_from_slice(buf);
Ok(buf.len())
}
fn flush(&mut self) -> io::Result<()> {
Ok(())
}
}
impl TerminatingWrite for InMemoryWriter {
fn terminate_ref(&mut self, _token: AntiCallToken) -> io::Result<()> {
let bytes = OwnedBytes::new(std::mem::take(&mut self.buffer));
self.blobs.write().unwrap().insert(self.path.clone(), bytes);
Ok(())
}
}
#[derive(Debug, Default)]
struct NullFileHandle;
impl HasLen for NullFileHandle {
fn len(&self) -> usize {
0
}
}
impl FileHandle for NullFileHandle {
fn read_bytes(&self, _range: std::ops::Range<usize>) -> io::Result<OwnedBytes> {
unimplemented!()
}
}
impl Directory for NullDirectory {
fn get_file_handle(&self, path: &Path) -> Result<Arc<dyn FileHandle>, OpenReadError> {
if let Some(bytes) = self.blobs.read().unwrap().get(path) {
return Ok(Arc::new(bytes.clone()));
}
Ok(Arc::new(NullFileHandle))
}
fn delete(&self, _path: &Path) -> Result<(), DeleteError> {
Ok(())
}
fn exists(&self, _path: &Path) -> Result<bool, OpenReadError> {
Ok(true)
}
fn open_write(&self, path: &Path) -> Result<WritePtr, OpenWriteError> {
let path_buf = path.to_path_buf();
if path.to_string_lossy().ends_with(".fieldnorm") {
let writer = InMemoryWriter {
path: path_buf,
buffer: Vec::new(),
blobs: Arc::clone(&self.blobs),
};
Ok(io::BufWriter::new(Box::new(writer)))
} else {
Ok(io::BufWriter::new(Box::new(NullWriter)))
}
}
fn atomic_read(&self, path: &Path) -> Result<Vec<u8>, OpenReadError> {
if let Some(bytes) = self.blobs.read().unwrap().get(path) {
return Ok(bytes.as_slice().to_vec());
}
Err(OpenReadError::FileDoesNotExist(path.to_path_buf()))
}
fn atomic_write(&self, _path: &Path, _data: &[u8]) -> io::Result<()> {
Ok(())
}
fn sync_directory(&self) -> io::Result<()> {
Ok(())
}
fn watch(&self, _watch_callback: WatchCallback) -> tantivy::Result<WatchHandle> {
Ok(WatchHandle::empty())
}
}
struct MergeScenario {
#[allow(dead_code)]
index: Index,
segments: Vec<Segment>,
settings: IndexSettings,
label: String,
}
fn build_index(
num_segments: usize,
docs_per_segment: usize,
tokens_per_doc: usize,
vocab_size: usize,
) -> MergeScenario {
let mut schema_builder = Schema::builder();
let body = schema_builder.add_text_field("body", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
assert!(vocab_size > 0);
let total_tokens = num_segments * docs_per_segment * tokens_per_doc;
let use_unique_terms = vocab_size >= total_tokens;
let mut rng = StdRng::from_seed([7u8; 32]);
let mut next_token_id: u64 = 0;
{
let mut writer = index.writer_with_num_threads(1, 256_000_000).unwrap();
writer.set_merge_policy(Box::new(NoMergePolicy));
for _ in 0..num_segments {
for _ in 0..docs_per_segment {
let mut tokens = Vec::with_capacity(tokens_per_doc);
for _ in 0..tokens_per_doc {
let token_id = if use_unique_terms {
let id = next_token_id;
next_token_id += 1;
id
} else {
rng.random_range(0..vocab_size as u64)
};
tokens.push(format!("term_{token_id}"));
}
writer.add_document(doc!(body => tokens.join(" "))).unwrap();
}
writer.commit().unwrap();
}
}
let segments = index.searchable_segments().unwrap();
let settings = index.settings().clone();
let label = format!(
"segments={}, docs/seg={}, tokens/doc={}, vocab={}",
num_segments, docs_per_segment, tokens_per_doc, vocab_size
);
MergeScenario {
index,
segments,
settings,
label,
}
}
fn main() {
let scenarios = vec![
build_index(8, 50_000, 12, 8),
build_index(16, 50_000, 12, 8),
build_index(16, 100_000, 12, 8),
build_index(8, 50_000, 8, 8 * 50_000 * 8),
];
let mut runner = BenchRunner::new();
for scenario in scenarios {
let mut group = runner.new_group();
group.set_name(format!("merge_segments inv_index — {}", scenario.label));
let segments = scenario.segments.clone();
let settings = scenario.settings.clone();
group.register("merge", move |_| {
let output_dir = NullDirectory::default();
let filter_doc_ids = vec![None; segments.len()];
let merged_index =
merge_filtered_segments(&segments, settings.clone(), filter_doc_ids, output_dir)
.unwrap();
black_box(merged_index);
});
group.run();
}
}

View File

@@ -33,7 +33,7 @@ fn build_shared_indices(num_docs: usize, distribution: &str) -> BenchIndex {
match distribution {
"dense" => {
for doc_id in 0..num_docs {
let num_rand = rng.gen_range(0u64..1000u64);
let num_rand = rng.random_range(0u64..1000u64);
let num_asc = (doc_id / 10000) as u64;
writer
@@ -46,7 +46,7 @@ fn build_shared_indices(num_docs: usize, distribution: &str) -> BenchIndex {
}
"sparse" => {
for doc_id in 0..num_docs {
let num_rand = rng.gen_range(0u64..10000000u64);
let num_rand = rng.random_range(0u64..10000000u64);
let num_asc = doc_id as u64;
writer

View File

@@ -97,20 +97,20 @@ fn get_index_0_to_100() -> Index {
let num_vals = 100_000;
let docs: Vec<_> = (0..num_vals)
.map(|_i| {
let id_name = if rng.gen_bool(0.01) {
let id_name = if rng.random_bool(0.01) {
"veryfew".to_string() // 1%
} else if rng.gen_bool(0.1) {
} else if rng.random_bool(0.1) {
"few".to_string() // 9%
} else {
"most".to_string() // 90%
};
Doc {
id_name,
id: rng.gen_range(0..100),
id: rng.random_range(0..100),
// Multiply by 1000, so that we create most buckets in the compact space
// The benches depend on this range to select n-percent of elements with the
// methods below.
ip: Ipv6Addr::from_u128(rng.gen_range(0..100) * 1000),
ip: Ipv6Addr::from_u128(rng.random_range(0..100) * 1000),
}
})
.collect();

113
benches/regex_all_terms.rs Normal file
View File

@@ -0,0 +1,113 @@
// Benchmarks regex query that matches all terms in a synthetic index.
//
// Corpus model:
// - N unique terms: t000000, t000001, ...
// - M docs
// - K tokens per doc: doc i gets terms derived from (i, token_index)
//
// Query:
// - Regex "t.*" to match all terms
//
// Run with:
// - cargo bench --bench regex_all_terms
//
use std::fmt::Write;
use binggan::{black_box, BenchRunner};
use tantivy::collector::Count;
use tantivy::query::RegexQuery;
use tantivy::schema::{Schema, TEXT};
use tantivy::{doc, Index, ReloadPolicy};
const HEAP_SIZE_BYTES: usize = 200_000_000;
#[derive(Clone, Copy)]
struct BenchConfig {
num_terms: usize,
num_docs: usize,
tokens_per_doc: usize,
}
fn main() {
let configs = default_configs();
let mut runner = BenchRunner::new();
for config in configs {
let (index, text_field) = build_index(config, HEAP_SIZE_BYTES);
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()
.expect("reader");
let searcher = reader.searcher();
let query = RegexQuery::from_pattern("t.*", text_field).expect("regex query");
let mut group = runner.new_group();
group.set_name(format!(
"regex_all_terms_t{}_d{}_k{}",
config.num_terms, config.num_docs, config.tokens_per_doc
));
group.register("regex_count", move |_| {
let count = searcher.search(&query, &Count).expect("search");
black_box(count);
});
group.run();
}
}
fn default_configs() -> Vec<BenchConfig> {
vec![
BenchConfig {
num_terms: 10_000,
num_docs: 100_000,
tokens_per_doc: 1,
},
BenchConfig {
num_terms: 10_000,
num_docs: 100_000,
tokens_per_doc: 8,
},
BenchConfig {
num_terms: 100_000,
num_docs: 100_000,
tokens_per_doc: 1,
},
BenchConfig {
num_terms: 100_000,
num_docs: 100_000,
tokens_per_doc: 8,
},
]
}
fn build_index(config: BenchConfig, heap_size_bytes: usize) -> (Index, tantivy::schema::Field) {
let mut schema_builder = Schema::builder();
let text_field = schema_builder.add_text_field("text", TEXT);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let term_width = config.num_terms.to_string().len();
{
let mut writer = index
.writer_with_num_threads(1, heap_size_bytes)
.expect("writer");
let mut buffer = String::new();
for doc_id in 0..config.num_docs {
buffer.clear();
for token_idx in 0..config.tokens_per_doc {
if token_idx > 0 {
buffer.push(' ');
}
let term_id = (doc_id * config.tokens_per_doc + token_idx) % config.num_terms;
write!(&mut buffer, "t{term_id:0term_width$}").expect("write token");
}
writer
.add_document(doc!(text_field => buffer.as_str()))
.expect("add_document");
}
writer.commit().expect("commit");
}
(index, text_field)
}

View File

@@ -0,0 +1,421 @@
// This benchmark compares different approaches for retrieving string values:
//
// 1. Fast Field Approach: retrieves string values via term_ords() and ord_to_str()
//
// 2. Doc Store Approach: retrieves string values via searcher.doc() and field extraction
//
// The benchmark includes various data distributions:
// - Dense Sequential: Sequential document IDs with dense data
// - Dense Random: Random document IDs with dense data
// - Sparse Sequential: Sequential document IDs with sparse data
// - Sparse Random: Random document IDs with sparse data
use std::ops::Bound;
use binggan::{black_box, BenchGroup, BenchRunner};
use rand::prelude::*;
use rand::rngs::StdRng;
use rand::SeedableRng;
use tantivy::collector::{Count, DocSetCollector};
use tantivy::query::RangeQuery;
use tantivy::schema::document::TantivyDocument;
use tantivy::schema::{Schema, Value, FAST, STORED, STRING};
use tantivy::{doc, Index, ReloadPolicy, Searcher, Term};
#[derive(Clone)]
struct BenchIndex {
#[allow(dead_code)]
index: Index,
searcher: Searcher,
}
fn build_shared_indices(num_docs: usize, distribution: &str) -> BenchIndex {
// Schema with string fast field and stored field for doc access
let mut schema_builder = Schema::builder();
let f_str_fast = schema_builder.add_text_field("str_fast", STRING | STORED | FAST);
let f_str_stored = schema_builder.add_text_field("str_stored", STRING | STORED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema.clone());
// Populate index with stable RNG for reproducibility.
let mut rng = StdRng::from_seed([7u8; 32]);
{
let mut writer = index.writer_with_num_threads(1, 4_000_000_000).unwrap();
match distribution {
"dense_random" => {
for _doc_id in 0..num_docs {
let suffix = rng.gen_range(0u64..1000u64);
let str_val = format!("str_{:03}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
"dense_sequential" => {
for doc_id in 0..num_docs {
let suffix = doc_id as u64 % 1000;
let str_val = format!("str_{:03}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
"sparse_random" => {
for _doc_id in 0..num_docs {
let suffix = rng.gen_range(0u64..1000000u64);
let str_val = format!("str_{:07}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
"sparse_sequential" => {
for doc_id in 0..num_docs {
let suffix = doc_id as u64;
let str_val = format!("str_{:07}", suffix);
writer
.add_document(doc!(
f_str_fast=>str_val.clone(),
f_str_stored=>str_val,
))
.unwrap();
}
}
_ => {
panic!("Unsupported distribution type");
}
}
writer.commit().unwrap();
}
// Prepare reader/searcher once.
let reader = index
.reader_builder()
.reload_policy(ReloadPolicy::Manual)
.try_into()
.unwrap();
let searcher = reader.searcher();
BenchIndex { index, searcher }
}
fn main() {
// Prepare corpora with varying scenarios
let scenarios = vec![
(
"dense_random_search_low_range".to_string(),
1_000_000,
"dense_random",
0,
9,
),
(
"dense_random_search_high_range".to_string(),
1_000_000,
"dense_random",
990,
999,
),
(
"dense_sequential_search_low_range".to_string(),
1_000_000,
"dense_sequential",
0,
9,
),
(
"dense_sequential_search_high_range".to_string(),
1_000_000,
"dense_sequential",
990,
999,
),
(
"sparse_random_search_low_range".to_string(),
1_000_000,
"sparse_random",
0,
9999,
),
(
"sparse_random_search_high_range".to_string(),
1_000_000,
"sparse_random",
990_000,
999_999,
),
(
"sparse_sequential_search_low_range".to_string(),
1_000_000,
"sparse_sequential",
0,
9999,
),
(
"sparse_sequential_search_high_range".to_string(),
1_000_000,
"sparse_sequential",
990_000,
999_999,
),
];
let mut runner = BenchRunner::new();
for (scenario_id, n, distribution, range_low, range_high) in scenarios {
let bench_index = build_shared_indices(n, distribution);
let mut group = runner.new_group();
group.set_name(scenario_id);
let field = bench_index.searcher.schema().get_field("str_fast").unwrap();
let (lower_str, upper_str) =
if distribution == "dense_sequential" || distribution == "dense_random" {
(
format!("str_{:03}", range_low),
format!("str_{:03}", range_high),
)
} else {
(
format!("str_{:07}", range_low),
format!("str_{:07}", range_high),
)
};
let lower_term = Term::from_field_text(field, &lower_str);
let upper_term = Term::from_field_text(field, &upper_str);
let query = RangeQuery::new(Bound::Included(lower_term), Bound::Included(upper_term));
run_benchmark_tasks(&mut group, &bench_index, query, range_low, range_high);
group.run();
}
}
/// Run all benchmark tasks for a given range query
fn run_benchmark_tasks(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
// Test count of matching documents
add_bench_task_count(
bench_group,
bench_index,
query.clone(),
range_low,
range_high,
);
// Test fetching all DocIds of matching documents
add_bench_task_docset(
bench_group,
bench_index,
query.clone(),
range_low,
range_high,
);
// Test fetching all string fast field values of matching documents
add_bench_task_fetch_all_strings(
bench_group,
bench_index,
query.clone(),
range_low,
range_high,
);
// Test fetching all string values of matching documents through doc() method
add_bench_task_fetch_all_strings_from_doc(
bench_group,
bench_index,
query,
range_low,
range_high,
);
}
fn add_bench_task_count(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!("string_search_count_[{}-{}]", range_low, range_high);
let search_task = CountSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_docset(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!("string_fetch_all_docset_[{}-{}]", range_low, range_high);
let search_task = DocSetSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| black_box(search_task.run()));
}
fn add_bench_task_fetch_all_strings(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!(
"string_fastfield_fetch_all_strings_[{}-{}]",
range_low, range_high
);
let search_task = FetchAllStringsSearchTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| {
let result = black_box(search_task.run());
result.len()
});
}
fn add_bench_task_fetch_all_strings_from_doc(
bench_group: &mut BenchGroup,
bench_index: &BenchIndex,
query: RangeQuery,
range_low: u64,
range_high: u64,
) {
let task_name = format!(
"string_doc_fetch_all_strings_[{}-{}]",
range_low, range_high
);
let search_task = FetchAllStringsFromDocTask {
searcher: bench_index.searcher.clone(),
query,
};
bench_group.register(task_name, move |_| {
let result = black_box(search_task.run());
result.len()
});
}
struct CountSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl CountSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
self.searcher.search(&self.query, &Count).unwrap()
}
}
struct DocSetSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl DocSetSearchTask {
#[inline(never)]
pub fn run(&self) -> usize {
let result = self.searcher.search(&self.query, &DocSetCollector).unwrap();
result.len()
}
}
struct FetchAllStringsSearchTask {
searcher: Searcher,
query: RangeQuery,
}
impl FetchAllStringsSearchTask {
#[inline(never)]
pub fn run(&self) -> Vec<String> {
let doc_addresses = self.searcher.search(&self.query, &DocSetCollector).unwrap();
let mut docs = doc_addresses.into_iter().collect::<Vec<_>>();
docs.sort();
let mut strings = Vec::with_capacity(docs.len());
for doc_address in docs {
let segment_reader = &self.searcher.segment_readers()[doc_address.segment_ord as usize];
let str_column_opt = segment_reader.fast_fields().str("str_fast");
if let Ok(Some(str_column)) = str_column_opt {
let doc_id = doc_address.doc_id;
let term_ord = str_column.term_ords(doc_id).next().unwrap();
let mut str_buffer = String::new();
if str_column.ord_to_str(term_ord, &mut str_buffer).is_ok() {
strings.push(str_buffer);
}
}
}
strings
}
}
struct FetchAllStringsFromDocTask {
searcher: Searcher,
query: RangeQuery,
}
impl FetchAllStringsFromDocTask {
#[inline(never)]
pub fn run(&self) -> Vec<String> {
let doc_addresses = self.searcher.search(&self.query, &DocSetCollector).unwrap();
let mut docs = doc_addresses.into_iter().collect::<Vec<_>>();
docs.sort();
let mut strings = Vec::with_capacity(docs.len());
let str_stored_field = self
.searcher
.schema()
.get_field("str_stored")
.expect("str_stored field should exist");
for doc_address in docs {
// Get the document from the doc store (row store access)
if let Ok(doc) = self.searcher.doc::<TantivyDocument>(doc_address) {
// Extract string values from the stored field
if let Some(field_value) = doc.get_first(str_stored_field) {
if let Some(text) = field_value.as_value().as_str() {
strings.push(text.to_string());
}
}
}
}
strings
}
}

View File

@@ -18,5 +18,5 @@ homepage = "https://github.com/quickwit-oss/tantivy"
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker1x"] }
[dev-dependencies]
rand = "0.8"
rand = "0.9"
proptest = "1"

View File

@@ -4,8 +4,8 @@ extern crate test;
#[cfg(test)]
mod tests {
use rand::rng;
use rand::seq::IteratorRandom;
use rand::thread_rng;
use tantivy_bitpacker::{BitPacker, BitUnpacker, BlockedBitpacker};
use test::Bencher;
@@ -27,7 +27,7 @@ mod tests {
let num_els = 1_000_000u32;
let bit_unpacker = BitUnpacker::new(bit_width);
let data = create_bitpacked_data(bit_width, num_els);
let idxs: Vec<u32> = (0..num_els).choose_multiple(&mut thread_rng(), 100_000);
let idxs: Vec<u32> = (0..num_els).choose_multiple(&mut rng(), 100_000);
b.iter(|| {
let mut out = 0u64;
for &idx in &idxs {

View File

@@ -22,7 +22,7 @@ downcast-rs = "2.0.1"
[dev-dependencies]
proptest = "1"
more-asserts = "0.3.1"
rand = "0.8"
rand = "0.9"
binggan = "0.14.0"
[[bench]]

View File

@@ -9,7 +9,7 @@ use tantivy_columnar::column_values::{CodecType, serialize_and_load_u64_based_co
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55_000_u64)
.map(|num| num + rng.r#gen::<u8>() as u64)
.map(|num| num + rng.random::<u8>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);

View File

@@ -6,7 +6,7 @@ use tantivy_columnar::column_values::{CodecType, serialize_u64_based_column_valu
fn get_data() -> Vec<u64> {
let mut rng = StdRng::seed_from_u64(2u64);
let mut data: Vec<_> = (100..55_000_u64)
.map(|num| num + rng.r#gen::<u8>() as u64)
.map(|num| num + rng.random::<u8>() as u64)
.collect();
data.push(99_000);
data.insert(1000, 2000);

View File

@@ -8,7 +8,7 @@ const TOTAL_NUM_VALUES: u32 = 1_000_000;
fn gen_optional_index(fill_ratio: f64) -> OptionalIndex {
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let vals: Vec<u32> = (0..TOTAL_NUM_VALUES)
.map(|_| rng.gen_bool(fill_ratio))
.map(|_| rng.random_bool(fill_ratio))
.enumerate()
.filter(|(_pos, val)| *val)
.map(|(pos, _)| pos as u32)
@@ -25,7 +25,7 @@ fn random_range_iterator(
let mut rng: StdRng = StdRng::from_seed([1u8; 32]);
let mut current = start;
std::iter::from_fn(move || {
current += rng.gen_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
current += rng.random_range(avg_step_size - avg_deviation..=avg_step_size + avg_deviation);
if current >= end { None } else { Some(current) }
})
}

View File

@@ -39,7 +39,7 @@ fn get_data_50percent_item() -> Vec<u128> {
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.gen_range(1..=100);
let val = rng.random_range(1..=100);
data.push(val);
}
data.push(SINGLE_ITEM);

View File

@@ -34,7 +34,7 @@ fn get_data_50percent_item() -> Vec<u128> {
let mut data = vec![];
for _ in 0..300_000 {
let val = rng.gen_range(1..=100);
let val = rng.random_range(1..=100);
data.push(val);
}
data.push(SINGLE_ITEM);

View File

@@ -268,7 +268,7 @@ mod tests {
#[test]
fn linear_interpol_fast_field_rand() {
let mut rng = rand::thread_rng();
let mut rng = rand::rng();
for _ in 0..50 {
let mut data = (0..10_000).map(|_| rng.next_u64()).collect::<Vec<_>>();
create_and_validate::<LinearCodec>(&data, "random");

View File

@@ -122,7 +122,7 @@ pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
assert_eq!(vals, buffer);
if !vals.is_empty() {
let test_rand_idx = rand::thread_rng().gen_range(0..=vals.len() - 1);
let test_rand_idx = rand::rng().random_range(0..=vals.len() - 1);
let expected_positions: Vec<u32> = vals
.iter()
.enumerate()

View File

@@ -59,7 +59,7 @@ pub struct RowAddr {
pub row_id: RowId,
}
pub use sstable::Dictionary;
pub use sstable::{Dictionary, TermOrdHit};
pub type Streamer<'a> = sstable::Streamer<'a, VoidSSTable>;
pub use common::DateTime;

View File

@@ -15,11 +15,10 @@ repository = "https://github.com/quickwit-oss/tantivy"
byteorder = "1.4.3"
ownedbytes = { version= "0.9", path="../ownedbytes" }
async-trait = "0.1"
time = { version = "0.3.10", features = ["serde-well-known"] }
time = { version = "0.3.47", features = ["serde-well-known"] }
serde = { version = "1.0.136", features = ["derive"] }
[dev-dependencies]
binggan = "0.14.0"
proptest = "1.0.0"
rand = "0.8.4"
rand = "0.9"

View File

@@ -1,6 +1,6 @@
use binggan::{BenchRunner, black_box};
use rand::rng;
use rand::seq::IteratorRandom;
use rand::thread_rng;
use tantivy_common::{BitSet, TinySet, serialize_vint_u32};
fn bench_vint() {
@@ -17,7 +17,7 @@ fn bench_vint() {
black_box(out);
});
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut thread_rng(), 100_000);
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut rng(), 100_000);
runner.bench_function("bench_vint_rand", move |_| {
let mut out = 0u64;
for val in vals.iter().cloned() {

View File

@@ -178,11 +178,13 @@ impl TinySet {
#[derive(Clone)]
pub struct BitSet {
tinysets: Box<[TinySet]>,
len: u64,
max_value: u32,
}
impl std::fmt::Debug for BitSet {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
f.debug_struct("BitSet")
.field("len", &self.len)
.field("max_value", &self.max_value)
.finish()
}
@@ -210,6 +212,7 @@ impl BitSet {
let tinybitsets = vec![TinySet::empty(); num_buckets as usize].into_boxed_slice();
BitSet {
tinysets: tinybitsets,
len: 0,
max_value,
}
}
@@ -227,6 +230,7 @@ impl BitSet {
}
BitSet {
tinysets: tinybitsets,
len: max_value as u64,
max_value,
}
}
@@ -245,19 +249,17 @@ impl BitSet {
/// Intersect with tinysets
fn intersect_update_with_iter(&mut self, other: impl Iterator<Item = TinySet>) {
self.len = 0;
for (left, right) in self.tinysets.iter_mut().zip(other) {
*left = left.intersect(right);
self.len += left.len() as u64;
}
}
/// Returns the number of elements in the `BitSet`.
#[inline]
pub fn len(&self) -> usize {
self.tinysets
.iter()
.copied()
.map(|tinyset| tinyset.len())
.sum::<u32>() as usize
self.len as usize
}
/// Inserts an element in the `BitSet`
@@ -266,7 +268,7 @@ impl BitSet {
// we do not check saturated els.
let higher = el / 64u32;
let lower = el % 64u32;
self.tinysets[higher as usize].insert_mut(lower);
self.len += u64::from(self.tinysets[higher as usize].insert_mut(lower));
}
/// Inserts an element in the `BitSet`
@@ -275,7 +277,7 @@ impl BitSet {
// we do not check saturated els.
let higher = el / 64u32;
let lower = el % 64u32;
self.tinysets[higher as usize].remove_mut(lower);
self.len -= u64::from(self.tinysets[higher as usize].remove_mut(lower));
}
/// Returns true iff the elements is in the `BitSet`.
@@ -414,7 +416,7 @@ mod tests {
use std::collections::HashSet;
use ownedbytes::OwnedBytes;
use rand::distributions::Bernoulli;
use rand::distr::Bernoulli;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};

View File

@@ -62,7 +62,9 @@ impl<W: TerminatingWrite> TerminatingWrite for CountingWriter<W> {
pub struct AntiCallToken(());
/// Trait used to indicate when no more write need to be done on a writer
pub trait TerminatingWrite: Write + Send + Sync {
///
/// Thread-safety is enforced at the call sites that require it.
pub trait TerminatingWrite: Write {
/// Indicate that the writer will no longer be used. Internally call terminate_ref.
fn terminate(mut self) -> io::Result<()>
where Self: Sized {

View File

@@ -60,7 +60,7 @@ At indexing, tantivy will try to interpret number and strings as different type
priority order.
Numbers will be interpreted as u64, i64 and f64 in that order.
Strings will be interpreted as rfc3999 dates or simple strings.
Strings will be interpreted as rfc3339 dates or simple strings.
The first working type is picked and is the only term that is emitted for indexing.
Note this interpretation happens on a per-document basis, and there is no effort to try to sniff
@@ -81,7 +81,7 @@ Will be interpreted as
(my_path.my_segment, String, 233) or (my_path.my_segment, u64, 233)
```
Likewise, we need to emit two tokens if the query contains an rfc3999 date.
Likewise, we need to emit two tokens if the query contains an rfc3339 date.
Indeed the date could have been actually a single token inside the text of a document at ingestion time. Generally speaking, we will always at least emit a string token in query parsing, and sometimes more.
If one more json field is defined, things get even more complicated.

View File

@@ -91,10 +91,46 @@ fn main() -> tantivy::Result<()> {
}
}
// Some other powerful operations (especially `.seek`) may be useful to consume these
// A `Term` is a text token associated with a field.
// Let's go through all docs containing the term `title:the` and access their position
let term_the = Term::from_field_text(title, "the");
// Some other powerful operations (especially `.skip_to`) may be useful to consume these
// posting lists rapidly.
// You can check for them in the [`DocSet`](https://docs.rs/tantivy/~0/tantivy/trait.DocSet.html) trait
// and the [`Postings`](https://docs.rs/tantivy/~0/tantivy/trait.Postings.html) trait
// Also, for some VERY specific high performance use case like an OLAP analysis of logs,
// you can get better performance by accessing directly the blocks of doc ids.
for segment_reader in searcher.segment_readers() {
// A segment contains different data structure.
// Inverted index stands for the combination of
// - the term dictionary
// - the inverted lists associated with each terms and their positions
let inverted_index = segment_reader.inverted_index(title)?;
// This segment posting object is like a cursor over the documents matching the term.
// The `IndexRecordOption` arguments tells tantivy we will be interested in both term
// frequencies and positions.
//
// If you don't need all this information, you may get better performance by decompressing
// less information.
if let Some(mut block_segment_postings) =
inverted_index.read_block_postings(&term_the, IndexRecordOption::Basic)?
{
loop {
let docs = block_segment_postings.docs();
if docs.is_empty() {
break;
}
// Once again these docs MAY contains deleted documents as well.
let docs = block_segment_postings.docs();
// Prints `Docs [0, 2].`
println!("Docs {docs:?}");
block_segment_postings.advance();
}
}
}
Ok(())
}

View File

@@ -560,7 +560,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
(
(
value((), tag(">=")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(")", false), |(bound, err)| {
(
(
bound
@@ -574,7 +574,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag("<=")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(")", false), |(bound, err)| {
(
(
UserInputBound::Unbounded,
@@ -588,7 +588,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag(">")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(")", false), |(bound, err)| {
(
(
bound
@@ -602,7 +602,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag("<")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(")", false), |(bound, err)| {
(
(
UserInputBound::Unbounded,
@@ -704,7 +704,11 @@ fn regex(inp: &str) -> IResult<&str, UserInputLeaf> {
many1(alt((preceded(char('\\'), char('/')), none_of("/")))),
char('/'),
),
peek(alt((multispace1, eof))),
peek(alt((
value((), multispace1),
value((), char(')')),
value((), eof),
))),
),
|elements| UserInputLeaf::Regex {
field: None,
@@ -721,8 +725,12 @@ fn regex_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
opt_i_err(char('/'), "missing delimiter /"),
),
opt_i_err(
peek(alt((multispace1, eof))),
"expected whitespace or end of input",
peek(alt((
value((), multispace1),
value((), char(')')),
value((), eof),
))),
"expected whitespace, closing parenthesis, or end of input",
),
)(inp)
{
@@ -1323,6 +1331,14 @@ mod test {
test_parse_query_to_ast_helper("<a", "{\"*\" TO \"a\"}");
test_parse_query_to_ast_helper("<=a", "{\"*\" TO \"a\"]");
test_parse_query_to_ast_helper("<=bsd", "{\"*\" TO \"bsd\"]");
test_parse_query_to_ast_helper("(<=42)", "{\"*\" TO \"42\"]");
test_parse_query_to_ast_helper("(<=42 )", "{\"*\" TO \"42\"]");
test_parse_query_to_ast_helper("(age:>5)", "\"age\":{\"5\" TO \"*\"}");
test_parse_query_to_ast_helper(
"(title:bar AND age:>12)",
"(+\"title\":bar +\"age\":{\"12\" TO \"*\"})",
);
}
#[test]
@@ -1699,6 +1715,10 @@ mod test {
test_parse_query_to_ast_helper("foo:(A OR B)", "(?\"foo\":A ?\"foo\":B)");
test_parse_query_to_ast_helper("foo:(A* OR B*)", "(?\"foo\":A* ?\"foo\":B*)");
test_parse_query_to_ast_helper("foo:(*A OR *B)", "(?\"foo\":*A ?\"foo\":*B)");
// Regexes between parentheses
test_parse_query_to_ast_helper("foo:(/A.*/)", "\"foo\":/A.*/");
test_parse_query_to_ast_helper("foo:(/A.*/ OR /B.*/)", "(?\"foo\":/A.*/ ?\"foo\":/B.*/)");
}
#[test]

View File

@@ -66,6 +66,7 @@ impl UserInputLeaf {
}
UserInputLeaf::Range { field, .. } if field.is_none() => *field = Some(default_field),
UserInputLeaf::Set { field, .. } if field.is_none() => *field = Some(default_field),
UserInputLeaf::Regex { field, .. } if field.is_none() => *field = Some(default_field),
_ => (), // field was already set, do nothing
}
}

View File

@@ -10,9 +10,10 @@ use crate::aggregation::accessor_helpers::{
};
use crate::aggregation::agg_req::{Aggregation, AggregationVariants, Aggregations};
use crate::aggregation::bucket::{
build_segment_filter_collector, build_segment_range_collector, FilterAggReqData,
HistogramAggReqData, HistogramBounds, IncludeExcludeParam, MissingTermAggReqData,
RangeAggReqData, SegmentHistogramCollector, TermMissingAgg, TermsAggReqData, TermsAggregation,
build_segment_filter_collector, build_segment_range_collector, CompositeAggReqData,
CompositeAggregation, CompositeSourceAccessors, FilterAggReqData, HistogramAggReqData,
HistogramBounds, IncludeExcludeParam, MissingTermAggReqData, RangeAggReqData,
SegmentHistogramCollector, TermMissingAgg, TermsAggReqData, TermsAggregation,
TermsAggregationInternal,
};
use crate::aggregation::metric::{
@@ -73,6 +74,12 @@ impl AggregationsSegmentCtx {
self.per_request.filter_req_data.push(Some(Box::new(data)));
self.per_request.filter_req_data.len() - 1
}
pub(crate) fn push_composite_req_data(&mut self, data: CompositeAggReqData) -> usize {
self.per_request
.composite_req_data
.push(Some(Box::new(data)));
self.per_request.composite_req_data.len() - 1
}
#[inline]
pub(crate) fn get_term_req_data(&self, idx: usize) -> &TermsAggReqData {
@@ -108,6 +115,12 @@ impl AggregationsSegmentCtx {
.as_deref()
.expect("range_req_data slot is empty (taken)")
}
#[inline]
pub(crate) fn get_composite_req_data(&self, idx: usize) -> &CompositeAggReqData {
self.per_request.composite_req_data[idx]
.as_deref()
.expect("composite_req_data slot is empty (taken)")
}
// ---------- mutable getters ----------
@@ -181,6 +194,25 @@ impl AggregationsSegmentCtx {
debug_assert!(self.per_request.filter_req_data[idx].is_none());
self.per_request.filter_req_data[idx] = Some(value);
}
/// Move out the Composite request at `idx`.
#[inline]
pub(crate) fn take_composite_req_data(&mut self, idx: usize) -> Box<CompositeAggReqData> {
self.per_request.composite_req_data[idx]
.take()
.expect("composite_req_data slot is empty (taken)")
}
/// Put back a Composite request into an empty slot at `idx`.
#[inline]
pub(crate) fn put_back_composite_req_data(
&mut self,
idx: usize,
value: Box<CompositeAggReqData>,
) {
debug_assert!(self.per_request.composite_req_data[idx].is_none());
self.per_request.composite_req_data[idx] = Some(value);
}
}
/// Each type of aggregation has its own request data struct. This struct holds
@@ -208,6 +240,8 @@ pub struct PerRequestAggSegCtx {
pub top_hits_req_data: Vec<TopHitsAggReqData>,
/// MissingTermAggReqData contains the request data for a missing term aggregation.
pub missing_term_req_data: Vec<MissingTermAggReqData>,
/// CompositeAggReqData contains the request data for a composite aggregation.
pub composite_req_data: Vec<Option<Box<CompositeAggReqData>>>,
/// Request tree used to build collectors.
pub agg_tree: Vec<AggRefNode>,
@@ -255,6 +289,11 @@ impl PerRequestAggSegCtx {
.iter()
.map(|t| t.get_memory_consumption())
.sum::<usize>()
+ self
.composite_req_data
.iter()
.map(|b| b.as_ref().map(|d| d.get_memory_consumption()).unwrap_or(0))
.sum::<usize>()
+ self.agg_tree.len() * std::mem::size_of::<AggRefNode>()
}
@@ -291,6 +330,11 @@ impl PerRequestAggSegCtx {
.expect("filter_req_data slot is empty (taken)")
.name
.as_str(),
AggKind::Composite => self.composite_req_data[idx]
.as_deref()
.expect("composite_req_data slot is empty (taken)")
.name
.as_str(),
}
}
@@ -417,6 +461,11 @@ pub(crate) fn build_segment_agg_collector(
)?)),
AggKind::Range => Ok(build_segment_range_collector(req, node)?),
AggKind::Filter => build_segment_filter_collector(req, node),
AggKind::Composite => Ok(Box::new(
crate::aggregation::bucket::SegmentCompositeCollector::from_req_and_validate(
req, node,
)?,
)),
}
}
@@ -447,6 +496,7 @@ pub enum AggKind {
DateHistogram,
Range,
Filter,
Composite,
}
impl AggKind {
@@ -462,6 +512,7 @@ impl AggKind {
AggKind::DateHistogram => "DateHistogram",
AggKind::Range => "Range",
AggKind::Filter => "Filter",
AggKind::Composite => "Composite",
}
}
}
@@ -709,6 +760,14 @@ fn build_nodes(
children,
}])
}
AggregationVariants::Composite(composite_req) => Ok(vec![build_composite_node(
agg_name,
reader,
segment_ordinal,
data,
&req.sub_aggregation,
composite_req,
)?]),
AggregationVariants::Filter(filter_req) => {
// Build the query and evaluator upfront
let schema = reader.schema();
@@ -743,6 +802,35 @@ fn build_nodes(
}
}
fn build_composite_node(
agg_name: &str,
reader: &SegmentReader,
_segment_ordinal: SegmentOrdinal,
data: &mut AggregationsSegmentCtx,
sub_aggs: &Aggregations,
req: &CompositeAggregation,
) -> crate::Result<AggRefNode> {
let mut composite_accessors = Vec::with_capacity(req.sources.len());
for source in &req.sources {
let source_after_key_opt = req.after.get(source.name()).map(|k| &k.0);
let source_accessor =
CompositeSourceAccessors::build_for_source(reader, source, source_after_key_opt)?;
composite_accessors.push(source_accessor);
}
let agg = CompositeAggReqData {
name: agg_name.to_string(),
req: req.clone(),
composite_accessors,
};
let idx = data.push_composite_req_data(agg);
let children = build_children(sub_aggs, reader, _segment_ordinal, data)?;
Ok(AggRefNode {
kind: AggKind::Composite,
idx_in_req_data: idx,
children,
})
}
fn build_children(
aggs: &Aggregations,
reader: &SegmentReader,

View File

@@ -32,8 +32,8 @@ use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::bucket::{
DateHistogramAggregationReq, FilterAggregation, HistogramAggregation, RangeAggregation,
TermsAggregation,
CompositeAggregation, DateHistogramAggregationReq, FilterAggregation, HistogramAggregation,
RangeAggregation, TermsAggregation,
};
use super::metric::{
AverageAggregation, CardinalityAggregationReq, CountAggregation, ExtendedStatsAggregation,
@@ -134,6 +134,9 @@ pub enum AggregationVariants {
/// Filter documents into a single bucket.
#[serde(rename = "filter")]
Filter(FilterAggregation),
/// Multi-dimensional, paginable bucket aggregation.
#[serde(rename = "composite")]
Composite(CompositeAggregation),
// Metric aggregation types
/// Computes the average of the extracted values.
@@ -180,6 +183,11 @@ impl AggregationVariants {
AggregationVariants::Histogram(histogram) => vec![histogram.field.as_str()],
AggregationVariants::DateHistogram(histogram) => vec![histogram.field.as_str()],
AggregationVariants::Filter(filter) => filter.get_fast_field_names(),
AggregationVariants::Composite(composite) => composite
.sources
.iter()
.map(|source| source.field())
.collect(),
AggregationVariants::Average(avg) => vec![avg.field_name()],
AggregationVariants::Count(count) => vec![count.field_name()],
AggregationVariants::Max(max) => vec![max.field_name()],
@@ -214,6 +222,12 @@ impl AggregationVariants {
_ => None,
}
}
pub(crate) fn as_composite(&self) -> Option<&CompositeAggregation> {
match &self {
AggregationVariants::Composite(composite) => Some(composite),
_ => None,
}
}
pub(crate) fn as_percentile(&self) -> Option<&PercentilesAggregationReq> {
match &self {
AggregationVariants::Percentiles(percentile_req) => Some(percentile_req),

View File

@@ -9,10 +9,12 @@ use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::bucket::GetDocCount;
use super::intermediate_agg_result::CompositeIntermediateKey;
use super::metric::{
ExtendedStats, PercentilesMetricResult, SingleMetricResult, Stats, TopHitsMetricResult,
};
use super::{AggregationError, Key};
use crate::aggregation::bucket::AfterKey;
use crate::TantivyError;
#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
@@ -158,6 +160,14 @@ pub enum BucketResult {
},
/// This is the filter result - a single bucket with sub-aggregations
Filter(FilterBucketResult),
/// This is the composite result
Composite {
/// The buckets
buckets: Vec<CompositeBucketEntry>,
/// The key to start after when paginating
#[serde(skip_serializing_if = "FxHashMap::is_empty")]
after_key: FxHashMap<String, AfterKey>,
},
}
impl BucketResult {
@@ -179,6 +189,9 @@ impl BucketResult {
// Only count sub-aggregation buckets
filter_result.sub_aggregations.get_bucket_count()
}
BucketResult::Composite { buckets, .. } => {
buckets.iter().map(|bucket| bucket.get_bucket_count()).sum()
}
}
}
}
@@ -337,3 +350,87 @@ pub struct FilterBucketResult {
#[serde(flatten)]
pub sub_aggregations: AggregationResults,
}
/// Note the type information loss compared to `CompositeIntermediateKey`.
/// Pagination is performed using `AfterKey`, which encodes type information.
#[derive(Clone, Debug, Serialize, Deserialize)]
#[serde(untagged)]
pub enum CompositeKey {
/// Boolean key
Bool(bool),
/// String key
Str(String),
/// `i64` key
I64(i64),
/// `u64` key
U64(u64),
/// `f64` key
F64(f64),
/// Null key
Null,
}
impl Eq for CompositeKey {}
impl std::hash::Hash for CompositeKey {
fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
core::mem::discriminant(self).hash(state);
match self {
Self::Bool(val) => val.hash(state),
Self::Str(text) => text.hash(state),
Self::F64(val) => val.to_bits().hash(state),
Self::U64(val) => val.hash(state),
Self::I64(val) => val.hash(state),
Self::Null => {}
}
}
}
impl PartialEq for CompositeKey {
fn eq(&self, other: &Self) -> bool {
match (self, other) {
(Self::Bool(l), Self::Bool(r)) => l == r,
(Self::Str(l), Self::Str(r)) => l == r,
(Self::F64(l), Self::F64(r)) => l.to_bits() == r.to_bits(),
(Self::I64(l), Self::I64(r)) => l == r,
(Self::U64(l), Self::U64(r)) => l == r,
(Self::Null, Self::Null) => true,
_ => false,
}
}
}
impl From<CompositeIntermediateKey> for CompositeKey {
fn from(value: CompositeIntermediateKey) -> Self {
match value {
CompositeIntermediateKey::Str(s) => Self::Str(s),
CompositeIntermediateKey::IpAddr(s) => {
if let Some(ip) = s.to_ipv4_mapped() {
Self::Str(ip.to_string())
} else {
Self::Str(s.to_string())
}
}
CompositeIntermediateKey::F64(f) => Self::F64(f),
CompositeIntermediateKey::Bool(f) => Self::Bool(f),
CompositeIntermediateKey::U64(f) => Self::U64(f),
CompositeIntermediateKey::I64(f) => Self::I64(f),
CompositeIntermediateKey::DateTime(f) => Self::I64(f / 1_000_000), // ns to ms
CompositeIntermediateKey::Null => Self::Null,
}
}
}
/// Composite bucket entry with a multi-dimensional key.
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct CompositeBucketEntry {
/// The identifier of the bucket.
pub key: FxHashMap<String, CompositeKey>,
/// Number of documents in the bucket.
pub doc_count: u64,
#[serde(flatten)]
/// Sub-aggregations in this bucket.
pub sub_aggregation: AggregationResults,
}
impl CompositeBucketEntry {
pub(crate) fn get_bucket_count(&self) -> u64 {
1 + self.sub_aggregation.get_bucket_count()
}
}

View File

@@ -0,0 +1,548 @@
use std::net::Ipv6Addr;
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{Column, ColumnType, MonotonicallyMappableToU64, StrColumn, TermOrdHit};
use crate::aggregation::accessor_helpers::get_numeric_or_date_column_types;
use crate::aggregation::bucket::composite::numeric_types::num_proj;
use crate::aggregation::bucket::composite::numeric_types::num_proj::ProjectedNumber;
use crate::aggregation::bucket::composite::ToTypePaginationOrder;
use crate::aggregation::bucket::{
parse_into_milliseconds, CalendarInterval, CompositeAggregation, CompositeAggregationSource,
MissingOrder, Order,
};
use crate::aggregation::intermediate_agg_result::CompositeIntermediateKey;
use crate::{SegmentReader, TantivyError};
/// Contains all information required by the SegmentCompositeCollector to perform the
/// composite aggregation on a segment.
pub struct CompositeAggReqData {
/// The name of the aggregation.
pub name: String,
/// The normalized term aggregation request.
pub req: CompositeAggregation,
/// Accessors for each source, each source can have multiple accessors (columns).
pub composite_accessors: Vec<CompositeSourceAccessors>,
}
impl CompositeAggReqData {
/// Estimate the memory consumption of this struct in bytes.
pub fn get_memory_consumption(&self) -> usize {
std::mem::size_of::<Self>()
+ self.composite_accessors.len() * std::mem::size_of::<CompositeSourceAccessors>()
}
}
/// Accessors for a single column in a composite source.
pub struct CompositeAccessor {
/// The fast field column
pub column: Column<u64>,
/// The column type
pub column_type: ColumnType,
/// Term dictionary if the column type is Str
///
/// Only used by term sources
pub str_dict_column: Option<StrColumn>,
/// Parsed date interval for date histogram sources
pub date_histogram_interval: PrecomputedDateInterval,
}
/// Accessors to all the columns that belong to the field of a composite source.
pub struct CompositeSourceAccessors {
/// The accessors for this source
pub accessors: Vec<CompositeAccessor>,
/// The key after which to start collecting results. Applies to the first
/// column of the source.
pub after_key: PrecomputedAfterKey,
/// The column index the after_key applies to. The after_key only applies to
/// one column. Columns before should be skipped. Columns after should be
/// kept without comparison to the after_key.
pub after_key_accessor_idx: usize,
/// Whether to skip missing values because of the after_key. Skipping only
/// applies if the value for previous columns were exactly equal to the
/// corresponding after keys (is_on_after_key).
pub skip_missing: bool,
/// The after key was set to null to indicate that the last collected key
/// was a missing value.
pub is_after_key_explicit_missing: bool,
}
impl CompositeSourceAccessors {
/// Creates a new set of accessors for the composite source.
///
/// Precomputes some values to make collection faster.
pub fn build_for_source(
reader: &SegmentReader,
source: &CompositeAggregationSource,
// First option is None when no after key was set in the query, the
// second option is None when the after key was set but its value for
// this source was set to `null`
source_after_key_opt: Option<&CompositeIntermediateKey>,
) -> crate::Result<Self> {
let is_after_key_explicit_missing = source_after_key_opt
.map(|after_key| matches!(after_key, CompositeIntermediateKey::Null))
.unwrap_or(false);
let mut skip_missing = false;
if let Some(CompositeIntermediateKey::Null) = source_after_key_opt {
if !source.missing_bucket() {
return Err(TantivyError::InvalidArgument(
"the 'after' key for a source cannot be null when 'missing_bucket' is false"
.to_string(),
));
}
} else if source_after_key_opt.is_some() {
// if missing buckets come first and we have a non null after key, we skip missing
if MissingOrder::First == source.missing_order() {
skip_missing = true;
}
if MissingOrder::Default == source.missing_order() && Order::Asc == source.order() {
skip_missing = true;
}
};
match source {
CompositeAggregationSource::Terms(source) => {
let allowed_column_types = [
ColumnType::I64,
ColumnType::U64,
ColumnType::F64,
ColumnType::Str,
ColumnType::DateTime,
ColumnType::Bool,
ColumnType::IpAddr,
// ColumnType::Bytes Unsupported
];
let mut columns_and_types = reader
.fast_fields()
.u64_lenient_for_type_all(Some(&allowed_column_types), &source.field)?;
// Sort columns by their pagination order and determine which to skip
columns_and_types.sort_by_key(|(_, col_type): &(Column, ColumnType)| {
col_type.column_pagination_order()
});
if source.order == Order::Desc {
columns_and_types.reverse();
}
let after_key_accessor_idx = find_first_column_to_collect(
&columns_and_types,
source_after_key_opt,
source.missing_order,
source.order,
)?;
let source_collectors: Vec<CompositeAccessor> = columns_and_types
.into_iter()
.map(|(column, column_type)| {
Ok(CompositeAccessor {
column,
column_type,
str_dict_column: reader.fast_fields().str(&source.field)?,
date_histogram_interval: PrecomputedDateInterval::NotApplicable,
})
})
.collect::<crate::Result<_>>()?;
let after_key = if let Some(first_col) =
source_collectors.get(after_key_accessor_idx)
{
match source_after_key_opt {
Some(after_key) => PrecomputedAfterKey::precompute(
&first_col,
after_key,
&source.field,
source.missing_order,
source.order,
)?,
None => {
precompute_missing_after_key(false, source.missing_order, source.order)
}
}
} else {
// if no columns, we don't care about the after_key
PrecomputedAfterKey::Next(0)
};
Ok(CompositeSourceAccessors {
accessors: source_collectors,
is_after_key_explicit_missing,
skip_missing,
after_key,
after_key_accessor_idx,
})
}
CompositeAggregationSource::Histogram(source) => {
let column_and_types: Vec<(Column, ColumnType)> =
reader.fast_fields().u64_lenient_for_type_all(
Some(get_numeric_or_date_column_types()),
&source.field,
)?;
let source_collectors: Vec<CompositeAccessor> = column_and_types
.into_iter()
.map(|(column, column_type)| {
Ok(CompositeAccessor {
column,
column_type,
str_dict_column: None,
date_histogram_interval: PrecomputedDateInterval::NotApplicable,
})
})
.collect::<crate::Result<_>>()?;
let after_key = match source_after_key_opt {
Some(CompositeIntermediateKey::F64(key)) => {
let normalized_key = *key / source.interval;
num_proj::f64_to_i64(normalized_key).into()
}
Some(CompositeIntermediateKey::Null) => {
precompute_missing_after_key(true, source.missing_order, source.order)
}
None => precompute_missing_after_key(true, source.missing_order, source.order),
_ => {
return Err(crate::TantivyError::InvalidArgument(
"After key type invalid for interval composite source".to_string(),
));
}
};
Ok(CompositeSourceAccessors {
accessors: source_collectors,
is_after_key_explicit_missing,
skip_missing,
after_key,
after_key_accessor_idx: 0,
})
}
CompositeAggregationSource::DateHistogram(source) => {
let column_and_types = reader
.fast_fields()
.u64_lenient_for_type_all(Some(&[ColumnType::DateTime]), &source.field)?;
let date_histogram_interval =
PrecomputedDateInterval::from_date_histogram_source_intervals(
&source.fixed_interval,
source.calendar_interval,
)?;
let source_collectors: Vec<CompositeAccessor> = column_and_types
.into_iter()
.map(|(column, column_type)| {
Ok(CompositeAccessor {
column,
column_type,
str_dict_column: None,
date_histogram_interval,
})
})
.collect::<crate::Result<_>>()?;
let after_key = match source_after_key_opt {
Some(CompositeIntermediateKey::DateTime(key)) => {
PrecomputedAfterKey::Exact(key.to_u64())
}
Some(CompositeIntermediateKey::Null) => {
precompute_missing_after_key(true, source.missing_order, source.order)
}
None => precompute_missing_after_key(true, source.missing_order, source.order),
_ => {
return Err(crate::TantivyError::InvalidArgument(
"After key type invalid for interval composite source".to_string(),
));
}
};
Ok(CompositeSourceAccessors {
accessors: source_collectors,
is_after_key_explicit_missing,
skip_missing,
after_key,
after_key_accessor_idx: 0,
})
}
}
}
}
/// Finds the index of the first column we should start collecting from to
/// resume the pagination from the after_key.
fn find_first_column_to_collect<T>(
sorted_columns: &[(T, ColumnType)],
after_key_opt: Option<&CompositeIntermediateKey>,
missing_order: MissingOrder,
order: Order,
) -> crate::Result<usize> {
let after_key = match after_key_opt {
None => return Ok(0), // No pagination, start from beginning
Some(key) => key,
};
// Handle null after_key (we were on a missing value last time)
if matches!(after_key, CompositeIntermediateKey::Null) {
return match (missing_order, order) {
// Missing values come first, so all columns remain
(MissingOrder::First, _) | (MissingOrder::Default, Order::Asc) => Ok(0),
// Missing values come last, so all columns are done
(MissingOrder::Last, _) | (MissingOrder::Default, Order::Desc) => {
Ok(sorted_columns.len())
}
};
}
// Find the first column whose type order matches or follows the after_key's
// type in the pagination sequence
let after_key_column_order = after_key.column_pagination_order();
for (idx, (_, col_type)) in sorted_columns.iter().enumerate() {
let col_order = col_type.column_pagination_order();
let is_first_to_collect = match order {
Order::Asc => col_order >= after_key_column_order,
Order::Desc => col_order <= after_key_column_order,
};
if is_first_to_collect {
return Ok(idx);
}
}
// All columns are before the after_key, nothing left to collect
Ok(sorted_columns.len())
}
fn precompute_missing_after_key(
is_after_key_explicit_missing: bool,
missing_order: MissingOrder,
order: Order,
) -> PrecomputedAfterKey {
let after_last = PrecomputedAfterKey::AfterLast;
let before_first = PrecomputedAfterKey::Next(0);
match (is_after_key_explicit_missing, missing_order, order) {
(true, MissingOrder::First, Order::Asc) => before_first,
(true, MissingOrder::First, Order::Desc) => after_last,
(true, MissingOrder::Last, Order::Asc) => after_last,
(true, MissingOrder::Last, Order::Desc) => before_first,
(true, MissingOrder::Default, Order::Asc) => before_first,
(true, MissingOrder::Default, Order::Desc) => after_last,
(false, _, Order::Asc) => before_first,
(false, _, Order::Desc) => after_last,
}
}
/// A parsed representation of the date interval for date histogram sources
#[derive(Clone, Copy, Debug)]
pub enum PrecomputedDateInterval {
/// This is not a date histogram source
NotApplicable,
/// Source was configured with a fixed interval
FixedNanoseconds(i64),
/// Source was configured with a calendar interval
Calendar(CalendarInterval),
}
impl PrecomputedDateInterval {
/// Validates the date histogram source interval fields and parses a date interval from them.
pub fn from_date_histogram_source_intervals(
fixed_interval: &Option<String>,
calendar_interval: Option<CalendarInterval>,
) -> crate::Result<Self> {
match (fixed_interval, calendar_interval) {
(Some(_), Some(_)) | (None, None) => Err(TantivyError::InvalidArgument(
"date histogram source must one and only one of fixed_interval or \
calendar_interval set"
.to_string(),
)),
(Some(fixed_interval), None) => {
let fixed_interval_ms = parse_into_milliseconds(&fixed_interval)?;
Ok(PrecomputedDateInterval::FixedNanoseconds(
fixed_interval_ms * 1_000_000,
))
}
(None, Some(calendar_interval)) => {
Ok(PrecomputedDateInterval::Calendar(calendar_interval))
}
}
}
}
/// The after key projected to the u64 column space
///
/// Some column types (term, IP) might not have an exact representation of the
/// specified after key
#[derive(Debug)]
pub enum PrecomputedAfterKey {
/// The after key could be exactly represented in the column space.
Exact(u64),
/// The after key could not be exactly represented exactly represented, so
/// this is the next closest one.
Next(u64),
/// The after key could not be represented in the column space, it is
/// greater than all value
AfterLast,
}
impl From<TermOrdHit> for PrecomputedAfterKey {
fn from(hit: TermOrdHit) -> Self {
match hit {
TermOrdHit::Exact(ord) => PrecomputedAfterKey::Exact(ord),
// TermOrdHit represents AfterLast as Next(u64::MAX), we keep it as is
TermOrdHit::Next(ord) => PrecomputedAfterKey::Next(ord),
}
}
}
impl<T: MonotonicallyMappableToU64> From<ProjectedNumber<T>> for PrecomputedAfterKey {
fn from(num: ProjectedNumber<T>) -> Self {
match num {
ProjectedNumber::Exact(number) => PrecomputedAfterKey::Exact(number.to_u64()),
ProjectedNumber::Next(number) => PrecomputedAfterKey::Next(number.to_u64()),
ProjectedNumber::AfterLast => PrecomputedAfterKey::AfterLast,
}
}
}
// /!\ These operators only makes sense if both values are in the same column space
impl PrecomputedAfterKey {
pub fn equals(&self, column_value: u64) -> bool {
match self {
PrecomputedAfterKey::Exact(v) => *v == column_value,
PrecomputedAfterKey::Next(_) => false,
PrecomputedAfterKey::AfterLast => false,
}
}
pub fn gt(&self, column_value: u64) -> bool {
match self {
PrecomputedAfterKey::Exact(v) => *v > column_value,
PrecomputedAfterKey::Next(v) => *v > column_value,
PrecomputedAfterKey::AfterLast => true,
}
}
pub fn lt(&self, column_value: u64) -> bool {
match self {
PrecomputedAfterKey::Exact(v) => *v < column_value,
// a value equal to the next is greater than the after key
PrecomputedAfterKey::Next(v) => *v <= column_value,
PrecomputedAfterKey::AfterLast => false,
}
}
fn precompute_ip_addr(column: &Column<u64>, key: &Ipv6Addr) -> crate::Result<Self> {
// For IP addresses we need to find the compact space value.
// We try to convert via the column's min/max range scan.
// Since CompactSpaceU64Accessor::u128_to_compact is not public,
// we search linearly for the exact u64 value by scanning column values.
let ip_u128 = key.to_bits();
// Scan for matching value - IP columns are typically small
let num_vals = column.values.num_vals();
let mut found_exact = false;
let mut exact_compact = 0u64;
let mut best_next: Option<u64> = None;
for doc_id in 0..num_vals {
let val = column.values.get_val(doc_id);
// We need the CompactSpaceU64Accessor to convert compact to u128
let compact_accessor = column
.values
.clone()
.downcast_arc::<CompactSpaceU64Accessor>()
.map_err(|_| {
TantivyError::AggregationError(
crate::aggregation::AggregationError::InternalError(
"type mismatch: could not downcast to CompactSpaceU64Accessor"
.to_string(),
),
)
})?;
let val_u128 = compact_accessor.compact_to_u128(val as u32);
if val_u128 == ip_u128 {
found_exact = true;
exact_compact = val;
break;
} else if val_u128 > ip_u128 {
match best_next {
None => best_next = Some(val),
Some(current_best) => {
let current_u128 = compact_accessor.compact_to_u128(current_best as u32);
if val_u128 < current_u128 {
best_next = Some(val);
}
}
}
}
}
if found_exact {
Ok(PrecomputedAfterKey::Exact(exact_compact))
} else if let Some(next) = best_next {
Ok(PrecomputedAfterKey::Next(next))
} else {
Ok(PrecomputedAfterKey::AfterLast)
}
}
fn precompute_term_ord(
str_dict_column: &Option<StrColumn>,
key: &str,
field: &str,
) -> crate::Result<Self> {
let dict = str_dict_column
.as_ref()
.expect("dictionary missing for str accessor")
.dictionary();
let next_ord = dict.term_ord_or_next(key).map_err(|_| {
TantivyError::InvalidArgument(format!(
"failed to lookup after_key '{}' for field '{}'",
key, field
))
})?;
Ok(next_ord.into())
}
/// Projects the after key into the column space of the given accessor.
///
/// The computed after key will not take care of skipping entire columns
/// when the after key type is ordered after the accessor's type, that
/// should be performed earlier.
pub fn precompute(
composite_accessor: &CompositeAccessor,
source_after_key: &CompositeIntermediateKey,
field: &str,
missing_order: MissingOrder,
order: Order,
) -> crate::Result<Self> {
use CompositeIntermediateKey as CIKey;
let precomputed_key = match (composite_accessor.column_type, source_after_key) {
(ColumnType::Bytes, _) => panic!("unsupported"),
// null after key
(_, CIKey::Null) => precompute_missing_after_key(false, missing_order, order),
// numerical
(ColumnType::I64, CIKey::I64(k)) => PrecomputedAfterKey::Exact(k.to_u64()),
(ColumnType::I64, CIKey::U64(k)) => num_proj::u64_to_i64(*k).into(),
(ColumnType::I64, CIKey::F64(k)) => num_proj::f64_to_i64(*k).into(),
(ColumnType::U64, CIKey::I64(k)) => num_proj::i64_to_u64(*k).into(),
(ColumnType::U64, CIKey::U64(k)) => PrecomputedAfterKey::Exact(*k),
(ColumnType::U64, CIKey::F64(k)) => num_proj::f64_to_u64(*k).into(),
(ColumnType::F64, CIKey::I64(k)) => num_proj::i64_to_f64(*k).into(),
(ColumnType::F64, CIKey::U64(k)) => num_proj::u64_to_f64(*k).into(),
(ColumnType::F64, CIKey::F64(k)) => PrecomputedAfterKey::Exact(k.to_u64()),
// boolean
(ColumnType::Bool, CIKey::Bool(key)) => PrecomputedAfterKey::Exact(key.to_u64()),
// string
(ColumnType::Str, CIKey::Str(key)) => PrecomputedAfterKey::precompute_term_ord(
&composite_accessor.str_dict_column,
key,
field,
)?,
// date time
(ColumnType::DateTime, CIKey::DateTime(key)) => {
PrecomputedAfterKey::Exact(key.to_u64())
}
// ip address
(ColumnType::IpAddr, CIKey::IpAddr(key)) => {
PrecomputedAfterKey::precompute_ip_addr(&composite_accessor.column, key)?
}
// assume the column's type is ordered after the after_key's type
_ => PrecomputedAfterKey::keep_all(order),
};
Ok(precomputed_key)
}
fn keep_all(order: Order) -> Self {
match order {
Order::Asc => PrecomputedAfterKey::Next(0),
Order::Desc => PrecomputedAfterKey::Next(u64::MAX),
}
}
}

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@@ -0,0 +1,140 @@
use time::convert::{Day, Nanosecond};
use time::{Time, UtcDateTime};
const NS_IN_DAY: i64 = Nanosecond::per_t::<i128>(Day) as i64;
/// Computes the timestamp in nanoseconds corresponding to the beginning of the
/// year (January 1st at midnight UTC).
pub(super) fn try_year_bucket(timestamp_ns: i64) -> crate::Result<i64> {
year_bucket_using_time_crate(timestamp_ns).map_err(|e| {
crate::TantivyError::InvalidArgument(format!(
"Failed to compute year bucket for timestamp {}: {}",
timestamp_ns,
e.to_string()
))
})
}
/// Computes the timestamp in nanoseconds corresponding to the beginning of the
/// month (1st at midnight UTC).
pub(super) fn try_month_bucket(timestamp_ns: i64) -> crate::Result<i64> {
month_bucket_using_time_crate(timestamp_ns).map_err(|e| {
crate::TantivyError::InvalidArgument(format!(
"Failed to compute month bucket for timestamp {}: {}",
timestamp_ns,
e.to_string()
))
})
}
/// Computes the timestamp in nanoseconds corresponding to the beginning of the
/// week (Monday at midnight UTC).
pub(super) fn week_bucket(timestamp_ns: i64) -> i64 {
// 1970-01-01 was a Thursday (weekday = 4)
let days_since_epoch = timestamp_ns.div_euclid(NS_IN_DAY);
// Find the weekday: 0=Monday, ..., 6=Sunday
let weekday = (days_since_epoch + 3).rem_euclid(7);
let monday_days_since_epoch = days_since_epoch - weekday;
monday_days_since_epoch * NS_IN_DAY
}
fn year_bucket_using_time_crate(timestamp_ns: i64) -> Result<i64, time::Error> {
let timestamp_ns = UtcDateTime::from_unix_timestamp_nanos(timestamp_ns as i128)?
.replace_ordinal(1)?
.replace_time(Time::MIDNIGHT)
.unix_timestamp_nanos();
Ok(timestamp_ns as i64)
}
fn month_bucket_using_time_crate(timestamp_ns: i64) -> Result<i64, time::Error> {
let timestamp_ns = UtcDateTime::from_unix_timestamp_nanos(timestamp_ns as i128)?
.replace_day(1)?
.replace_time(Time::MIDNIGHT)
.unix_timestamp_nanos();
Ok(timestamp_ns as i64)
}
#[cfg(test)]
mod tests {
use std::i64;
use time::format_description::well_known::Iso8601;
use time::UtcDateTime;
use super::*;
fn ts_ns(iso: &str) -> i64 {
UtcDateTime::parse(iso, &Iso8601::DEFAULT)
.unwrap()
.unix_timestamp_nanos() as i64
}
#[test]
fn test_year_bucket() {
let ts = ts_ns("1970-01-01T00:00:00Z");
let res = try_year_bucket(ts).unwrap();
assert_eq!(res, ts_ns("1970-01-01T00:00:00Z"));
let ts = ts_ns("1970-06-01T10:00:01.010Z");
let res = try_year_bucket(ts).unwrap();
assert_eq!(res, ts_ns("1970-01-01T00:00:00Z"));
let ts = ts_ns("2008-12-31T23:59:59.999999999Z"); // leap year
let res = try_year_bucket(ts).unwrap();
assert_eq!(res, ts_ns("2008-01-01T00:00:00Z"));
let ts = ts_ns("2008-01-01T00:00:00Z"); // leap year
let res = try_year_bucket(ts).unwrap();
assert_eq!(res, ts_ns("2008-01-01T00:00:00Z"));
let ts = ts_ns("2010-12-31T23:59:59.999999999Z");
let res = try_year_bucket(ts).unwrap();
assert_eq!(res, ts_ns("2010-01-01T00:00:00Z"));
let ts = ts_ns("1972-06-01T00:10:00Z");
let res = try_year_bucket(ts).unwrap();
assert_eq!(res, ts_ns("1972-01-01T00:00:00Z"));
}
#[test]
fn test_month_bucket() {
let ts = ts_ns("1970-01-15T00:00:00Z");
let res = try_month_bucket(ts).unwrap();
assert_eq!(res, ts_ns("1970-01-01T00:00:00Z"));
let ts = ts_ns("1970-02-01T00:00:00Z");
let res = try_month_bucket(ts).unwrap();
assert_eq!(res, ts_ns("1970-02-01T00:00:00Z"));
let ts = ts_ns("2000-01-31T23:59:59.999999999Z");
let res = try_month_bucket(ts).unwrap();
assert_eq!(res, ts_ns("2000-01-01T00:00:00Z"));
}
#[test]
fn test_week_bucket() {
let ts = ts_ns("1970-01-05T00:00:00Z"); // Monday
let res = week_bucket(ts);
assert_eq!(res, ts_ns("1970-01-05T00:00:00Z"));
let ts = ts_ns("1970-01-05T23:59:59Z"); // Monday
let res = week_bucket(ts);
assert_eq!(res, ts_ns("1970-01-05T00:00:00Z"));
let ts = ts_ns("1970-01-07T01:13:00Z"); // Wednesday
let res = week_bucket(ts);
assert_eq!(res, ts_ns("1970-01-05T00:00:00Z"));
let ts = ts_ns("1970-01-11T23:59:59.999999999Z"); // Sunday
let res = week_bucket(ts);
assert_eq!(res, ts_ns("1970-01-05T00:00:00Z"));
let ts = ts_ns("2025-10-16T10:41:59.010Z"); // Thursday
let res = week_bucket(ts);
assert_eq!(res, ts_ns("2025-10-13T00:00:00Z"));
let ts = ts_ns("1970-01-01T00:00:00Z"); // Thursday
let res = week_bucket(ts);
assert_eq!(res, ts_ns("1969-12-29T00:00:00Z")); // Negative
}
}

View File

@@ -0,0 +1,674 @@
use std::fmt::Debug;
use std::mem;
use std::net::Ipv6Addr;
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{
Column, ColumnType, Dictionary, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
NumericalValue, StrColumn,
};
use rustc_hash::FxHashMap;
use smallvec::SmallVec;
use crate::aggregation::agg_data::{
build_segment_agg_collectors, AggRefNode, AggregationsSegmentCtx,
};
use crate::aggregation::bucket::composite::accessors::{
CompositeAccessor, CompositeAggReqData, PrecomputedDateInterval,
};
use crate::aggregation::bucket::composite::calendar_interval;
use crate::aggregation::bucket::composite::map::{DynArrayHeapMap, MAX_DYN_ARRAY_SIZE};
use crate::aggregation::bucket::{
CalendarInterval, CompositeAggregationSource, MissingOrder, Order,
};
use crate::aggregation::cached_sub_aggs::{CachedSubAggs, HighCardSubAggCache};
use crate::aggregation::intermediate_agg_result::{
CompositeIntermediateKey, IntermediateAggregationResult, IntermediateAggregationResults,
IntermediateBucketResult, IntermediateCompositeBucketEntry, IntermediateCompositeBucketResult,
};
use crate::aggregation::segment_agg_result::{BucketIdProvider, SegmentAggregationCollector};
use crate::aggregation::BucketId;
use crate::TantivyError;
#[derive(Clone, Debug)]
struct CompositeBucketCollector {
count: u32,
bucket_id: BucketId,
}
/// Compact sortable representation of a single source value within a composite key.
///
/// The struct encodes both the column identity and the fast field value in a way
/// that preserves the desired sort order via the derived `Ord` implementation
/// (fields are compared top-to-bottom: `sort_key` first, then `encoded_value`).
///
/// ## `sort_key` encoding
/// - `0` — missing value, sorted first
/// - `1..=254` — present value; the original accessor index is `sort_key - 1`
/// - `u8::MAX` (255) — missing value, sorted last
///
/// ## `encoded_value` encoding
/// - `0` when the field is missing
/// - The raw u64 fast-field representation when order is ascending
/// - Bitwise NOT of the raw u64 when order is descending
#[derive(Clone, Copy, Debug, PartialEq, Eq, PartialOrd, Ord, Default, Hash)]
struct InternalValueRepr {
/// Column index biased by +1 (so 0 and u8::MAX are reserved for missing sentinels).
sort_key: u8,
/// Fast field value, possibly bit-flipped for descending order.
encoded_value: u64,
}
impl InternalValueRepr {
#[inline]
fn new_term(raw: u64, accessor_idx: u8, order: Order) -> Self {
let encoded_value = match order {
Order::Asc => raw,
Order::Desc => !raw,
};
InternalValueRepr {
sort_key: accessor_idx + 1,
encoded_value,
}
}
/// For histogram sources the column index is irrelevant (always 1).
#[inline]
fn new_histogram(raw: u64, order: Order) -> Self {
let encoded_value = match order {
Order::Asc => raw,
Order::Desc => !raw,
};
InternalValueRepr {
sort_key: 1,
encoded_value,
}
}
#[inline]
fn new_missing(order: Order, missing_order: MissingOrder) -> Self {
let sort_key = match (missing_order, order) {
(MissingOrder::First, _) | (MissingOrder::Default, Order::Asc) => 0,
(MissingOrder::Last, _) | (MissingOrder::Default, Order::Desc) => u8::MAX,
};
InternalValueRepr {
sort_key,
encoded_value: 0,
}
}
/// Decode back to `(accessor_idx, raw_value)`.
/// Returns `None` when the value represents a missing field.
#[inline]
fn decode(self, order: Order) -> Option<(u8, u64)> {
if self.sort_key == 0 || self.sort_key == u8::MAX {
return None;
}
let raw = match order {
Order::Asc => self.encoded_value,
Order::Desc => !self.encoded_value,
};
Some((self.sort_key - 1, raw))
}
}
/// The collector puts values from the fast field into the correct buckets and
/// does a conversion to the correct datatype.
#[derive(Debug)]
pub struct SegmentCompositeCollector {
/// One DynArrayHeapMap per parent bucket.
parent_buckets: Vec<DynArrayHeapMap<InternalValueRepr, CompositeBucketCollector>>,
accessor_idx: usize,
sub_agg: Option<CachedSubAggs<HighCardSubAggCache>>,
bucket_id_provider: BucketIdProvider,
/// Number of sources, needed when creating new DynArrayHeapMaps.
num_sources: usize,
}
impl SegmentAggregationCollector for SegmentCompositeCollector {
fn add_intermediate_aggregation_result(
&mut self,
agg_data: &AggregationsSegmentCtx,
results: &mut IntermediateAggregationResults,
parent_bucket_id: BucketId,
) -> crate::Result<()> {
let name = agg_data
.get_composite_req_data(self.accessor_idx)
.name
.clone();
let buckets = self.into_intermediate_bucket_result(agg_data, parent_bucket_id)?;
results.push(
name,
IntermediateAggregationResult::Bucket(IntermediateBucketResult::Composite { buckets }),
)?;
Ok(())
}
fn collect(
&mut self,
parent_bucket_id: BucketId,
docs: &[crate::DocId],
agg_data: &mut AggregationsSegmentCtx,
) -> crate::Result<()> {
let mem_pre = self.get_memory_consumption();
let composite_agg_data = agg_data.take_composite_req_data(self.accessor_idx);
for doc in docs {
let mut sub_level_values = SmallVec::new();
recursive_key_visitor(
*doc,
&composite_agg_data,
0,
&mut sub_level_values,
&mut self.parent_buckets[parent_bucket_id as usize],
true,
&mut self.sub_agg,
&mut self.bucket_id_provider,
)?;
}
agg_data.put_back_composite_req_data(self.accessor_idx, composite_agg_data);
if let Some(sub_agg) = &mut self.sub_agg {
sub_agg.check_flush_local(agg_data)?;
}
let mem_delta = self.get_memory_consumption() - mem_pre;
if mem_delta > 0 {
agg_data.context.limits.add_memory_consumed(mem_delta)?;
}
Ok(())
}
fn flush(&mut self, agg_data: &mut AggregationsSegmentCtx) -> crate::Result<()> {
if let Some(sub_agg) = &mut self.sub_agg {
sub_agg.flush(agg_data)?;
}
Ok(())
}
fn prepare_max_bucket(
&mut self,
max_bucket: BucketId,
_agg_data: &AggregationsSegmentCtx,
) -> crate::Result<()> {
let required_len = max_bucket as usize + 1;
while self.parent_buckets.len() < required_len {
let map = DynArrayHeapMap::try_new(self.num_sources)?;
self.parent_buckets.push(map);
}
Ok(())
}
}
impl SegmentCompositeCollector {
fn get_memory_consumption(&self) -> u64 {
self.parent_buckets
.iter()
.map(|m| m.memory_consumption())
.sum()
}
pub(crate) fn from_req_and_validate(
req_data: &mut AggregationsSegmentCtx,
node: &AggRefNode,
) -> crate::Result<Self> {
validate_req(req_data, node.idx_in_req_data)?;
let has_sub_aggregations = !node.children.is_empty();
let sub_agg = if has_sub_aggregations {
let sub_agg_collector = build_segment_agg_collectors(req_data, &node.children)?;
Some(CachedSubAggs::new(sub_agg_collector))
} else {
None
};
let composite_req_data = req_data.get_composite_req_data(node.idx_in_req_data);
let num_sources = composite_req_data.req.sources.len();
Ok(SegmentCompositeCollector {
parent_buckets: vec![DynArrayHeapMap::try_new(num_sources)?],
accessor_idx: node.idx_in_req_data,
sub_agg,
bucket_id_provider: BucketIdProvider::default(),
num_sources,
})
}
#[inline]
fn into_intermediate_bucket_result(
&mut self,
agg_data: &AggregationsSegmentCtx,
parent_bucket_id: BucketId,
) -> crate::Result<IntermediateCompositeBucketResult> {
let empty_map = DynArrayHeapMap::try_new(self.num_sources)?;
let heap_map = mem::replace(
&mut self.parent_buckets[parent_bucket_id as usize],
empty_map,
);
let mut dict: FxHashMap<Vec<CompositeIntermediateKey>, IntermediateCompositeBucketEntry> =
Default::default();
dict.reserve(heap_map.size());
let composite_data = agg_data.get_composite_req_data(self.accessor_idx);
for (key_internal_repr, agg) in heap_map.into_iter() {
let key = resolve_key(&key_internal_repr, composite_data)?;
let mut sub_aggregation_res = IntermediateAggregationResults::default();
if let Some(sub_agg) = &mut self.sub_agg {
sub_agg
.get_sub_agg_collector()
.add_intermediate_aggregation_result(
agg_data,
&mut sub_aggregation_res,
agg.bucket_id,
)?;
}
dict.insert(
key,
IntermediateCompositeBucketEntry {
doc_count: agg.count,
sub_aggregation: sub_aggregation_res,
},
);
}
Ok(IntermediateCompositeBucketResult {
entries: dict,
target_size: composite_data.req.size,
orders: composite_data
.req
.sources
.iter()
.map(|source| match source {
CompositeAggregationSource::Terms(t) => (t.order, t.missing_order),
CompositeAggregationSource::Histogram(h) => (h.order, h.missing_order),
CompositeAggregationSource::DateHistogram(d) => (d.order, d.missing_order),
})
.collect(),
})
}
}
fn validate_req(req_data: &mut AggregationsSegmentCtx, accessor_idx: usize) -> crate::Result<()> {
let composite_data = req_data.get_composite_req_data(accessor_idx);
let req = &composite_data.req;
if req.sources.is_empty() {
return Err(TantivyError::InvalidArgument(
"composite aggregation must have at least one source".to_string(),
));
}
if req.size == 0 {
return Err(TantivyError::InvalidArgument(
"composite aggregation 'size' must be > 0".to_string(),
));
}
let column_types_for_sources = composite_data.composite_accessors.iter().map(|item| {
item.accessors
.iter()
.map(|a| a.column_type)
.collect::<Vec<_>>()
});
for column_types in column_types_for_sources {
if column_types.len() > MAX_DYN_ARRAY_SIZE {
return Err(TantivyError::InvalidArgument(format!(
"composite aggregation source supports maximum {MAX_DYN_ARRAY_SIZE} sources",
)));
}
if column_types.contains(&ColumnType::Bytes) {
return Err(TantivyError::InvalidArgument(
"composite aggregation does not support 'bytes' field type".to_string(),
));
}
}
Ok(())
}
fn collect_bucket_with_limit(
doc_id: crate::DocId,
limit_num_buckets: usize,
buckets: &mut DynArrayHeapMap<InternalValueRepr, CompositeBucketCollector>,
key: &[InternalValueRepr],
sub_agg: &mut Option<CachedSubAggs<HighCardSubAggCache>>,
bucket_id_provider: &mut BucketIdProvider,
) {
let mut record_in_bucket = |bucket: &mut CompositeBucketCollector| {
bucket.count += 1;
if let Some(sub_agg) = sub_agg {
sub_agg.push(bucket.bucket_id, doc_id);
}
};
// We still have room for buckets, just insert
if buckets.size() < limit_num_buckets {
let bucket = buckets.get_or_insert_with(key, || CompositeBucketCollector {
count: 0,
bucket_id: bucket_id_provider.next_bucket_id(),
});
record_in_bucket(bucket);
return;
}
// Map is full, but we can still update the bucket if it already exists
if let Some(bucket) = buckets.get_mut(key) {
record_in_bucket(bucket);
return;
}
// Check if the item qualifies to enter the top-k, and evict the highest if it does
if let Some(highest_key) = buckets.peek_highest() {
if key < highest_key {
buckets.evict_highest();
let bucket = buckets.get_or_insert_with(key, || CompositeBucketCollector {
count: 0,
bucket_id: bucket_id_provider.next_bucket_id(),
});
record_in_bucket(bucket);
}
}
}
/// Converts the composite key from its internal column space representation
/// (segment specific) into its intermediate form.
fn resolve_key(
internal_key: &[InternalValueRepr],
agg_data: &CompositeAggReqData,
) -> crate::Result<Vec<CompositeIntermediateKey>> {
internal_key
.iter()
.enumerate()
.map(|(idx, val)| {
resolve_internal_value_repr(
*val,
&agg_data.req.sources[idx],
&agg_data.composite_accessors[idx].accessors,
)
})
.collect()
}
fn resolve_internal_value_repr(
internal_value_repr: InternalValueRepr,
source: &CompositeAggregationSource,
composite_accessors: &[CompositeAccessor],
) -> crate::Result<CompositeIntermediateKey> {
let decoded_value_opt = match source {
CompositeAggregationSource::Terms(source) => internal_value_repr.decode(source.order),
CompositeAggregationSource::Histogram(source) => internal_value_repr.decode(source.order),
CompositeAggregationSource::DateHistogram(source) => {
internal_value_repr.decode(source.order)
}
};
let Some((decoded_accessor_idx, val)) = decoded_value_opt else {
return Ok(CompositeIntermediateKey::Null);
};
let key = match source {
CompositeAggregationSource::Terms(_) => {
let CompositeAccessor {
column_type,
str_dict_column,
column,
..
} = &composite_accessors[decoded_accessor_idx as usize];
resolve_term(val, column_type, str_dict_column, column)?
}
CompositeAggregationSource::Histogram(source) => {
CompositeIntermediateKey::F64(i64::from_u64(val) as f64 * source.interval)
}
CompositeAggregationSource::DateHistogram(_) => {
CompositeIntermediateKey::DateTime(i64::from_u64(val))
}
};
Ok(key)
}
fn resolve_term(
val: u64,
column_type: &ColumnType,
str_dict_column: &Option<StrColumn>,
column: &Column,
) -> crate::Result<CompositeIntermediateKey> {
let key = if *column_type == ColumnType::Str {
let fallback_dict = Dictionary::empty();
let term_dict = str_dict_column
.as_ref()
.map(|el| el.dictionary())
.unwrap_or_else(|| &fallback_dict);
let mut buffer = Vec::new();
term_dict.ord_to_term(val, &mut buffer)?;
CompositeIntermediateKey::Str(
String::from_utf8(buffer.to_vec()).expect("could not convert to String"),
)
} else if *column_type == ColumnType::DateTime {
let val = i64::from_u64(val);
CompositeIntermediateKey::DateTime(val)
} else if *column_type == ColumnType::Bool {
let val = bool::from_u64(val);
CompositeIntermediateKey::Bool(val)
} else if *column_type == ColumnType::IpAddr {
let compact_space_accessor = column
.values
.clone()
.downcast_arc::<CompactSpaceU64Accessor>()
.map_err(|_| {
TantivyError::AggregationError(crate::aggregation::AggregationError::InternalError(
"Type mismatch: Could not downcast to CompactSpaceU64Accessor".to_string(),
))
})?;
let val: u128 = compact_space_accessor.compact_to_u128(val as u32);
let val = Ipv6Addr::from_u128(val);
CompositeIntermediateKey::IpAddr(val)
} else if *column_type == ColumnType::U64 {
CompositeIntermediateKey::U64(val)
} else if *column_type == ColumnType::I64 {
CompositeIntermediateKey::I64(i64::from_u64(val))
} else {
let val = f64::from_u64(val);
let val: NumericalValue = val.into();
match val.normalize() {
NumericalValue::U64(val) => CompositeIntermediateKey::U64(val),
NumericalValue::I64(val) => CompositeIntermediateKey::I64(val),
NumericalValue::F64(val) => CompositeIntermediateKey::F64(val),
}
};
Ok(key)
}
/// Depth-first walk of the accessors to build the composite key combinations
/// and update the buckets.
fn recursive_key_visitor(
doc_id: crate::DocId,
composite_agg_data: &CompositeAggReqData,
source_idx_for_recursion: usize,
sub_level_values: &mut SmallVec<[InternalValueRepr; MAX_DYN_ARRAY_SIZE]>,
buckets: &mut DynArrayHeapMap<InternalValueRepr, CompositeBucketCollector>,
// whether we need to consider the after_key in the following levels
is_on_after_key: bool,
sub_agg: &mut Option<CachedSubAggs<HighCardSubAggCache>>,
bucket_id_provider: &mut BucketIdProvider,
) -> crate::Result<()> {
if source_idx_for_recursion == composite_agg_data.req.sources.len() {
if !is_on_after_key {
collect_bucket_with_limit(
doc_id,
composite_agg_data.req.size as usize,
buckets,
sub_level_values,
sub_agg,
bucket_id_provider,
);
}
return Ok(());
}
let current_level_accessors = &composite_agg_data.composite_accessors[source_idx_for_recursion];
let current_level_source = &composite_agg_data.req.sources[source_idx_for_recursion];
let mut missing = true;
for (accessor_idx, accessor) in current_level_accessors.accessors.iter().enumerate() {
let values = accessor.column.values_for_doc(doc_id);
for value in values {
missing = false;
match current_level_source {
CompositeAggregationSource::Terms(_) => {
let preceeds_after_key_type =
accessor_idx < current_level_accessors.after_key_accessor_idx;
if is_on_after_key && preceeds_after_key_type {
break;
}
let matches_after_key_type =
accessor_idx == current_level_accessors.after_key_accessor_idx;
if matches_after_key_type && is_on_after_key {
let should_skip = match current_level_source.order() {
Order::Asc => current_level_accessors.after_key.gt(value),
Order::Desc => current_level_accessors.after_key.lt(value),
};
if should_skip {
continue;
}
}
sub_level_values.push(InternalValueRepr::new_term(
value,
accessor_idx as u8,
current_level_source.order(),
));
let still_on_after_key =
matches_after_key_type && current_level_accessors.after_key.equals(value);
recursive_key_visitor(
doc_id,
composite_agg_data,
source_idx_for_recursion + 1,
sub_level_values,
buckets,
is_on_after_key && still_on_after_key,
sub_agg,
bucket_id_provider,
)?;
sub_level_values.pop();
}
CompositeAggregationSource::Histogram(source) => {
let float_value = match accessor.column_type {
ColumnType::U64 => value as f64,
ColumnType::I64 => i64::from_u64(value) as f64,
ColumnType::DateTime => i64::from_u64(value) as f64 / 1_000_000.,
ColumnType::F64 => f64::from_u64(value),
_ => {
panic!(
"unexpected type {:?}. This should not happen",
accessor.column_type
)
}
};
let bucket_index = (float_value / source.interval).floor() as i64;
let bucket_value = i64::to_u64(bucket_index);
if is_on_after_key {
let should_skip = match current_level_source.order() {
Order::Asc => current_level_accessors.after_key.gt(bucket_value),
Order::Desc => current_level_accessors.after_key.lt(bucket_value),
};
if should_skip {
continue;
}
}
sub_level_values.push(InternalValueRepr::new_histogram(
bucket_value,
current_level_source.order(),
));
let still_on_after_key = current_level_accessors.after_key.equals(bucket_value);
recursive_key_visitor(
doc_id,
composite_agg_data,
source_idx_for_recursion + 1,
sub_level_values,
buckets,
is_on_after_key && still_on_after_key,
sub_agg,
bucket_id_provider,
)?;
sub_level_values.pop();
}
CompositeAggregationSource::DateHistogram(_) => {
let value_ns = match accessor.column_type {
ColumnType::DateTime => i64::from_u64(value),
_ => {
panic!(
"unexpected type {:?}. This should not happen",
accessor.column_type
)
}
};
let bucket_index = match accessor.date_histogram_interval {
PrecomputedDateInterval::FixedNanoseconds(fixed_interval_ns) => {
(value_ns / fixed_interval_ns) * fixed_interval_ns
}
PrecomputedDateInterval::Calendar(CalendarInterval::Year) => {
calendar_interval::try_year_bucket(value_ns)?
}
PrecomputedDateInterval::Calendar(CalendarInterval::Month) => {
calendar_interval::try_month_bucket(value_ns)?
}
PrecomputedDateInterval::Calendar(CalendarInterval::Week) => {
calendar_interval::week_bucket(value_ns)
}
PrecomputedDateInterval::NotApplicable => {
panic!("interval not precomputed for date histogram source")
}
};
let bucket_value = i64::to_u64(bucket_index);
if is_on_after_key {
let should_skip = match current_level_source.order() {
Order::Asc => current_level_accessors.after_key.gt(bucket_value),
Order::Desc => current_level_accessors.after_key.lt(bucket_value),
};
if should_skip {
continue;
}
}
sub_level_values.push(InternalValueRepr::new_histogram(
bucket_value,
current_level_source.order(),
));
let still_on_after_key = current_level_accessors.after_key.equals(bucket_value);
recursive_key_visitor(
doc_id,
composite_agg_data,
source_idx_for_recursion + 1,
sub_level_values,
buckets,
is_on_after_key && still_on_after_key,
sub_agg,
bucket_id_provider,
)?;
sub_level_values.pop();
}
};
}
}
if missing && current_level_source.missing_bucket() {
if is_on_after_key && current_level_accessors.skip_missing {
return Ok(());
}
sub_level_values.push(InternalValueRepr::new_missing(
current_level_source.order(),
current_level_source.missing_order(),
));
recursive_key_visitor(
doc_id,
composite_agg_data,
source_idx_for_recursion + 1,
sub_level_values,
buckets,
is_on_after_key && current_level_accessors.is_after_key_explicit_missing,
sub_agg,
bucket_id_provider,
)?;
sub_level_values.pop();
}
Ok(())
}

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@@ -0,0 +1,329 @@
use std::collections::BinaryHeap;
use std::fmt::Debug;
use std::hash::Hash;
use rustc_hash::FxHashMap;
use smallvec::SmallVec;
use crate::TantivyError;
/// Map backed by a hash map for fast access and a binary heap to track the
/// highest key. The key is an array of fixed size S.
#[derive(Clone, Debug)]
struct ArrayHeapMap<K: Ord, V, const S: usize> {
pub(crate) buckets: FxHashMap<[K; S], V>,
pub(crate) heap: BinaryHeap<[K; S]>,
}
impl<K: Ord, V, const S: usize> Default for ArrayHeapMap<K, V, S> {
fn default() -> Self {
ArrayHeapMap {
buckets: FxHashMap::default(),
heap: BinaryHeap::default(),
}
}
}
impl<K: Eq + Hash + Clone + Ord, V, const S: usize> ArrayHeapMap<K, V, S> {
/// Panics if the length of `key` is not S.
fn get_or_insert_with<F: FnOnce() -> V>(&mut self, key: &[K], f: F) -> &mut V {
let key_array: &[K; S] = key.try_into().expect("Key length mismatch");
self.buckets.entry(key_array.clone()).or_insert_with(|| {
self.heap.push(key_array.clone());
f()
})
}
/// Panics if the length of `key` is not S.
fn get_mut(&mut self, key: &[K]) -> Option<&mut V> {
let key_array: &[K; S] = key.try_into().expect("Key length mismatch");
self.buckets.get_mut(key_array)
}
fn peek_highest(&self) -> Option<&[K]> {
self.heap.peek().map(|k_array| k_array.as_slice())
}
fn evict_highest(&mut self) {
if let Some(highest) = self.heap.pop() {
self.buckets.remove(&highest);
}
}
fn memory_consumption(&self) -> u64 {
let key_size = std::mem::size_of::<[K; S]>();
let map_size = (key_size + std::mem::size_of::<V>()) * self.buckets.capacity();
let heap_size = key_size * self.heap.capacity();
(map_size + heap_size) as u64
}
}
impl<K: Copy + Ord + Clone + 'static, V: 'static, const S: usize> ArrayHeapMap<K, V, S> {
fn into_iter(self) -> Box<dyn Iterator<Item = (SmallVec<[K; MAX_DYN_ARRAY_SIZE]>, V)>> {
Box::new(
self.buckets
.into_iter()
.map(|(k, v)| (SmallVec::from_slice(&k), v)),
)
}
}
pub(super) const MAX_DYN_ARRAY_SIZE: usize = 16;
const MAX_DYN_ARRAY_SIZE_PLUS_ONE: usize = MAX_DYN_ARRAY_SIZE + 1;
/// A map optimized for memory footprint, fast access and efficient eviction of
/// the highest key.
///
/// Keys are inlined arrays of size 1 to [MAX_DYN_ARRAY_SIZE] but for a given
/// instance the key size is fixed. This allows to avoid heap allocations for the
/// keys.
#[derive(Clone, Debug)]
pub(super) struct DynArrayHeapMap<K: Ord, V>(DynArrayHeapMapInner<K, V>);
/// Wrapper around ArrayHeapMap to dynamically dispatch on the array size.
#[derive(Clone, Debug)]
enum DynArrayHeapMapInner<K: Ord, V> {
Dim1(ArrayHeapMap<K, V, 1>),
Dim2(ArrayHeapMap<K, V, 2>),
Dim3(ArrayHeapMap<K, V, 3>),
Dim4(ArrayHeapMap<K, V, 4>),
Dim5(ArrayHeapMap<K, V, 5>),
Dim6(ArrayHeapMap<K, V, 6>),
Dim7(ArrayHeapMap<K, V, 7>),
Dim8(ArrayHeapMap<K, V, 8>),
Dim9(ArrayHeapMap<K, V, 9>),
Dim10(ArrayHeapMap<K, V, 10>),
Dim11(ArrayHeapMap<K, V, 11>),
Dim12(ArrayHeapMap<K, V, 12>),
Dim13(ArrayHeapMap<K, V, 13>),
Dim14(ArrayHeapMap<K, V, 14>),
Dim15(ArrayHeapMap<K, V, 15>),
Dim16(ArrayHeapMap<K, V, 16>),
}
impl<K: Ord, V> DynArrayHeapMap<K, V> {
/// Creates a new heap map with dynamic array keys of size `key_dimension`.
pub(super) fn try_new(key_dimension: usize) -> crate::Result<Self> {
let inner = match key_dimension {
0 => {
return Err(TantivyError::InvalidArgument(
"DynArrayHeapMap dimension must be at least 1".to_string(),
))
}
1 => DynArrayHeapMapInner::Dim1(ArrayHeapMap::default()),
2 => DynArrayHeapMapInner::Dim2(ArrayHeapMap::default()),
3 => DynArrayHeapMapInner::Dim3(ArrayHeapMap::default()),
4 => DynArrayHeapMapInner::Dim4(ArrayHeapMap::default()),
5 => DynArrayHeapMapInner::Dim5(ArrayHeapMap::default()),
6 => DynArrayHeapMapInner::Dim6(ArrayHeapMap::default()),
7 => DynArrayHeapMapInner::Dim7(ArrayHeapMap::default()),
8 => DynArrayHeapMapInner::Dim8(ArrayHeapMap::default()),
9 => DynArrayHeapMapInner::Dim9(ArrayHeapMap::default()),
10 => DynArrayHeapMapInner::Dim10(ArrayHeapMap::default()),
11 => DynArrayHeapMapInner::Dim11(ArrayHeapMap::default()),
12 => DynArrayHeapMapInner::Dim12(ArrayHeapMap::default()),
13 => DynArrayHeapMapInner::Dim13(ArrayHeapMap::default()),
14 => DynArrayHeapMapInner::Dim14(ArrayHeapMap::default()),
15 => DynArrayHeapMapInner::Dim15(ArrayHeapMap::default()),
16 => DynArrayHeapMapInner::Dim16(ArrayHeapMap::default()),
MAX_DYN_ARRAY_SIZE_PLUS_ONE.. => {
return Err(TantivyError::InvalidArgument(format!(
"DynArrayHeapMap supports maximum {MAX_DYN_ARRAY_SIZE} dimensions, got \
{key_dimension}",
)))
}
};
Ok(DynArrayHeapMap(inner))
}
/// Number of elements in the map. This is not the dimension of the keys.
pub(super) fn size(&self) -> usize {
match &self.0 {
DynArrayHeapMapInner::Dim1(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim2(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim3(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim4(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim5(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim6(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim7(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim8(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim9(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim10(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim11(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim12(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim13(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim14(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim15(map) => map.buckets.len(),
DynArrayHeapMapInner::Dim16(map) => map.buckets.len(),
}
}
}
impl<K: Ord + Hash + Clone, V> DynArrayHeapMap<K, V> {
/// Get a mutable reference to the value corresponding to `key` or inserts a new
/// value created by calling `f`.
///
/// Panics if the length of `key` does not match the key dimension of the map.
pub(super) fn get_or_insert_with<F: FnOnce() -> V>(&mut self, key: &[K], f: F) -> &mut V {
match &mut self.0 {
DynArrayHeapMapInner::Dim1(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim2(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim3(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim4(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim5(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim6(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim7(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim8(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim9(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim10(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim11(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim12(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim13(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim14(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim15(map) => map.get_or_insert_with(key, f),
DynArrayHeapMapInner::Dim16(map) => map.get_or_insert_with(key, f),
}
}
/// Returns a mutable reference to the value corresponding to `key`.
///
/// Panics if the length of `key` does not match the key dimension of the map.
pub fn get_mut(&mut self, key: &[K]) -> Option<&mut V> {
match &mut self.0 {
DynArrayHeapMapInner::Dim1(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim2(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim3(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim4(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim5(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim6(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim7(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim8(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim9(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim10(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim11(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim12(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim13(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim14(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim15(map) => map.get_mut(key),
DynArrayHeapMapInner::Dim16(map) => map.get_mut(key),
}
}
/// Returns a reference to the highest key in the map.
pub(super) fn peek_highest(&self) -> Option<&[K]> {
match &self.0 {
DynArrayHeapMapInner::Dim1(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim2(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim3(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim4(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim5(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim6(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim7(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim8(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim9(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim10(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim11(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim12(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim13(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim14(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim15(map) => map.peek_highest(),
DynArrayHeapMapInner::Dim16(map) => map.peek_highest(),
}
}
/// Removes the entry with the highest key from the map.
pub(super) fn evict_highest(&mut self) {
match &mut self.0 {
DynArrayHeapMapInner::Dim1(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim2(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim3(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim4(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim5(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim6(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim7(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim8(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim9(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim10(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim11(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim12(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim13(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim14(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim15(map) => map.evict_highest(),
DynArrayHeapMapInner::Dim16(map) => map.evict_highest(),
}
}
pub(crate) fn memory_consumption(&self) -> u64 {
match &self.0 {
DynArrayHeapMapInner::Dim1(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim2(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim3(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim4(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim5(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim6(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim7(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim8(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim9(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim10(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim11(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim12(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim13(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim14(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim15(map) => map.memory_consumption(),
DynArrayHeapMapInner::Dim16(map) => map.memory_consumption(),
}
}
}
impl<K: Ord + Clone + Copy + 'static, V: 'static> DynArrayHeapMap<K, V> {
/// Turns this map into an iterator over key-value pairs.
pub fn into_iter(self) -> impl Iterator<Item = (SmallVec<[K; MAX_DYN_ARRAY_SIZE]>, V)> {
match self.0 {
DynArrayHeapMapInner::Dim1(map) => map.into_iter(),
DynArrayHeapMapInner::Dim2(map) => map.into_iter(),
DynArrayHeapMapInner::Dim3(map) => map.into_iter(),
DynArrayHeapMapInner::Dim4(map) => map.into_iter(),
DynArrayHeapMapInner::Dim5(map) => map.into_iter(),
DynArrayHeapMapInner::Dim6(map) => map.into_iter(),
DynArrayHeapMapInner::Dim7(map) => map.into_iter(),
DynArrayHeapMapInner::Dim8(map) => map.into_iter(),
DynArrayHeapMapInner::Dim9(map) => map.into_iter(),
DynArrayHeapMapInner::Dim10(map) => map.into_iter(),
DynArrayHeapMapInner::Dim11(map) => map.into_iter(),
DynArrayHeapMapInner::Dim12(map) => map.into_iter(),
DynArrayHeapMapInner::Dim13(map) => map.into_iter(),
DynArrayHeapMapInner::Dim14(map) => map.into_iter(),
DynArrayHeapMapInner::Dim15(map) => map.into_iter(),
DynArrayHeapMapInner::Dim16(map) => map.into_iter(),
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn test_dyn_array_heap_map() {
let mut map = DynArrayHeapMap::<u32, &str>::try_new(2).unwrap();
// insert
let key1 = [1u32, 2u32];
let key2 = [2u32, 1u32];
map.get_or_insert_with(&key1, || "a");
map.get_or_insert_with(&key2, || "b");
assert_eq!(map.size(), 2);
// evict highest
assert_eq!(map.peek_highest(), Some(&key2[..]));
map.evict_highest();
assert_eq!(map.size(), 1);
assert_eq!(map.peek_highest(), Some(&key1[..]));
// into_iter
let mut iter = map.into_iter();
let (k, v) = iter.next().unwrap();
assert_eq!(k.as_slice(), &key1);
assert_eq!(v, "c");
assert_eq!(iter.next(), None);
}
}

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@@ -0,0 +1,460 @@
/// This modules helps comparing numerical values of different types (i64, u64
/// and f64).
pub(super) mod num_cmp {
use std::cmp::Ordering;
use crate::TantivyError;
pub fn cmp_i64_f64(left_i: i64, right_f: f64) -> crate::Result<Ordering> {
if right_f.is_nan() {
return Err(TantivyError::InvalidArgument(
"NaN comparison is not supported".to_string(),
));
}
// If right_f is < i64::MIN then left_i > right_f (i64::MIN=-2^63 can be
// exactly represented as f64)
if right_f < i64::MIN as f64 {
return Ok(Ordering::Greater);
}
// If right_f is >= i64::MAX then left_i < right_f (i64::MAX=2^63-1 cannot
// be exactly represented as f64)
if right_f >= i64::MAX as f64 {
return Ok(Ordering::Less);
}
// Now right_f is in (i64::MIN, i64::MAX), so `right_f as i64` is
// well-defined (truncation toward 0)
let right_as_i = right_f as i64;
let result = match left_i.cmp(&right_as_i) {
Ordering::Less => Ordering::Less,
Ordering::Greater => Ordering::Greater,
Ordering::Equal => {
// they have the same integer part, compare the fraction
let rem = right_f - (right_as_i as f64);
if rem == 0.0 {
Ordering::Equal
} else if right_f > 0.0 {
Ordering::Less
} else {
Ordering::Greater
}
}
};
Ok(result)
}
pub fn cmp_u64_f64(left_u: u64, right_f: f64) -> crate::Result<Ordering> {
if right_f.is_nan() {
return Err(TantivyError::InvalidArgument(
"NaN comparison is not supported".to_string(),
));
}
// Negative floats are always less than any u64 >= 0
if right_f < 0.0 {
return Ok(Ordering::Greater);
}
// If right_f is >= u64::MAX then left_u < right_f (u64::MAX=2^64-1 cannot be exactly)
let max_as_f = u64::MAX as f64;
if right_f > max_as_f {
return Ok(Ordering::Less);
}
// Now right_f is in (0, u64::MAX), so `right_f as u64` is well-defined
// (truncation toward 0)
let right_as_u = right_f as u64;
let result = match left_u.cmp(&right_as_u) {
Ordering::Less => Ordering::Less,
Ordering::Greater => Ordering::Greater,
Ordering::Equal => {
// they have the same integer part, compare the fraction
let rem = right_f - (right_as_u as f64);
if rem == 0.0 {
Ordering::Equal
} else {
Ordering::Less
}
}
};
Ok(result)
}
pub fn cmp_i64_u64(left_i: i64, right_u: u64) -> Ordering {
if left_i < 0 {
Ordering::Less
} else {
let left_as_u = left_i as u64;
left_as_u.cmp(&right_u)
}
}
}
/// This modules helps projecting numerical values to other numerical types.
/// When the target value space cannot exactly represent the source value, the
/// next representable value is returned (or AfterLast if the source value is
/// larger than the largest representable value).
///
/// All functions in this module assume that f64 values are not NaN.
pub(super) mod num_proj {
#[derive(Debug, PartialEq)]
pub enum ProjectedNumber<T> {
Exact(T),
Next(T),
AfterLast,
}
pub fn i64_to_u64(value: i64) -> ProjectedNumber<u64> {
if value < 0 {
ProjectedNumber::Next(0)
} else {
ProjectedNumber::Exact(value as u64)
}
}
pub fn u64_to_i64(value: u64) -> ProjectedNumber<i64> {
if value > i64::MAX as u64 {
ProjectedNumber::AfterLast
} else {
ProjectedNumber::Exact(value as i64)
}
}
pub fn f64_to_u64(value: f64) -> ProjectedNumber<u64> {
if value < 0.0 {
ProjectedNumber::Next(0)
} else if value > u64::MAX as f64 {
ProjectedNumber::AfterLast
} else if value.fract() == 0.0 {
ProjectedNumber::Exact(value as u64)
} else {
// casting f64 to u64 truncates toward zero
ProjectedNumber::Next(value as u64 + 1)
}
}
pub fn f64_to_i64(value: f64) -> ProjectedNumber<i64> {
if value < (i64::MIN as f64) {
return ProjectedNumber::Next(i64::MIN);
} else if value >= (i64::MAX as f64) {
return ProjectedNumber::AfterLast;
} else if value.fract() == 0.0 {
ProjectedNumber::Exact(value as i64)
} else if value > 0.0 {
// casting f64 to i64 truncates toward zero
ProjectedNumber::Next(value as i64 + 1)
} else {
ProjectedNumber::Next(value as i64)
}
}
pub fn i64_to_f64(value: i64) -> ProjectedNumber<f64> {
let value_f = value as f64;
let k_roundtrip = value_f as i64;
if k_roundtrip == value {
// between -2^53 and 2^53 all i64 are exactly represented as f64
ProjectedNumber::Exact(value_f)
} else {
// for very large/small i64 values, it is approximated to the closest f64
if k_roundtrip > value {
ProjectedNumber::Next(value_f)
} else {
ProjectedNumber::Next(value_f.next_up())
}
}
}
pub fn u64_to_f64(value: u64) -> ProjectedNumber<f64> {
let value_f = value as f64;
let k_roundtrip = value_f as u64;
if k_roundtrip == value {
// between 0 and 2^53 all u64 are exactly represented as f64
ProjectedNumber::Exact(value_f)
} else if k_roundtrip > value {
ProjectedNumber::Next(value_f)
} else {
ProjectedNumber::Next(value_f.next_up())
}
}
}
#[cfg(test)]
mod num_cmp_tests {
use std::cmp::Ordering;
use super::num_cmp::*;
#[test]
fn test_cmp_u64_f64() {
// Basic comparisons
assert_eq!(cmp_u64_f64(5, 5.0).unwrap(), Ordering::Equal);
assert_eq!(cmp_u64_f64(5, 6.0).unwrap(), Ordering::Less);
assert_eq!(cmp_u64_f64(6, 5.0).unwrap(), Ordering::Greater);
assert_eq!(cmp_u64_f64(0, 0.0).unwrap(), Ordering::Equal);
assert_eq!(cmp_u64_f64(0, 0.1).unwrap(), Ordering::Less);
// Negative float values should always be less than any u64
assert_eq!(cmp_u64_f64(0, -0.1).unwrap(), Ordering::Greater);
assert_eq!(cmp_u64_f64(5, -5.0).unwrap(), Ordering::Greater);
assert_eq!(cmp_u64_f64(u64::MAX, -1e20).unwrap(), Ordering::Greater);
// Tests with extreme values
assert_eq!(cmp_u64_f64(u64::MAX, 1e20).unwrap(), Ordering::Less);
// Precision edge cases: large u64 that loses precision when converted to f64
// => 2^54, exactly represented as f64
let large_f64 = 18_014_398_509_481_984.0;
let large_u64 = 18_014_398_509_481_984;
// prove that large_u64 is exactly represented as f64
assert_eq!(large_u64 as f64, large_f64);
assert_eq!(cmp_u64_f64(large_u64, large_f64).unwrap(), Ordering::Equal);
// => (2^54 + 1) cannot be exactly represented in f64
let large_u64_plus_1 = 18_014_398_509_481_985;
// prove that it is represented as f64 by large_f64
assert_eq!(large_u64_plus_1 as f64, large_f64);
assert_eq!(
cmp_u64_f64(large_u64_plus_1, large_f64).unwrap(),
Ordering::Greater
);
// => (2^54 - 1) cannot be exactly represented in f64
let large_u64_minus_1 = 18_014_398_509_481_983;
// prove that it is also represented as f64 by large_f64
assert_eq!(large_u64_minus_1 as f64, large_f64);
assert_eq!(
cmp_u64_f64(large_u64_minus_1, large_f64).unwrap(),
Ordering::Less
);
// NaN comparison results in an error
assert!(cmp_u64_f64(0, f64::NAN).is_err());
}
#[test]
fn test_cmp_i64_f64() {
// Basic comparisons
assert_eq!(cmp_i64_f64(5, 5.0).unwrap(), Ordering::Equal);
assert_eq!(cmp_i64_f64(5, 6.0).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(6, 5.0).unwrap(), Ordering::Greater);
assert_eq!(cmp_i64_f64(-5, -5.0).unwrap(), Ordering::Equal);
assert_eq!(cmp_i64_f64(-5, -4.0).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(-4, -5.0).unwrap(), Ordering::Greater);
assert_eq!(cmp_i64_f64(-5, 5.0).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(5, -5.0).unwrap(), Ordering::Greater);
assert_eq!(cmp_i64_f64(0, -0.1).unwrap(), Ordering::Greater);
assert_eq!(cmp_i64_f64(0, 0.1).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(-1, -0.5).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(-1, 0.0).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(0, 0.0).unwrap(), Ordering::Equal);
// Tests with extreme values
assert_eq!(cmp_i64_f64(i64::MAX, 1e20).unwrap(), Ordering::Less);
assert_eq!(cmp_i64_f64(i64::MIN, -1e20).unwrap(), Ordering::Greater);
// Precision edge cases: large i64 that loses precision when converted to f64
// => 2^54, exactly represented as f64
let large_f64 = 18_014_398_509_481_984.0;
let large_i64 = 18_014_398_509_481_984;
// prove that large_i64 is exactly represented as f64
assert_eq!(large_i64 as f64, large_f64);
assert_eq!(cmp_i64_f64(large_i64, large_f64).unwrap(), Ordering::Equal);
// => (1_i64 << 54) + 1 cannot be exactly represented in f64
let large_i64_plus_1 = 18_014_398_509_481_985;
// prove that it is represented as f64 by large_f64
assert_eq!(large_i64_plus_1 as f64, large_f64);
assert_eq!(
cmp_i64_f64(large_i64_plus_1, large_f64).unwrap(),
Ordering::Greater
);
// => (1_i64 << 54) - 1 cannot be exactly represented in f64
let large_i64_minus_1 = 18_014_398_509_481_983;
// prove that it is also represented as f64 by large_f64
assert_eq!(large_i64_minus_1 as f64, large_f64);
assert_eq!(
cmp_i64_f64(large_i64_minus_1, large_f64).unwrap(),
Ordering::Less
);
// Same precision edge case but with negative values
// => -2^54, exactly represented as f64
let large_neg_f64 = -18_014_398_509_481_984.0;
let large_neg_i64 = -18_014_398_509_481_984;
// prove that large_neg_i64 is exactly represented as f64
assert_eq!(large_neg_i64 as f64, large_neg_f64);
assert_eq!(
cmp_i64_f64(large_neg_i64, large_neg_f64).unwrap(),
Ordering::Equal
);
// => (-2^54 + 1) cannot be exactly represented in f64
let large_neg_i64_plus_1 = -18_014_398_509_481_985;
// prove that it is represented as f64 by large_neg_f64
assert_eq!(large_neg_i64_plus_1 as f64, large_neg_f64);
assert_eq!(
cmp_i64_f64(large_neg_i64_plus_1, large_neg_f64).unwrap(),
Ordering::Less
);
// => (-2^54 - 1) cannot be exactly represented in f64
let large_neg_i64_minus_1 = -18_014_398_509_481_983;
// prove that it is also represented as f64 by large_neg_f64
assert_eq!(large_neg_i64_minus_1 as f64, large_neg_f64);
assert_eq!(
cmp_i64_f64(large_neg_i64_minus_1, large_neg_f64).unwrap(),
Ordering::Greater
);
// NaN comparison results in an error
assert!(cmp_i64_f64(0, f64::NAN).is_err());
}
#[test]
fn test_cmp_i64_u64() {
// Test with negative i64 values (should always be less than any u64)
assert_eq!(cmp_i64_u64(-1, 0), Ordering::Less);
assert_eq!(cmp_i64_u64(i64::MIN, 0), Ordering::Less);
assert_eq!(cmp_i64_u64(i64::MIN, u64::MAX), Ordering::Less);
// Test with positive i64 values
assert_eq!(cmp_i64_u64(0, 0), Ordering::Equal);
assert_eq!(cmp_i64_u64(1, 0), Ordering::Greater);
assert_eq!(cmp_i64_u64(1, 1), Ordering::Equal);
assert_eq!(cmp_i64_u64(0, 1), Ordering::Less);
assert_eq!(cmp_i64_u64(5, 10), Ordering::Less);
assert_eq!(cmp_i64_u64(10, 5), Ordering::Greater);
// Test with values near i64::MAX and u64 conversion
assert_eq!(cmp_i64_u64(i64::MAX, i64::MAX as u64), Ordering::Equal);
assert_eq!(cmp_i64_u64(i64::MAX, (i64::MAX as u64) + 1), Ordering::Less);
assert_eq!(cmp_i64_u64(i64::MAX, u64::MAX), Ordering::Less);
}
}
#[cfg(test)]
mod num_proj_tests {
use super::num_proj::{self, ProjectedNumber};
#[test]
fn test_i64_to_u64() {
assert_eq!(num_proj::i64_to_u64(-1), ProjectedNumber::Next(0));
assert_eq!(num_proj::i64_to_u64(i64::MIN), ProjectedNumber::Next(0));
assert_eq!(num_proj::i64_to_u64(0), ProjectedNumber::Exact(0));
assert_eq!(num_proj::i64_to_u64(42), ProjectedNumber::Exact(42));
assert_eq!(
num_proj::i64_to_u64(i64::MAX),
ProjectedNumber::Exact(i64::MAX as u64)
);
}
#[test]
fn test_u64_to_i64() {
assert_eq!(num_proj::u64_to_i64(0), ProjectedNumber::Exact(0));
assert_eq!(num_proj::u64_to_i64(42), ProjectedNumber::Exact(42));
assert_eq!(
num_proj::u64_to_i64(i64::MAX as u64),
ProjectedNumber::Exact(i64::MAX)
);
assert_eq!(
num_proj::u64_to_i64((i64::MAX as u64) + 1),
ProjectedNumber::AfterLast
);
assert_eq!(num_proj::u64_to_i64(u64::MAX), ProjectedNumber::AfterLast);
}
#[test]
fn test_f64_to_u64() {
assert_eq!(num_proj::f64_to_u64(-1e25), ProjectedNumber::Next(0));
assert_eq!(num_proj::f64_to_u64(-0.1), ProjectedNumber::Next(0));
assert_eq!(num_proj::f64_to_u64(1e20), ProjectedNumber::AfterLast);
assert_eq!(
num_proj::f64_to_u64(f64::INFINITY),
ProjectedNumber::AfterLast
);
assert_eq!(num_proj::f64_to_u64(0.0), ProjectedNumber::Exact(0));
assert_eq!(num_proj::f64_to_u64(42.0), ProjectedNumber::Exact(42));
assert_eq!(num_proj::f64_to_u64(0.5), ProjectedNumber::Next(1));
assert_eq!(num_proj::f64_to_u64(42.1), ProjectedNumber::Next(43));
}
#[test]
fn test_f64_to_i64() {
assert_eq!(num_proj::f64_to_i64(-1e20), ProjectedNumber::Next(i64::MIN));
assert_eq!(
num_proj::f64_to_i64(f64::NEG_INFINITY),
ProjectedNumber::Next(i64::MIN)
);
assert_eq!(num_proj::f64_to_i64(1e20), ProjectedNumber::AfterLast);
assert_eq!(
num_proj::f64_to_i64(f64::INFINITY),
ProjectedNumber::AfterLast
);
assert_eq!(num_proj::f64_to_i64(0.0), ProjectedNumber::Exact(0));
assert_eq!(num_proj::f64_to_i64(42.0), ProjectedNumber::Exact(42));
assert_eq!(num_proj::f64_to_i64(-42.0), ProjectedNumber::Exact(-42));
assert_eq!(num_proj::f64_to_i64(0.5), ProjectedNumber::Next(1));
assert_eq!(num_proj::f64_to_i64(42.1), ProjectedNumber::Next(43));
assert_eq!(num_proj::f64_to_i64(-0.5), ProjectedNumber::Next(0));
assert_eq!(num_proj::f64_to_i64(-42.1), ProjectedNumber::Next(-42));
}
#[test]
fn test_i64_to_f64() {
assert_eq!(num_proj::i64_to_f64(0), ProjectedNumber::Exact(0.0));
assert_eq!(num_proj::i64_to_f64(42), ProjectedNumber::Exact(42.0));
assert_eq!(num_proj::i64_to_f64(-42), ProjectedNumber::Exact(-42.0));
let max_exact = 9_007_199_254_740_992; // 2^53
assert_eq!(
num_proj::i64_to_f64(max_exact),
ProjectedNumber::Exact(max_exact as f64)
);
// Test values that cannot be exactly represented as f64 (integers above 2^53)
let large_i64 = 9_007_199_254_740_993; // 2^53 + 1
let closest_f64 = 9_007_199_254_740_992.0;
assert_eq!(large_i64 as f64, closest_f64);
if let ProjectedNumber::Next(val) = num_proj::i64_to_f64(large_i64) {
// Verify that the returned float is different from the direct cast
assert!(val > closest_f64);
assert!(val - closest_f64 < 2. * f64::EPSILON * closest_f64);
} else {
panic!("Expected ProjectedNumber::Next for large_i64");
}
// Test with very large negative value
let large_neg_i64 = -9_007_199_254_740_993; // -(2^53 + 1)
let closest_neg_f64 = -9_007_199_254_740_992.0;
assert_eq!(large_neg_i64 as f64, closest_neg_f64);
if let ProjectedNumber::Next(val) = num_proj::i64_to_f64(large_neg_i64) {
// Verify that the returned float is the closest representable f64
assert_eq!(val, closest_neg_f64);
} else {
panic!("Expected ProjectedNumber::Next for large_neg_i64");
}
}
#[test]
fn test_u64_to_f64() {
assert_eq!(num_proj::u64_to_f64(0), ProjectedNumber::Exact(0.0));
assert_eq!(num_proj::u64_to_f64(42), ProjectedNumber::Exact(42.0));
// Test the largest u64 value that can be exactly represented as f64 (2^53)
let max_exact = 9_007_199_254_740_992; // 2^53
assert_eq!(
num_proj::u64_to_f64(max_exact),
ProjectedNumber::Exact(max_exact as f64)
);
// Test values that cannot be exactly represented as f64 (integers above 2^53)
let large_u64 = 9_007_199_254_740_993; // 2^53 + 1
let closest_f64 = 9_007_199_254_740_992.0;
assert_eq!(large_u64 as f64, closest_f64);
if let ProjectedNumber::Next(val) = num_proj::u64_to_f64(large_u64) {
// Verify that the returned float is different from the direct cast
assert!(val > closest_f64);
assert!(val - closest_f64 < 2. * f64::EPSILON * closest_f64);
} else {
panic!("Expected ProjectedNumber::Next for large_u64");
}
}
}

View File

@@ -207,7 +207,7 @@ fn parse_offset_into_milliseconds(input: &str) -> Result<i64, AggregationError>
}
}
fn parse_into_milliseconds(input: &str) -> Result<i64, AggregationError> {
pub(crate) fn parse_into_milliseconds(input: &str) -> Result<i64, AggregationError> {
let split_boundary = input
.as_bytes()
.iter()

View File

@@ -22,6 +22,7 @@
//! - [Range](RangeAggregation)
//! - [Terms](TermsAggregation)
mod composite;
mod filter;
mod histogram;
mod range;
@@ -31,6 +32,7 @@ mod term_missing_agg;
use std::collections::HashMap;
use std::fmt;
pub use composite::*;
pub use filter::*;
pub use histogram::*;
pub use range::*;

View File

@@ -15,8 +15,9 @@ use serde::{Deserialize, Serialize};
use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
use super::agg_result::{AggregationResult, BucketResult, MetricResult, RangeBucketEntry};
use super::bucket::{
cut_off_buckets, get_agg_name_and_property, intermediate_histogram_buckets_to_final_buckets,
GetDocCount, Order, OrderTarget, RangeAggregation, TermsAggregation,
composite_intermediate_key_ordering, cut_off_buckets, get_agg_name_and_property,
intermediate_histogram_buckets_to_final_buckets, CompositeAggregation, GetDocCount,
MissingOrder, Order, OrderTarget, RangeAggregation, TermsAggregation,
};
use super::metric::{
IntermediateAverage, IntermediateCount, IntermediateExtendedStats, IntermediateMax,
@@ -25,7 +26,7 @@ use super::metric::{
use super::segment_agg_result::AggregationLimitsGuard;
use super::{format_date, AggregationError, Key, SerializedKey};
use crate::aggregation::agg_result::{
AggregationResults, BucketEntries, BucketEntry, FilterBucketResult,
AggregationResults, BucketEntries, BucketEntry, CompositeBucketEntry, FilterBucketResult,
};
use crate::aggregation::bucket::TermsAggregationInternal;
use crate::aggregation::metric::CardinalityCollector;
@@ -90,6 +91,19 @@ impl From<IntermediateKey> for Key {
impl Eq for IntermediateKey {}
impl std::fmt::Display for IntermediateKey {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
match self {
IntermediateKey::Str(val) => f.write_str(val),
IntermediateKey::F64(val) => f.write_str(&val.to_string()),
IntermediateKey::U64(val) => f.write_str(&val.to_string()),
IntermediateKey::I64(val) => f.write_str(&val.to_string()),
IntermediateKey::Bool(val) => f.write_str(&val.to_string()),
IntermediateKey::IpAddr(val) => f.write_str(&val.to_string()),
}
}
}
impl std::hash::Hash for IntermediateKey {
fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
core::mem::discriminant(self).hash(state);
@@ -105,6 +119,21 @@ impl std::hash::Hash for IntermediateKey {
}
impl IntermediateAggregationResults {
/// Returns a reference to the intermediate aggregation result for the given key.
pub fn get(&self, key: &str) -> Option<&IntermediateAggregationResult> {
self.aggs_res.get(key)
}
/// Removes and returns the intermediate aggregation result for the given key.
pub fn remove(&mut self, key: &str) -> Option<IntermediateAggregationResult> {
self.aggs_res.remove(key)
}
/// Returns an iterator over the keys in the intermediate aggregation results.
pub fn keys(&self) -> impl Iterator<Item = &String> {
self.aggs_res.keys()
}
/// Add a result
pub fn push(&mut self, key: String, value: IntermediateAggregationResult) -> crate::Result<()> {
let entry = self.aggs_res.entry(key);
@@ -252,6 +281,11 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
doc_count: 0,
sub_aggregations: IntermediateAggregationResults::default(),
}),
Composite(_) => {
IntermediateAggregationResult::Bucket(IntermediateBucketResult::Composite {
buckets: IntermediateCompositeBucketResult::default(),
})
}
}
}
@@ -445,6 +479,11 @@ pub enum IntermediateBucketResult {
/// Sub-aggregation results
sub_aggregations: IntermediateAggregationResults,
},
/// Composite aggregation
Composite {
/// The composite buckets
buckets: IntermediateCompositeBucketResult,
},
}
impl IntermediateBucketResult {
@@ -540,6 +579,13 @@ impl IntermediateBucketResult {
sub_aggregations: final_sub_aggregations,
}))
}
IntermediateBucketResult::Composite { buckets } => {
let composite_req = req
.agg
.as_composite()
.expect("unexpected aggregation, expected composite aggregation");
buckets.into_final_result(composite_req, req.sub_aggregation(), limits)
}
}
}
@@ -606,6 +652,16 @@ impl IntermediateBucketResult {
*doc_count_left += doc_count_right;
sub_aggs_left.merge_fruits(sub_aggs_right)?;
}
(
IntermediateBucketResult::Composite {
buckets: composite_left,
},
IntermediateBucketResult::Composite {
buckets: composite_right,
},
) => {
composite_left.merge_fruits(composite_right)?;
}
(IntermediateBucketResult::Range(_), _) => {
panic!("try merge on different types")
}
@@ -618,6 +674,9 @@ impl IntermediateBucketResult {
(IntermediateBucketResult::Filter { .. }, _) => {
panic!("try merge on different types")
}
(IntermediateBucketResult::Composite { .. }, _) => {
panic!("try merge on different types")
}
}
Ok(())
}
@@ -639,6 +698,21 @@ pub struct IntermediateTermBucketResult {
}
impl IntermediateTermBucketResult {
/// Returns a reference to the map of bucket entries keyed by [`IntermediateKey`].
pub fn entries(&self) -> &FxHashMap<IntermediateKey, IntermediateTermBucketEntry> {
&self.entries
}
/// Returns the count of documents not included in the returned buckets.
pub fn sum_other_doc_count(&self) -> u64 {
self.sum_other_doc_count
}
/// Returns the upper bound of the error on document counts in the returned buckets.
pub fn doc_count_error_upper_bound(&self) -> u64 {
self.doc_count_error_upper_bound
}
pub(crate) fn into_final_result(
self,
req: &TermsAggregation,
@@ -820,7 +894,7 @@ impl IntermediateRangeBucketEntry {
};
// If we have a date type on the histogram buckets, we add the `key_as_string` field as
// rfc339
// rfc3339
if column_type == Some(ColumnType::DateTime) {
if let Some(val) = range_bucket_entry.to {
let key_as_string = format_date(val as i64)?;
@@ -871,6 +945,176 @@ impl MergeFruits for IntermediateHistogramBucketEntry {
}
}
/// Entry for the composite bucket.
pub type IntermediateCompositeBucketEntry = IntermediateTermBucketEntry;
/// The fully typed key for composite aggregation
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub enum CompositeIntermediateKey {
/// Bool key
Bool(bool),
/// String key
Str(String),
/// Float key
F64(f64),
/// Signed integer key
I64(i64),
/// Unsigned integer key
U64(u64),
/// DateTime key, nanoseconds since epoch
DateTime(i64),
/// IP Address key
IpAddr(Ipv6Addr),
/// Missing value key
Null,
}
impl Eq for CompositeIntermediateKey {}
impl std::hash::Hash for CompositeIntermediateKey {
fn hash<H: std::hash::Hasher>(&self, state: &mut H) {
core::mem::discriminant(self).hash(state);
match self {
CompositeIntermediateKey::Bool(val) => val.hash(state),
CompositeIntermediateKey::Str(text) => text.hash(state),
CompositeIntermediateKey::F64(val) => val.to_bits().hash(state),
CompositeIntermediateKey::U64(val) => val.hash(state),
CompositeIntermediateKey::I64(val) => val.hash(state),
CompositeIntermediateKey::DateTime(val) => val.hash(state),
CompositeIntermediateKey::IpAddr(val) => val.hash(state),
CompositeIntermediateKey::Null => {}
}
}
}
/// Composite aggregation page.
#[derive(Default, Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct IntermediateCompositeBucketResult {
pub(crate) entries: FxHashMap<Vec<CompositeIntermediateKey>, IntermediateCompositeBucketEntry>,
pub(crate) target_size: u32,
pub(crate) orders: Vec<(Order, MissingOrder)>,
}
impl IntermediateCompositeBucketResult {
pub(crate) fn into_final_result(
self,
req: &CompositeAggregation,
sub_aggregation_req: &Aggregations,
limits: &mut AggregationLimitsGuard,
) -> crate::Result<BucketResult> {
let trimmed_entry_vec =
trim_composite_buckets(self.entries, &self.orders, self.target_size)?;
let after_key = if trimmed_entry_vec.len() == req.size as usize {
trimmed_entry_vec
.last()
.map(|bucket| {
let (intermediate_key, _entry) = bucket;
intermediate_key
.iter()
.enumerate()
.map(|(idx, intermediate_key)| {
let source = &req.sources[idx];
(source.name().to_string(), intermediate_key.clone().into())
})
.collect()
})
.unwrap()
} else {
FxHashMap::default()
};
let buckets = trimmed_entry_vec
.into_iter()
.map(|(intermediate_key, entry)| {
let key = intermediate_key
.into_iter()
.enumerate()
.map(|(idx, intermediate_key)| {
let source = &req.sources[idx];
(source.name().to_string(), intermediate_key.into())
})
.collect();
Ok(CompositeBucketEntry {
key,
doc_count: entry.doc_count as u64,
sub_aggregation: entry
.sub_aggregation
.into_final_result_internal(sub_aggregation_req, limits)?,
})
})
.collect::<crate::Result<Vec<_>>>()?;
Ok(BucketResult::Composite { after_key, buckets })
}
fn merge_fruits(&mut self, other: IntermediateCompositeBucketResult) -> crate::Result<()> {
merge_maps(&mut self.entries, other.entries)?;
if self.entries.len() as u32 > 2 * self.target_size {
self.trim()?;
}
Ok(())
}
/// Trim the composite buckets to the target size, according to the ordering.
pub(crate) fn trim(&mut self) -> crate::Result<()> {
if self.entries.len() as u32 <= self.target_size {
return Ok(());
}
let sorted_entries = trim_composite_buckets(
std::mem::take(&mut self.entries),
&self.orders,
self.target_size,
)?;
self.entries = sorted_entries.into_iter().collect();
Ok(())
}
}
fn trim_composite_buckets(
entries: FxHashMap<Vec<CompositeIntermediateKey>, IntermediateCompositeBucketEntry>,
orders: &[(Order, MissingOrder)],
target_size: u32,
) -> crate::Result<
Vec<(
Vec<CompositeIntermediateKey>,
IntermediateCompositeBucketEntry,
)>,
> {
let mut entries: Vec<_> = entries.into_iter().collect();
let mut sort_error: Option<TantivyError> = None;
entries.sort_by(|(left_key, _), (right_key, _)| {
if sort_error.is_some() {
return Ordering::Equal;
}
for idx in 0..orders.len() {
match composite_intermediate_key_ordering(
&left_key[idx],
&right_key[idx],
orders[idx].0,
orders[idx].1,
) {
Ok(ordering) if ordering != Ordering::Equal => return ordering,
Ok(_) => continue,
Err(err) => {
sort_error = Some(err);
break;
}
}
}
Ordering::Equal
});
if let Some(err) = sort_error {
return Err(err);
}
entries.truncate(target_size as usize);
Ok(entries)
}
#[cfg(test)]
mod tests {
use std::collections::HashMap;

View File

@@ -55,6 +55,12 @@ impl IntermediateAverage {
pub(crate) fn from_stats(stats: IntermediateStats) -> Self {
Self { stats }
}
/// Returns a reference to the underlying [`IntermediateStats`].
pub fn stats(&self) -> &IntermediateStats {
&self.stats
}
/// Merges the other intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateAverage) {
self.stats.merge_fruits(other.stats);

View File

@@ -1,12 +1,11 @@
use std::collections::hash_map::DefaultHasher;
use std::hash::{BuildHasher, Hasher};
use std::hash::Hash;
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{Column, ColumnType, Dictionary, StrColumn};
use common::f64_to_u64;
use hyperloglogplus::{HyperLogLog, HyperLogLogPlus};
use datasketches::hll::{HllSketch, HllType, HllUnion};
use rustc_hash::FxHashSet;
use serde::{Deserialize, Serialize};
use serde::{Deserialize, Deserializer, Serialize, Serializer};
use crate::aggregation::agg_data::AggregationsSegmentCtx;
use crate::aggregation::intermediate_agg_result::{
@@ -16,29 +15,17 @@ use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::*;
use crate::TantivyError;
#[derive(Clone, Debug, Serialize, Deserialize)]
struct BuildSaltedHasher {
salt: u8,
}
impl BuildHasher for BuildSaltedHasher {
type Hasher = DefaultHasher;
fn build_hasher(&self) -> Self::Hasher {
let mut hasher = DefaultHasher::new();
hasher.write_u8(self.salt);
hasher
}
}
/// Log2 of the number of registers for the HLL sketch.
/// 2^11 = 2048 registers, giving ~2.3% relative error and ~1KB per sketch (Hll4).
const LG_K: u8 = 11;
/// # Cardinality
///
/// The cardinality aggregation allows for computing an estimate
/// of the number of different values in a data set based on the
/// HyperLogLog++ algorithm. This is particularly useful for understanding the
/// uniqueness of values in a large dataset where counting each unique value
/// individually would be computationally expensive.
/// Apache DataSketches HyperLogLog algorithm. This is particularly useful for
/// understanding the uniqueness of values in a large dataset where counting
/// each unique value individually would be computationally expensive.
///
/// For example, you might use a cardinality aggregation to estimate the number
/// of unique visitors to a website by aggregating on a field that contains
@@ -184,7 +171,7 @@ impl SegmentCardinalityCollectorBucket {
term_ids.sort_unstable();
dict.sorted_ords_to_term_cb(term_ids.iter().map(|term| *term as u64), |term| {
self.cardinality.sketch.insert_any(&term);
self.cardinality.insert(term);
Ok(())
})?;
if has_missing {
@@ -195,17 +182,17 @@ impl SegmentCardinalityCollectorBucket {
);
match missing_key {
Key::Str(missing) => {
self.cardinality.sketch.insert_any(&missing);
self.cardinality.insert(missing.as_str());
}
Key::F64(val) => {
let val = f64_to_u64(*val);
self.cardinality.sketch.insert_any(&val);
self.cardinality.insert(val);
}
Key::U64(val) => {
self.cardinality.sketch.insert_any(&val);
self.cardinality.insert(*val);
}
Key::I64(val) => {
self.cardinality.sketch.insert_any(&val);
self.cardinality.insert(*val);
}
}
}
@@ -296,11 +283,11 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
})?;
for val in col_block_accessor.iter_vals() {
let val: u128 = compact_space_accessor.compact_to_u128(val as u32);
bucket.cardinality.sketch.insert_any(&val);
bucket.cardinality.insert(val);
}
} else {
for val in col_block_accessor.iter_vals() {
bucket.cardinality.sketch.insert_any(&val);
bucket.cardinality.insert(val);
}
}
@@ -321,11 +308,18 @@ impl SegmentAggregationCollector for SegmentCardinalityCollector {
}
}
#[derive(Clone, Debug, Serialize, Deserialize)]
/// The percentiles collector used during segment collection and for merging results.
#[derive(Clone, Debug)]
/// The cardinality collector used during segment collection and for merging results.
/// Uses Apache DataSketches HLL (lg_k=11, Hll4) for compact binary serialization
/// and cross-language compatibility (e.g. Java `datasketches` library).
pub struct CardinalityCollector {
sketch: HyperLogLogPlus<u64, BuildSaltedHasher>,
sketch: HllSketch,
/// Salt derived from `ColumnType`, used to differentiate values of different column types
/// that map to the same u64 (e.g. bool `false` = 0 vs i64 `0`).
/// Not serialized — only needed during insertion, not after sketch registers are populated.
salt: u8,
}
impl Default for CardinalityCollector {
fn default() -> Self {
Self::new(0)
@@ -338,25 +332,52 @@ impl PartialEq for CardinalityCollector {
}
}
impl CardinalityCollector {
/// Compute the final cardinality estimate.
pub fn finalize(self) -> Option<f64> {
Some(self.sketch.clone().count().trunc())
impl Serialize for CardinalityCollector {
fn serialize<S: Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
let bytes = self.sketch.serialize();
serializer.serialize_bytes(&bytes)
}
}
impl<'de> Deserialize<'de> for CardinalityCollector {
fn deserialize<D: Deserializer<'de>>(deserializer: D) -> Result<Self, D::Error> {
let bytes: Vec<u8> = Deserialize::deserialize(deserializer)?;
let sketch = HllSketch::deserialize(&bytes).map_err(serde::de::Error::custom)?;
Ok(Self { sketch, salt: 0 })
}
}
impl CardinalityCollector {
fn new(salt: u8) -> Self {
Self {
sketch: HyperLogLogPlus::new(16, BuildSaltedHasher { salt }).unwrap(),
sketch: HllSketch::new(LG_K, HllType::Hll4),
salt,
}
}
pub(crate) fn merge_fruits(&mut self, right: CardinalityCollector) -> crate::Result<()> {
self.sketch.merge(&right.sketch).map_err(|err| {
TantivyError::AggregationError(AggregationError::InternalError(format!(
"Error while merging cardinality {err:?}"
)))
})?;
/// Insert a value into the HLL sketch, salted by the column type.
/// The salt ensures that identical u64 values from different column types
/// (e.g. bool `false` vs i64 `0`) are counted as distinct.
pub(crate) fn insert<T: Hash>(&mut self, value: T) {
self.sketch.update((self.salt, value));
}
/// Compute the final cardinality estimate.
pub fn finalize(self) -> Option<f64> {
Some(self.sketch.estimate().trunc())
}
/// Serialize the HLL sketch to its compact binary representation.
/// The format is cross-language compatible with Apache DataSketches (Java, C++, Python).
pub fn to_sketch_bytes(&self) -> Vec<u8> {
self.sketch.serialize()
}
pub(crate) fn merge_fruits(&mut self, right: CardinalityCollector) -> crate::Result<()> {
let mut union = HllUnion::new(LG_K);
union.update(&self.sketch);
union.update(&right.sketch);
self.sketch = union.get_result(HllType::Hll4);
Ok(())
}
}
@@ -518,4 +539,75 @@ mod tests {
Ok(())
}
#[test]
fn cardinality_collector_serde_roundtrip() {
use super::CardinalityCollector;
let mut collector = CardinalityCollector::default();
collector.insert("hello");
collector.insert("world");
collector.insert("hello"); // duplicate
let serialized = serde_json::to_vec(&collector).unwrap();
let deserialized: CardinalityCollector = serde_json::from_slice(&serialized).unwrap();
let original_estimate = collector.finalize().unwrap();
let roundtrip_estimate = deserialized.finalize().unwrap();
assert_eq!(original_estimate, roundtrip_estimate);
assert_eq!(original_estimate, 2.0);
}
#[test]
fn cardinality_collector_merge() {
use super::CardinalityCollector;
let mut left = CardinalityCollector::default();
left.insert("a");
left.insert("b");
let mut right = CardinalityCollector::default();
right.insert("b");
right.insert("c");
left.merge_fruits(right).unwrap();
let estimate = left.finalize().unwrap();
assert_eq!(estimate, 3.0);
}
#[test]
fn cardinality_collector_serialize_deserialize_binary() {
use datasketches::hll::HllSketch;
use super::CardinalityCollector;
let mut collector = CardinalityCollector::default();
collector.insert("apple");
collector.insert("banana");
collector.insert("cherry");
let bytes = collector.to_sketch_bytes();
let deserialized = HllSketch::deserialize(&bytes).unwrap();
assert!((deserialized.estimate() - 3.0).abs() < 0.01);
}
#[test]
fn cardinality_collector_salt_differentiates_types() {
use super::CardinalityCollector;
// Without salt, same u64 value from different column types would collide
let mut collector_bool = CardinalityCollector::new(5); // e.g. ColumnType::Bool
collector_bool.insert(0u64); // false
collector_bool.insert(1u64); // true
let mut collector_i64 = CardinalityCollector::new(2); // e.g. ColumnType::I64
collector_i64.insert(0u64);
collector_i64.insert(1u64);
// Merge them
collector_bool.merge_fruits(collector_i64).unwrap();
let estimate = collector_bool.finalize().unwrap();
// Should be 4 because salt makes (5, 0) != (2, 0) and (5, 1) != (2, 1)
assert_eq!(estimate, 4.0);
}
}

View File

@@ -107,8 +107,11 @@ pub enum PercentileValues {
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
/// The entry when requesting percentiles with keyed: false
pub struct PercentileValuesVecEntry {
key: f64,
value: f64,
/// Percentile
pub key: f64,
/// Value at the percentile
pub value: f64,
}
/// Single-metric aggregations use this common result structure.

View File

@@ -222,6 +222,12 @@ impl PercentilesCollector {
self.sketch.add(val);
}
/// Encode the underlying DDSketch to Java-compatible binary format
/// for cross-language serialization with Java consumers.
pub fn to_sketch_bytes(&self) -> Vec<u8> {
self.sketch.to_java_bytes()
}
pub(crate) fn merge_fruits(&mut self, right: PercentilesCollector) -> crate::Result<()> {
self.sketch.merge(&right.sketch).map_err(|err| {
TantivyError::AggregationError(AggregationError::InternalError(format!(
@@ -325,7 +331,7 @@ mod tests {
use crate::aggregation::AggregationCollector;
use crate::query::AllQuery;
use crate::schema::{Schema, FAST};
use crate::Index;
use crate::{assert_nearly_equals, Index};
#[test]
fn test_aggregation_percentiles_empty_index() -> crate::Result<()> {
@@ -608,12 +614,16 @@ mod tests {
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"],
assert_nearly_equals!(
res["range_with_stats"]["buckets"][0]["percentiles"]["values"]["1.0"]
.as_f64()
.unwrap(),
5.0028295751107414
);
assert_eq!(
res["range_with_stats"]["buckets"][0]["percentiles"]["values"]["99.0"],
assert_nearly_equals!(
res["range_with_stats"]["buckets"][0]["percentiles"]["values"]["99.0"]
.as_f64()
.unwrap(),
10.07469668951144
);
@@ -659,8 +669,14 @@ mod tests {
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);
assert_nearly_equals!(
res["percentiles"]["values"]["1.0"].as_f64().unwrap(),
5.0028295751107414
);
assert_nearly_equals!(
res["percentiles"]["values"]["99.0"].as_f64().unwrap(),
10.07469668951144
);
Ok(())
}

View File

@@ -110,6 +110,16 @@ impl Default for IntermediateStats {
}
impl IntermediateStats {
/// Returns the number of values collected.
pub fn count(&self) -> u64 {
self.count
}
/// Returns the sum of all values collected.
pub fn sum(&self) -> f64 {
self.sum
}
/// Merges the other stats intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateStats) {
self.count += other.count;

View File

@@ -1,169 +0,0 @@
/// Codec specific to postings data.
pub mod postings;
/// Standard tantivy codec. This is the codec you use by default.
pub mod standard;
use std::io;
pub use standard::StandardCodec;
use crate::codec::postings::PostingsCodec;
use crate::fieldnorm::FieldNormReader;
use crate::postings::{Postings, TermInfo};
use crate::query::{box_scorer, Bm25Weight, Scorer};
use crate::schema::IndexRecordOption;
use crate::{DocId, InvertedIndexReader, Score};
/// Codecs describes how data is layed out on disk.
///
/// For the moment, only postings codec can be custom.
pub trait Codec: Clone + std::fmt::Debug + Send + Sync + 'static {
/// The specific postings type used by this codec.
type PostingsCodec: PostingsCodec;
/// Name of the codec. It should be unique to your codec.
const NAME: &'static str;
/// Load codec based on the codec configuration.
fn from_json_props(json_value: &serde_json::Value) -> crate::Result<Self>;
/// Get codec configuration.
fn to_json_props(&self) -> serde_json::Value;
/// Returns the postings codec.
fn postings_codec(&self) -> &Self::PostingsCodec;
}
/// Object-safe codec is a Codec that can be used in a trait object.
///
/// The point of it is to offer a way to use a codec without a proliferation of generics.
pub trait ObjectSafeCodec: 'static + Send + Sync {
/// Loads a type-erased Postings object for the given term.
///
/// If the schema used to build the index did not provide enough
/// information to match the requested `option`, a Postings is still
/// returned in a best-effort manner.
fn load_postings_type_erased(
&self,
term_info: &TermInfo,
option: IndexRecordOption,
inverted_index_reader: &InvertedIndexReader,
) -> io::Result<Box<dyn Postings>>;
/// Loads a type-erased TermScorer object for the given term.
///
/// If the schema used to build the index did not provide enough
/// information to match the requested `option`, a TermScorer is still
/// returned in a best-effort manner.
///
/// The point of this contraption is that the return TermScorer is backed,
/// not by Box<dyn Postings> but by the codec's concrete Postings type.
fn load_term_scorer_type_erased(
&self,
term_info: &TermInfo,
option: IndexRecordOption,
inverted_index_reader: &InvertedIndexReader,
fieldnorm_reader: FieldNormReader,
similarity_weight: Bm25Weight,
) -> io::Result<Box<dyn Scorer>>;
/// Loads a type-erased PhraseScorer object for the given term.
///
/// If the schema used to build the index did not provide enough
/// information to match the requested `option`, a TermScorer is still
/// returned in a best-effort manner.
///
/// The point of this contraption is that the return PhraseScorer is backed,
/// not by Box<dyn Postings> but by the codec's concrete Postings type.
fn new_phrase_scorer_type_erased(
&self,
term_infos: &[(usize, TermInfo)],
similarity_weight: Option<Bm25Weight>,
fieldnorm_reader: FieldNormReader,
slop: u32,
inverted_index_reader: &InvertedIndexReader,
) -> io::Result<Box<dyn Scorer>>;
/// Performs a for_each_pruning operation on the given scorer.
///
/// The function will go through matching documents and call the callback
/// function for all docs with a score exceeding the threshold.
///
/// The function itself will return a larger threshold value,
/// meant to update the threshold value.
///
/// If the codec and the scorer allow it, this function can rely on
/// optimizations like the block-max wand.
fn for_each_pruning(
&self,
threshold: Score,
scorer: Box<dyn Scorer>,
callback: &mut dyn FnMut(DocId, Score) -> Score,
);
}
impl<TCodec: Codec> ObjectSafeCodec for TCodec {
fn load_postings_type_erased(
&self,
term_info: &TermInfo,
option: IndexRecordOption,
inverted_index_reader: &InvertedIndexReader,
) -> io::Result<Box<dyn Postings>> {
let postings = inverted_index_reader
.read_postings_from_terminfo_specialized(term_info, option, self)?;
Ok(Box::new(postings))
}
fn load_term_scorer_type_erased(
&self,
term_info: &TermInfo,
option: IndexRecordOption,
inverted_index_reader: &InvertedIndexReader,
fieldnorm_reader: FieldNormReader,
similarity_weight: Bm25Weight,
) -> io::Result<Box<dyn Scorer>> {
let scorer = inverted_index_reader.new_term_scorer_specialized(
term_info,
option,
fieldnorm_reader,
similarity_weight,
self,
)?;
Ok(box_scorer(scorer))
}
fn new_phrase_scorer_type_erased(
&self,
term_infos: &[(usize, TermInfo)],
similarity_weight: Option<Bm25Weight>,
fieldnorm_reader: FieldNormReader,
slop: u32,
inverted_index_reader: &InvertedIndexReader,
) -> io::Result<Box<dyn Scorer>> {
let scorer = inverted_index_reader.new_phrase_scorer_type_specialized(
term_infos,
similarity_weight,
fieldnorm_reader,
slop,
self,
)?;
Ok(box_scorer(scorer))
}
fn for_each_pruning(
&self,
threshold: Score,
scorer: Box<dyn Scorer>,
callback: &mut dyn FnMut(DocId, Score) -> Score,
) {
let accerelerated_foreach_pruning_res =
<TCodec as Codec>::PostingsCodec::try_accelerated_for_each_pruning(
threshold, scorer, callback,
);
if let Err(mut scorer) = accerelerated_foreach_pruning_res {
// No acceleration available. We need to do things manually.
scorer.for_each_pruning(threshold, callback);
}
}
}

View File

@@ -1,119 +0,0 @@
use std::io;
/// Block-max WAND algorithm.
pub mod block_wand;
use common::OwnedBytes;
use crate::fieldnorm::FieldNormReader;
use crate::postings::Postings;
use crate::query::{Bm25Weight, Scorer};
use crate::schema::IndexRecordOption;
use crate::{DocId, Score};
/// Postings codec.
pub trait PostingsCodec: Send + Sync + 'static {
/// Serializer type for the postings codec.
type PostingsSerializer: PostingsSerializer;
/// Postings type for the postings codec.
type Postings: Postings + Clone;
/// Creates a new postings serializer.
fn new_serializer(
&self,
avg_fieldnorm: Score,
mode: IndexRecordOption,
fieldnorm_reader: Option<FieldNormReader>,
) -> Self::PostingsSerializer;
/// Loads postings
///
/// Record option is the option that was passed at indexing time.
/// Requested option is the option that is requested.
///
/// For instance, we may have term_freq in the posting list
/// but we can skip decompressing as we read the posting list.
///
/// If record option does not support the requested option,
/// this method does NOT return an error and will in fact restrict
/// requested_option to what is available.
fn load_postings(
&self,
doc_freq: u32,
postings_data: OwnedBytes,
record_option: IndexRecordOption,
requested_option: IndexRecordOption,
positions_data: Option<OwnedBytes>,
) -> io::Result<Self::Postings>;
/// If your codec supports different ways to accelerate `for_each_pruning` that's
/// where you should implement it.
///
/// Returning `Err(scorer)` without mutating the scorer nor calling the callback function,
/// is never "wrong". It just leaves the responsability to the caller to call a fallback
/// implementation on the scorer.
///
/// If your codec supports BlockMax-Wand, you just need to have your
/// postings implement `PostingsWithBlockMax` and copy what is done in the StandardPostings
/// codec to enable it.
fn try_accelerated_for_each_pruning(
_threshold: Score,
scorer: Box<dyn Scorer>,
_callback: &mut dyn FnMut(DocId, Score) -> Score,
) -> Result<(), Box<dyn Scorer>> {
Err(scorer)
}
}
/// A postings serializer is a listener that is in charge of serializing postings
///
/// IO is done only once per postings, once all of the data has been received.
/// A serializer will therefore contain internal buffers.
///
/// A serializer is created once and recycled for all postings.
///
/// Clients should use PostingsSerializer as follows.
/// ```
/// // First postings list
/// serializer.new_term(2, true);
/// serializer.write_doc(2, 1);
/// serializer.write_doc(6, 2);
/// serializer.close_term(3);
/// serializer.clear();
/// // Second postings list
/// serializer.new_term(1, true);
/// serializer.write_doc(3, 1);
/// serializer.close_term(3);
/// ```
pub trait PostingsSerializer {
/// The term_doc_freq here is the number of documents
/// in the postings lists.
///
/// It can be used to compute the idf that will be used for the
/// blockmax parameters.
///
/// If not available (e.g. if we do not collect `term_frequencies`
/// blockwand is disabled), the term_doc_freq passed will be set 0.
fn new_term(&mut self, term_doc_freq: u32, record_term_freq: bool);
/// Records a new document id for the current term.
/// The serializer may ignore it.
fn write_doc(&mut self, doc_id: DocId, term_freq: u32);
/// Closes the current term and writes the postings list associated.
fn close_term(&mut self, doc_freq: u32, wrt: &mut impl io::Write) -> io::Result<()>;
}
/// A light complement interface to Postings to allow block-max wand acceleration.
pub trait PostingsWithBlockMax: Postings {
/// Moves the postings to the block containign `target_doc` and returns
/// an upperbound of the score for documents in the block.
///
/// `Warning`: Calling this method may leave the postings in an invalid state.
/// callers are required to call seek before calling any other of the
/// `Postings` method (like doc / advance etc.).
fn seek_block_max(&mut self, target_doc: crate::DocId, similarity_weight: &Bm25Weight)
-> Score;
/// Returns the last document in the current block (or Terminated if this
/// is the last block).
fn last_doc_in_block(&self) -> crate::DocId;
}

View File

@@ -1,35 +0,0 @@
use serde::{Deserialize, Serialize};
use crate::codec::standard::postings::StandardPostingsCodec;
use crate::codec::Codec;
/// Tantivy's default postings codec.
pub mod postings;
/// Tantivy's default codec.
#[derive(Debug, Default, Clone, Serialize, Deserialize)]
pub struct StandardCodec;
impl Codec for StandardCodec {
type PostingsCodec = StandardPostingsCodec;
const NAME: &'static str = "standard";
fn from_json_props(json_value: &serde_json::Value) -> crate::Result<Self> {
if !json_value.is_null() {
return Err(crate::TantivyError::InvalidArgument(format!(
"Codec property for the StandardCodec are unexpected. expected null, got {}",
json_value.as_str().unwrap_or("null")
)));
}
Ok(StandardCodec)
}
fn to_json_props(&self) -> serde_json::Value {
serde_json::Value::Null
}
fn postings_codec(&self) -> &Self::PostingsCodec {
&StandardPostingsCodec
}
}

View File

@@ -1,50 +0,0 @@
use crate::postings::compression::COMPRESSION_BLOCK_SIZE;
use crate::DocId;
pub struct Block {
doc_ids: [DocId; COMPRESSION_BLOCK_SIZE],
term_freqs: [u32; COMPRESSION_BLOCK_SIZE],
len: usize,
}
impl Block {
pub fn new() -> Self {
Block {
doc_ids: [0u32; COMPRESSION_BLOCK_SIZE],
term_freqs: [0u32; COMPRESSION_BLOCK_SIZE],
len: 0,
}
}
pub fn doc_ids(&self) -> &[DocId] {
&self.doc_ids[..self.len]
}
pub fn term_freqs(&self) -> &[u32] {
&self.term_freqs[..self.len]
}
pub fn clear(&mut self) {
self.len = 0;
}
pub fn append_doc(&mut self, doc: DocId, term_freq: u32) {
let len = self.len;
self.doc_ids[len] = doc;
self.term_freqs[len] = term_freq;
self.len = len + 1;
}
pub fn is_full(&self) -> bool {
self.len == COMPRESSION_BLOCK_SIZE
}
pub fn is_empty(&self) -> bool {
self.len == 0
}
pub fn last_doc(&self) -> DocId {
assert_eq!(self.len, COMPRESSION_BLOCK_SIZE);
self.doc_ids[COMPRESSION_BLOCK_SIZE - 1]
}
}

View File

@@ -1,107 +0,0 @@
use std::io;
use crate::codec::postings::block_wand::{block_wand, block_wand_single_scorer};
use crate::codec::postings::PostingsCodec;
use crate::codec::standard::postings::block_segment_postings::BlockSegmentPostings;
pub use crate::codec::standard::postings::segment_postings::SegmentPostings;
use crate::fieldnorm::FieldNormReader;
use crate::positions::PositionReader;
use crate::query::term_query::TermScorer;
use crate::query::{BufferedUnionScorer, Scorer, SumCombiner};
use crate::schema::IndexRecordOption;
use crate::{DocSet as _, Score, TERMINATED};
mod block;
mod block_segment_postings;
mod segment_postings;
mod skip;
mod standard_postings_serializer;
pub use segment_postings::SegmentPostings as StandardPostings;
pub use standard_postings_serializer::StandardPostingsSerializer;
/// The default postings codec for tantivy.
pub struct StandardPostingsCodec;
#[expect(clippy::enum_variant_names)]
#[derive(Debug, PartialEq, Clone, Copy, Eq)]
pub(crate) enum FreqReadingOption {
NoFreq,
SkipFreq,
ReadFreq,
}
impl PostingsCodec for StandardPostingsCodec {
type PostingsSerializer = StandardPostingsSerializer;
type Postings = SegmentPostings;
fn new_serializer(
&self,
avg_fieldnorm: Score,
mode: IndexRecordOption,
fieldnorm_reader: Option<FieldNormReader>,
) -> Self::PostingsSerializer {
StandardPostingsSerializer::new(avg_fieldnorm, mode, fieldnorm_reader)
}
fn load_postings(
&self,
doc_freq: u32,
postings_data: common::OwnedBytes,
record_option: IndexRecordOption,
requested_option: IndexRecordOption,
positions_data_opt: Option<common::OwnedBytes>,
) -> io::Result<Self::Postings> {
// Rationalize record_option/requested_option.
let requested_option = requested_option.downgrade(record_option);
let block_segment_postings =
BlockSegmentPostings::open(doc_freq, postings_data, record_option, requested_option)?;
let position_reader = positions_data_opt.map(PositionReader::open).transpose()?;
Ok(SegmentPostings::from_block_postings(
block_segment_postings,
position_reader,
))
}
fn try_accelerated_for_each_pruning(
mut threshold: Score,
mut scorer: Box<dyn Scorer>,
callback: &mut dyn FnMut(crate::DocId, Score) -> Score,
) -> Result<(), Box<dyn Scorer>> {
scorer = match scorer.downcast::<TermScorer<Self::Postings>>() {
Ok(term_scorer) => {
block_wand_single_scorer(*term_scorer, threshold, callback);
return Ok(());
}
Err(scorer) => scorer,
};
let mut union_scorer =
scorer.downcast::<BufferedUnionScorer<Box<dyn Scorer>, SumCombiner>>()?;
if !union_scorer
.scorers()
.iter()
.all(|scorer| scorer.is::<TermScorer<Self::Postings>>())
{
return Err(union_scorer);
}
let doc = union_scorer.doc();
if doc == TERMINATED {
return Ok(());
}
let score = union_scorer.score();
if score > threshold {
threshold = callback(doc, score);
}
let boxed_scorers: Vec<Box<dyn Scorer>> = union_scorer.into_scorers();
let scorers: Vec<TermScorer<Self::Postings>> = boxed_scorers
.into_iter()
.map(|scorer| {
*scorer.downcast::<TermScorer<Self::Postings>>().ok().expect(
"Downcast failed despite the fact we already checked the type was correct",
)
})
.collect();
block_wand(scorers, threshold, callback);
Ok(())
}
}

View File

@@ -1,183 +0,0 @@
use std::cmp::Ordering;
use std::io::{self, Write as _};
use common::{BinarySerializable as _, VInt};
use crate::codec::postings::PostingsSerializer;
use crate::codec::standard::postings::block::Block;
use crate::codec::standard::postings::skip::SkipSerializer;
use crate::fieldnorm::FieldNormReader;
use crate::postings::compression::{BlockEncoder, VIntEncoder as _, COMPRESSION_BLOCK_SIZE};
use crate::query::Bm25Weight;
use crate::schema::IndexRecordOption;
use crate::{DocId, Score};
pub struct StandardPostingsSerializer {
last_doc_id_encoded: u32,
block_encoder: BlockEncoder,
block: Box<Block>,
postings_write: Vec<u8>,
skip_write: SkipSerializer,
mode: IndexRecordOption,
fieldnorm_reader: Option<FieldNormReader>,
bm25_weight: Option<Bm25Weight>,
avg_fieldnorm: Score, /* Average number of term in the field for that segment.
* this value is used to compute the block wand information. */
term_has_freq: bool,
}
impl StandardPostingsSerializer {
pub fn new(
avg_fieldnorm: Score,
mode: IndexRecordOption,
fieldnorm_reader: Option<FieldNormReader>,
) -> StandardPostingsSerializer {
Self {
last_doc_id_encoded: 0,
block_encoder: BlockEncoder::new(),
block: Box::new(Block::new()),
postings_write: Vec::new(),
skip_write: SkipSerializer::new(),
mode,
fieldnorm_reader,
bm25_weight: None,
avg_fieldnorm,
term_has_freq: false,
}
}
}
impl PostingsSerializer for StandardPostingsSerializer {
fn new_term(&mut self, term_doc_freq: u32, record_term_freq: bool) {
self.clear();
self.term_has_freq = self.mode.has_freq() && record_term_freq;
if !self.term_has_freq {
return;
}
let num_docs_in_segment: u64 =
if let Some(fieldnorm_reader) = self.fieldnorm_reader.as_ref() {
fieldnorm_reader.num_docs() as u64
} else {
return;
};
if num_docs_in_segment == 0 {
return;
}
self.bm25_weight = Some(Bm25Weight::for_one_term_without_explain(
term_doc_freq as u64,
num_docs_in_segment,
self.avg_fieldnorm,
));
}
fn write_doc(&mut self, doc_id: DocId, term_freq: u32) {
self.block.append_doc(doc_id, term_freq);
if self.block.is_full() {
self.write_block();
}
}
fn close_term(&mut self, doc_freq: u32, output_write: &mut impl io::Write) -> io::Result<()> {
if !self.block.is_empty() {
// we have doc ids waiting to be written
// this happens when the number of doc ids is
// not a perfect multiple of our block size.
//
// In that case, the remaining part is encoded
// using variable int encoding.
{
let block_encoded = self
.block_encoder
.compress_vint_sorted(self.block.doc_ids(), self.last_doc_id_encoded);
self.postings_write.write_all(block_encoded)?;
}
// ... Idem for term frequencies
if self.term_has_freq {
let block_encoded = self
.block_encoder
.compress_vint_unsorted(self.block.term_freqs());
self.postings_write.write_all(block_encoded)?;
}
self.block.clear();
}
if doc_freq >= COMPRESSION_BLOCK_SIZE as u32 {
let skip_data = self.skip_write.data();
VInt(skip_data.len() as u64).serialize(output_write)?;
output_write.write_all(skip_data)?;
}
output_write.write_all(&self.postings_write[..])?;
self.skip_write.clear();
self.postings_write.clear();
self.bm25_weight = None;
Ok(())
}
}
impl StandardPostingsSerializer {
fn clear(&mut self) {
self.bm25_weight = None;
self.block.clear();
self.last_doc_id_encoded = 0;
}
fn write_block(&mut self) {
{
// encode the doc ids
let (num_bits, block_encoded): (u8, &[u8]) = self
.block_encoder
.compress_block_sorted(self.block.doc_ids(), self.last_doc_id_encoded);
self.last_doc_id_encoded = self.block.last_doc();
self.skip_write
.write_doc(self.last_doc_id_encoded, num_bits);
// last el block 0, offset block 1,
self.postings_write.extend(block_encoded);
}
if self.term_has_freq {
let (num_bits, block_encoded): (u8, &[u8]) = self
.block_encoder
.compress_block_unsorted(self.block.term_freqs(), true);
self.postings_write.extend(block_encoded);
self.skip_write.write_term_freq(num_bits);
if self.mode.has_positions() {
// We serialize the sum of term freqs within the skip information
// in order to navigate through positions.
let sum_freq = self.block.term_freqs().iter().cloned().sum();
self.skip_write.write_total_term_freq(sum_freq);
}
let mut blockwand_params = (0u8, 0u32);
if let Some(bm25_weight) = self.bm25_weight.as_ref() {
if let Some(fieldnorm_reader) = self.fieldnorm_reader.as_ref() {
let docs = self.block.doc_ids().iter().cloned();
let term_freqs = self.block.term_freqs().iter().cloned();
let fieldnorms = docs.map(|doc| fieldnorm_reader.fieldnorm_id(doc));
blockwand_params = fieldnorms
.zip(term_freqs)
.max_by(
|(left_fieldnorm_id, left_term_freq),
(right_fieldnorm_id, right_term_freq)| {
let left_score =
bm25_weight.tf_factor(*left_fieldnorm_id, *left_term_freq);
let right_score =
bm25_weight.tf_factor(*right_fieldnorm_id, *right_term_freq);
left_score
.partial_cmp(&right_score)
.unwrap_or(Ordering::Equal)
},
)
.unwrap();
}
}
let (fieldnorm_id, term_freq) = blockwand_params;
self.skip_write.write_blockwand_max(fieldnorm_id, term_freq);
}
self.block.clear();
}
}

View File

@@ -486,9 +486,9 @@ mod tests {
use std::collections::BTreeSet;
use columnar::Dictionary;
use rand::distributions::Uniform;
use rand::distr::Uniform;
use rand::prelude::SliceRandom;
use rand::{thread_rng, Rng};
use rand::{rng, Rng};
use super::{FacetCollector, FacetCounts};
use crate::collector::facet_collector::compress_mapping;
@@ -731,7 +731,7 @@ mod tests {
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let uniform = Uniform::new_inclusive(1, 100_000);
let uniform = Uniform::new_inclusive(1, 100_000).unwrap();
let mut docs: Vec<TantivyDocument> =
vec![("a", 10), ("b", 100), ("c", 7), ("d", 12), ("e", 21)]
.into_iter()
@@ -741,14 +741,11 @@ mod tests {
std::iter::repeat_n(doc, count)
})
.map(|mut doc| {
doc.add_facet(
facet_field,
&format!("/facet/{}", thread_rng().sample(uniform)),
);
doc.add_facet(facet_field, &format!("/facet/{}", rng().sample(uniform)));
doc
})
.collect();
docs[..].shuffle(&mut thread_rng());
docs[..].shuffle(&mut rng());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
for doc in docs {
@@ -822,8 +819,8 @@ mod tests {
#[cfg(all(test, feature = "unstable"))]
mod bench {
use rand::rng;
use rand::seq::SliceRandom;
use rand::thread_rng;
use test::Bencher;
use crate::collector::FacetCollector;
@@ -846,7 +843,7 @@ mod bench {
}
}
// 40425 docs
docs[..].shuffle(&mut thread_rng());
docs[..].shuffle(&mut rng());
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
for doc in docs {

View File

@@ -1,4 +1,5 @@
mod order;
mod sort_by_bytes;
mod sort_by_erased_type;
mod sort_by_score;
mod sort_by_static_fast_value;
@@ -6,6 +7,7 @@ mod sort_by_string;
mod sort_key_computer;
pub use order::*;
pub use sort_by_bytes::SortByBytes;
pub use sort_by_erased_type::SortByErasedType;
pub use sort_by_score::SortBySimilarityScore;
pub use sort_by_static_fast_value::SortByStaticFastValue;

View File

@@ -0,0 +1,168 @@
use columnar::BytesColumn;
use crate::collector::sort_key::NaturalComparator;
use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
use crate::termdict::TermOrdinal;
use crate::{DocId, Score};
/// Sort by the first value of a bytes column.
///
/// If the field is multivalued, only the first value is considered.
///
/// Documents that do not have this value are still considered.
/// Their sort key will simply be `None`.
#[derive(Debug, Clone)]
pub struct SortByBytes {
column_name: String,
}
impl SortByBytes {
/// Creates a new sort by bytes sort key computer.
pub fn for_field(column_name: impl ToString) -> Self {
SortByBytes {
column_name: column_name.to_string(),
}
}
}
impl SortKeyComputer for SortByBytes {
type SortKey = Option<Vec<u8>>;
type Child = ByBytesColumnSegmentSortKeyComputer;
type Comparator = NaturalComparator;
fn segment_sort_key_computer(
&self,
segment_reader: &crate::SegmentReader,
) -> crate::Result<Self::Child> {
let bytes_column_opt = segment_reader.fast_fields().bytes(&self.column_name)?;
Ok(ByBytesColumnSegmentSortKeyComputer { bytes_column_opt })
}
}
/// Segment-level sort key computer for bytes columns.
pub struct ByBytesColumnSegmentSortKeyComputer {
bytes_column_opt: Option<BytesColumn>,
}
impl SegmentSortKeyComputer for ByBytesColumnSegmentSortKeyComputer {
type SortKey = Option<Vec<u8>>;
type SegmentSortKey = Option<TermOrdinal>;
type SegmentComparator = NaturalComparator;
#[inline(always)]
fn segment_sort_key(&mut self, doc: DocId, _score: Score) -> Option<TermOrdinal> {
let bytes_column = self.bytes_column_opt.as_ref()?;
bytes_column.ords().first(doc)
}
fn convert_segment_sort_key(&self, term_ord_opt: Option<TermOrdinal>) -> Option<Vec<u8>> {
// TODO: Individual lookups to the dictionary like this are very likely to repeatedly
// decompress the same blocks. See https://github.com/quickwit-oss/tantivy/issues/2776
let term_ord = term_ord_opt?;
let bytes_column = self.bytes_column_opt.as_ref()?;
let mut bytes = Vec::new();
bytes_column
.dictionary()
.ord_to_term(term_ord, &mut bytes)
.ok()?;
Some(bytes)
}
}
#[cfg(test)]
mod tests {
use super::SortByBytes;
use crate::collector::TopDocs;
use crate::query::AllQuery;
use crate::schema::{BytesOptions, Schema, FAST, INDEXED};
use crate::{Index, IndexWriter, Order, TantivyDocument};
#[test]
fn test_sort_by_bytes_asc() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let bytes_field = schema_builder
.add_bytes_field("data", BytesOptions::default().set_fast().set_indexed());
let id_field = schema_builder.add_u64_field("id", FAST | INDEXED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests()?;
// Insert documents with byte values in non-sorted order
let test_data: Vec<(u64, Vec<u8>)> = vec![
(1, vec![0x02, 0x00]),
(2, vec![0x00, 0x10]),
(3, vec![0x01, 0x00]),
(4, vec![0x00, 0x20]),
];
for (id, bytes) in &test_data {
let mut doc = TantivyDocument::new();
doc.add_u64(id_field, *id);
doc.add_bytes(bytes_field, bytes);
index_writer.add_document(doc)?;
}
index_writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
// Sort ascending by bytes
let top_docs =
TopDocs::with_limit(10).order_by((SortByBytes::for_field("data"), Order::Asc));
let results: Vec<(Option<Vec<u8>>, _)> = searcher.search(&AllQuery, &top_docs)?;
// Expected order: [0x00,0x10], [0x00,0x20], [0x01,0x00], [0x02,0x00]
let sorted_bytes: Vec<Option<Vec<u8>>> = results.into_iter().map(|(b, _)| b).collect();
assert_eq!(
sorted_bytes,
vec![
Some(vec![0x00, 0x10]),
Some(vec![0x00, 0x20]),
Some(vec![0x01, 0x00]),
Some(vec![0x02, 0x00]),
]
);
Ok(())
}
#[test]
fn test_sort_by_bytes_desc() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let bytes_field = schema_builder
.add_bytes_field("data", BytesOptions::default().set_fast().set_indexed());
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer: IndexWriter = index.writer_for_tests()?;
let test_data: Vec<Vec<u8>> = vec![vec![0x00, 0x10], vec![0x02, 0x00], vec![0x01, 0x00]];
for bytes in &test_data {
let mut doc = TantivyDocument::new();
doc.add_bytes(bytes_field, bytes);
index_writer.add_document(doc)?;
}
index_writer.commit()?;
let reader = index.reader()?;
let searcher = reader.searcher();
// Sort descending by bytes
let top_docs =
TopDocs::with_limit(10).order_by((SortByBytes::for_field("data"), Order::Desc));
let results: Vec<(Option<Vec<u8>>, _)> = searcher.search(&AllQuery, &top_docs)?;
// Expected order (descending): [0x02,0x00], [0x01,0x00], [0x00,0x10]
let sorted_bytes: Vec<Option<Vec<u8>>> = results.into_iter().map(|(b, _)| b).collect();
assert_eq!(
sorted_bytes,
vec![
Some(vec![0x02, 0x00]),
Some(vec![0x01, 0x00]),
Some(vec![0x00, 0x10]),
]
);
Ok(())
}
}

View File

@@ -1,7 +1,7 @@
use columnar::{ColumnType, MonotonicallyMappableToU64};
use crate::collector::sort_key::{
NaturalComparator, SortBySimilarityScore, SortByStaticFastValue, SortByString,
NaturalComparator, SortByBytes, SortBySimilarityScore, SortByStaticFastValue, SortByString,
};
use crate::collector::{SegmentSortKeyComputer, SortKeyComputer};
use crate::fastfield::FastFieldNotAvailableError;
@@ -114,6 +114,16 @@ impl SortKeyComputer for SortByErasedType {
},
})
}
ColumnType::Bytes => {
let computer = SortByBytes::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
Box::new(ErasedSegmentSortKeyComputerWrapper {
inner,
converter: |val: Option<Vec<u8>>| {
val.map(OwnedValue::Bytes).unwrap_or(OwnedValue::Null)
},
})
}
ColumnType::U64 => {
let computer = SortByStaticFastValue::<u64>::for_field(column_name);
let inner = computer.segment_sort_key_computer(segment_reader)?;
@@ -281,6 +291,65 @@ mod tests {
);
}
#[test]
fn test_sort_by_owned_bytes() {
let mut schema_builder = Schema::builder();
let data_field = schema_builder.add_bytes_field("data", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut writer = index.writer_for_tests().unwrap();
writer
.add_document(doc!(data_field => vec![0x03u8, 0x00]))
.unwrap();
writer
.add_document(doc!(data_field => vec![0x01u8, 0x00]))
.unwrap();
writer
.add_document(doc!(data_field => vec![0x02u8, 0x00]))
.unwrap();
writer.add_document(doc!()).unwrap();
writer.commit().unwrap();
let reader = index.reader().unwrap();
let searcher = reader.searcher();
// Sort descending (Natural - highest first)
let collector = TopDocs::with_limit(10)
.order_by((SortByErasedType::for_field("data"), ComparatorEnum::Natural));
let top_docs = searcher.search(&AllQuery, &collector).unwrap();
let values: Vec<OwnedValue> = top_docs.into_iter().map(|(key, _)| key).collect();
assert_eq!(
values,
vec![
OwnedValue::Bytes(vec![0x03, 0x00]),
OwnedValue::Bytes(vec![0x02, 0x00]),
OwnedValue::Bytes(vec![0x01, 0x00]),
OwnedValue::Null
]
);
// Sort ascending (ReverseNoneLower - lowest first, nulls last)
let collector = TopDocs::with_limit(10).order_by((
SortByErasedType::for_field("data"),
ComparatorEnum::ReverseNoneLower,
));
let top_docs = searcher.search(&AllQuery, &collector).unwrap();
let values: Vec<OwnedValue> = top_docs.into_iter().map(|(key, _)| key).collect();
assert_eq!(
values,
vec![
OwnedValue::Bytes(vec![0x01, 0x00]),
OwnedValue::Bytes(vec![0x02, 0x00]),
OwnedValue::Bytes(vec![0x03, 0x00]),
OwnedValue::Null
]
);
}
#[test]
fn test_sort_by_owned_reverse() {
let mut schema_builder = Schema::builder();

View File

@@ -160,7 +160,7 @@ mod tests {
expected: &[(crate::Score, usize)],
) {
let mut vals: Vec<(crate::Score, usize)> = (0..10).map(|val| (val as f32, val)).collect();
vals.shuffle(&mut rand::thread_rng());
vals.shuffle(&mut rand::rng());
let vals_merged = merge_top_k(vals.into_iter(), doc_range, ComparatorEnum::from(order));
assert_eq!(&vals_merged, expected);
}

View File

@@ -4,7 +4,7 @@ use common::{replace_in_place, JsonPathWriter};
use rustc_hash::FxHashMap;
use crate::indexer::indexing_term::IndexingTerm;
use crate::postings::{IndexingContext, IndexingPosition, PostingsWriter as _, PostingsWriterEnum};
use crate::postings::{IndexingContext, IndexingPosition, PostingsWriter};
use crate::schema::document::{ReferenceValue, ReferenceValueLeaf, Value};
use crate::schema::{Type, DATE_TIME_PRECISION_INDEXED};
use crate::time::format_description::well_known::Rfc3339;
@@ -80,7 +80,7 @@ fn index_json_object<'a, V: Value<'a>>(
text_analyzer: &mut TextAnalyzer,
term_buffer: &mut IndexingTerm,
json_path_writer: &mut JsonPathWriter,
postings_writer: &mut PostingsWriterEnum,
postings_writer: &mut dyn PostingsWriter,
ctx: &mut IndexingContext,
positions_per_path: &mut IndexingPositionsPerPath,
) {
@@ -110,7 +110,7 @@ pub(crate) fn index_json_value<'a, V: Value<'a>>(
text_analyzer: &mut TextAnalyzer,
term_buffer: &mut IndexingTerm,
json_path_writer: &mut JsonPathWriter,
postings_writer: &mut PostingsWriterEnum,
postings_writer: &mut dyn PostingsWriter,
ctx: &mut IndexingContext,
positions_per_path: &mut IndexingPositionsPerPath,
) {

View File

@@ -676,7 +676,7 @@ mod tests {
let num_segments = reader.searcher().segment_readers().len();
assert!(num_segments <= 4);
let num_components_except_deletes_and_tempstore =
crate::index::SegmentComponent::iterator().len() - 2;
crate::index::SegmentComponent::iterator().len() - 1;
let max_num_mmapped = num_components_except_deletes_and_tempstore * num_segments;
assert_eventually(|| {
let num_mmapped = mmap_directory.get_cache_info().mmapped.len();

View File

@@ -21,7 +21,7 @@ use std::path::PathBuf;
pub use common::file_slice::{FileHandle, FileSlice};
pub use common::{AntiCallToken, OwnedBytes, TerminatingWrite};
pub(crate) use self::composite_file::{CompositeFile, CompositeWrite};
pub use self::composite_file::{CompositeFile, CompositeWrite};
pub use self::directory::{Directory, DirectoryClone, DirectoryLock};
pub use self::directory_lock::{Lock, INDEX_WRITER_LOCK, META_LOCK};
pub use self::ram_directory::RamDirectory;
@@ -52,7 +52,7 @@ pub use self::mmap_directory::MmapDirectory;
///
/// `WritePtr` are required to implement both Write
/// and Seek.
pub type WritePtr = BufWriter<Box<dyn TerminatingWrite>>;
pub type WritePtr = BufWriter<Box<dyn TerminatingWrite + Send + Sync>>;
#[cfg(test)]
mod tests;

View File

@@ -1,7 +1,5 @@
use std::borrow::{Borrow, BorrowMut};
use common::BitSet;
use crate::fastfield::AliveBitSet;
use crate::DocId;
@@ -53,31 +51,55 @@ pub trait DocSet: Send {
doc
}
/// Seeks to the target if possible and returns true if the target is in the DocSet.
/// !!!Dragons ahead!!!
/// In spirit, this is an approximate and dangerous version of `seek`.
///
/// It can leave the DocSet in an `invalid` state and might return a
/// lower bound of what the result of Seek would have been.
///
///
/// More accurately it returns either:
/// - Found if the target is in the docset. In that case, the DocSet is left in a valid state.
/// - SeekLowerBound(seek_lower_bound) if the target is not in the docset. In that case, The
/// DocSet can be the left in a invalid state. The DocSet should then only receives call to
/// `seek_danger(..)` until it returns `Found`, and get back to a valid state.
///
/// `seek_lower_bound` can be any `DocId` (in the docset or not) as long as it is in
/// `(target .. seek_result] U {TERMINATED}` where `seek_result` is the first document in the
/// docset greater than to `target`.
///
/// `seek_danger` may return `SeekLowerBound(TERMINATED)`.
///
/// Calling `seek_danger` with TERMINATED as a target is allowed,
/// and should always return NewTarget(TERMINATED) or anything larger as TERMINATED is NOT in
/// the DocSet.
///
/// DocSets that already have an efficient `seek` method don't need to implement
/// `seek_into_the_danger_zone`. All wrapper DocSets should forward
/// `seek_into_the_danger_zone` to the underlying DocSet.
/// `seek_danger`.
///
/// ## API Behaviour
/// If `seek_into_the_danger_zone` is returning true, a call to `doc()` has to return target.
/// If `seek_into_the_danger_zone` is returning false, a call to `doc()` may return any doc
/// between the last doc that matched and target or a doc that is a valid next hit after
/// target. The DocSet is considered to be in an invalid state until
/// `seek_into_the_danger_zone` returns true again.
///
/// `target` needs to be equal or larger than `doc` when in a valid state.
///
/// Consecutive calls are not allowed to have decreasing `target` values.
///
/// # Warning
/// This is an advanced API used by intersection. The API contract is tricky, avoid using it.
fn seek_into_the_danger_zone(&mut self, target: DocId) -> bool {
let current_doc = self.doc();
if current_doc < target {
self.seek(target);
/// Consecutive calls to seek_danger are guaranteed to have strictly increasing `target`
/// values.
fn seek_danger(&mut self, target: DocId) -> SeekDangerResult {
if target >= TERMINATED {
debug_assert!(target == TERMINATED);
// No need to advance.
return SeekDangerResult::SeekLowerBound(target);
}
// The default implementation does not include any
// `danger zone` behavior.
//
// It does not leave the scorer in an invalid state.
// For this reason, we can safely call `self.doc()`.
let mut doc = self.doc();
if doc < target {
doc = self.seek(target);
}
if doc == target {
SeekDangerResult::Found
} else {
SeekDangerResult::SeekLowerBound(doc)
}
self.doc() == target
}
/// Fills a given mutable buffer with the next doc ids from the
@@ -108,15 +130,6 @@ pub trait DocSet: Send {
buffer.len()
}
/// TODO comment on the size of the bitset
fn fill_bitset(&mut self, bitset: &mut BitSet) {
let mut doc = self.doc();
while doc != TERMINATED {
bitset.insert(doc);
doc = self.advance();
}
}
/// Returns the current document
/// Right after creating a new `DocSet`, the docset points to the first document.
///
@@ -177,6 +190,17 @@ pub trait DocSet: Send {
}
}
#[derive(Clone, Copy, Debug, PartialEq, Eq)]
pub enum SeekDangerResult {
/// The target was found in the DocSet.
Found,
/// The target was not found in the DocSet.
/// We return a range in which the value could be.
/// The given target can be any DocId, that is <= than the first document
/// in the docset after the target.
SeekLowerBound(DocId),
}
impl DocSet for &mut dyn DocSet {
fn advance(&mut self) -> u32 {
(**self).advance()
@@ -186,8 +210,8 @@ impl DocSet for &mut dyn DocSet {
(**self).seek(target)
}
fn seek_into_the_danger_zone(&mut self, target: DocId) -> bool {
(**self).seek_into_the_danger_zone(target)
fn seek_danger(&mut self, target: DocId) -> SeekDangerResult {
(**self).seek_danger(target)
}
fn doc(&self) -> u32 {
@@ -222,9 +246,9 @@ impl<TDocSet: DocSet + ?Sized> DocSet for Box<TDocSet> {
unboxed.seek(target)
}
fn seek_into_the_danger_zone(&mut self, target: DocId) -> bool {
fn seek_danger(&mut self, target: DocId) -> SeekDangerResult {
let unboxed: &mut TDocSet = self.borrow_mut();
unboxed.seek_into_the_danger_zone(target)
unboxed.seek_danger(target)
}
fn fill_buffer(&mut self, buffer: &mut [DocId; COLLECT_BLOCK_BUFFER_LEN]) -> usize {

View File

@@ -162,7 +162,7 @@ mod tests {
mod bench {
use rand::prelude::IteratorRandom;
use rand::thread_rng;
use rand::rng;
use test::Bencher;
use super::AliveBitSet;
@@ -176,7 +176,7 @@ mod bench {
}
fn remove_rand(raw: &mut Vec<u32>) {
let i = (0..raw.len()).choose(&mut thread_rng()).unwrap();
let i = (0..raw.len()).choose(&mut rng()).unwrap();
raw.remove(i);
}

View File

@@ -879,7 +879,7 @@ mod tests {
const ONE_HOUR_IN_MICROSECS: i64 = 3_600 * 1_000_000;
let times: Vec<DateTime> = std::iter::repeat_with(|| {
// +- One hour.
let t = T0 + rng.gen_range(-ONE_HOUR_IN_MICROSECS..ONE_HOUR_IN_MICROSECS);
let t = T0 + rng.random_range(-ONE_HOUR_IN_MICROSECS..ONE_HOUR_IN_MICROSECS);
DateTime::from_timestamp_micros(t)
})
.take(1_000)

View File

@@ -1,6 +1,6 @@
use std::collections::HashSet;
use rand::{thread_rng, Rng};
use rand::{rng, Rng};
use crate::indexer::index_writer::MEMORY_BUDGET_NUM_BYTES_MIN;
use crate::schema::*;
@@ -29,7 +29,7 @@ fn test_functional_store() -> crate::Result<()> {
let index = Index::create_in_ram(schema);
let reader = index.reader()?;
let mut rng = thread_rng();
let mut rng = rng();
let mut index_writer: IndexWriter =
index.writer_with_num_threads(3, 3 * MEMORY_BUDGET_NUM_BYTES_MIN)?;
@@ -38,9 +38,9 @@ fn test_functional_store() -> crate::Result<()> {
let mut doc_id = 0u64;
for _iteration in 0..get_num_iterations() {
let num_docs: usize = rng.gen_range(0..4);
let num_docs: usize = rng.random_range(0..4);
if !doc_set.is_empty() {
let doc_to_remove_id = rng.gen_range(0..doc_set.len());
let doc_to_remove_id = rng.random_range(0..doc_set.len());
let removed_doc_id = doc_set.swap_remove(doc_to_remove_id);
index_writer.delete_term(Term::from_field_u64(id_field, removed_doc_id));
}
@@ -70,10 +70,10 @@ const LOREM: &str = "Doc Lorem ipsum dolor sit amet, consectetur adipiscing elit
cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat \
non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.";
fn get_text() -> String {
use rand::seq::SliceRandom;
let mut rng = thread_rng();
use rand::seq::IndexedRandom;
let mut rng = rng();
let tokens: Vec<_> = LOREM.split(' ').collect();
let random_val = rng.gen_range(0..20);
let random_val = rng.random_range(0..20);
(0..random_val)
.map(|_| tokens.choose(&mut rng).unwrap())
@@ -101,7 +101,7 @@ fn test_functional_indexing_unsorted() -> crate::Result<()> {
let index = Index::create_from_tempdir(schema)?;
let reader = index.reader()?;
let mut rng = thread_rng();
let mut rng = rng();
let mut index_writer: IndexWriter =
index.writer_with_num_threads(3, 3 * MEMORY_BUDGET_NUM_BYTES_MIN)?;
@@ -110,7 +110,7 @@ fn test_functional_indexing_unsorted() -> crate::Result<()> {
let mut uncommitted_docs: HashSet<u64> = HashSet::new();
for _ in 0..get_num_iterations() {
let random_val = rng.gen_range(0..20);
let random_val = rng.random_range(0..20);
if random_val == 0 {
index_writer.commit()?;
committed_docs.extend(&uncommitted_docs);

View File

@@ -1,38 +0,0 @@
use std::borrow::Cow;
use serde::{Deserialize, Serialize};
use crate::codec::{Codec, StandardCodec};
#[derive(Serialize, Deserialize, Clone, Debug)]
pub struct CodecConfiguration {
name: Cow<'static, str>,
#[serde(default, skip_serializing_if = "serde_json::Value::is_null")]
props: serde_json::Value,
}
impl CodecConfiguration {
pub fn from_codec<C: Codec>(codec: &C) -> Self {
CodecConfiguration {
name: Cow::Borrowed(C::NAME),
props: codec.to_json_props(),
}
}
pub fn to_codec<C: Codec>(&self) -> crate::Result<C> {
if self.name != C::NAME {
return Err(crate::TantivyError::InvalidArgument(format!(
"Codec name mismatch: expected {}, got {}",
C::NAME,
self.name
)));
}
C::from_json_props(&self.props)
}
}
impl Default for CodecConfiguration {
fn default() -> Self {
CodecConfiguration::from_codec(&StandardCodec)
}
}

View File

@@ -8,14 +8,12 @@ use std::thread::available_parallelism;
use super::segment::Segment;
use super::segment_reader::merge_field_meta_data;
use super::{FieldMetadata, IndexSettings};
use crate::codec::StandardCodec;
use crate::core::{Executor, META_FILEPATH};
use crate::directory::error::OpenReadError;
#[cfg(feature = "mmap")]
use crate::directory::MmapDirectory;
use crate::directory::{Directory, ManagedDirectory, RamDirectory, INDEX_WRITER_LOCK};
use crate::error::{DataCorruption, TantivyError};
use crate::index::codec_configuration::CodecConfiguration;
use crate::index::{IndexMeta, SegmentId, SegmentMeta, SegmentMetaInventory};
use crate::indexer::index_writer::{
IndexWriterOptions, MAX_NUM_THREAD, MEMORY_BUDGET_NUM_BYTES_MIN,
@@ -61,7 +59,6 @@ fn save_new_metas(
schema: Schema,
index_settings: IndexSettings,
directory: &dyn Directory,
codec: CodecConfiguration,
) -> crate::Result<()> {
save_metas(
&IndexMeta {
@@ -70,7 +67,6 @@ fn save_new_metas(
schema,
opstamp: 0u64,
payload: None,
codec,
},
directory,
)?;
@@ -105,21 +101,18 @@ fn save_new_metas(
/// };
/// let index = Index::builder().schema(schema).settings(settings).create_in_ram();
/// ```
pub struct IndexBuilder<Codec: crate::codec::Codec = StandardCodec> {
pub struct IndexBuilder {
schema: Option<Schema>,
index_settings: IndexSettings,
tokenizer_manager: TokenizerManager,
fast_field_tokenizer_manager: TokenizerManager,
codec: Codec,
}
impl Default for IndexBuilder<StandardCodec> {
impl Default for IndexBuilder {
fn default() -> Self {
IndexBuilder::new()
}
}
impl IndexBuilder<StandardCodec> {
impl IndexBuilder {
/// Creates a new `IndexBuilder`
pub fn new() -> Self {
Self {
@@ -127,21 +120,6 @@ impl IndexBuilder<StandardCodec> {
index_settings: IndexSettings::default(),
tokenizer_manager: TokenizerManager::default(),
fast_field_tokenizer_manager: TokenizerManager::default(),
codec: StandardCodec,
}
}
}
impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
/// Set the codec
#[must_use]
pub fn codec<NewCodec: crate::codec::Codec>(self, codec: NewCodec) -> IndexBuilder<NewCodec> {
IndexBuilder {
schema: self.schema,
index_settings: self.index_settings,
tokenizer_manager: self.tokenizer_manager,
fast_field_tokenizer_manager: self.fast_field_tokenizer_manager,
codec,
}
}
@@ -176,7 +154,7 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
/// The index will be allocated in anonymous memory.
/// This is useful for indexing small set of documents
/// for instances like unit test or temporary in memory index.
pub fn create_in_ram(self) -> Result<Index<Codec>, TantivyError> {
pub fn create_in_ram(self) -> Result<Index, TantivyError> {
let ram_directory = RamDirectory::create();
self.create(ram_directory)
}
@@ -187,7 +165,7 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
/// If a previous index was in this directory, it returns an
/// [`TantivyError::IndexAlreadyExists`] error.
#[cfg(feature = "mmap")]
pub fn create_in_dir<P: AsRef<Path>>(self, directory_path: P) -> crate::Result<Index<Codec>> {
pub fn create_in_dir<P: AsRef<Path>>(self, directory_path: P) -> crate::Result<Index> {
let mmap_directory: Box<dyn Directory> = Box::new(MmapDirectory::open(directory_path)?);
if Index::exists(&*mmap_directory)? {
return Err(TantivyError::IndexAlreadyExists);
@@ -208,7 +186,7 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
self,
dir: impl Into<Box<dyn Directory>>,
mem_budget: usize,
) -> crate::Result<SingleSegmentIndexWriter<Codec, D>> {
) -> crate::Result<SingleSegmentIndexWriter<D>> {
let index = self.create(dir)?;
let index_simple_writer = SingleSegmentIndexWriter::new(index, mem_budget)?;
Ok(index_simple_writer)
@@ -224,7 +202,7 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
/// For other unit tests, prefer the [`RamDirectory`], see:
/// [`IndexBuilder::create_in_ram()`].
#[cfg(feature = "mmap")]
pub fn create_from_tempdir(self) -> crate::Result<Index<Codec>> {
pub fn create_from_tempdir(self) -> crate::Result<Index> {
let mmap_directory: Box<dyn Directory> = Box::new(MmapDirectory::create_from_tempdir()?);
self.create(mmap_directory)
}
@@ -237,15 +215,12 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
}
/// Opens or creates a new index in the provided directory
pub fn open_or_create<T: Into<Box<dyn Directory>>>(
self,
dir: T,
) -> crate::Result<Index<Codec>> {
pub fn open_or_create<T: Into<Box<dyn Directory>>>(self, dir: T) -> crate::Result<Index> {
let dir: Box<dyn Directory> = dir.into();
if !Index::exists(&*dir)? {
return self.create(dir);
}
let mut index: Index<Codec> = Index::<Codec>::open_with_codec(dir)?;
let mut index = Index::open(dir)?;
index.set_tokenizers(self.tokenizer_manager.clone());
if index.schema() == self.get_expect_schema()? {
Ok(index)
@@ -269,25 +244,18 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
/// Creates a new index given an implementation of the trait `Directory`.
///
/// If a directory previously existed, it will be erased.
pub fn create<T: Into<Box<dyn Directory>>>(self, dir: T) -> crate::Result<Index<Codec>> {
self.create_avoid_monomorphization(dir.into())
}
fn create_avoid_monomorphization(self, dir: Box<dyn Directory>) -> crate::Result<Index<Codec>> {
fn create<T: Into<Box<dyn Directory>>>(self, dir: T) -> crate::Result<Index> {
self.validate()?;
let dir = dir.into();
let directory = ManagedDirectory::wrap(dir)?;
let codec: CodecConfiguration = CodecConfiguration::from_codec(&self.codec);
save_new_metas(
self.get_expect_schema()?,
self.index_settings.clone(),
&directory,
codec,
)?;
let schema = self.get_expect_schema()?;
let mut metas = IndexMeta::with_schema_and_codec(schema, &self.codec);
let mut metas = IndexMeta::with_schema(self.get_expect_schema()?);
metas.index_settings = self.index_settings;
let mut index: Index<Codec> =
Index::<Codec>::open_from_metas(directory, &metas, SegmentMetaInventory::default())?;
let mut index = Index::open_from_metas(directory, &metas, SegmentMetaInventory::default());
index.set_tokenizers(self.tokenizer_manager);
index.set_fast_field_tokenizers(self.fast_field_tokenizer_manager);
Ok(index)
@@ -296,7 +264,7 @@ impl<Codec: crate::codec::Codec> IndexBuilder<Codec> {
/// Search Index
#[derive(Clone)]
pub struct Index<Codec: crate::codec::Codec = crate::codec::StandardCodec> {
pub struct Index {
directory: ManagedDirectory,
schema: Schema,
settings: IndexSettings,
@@ -304,7 +272,6 @@ pub struct Index<Codec: crate::codec::Codec = crate::codec::StandardCodec> {
tokenizers: TokenizerManager,
fast_field_tokenizers: TokenizerManager,
inventory: SegmentMetaInventory,
codec: Codec,
}
impl Index {
@@ -312,6 +279,41 @@ impl Index {
pub fn builder() -> IndexBuilder {
IndexBuilder::new()
}
/// Examines the directory to see if it contains an index.
///
/// Effectively, it only checks for the presence of the `meta.json` file.
pub fn exists(dir: &dyn Directory) -> Result<bool, OpenReadError> {
dir.exists(&META_FILEPATH)
}
/// Accessor to the search executor.
///
/// This pool is used by default when calling `searcher.search(...)`
/// to perform search on the individual segments.
///
/// By default the executor is single thread, and simply runs in the calling thread.
pub fn search_executor(&self) -> &Executor {
&self.executor
}
/// Replace the default single thread search executor pool
/// by a thread pool with a given number of threads.
pub fn set_multithread_executor(&mut self, num_threads: usize) -> crate::Result<()> {
self.executor = Executor::multi_thread(num_threads, "tantivy-search-")?;
Ok(())
}
/// Custom thread pool by a outer thread pool.
pub fn set_executor(&mut self, executor: Executor) {
self.executor = executor;
}
/// Replace the default single thread search executor pool
/// by a thread pool with as many threads as there are CPUs on the system.
pub fn set_default_multithread_executor(&mut self) -> crate::Result<()> {
let default_num_threads = available_parallelism()?.get();
self.set_multithread_executor(default_num_threads)
}
/// Creates a new index using the [`RamDirectory`].
///
@@ -322,13 +324,6 @@ impl Index {
IndexBuilder::new().schema(schema).create_in_ram().unwrap()
}
/// Examines the directory to see if it contains an index.
///
/// Effectively, it only checks for the presence of the `meta.json` file.
pub fn exists(directory: &dyn Directory) -> Result<bool, OpenReadError> {
directory.exists(&META_FILEPATH)
}
/// Creates a new index in a given filepath.
/// The index will use the [`MmapDirectory`].
///
@@ -375,107 +370,20 @@ impl Index {
schema: Schema,
settings: IndexSettings,
) -> crate::Result<Index> {
Self::create_to_avoid_monomorphization(dir.into(), schema, settings)
}
fn create_to_avoid_monomorphization(
dir: Box<dyn Directory>,
schema: Schema,
settings: IndexSettings,
) -> crate::Result<Index> {
let dir: Box<dyn Directory> = dir.into();
let mut builder = IndexBuilder::new().schema(schema);
builder = builder.settings(settings);
builder.create(dir)
}
/// Opens a new directory from an index path.
#[cfg(feature = "mmap")]
pub fn open_in_dir<P: AsRef<Path>>(directory_path: P) -> crate::Result<Index> {
Self::open_in_dir_to_avoid_monomorphization(directory_path.as_ref())
}
#[inline(never)]
fn open_in_dir_to_avoid_monomorphization(directory_path: &Path) -> crate::Result<Index> {
let mmap_directory = MmapDirectory::open(directory_path)?;
Index::open(mmap_directory)
}
/// Open the index using the provided directory
pub fn open<T: Into<Box<dyn Directory>>>(directory: T) -> crate::Result<Index> {
Index::<StandardCodec>::open_with_codec(directory.into())
}
}
impl<Codec: crate::codec::Codec> Index<Codec> {
/// Returns a version of this index with the standard codec.
/// This is useful when you need to pass the index to APIs that
/// don't care about the codec (e.g., for reading).
pub(crate) fn with_standard_codec(&self) -> Index<StandardCodec> {
Index {
directory: self.directory.clone(),
schema: self.schema.clone(),
settings: self.settings.clone(),
executor: self.executor.clone(),
tokenizers: self.tokenizers.clone(),
fast_field_tokenizers: self.fast_field_tokenizers.clone(),
inventory: self.inventory.clone(),
codec: StandardCodec,
}
}
/// Open the index using the provided directory
#[inline(never)]
pub fn open_with_codec(directory: Box<dyn Directory>) -> crate::Result<Index<Codec>> {
let directory = ManagedDirectory::wrap(directory)?;
let inventory = SegmentMetaInventory::default();
let metas = load_metas(&directory, &inventory)?;
let index: Index<Codec> = Index::<Codec>::open_from_metas(directory, &metas, inventory)?;
Ok(index)
}
/// Accessor to the codec.
pub fn codec(&self) -> &Codec {
&self.codec
}
/// Accessor to the search executor.
///
/// This pool is used by default when calling `searcher.search(...)`
/// to perform search on the individual segments.
///
/// By default the executor is single thread, and simply runs in the calling thread.
pub fn search_executor(&self) -> &Executor {
&self.executor
}
/// Replace the default single thread search executor pool
/// by a thread pool with a given number of threads.
pub fn set_multithread_executor(&mut self, num_threads: usize) -> crate::Result<()> {
self.executor = Executor::multi_thread(num_threads, "tantivy-search-")?;
Ok(())
}
/// Custom thread pool by a outer thread pool.
pub fn set_executor(&mut self, executor: Executor) {
self.executor = executor;
}
/// Replace the default single thread search executor pool
/// by a thread pool with as many threads as there are CPUs on the system.
pub fn set_default_multithread_executor(&mut self) -> crate::Result<()> {
let default_num_threads = available_parallelism()?.get();
self.set_multithread_executor(default_num_threads)
}
/// Creates a new index given a directory and an [`IndexMeta`].
fn open_from_metas<C: crate::codec::Codec>(
fn open_from_metas(
directory: ManagedDirectory,
metas: &IndexMeta,
inventory: SegmentMetaInventory,
) -> crate::Result<Index<C>> {
) -> Index {
let schema = metas.schema.clone();
let codec = metas.codec.to_codec::<C>()?;
Ok(Index {
Index {
settings: metas.index_settings.clone(),
directory,
schema,
@@ -483,8 +391,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
fast_field_tokenizers: TokenizerManager::default(),
executor: Executor::single_thread(),
inventory,
codec,
})
}
}
/// Setter for the tokenizer manager.
@@ -540,7 +447,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
/// Create a default [`IndexReader`] for the given index.
///
/// See [`Index.reader_builder()`].
pub fn reader(&self) -> crate::Result<IndexReader<Codec>> {
pub fn reader(&self) -> crate::Result<IndexReader> {
self.reader_builder().try_into()
}
@@ -548,10 +455,17 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
///
/// Most project should create at most one reader for a given index.
/// This method is typically called only once per `Index` instance.
pub fn reader_builder(&self) -> IndexReaderBuilder<Codec> {
pub fn reader_builder(&self) -> IndexReaderBuilder {
IndexReaderBuilder::new(self.clone())
}
/// Opens a new directory from an index path.
#[cfg(feature = "mmap")]
pub fn open_in_dir<P: AsRef<Path>>(directory_path: P) -> crate::Result<Index> {
let mmap_directory = MmapDirectory::open(directory_path)?;
Index::open(mmap_directory)
}
/// Returns the list of the segment metas tracked by the index.
///
/// Such segments can of course be part of the index,
@@ -592,6 +506,16 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
self.inventory.new_segment_meta(segment_id, max_doc)
}
/// Open the index using the provided directory
pub fn open<T: Into<Box<dyn Directory>>>(directory: T) -> crate::Result<Index> {
let directory = directory.into();
let directory = ManagedDirectory::wrap(directory)?;
let inventory = SegmentMetaInventory::default();
let metas = load_metas(&directory, &inventory)?;
let index = Index::open_from_metas(directory, &metas, inventory);
Ok(index)
}
/// Reads the index meta file from the directory.
pub fn load_metas(&self) -> crate::Result<IndexMeta> {
load_metas(self.directory(), &self.inventory)
@@ -615,7 +539,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
pub fn writer_with_options<D: Document>(
&self,
options: IndexWriterOptions,
) -> crate::Result<IndexWriter<Codec, D>> {
) -> crate::Result<IndexWriter<D>> {
let directory_lock = self
.directory
.acquire_lock(&INDEX_WRITER_LOCK)
@@ -657,7 +581,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
&self,
num_threads: usize,
overall_memory_budget_in_bytes: usize,
) -> crate::Result<IndexWriter<Codec, D>> {
) -> crate::Result<IndexWriter<D>> {
let memory_arena_in_bytes_per_thread = overall_memory_budget_in_bytes / num_threads;
let options = IndexWriterOptions::builder()
.num_worker_threads(num_threads)
@@ -671,7 +595,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
/// That index writer only simply has a single thread and a memory budget of 15 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<Codec, D>> {
pub fn writer_for_tests<D: Document>(&self) -> crate::Result<IndexWriter<D>> {
self.writer_with_num_threads(1, MEMORY_BUDGET_NUM_BYTES_MIN)
}
@@ -689,7 +613,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
pub fn writer<D: Document>(
&self,
memory_budget_in_bytes: usize,
) -> crate::Result<IndexWriter<Codec, D>> {
) -> crate::Result<IndexWriter<D>> {
let mut num_threads = std::cmp::min(available_parallelism()?.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 {
@@ -716,7 +640,7 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
}
/// Returns the list of segments that are searchable
pub fn searchable_segments(&self) -> crate::Result<Vec<Segment<Codec>>> {
pub fn searchable_segments(&self) -> crate::Result<Vec<Segment>> {
Ok(self
.searchable_segment_metas()?
.into_iter()
@@ -725,12 +649,12 @@ impl<Codec: crate::codec::Codec> Index<Codec> {
}
#[doc(hidden)]
pub fn segment(&self, segment_meta: SegmentMeta) -> Segment<Codec> {
pub fn segment(&self, segment_meta: SegmentMeta) -> Segment {
Segment::for_index(self.clone(), segment_meta)
}
/// Creates a new segment.
pub fn new_segment(&self) -> Segment<Codec> {
pub fn new_segment(&self) -> Segment {
let segment_meta = self
.inventory
.new_segment_meta(SegmentId::generate_random(), 0);

View File

@@ -1,14 +1,11 @@
use std::collections::HashSet;
use std::fmt;
use std::path::PathBuf;
use std::sync::atomic::AtomicBool;
use std::sync::Arc;
use serde::{Deserialize, Serialize};
use super::SegmentComponent;
use crate::codec::Codec;
use crate::index::{CodecConfiguration, SegmentId};
use crate::index::SegmentId;
use crate::schema::Schema;
use crate::store::Compressor;
use crate::{Inventory, Opstamp, TrackedObject};
@@ -38,7 +35,6 @@ impl SegmentMetaInventory {
let inner = InnerSegmentMeta {
segment_id,
max_doc,
include_temp_doc_store: Arc::new(AtomicBool::new(true)),
deletes: None,
};
SegmentMeta::from(self.inventory.track(inner))
@@ -86,15 +82,6 @@ impl SegmentMeta {
self.tracked.segment_id
}
/// Removes the Component::TempStore from the alive list and
/// therefore marks the temp docstore file to be deleted by
/// the garbage collection.
pub fn untrack_temp_docstore(&self) {
self.tracked
.include_temp_doc_store
.store(false, std::sync::atomic::Ordering::Relaxed);
}
/// Returns the number of deleted documents.
pub fn num_deleted_docs(&self) -> u32 {
self.tracked
@@ -112,20 +99,9 @@ impl SegmentMeta {
/// is by removing all files that have been created by tantivy
/// and are not used by any segment anymore.
pub fn list_files(&self) -> HashSet<PathBuf> {
if self
.tracked
.include_temp_doc_store
.load(std::sync::atomic::Ordering::Relaxed)
{
SegmentComponent::iterator()
.map(|component| self.relative_path(*component))
.collect::<HashSet<PathBuf>>()
} else {
SegmentComponent::iterator()
.filter(|comp| *comp != &SegmentComponent::TempStore)
.map(|component| self.relative_path(*component))
.collect::<HashSet<PathBuf>>()
}
SegmentComponent::iterator()
.map(|component| self.relative_path(*component))
.collect::<HashSet<PathBuf>>()
}
/// Returns the relative path of a component of our segment.
@@ -139,7 +115,6 @@ impl SegmentMeta {
SegmentComponent::Positions => ".pos".to_string(),
SegmentComponent::Terms => ".term".to_string(),
SegmentComponent::Store => ".store".to_string(),
SegmentComponent::TempStore => ".store.temp".to_string(),
SegmentComponent::FastFields => ".fast".to_string(),
SegmentComponent::FieldNorms => ".fieldnorm".to_string(),
SegmentComponent::Delete => format!(".{}.del", self.delete_opstamp().unwrap_or(0)),
@@ -184,7 +159,6 @@ impl SegmentMeta {
segment_id: inner_meta.segment_id,
max_doc,
deletes: None,
include_temp_doc_store: Arc::new(AtomicBool::new(true)),
});
SegmentMeta { tracked }
}
@@ -203,7 +177,6 @@ impl SegmentMeta {
let tracked = self.tracked.map(move |inner_meta| InnerSegmentMeta {
segment_id: inner_meta.segment_id,
max_doc: inner_meta.max_doc,
include_temp_doc_store: Arc::new(AtomicBool::new(true)),
deletes: Some(delete_meta),
});
SegmentMeta { tracked }
@@ -215,14 +188,6 @@ struct InnerSegmentMeta {
segment_id: SegmentId,
max_doc: u32,
pub deletes: Option<DeleteMeta>,
/// If you want to avoid the SegmentComponent::TempStore file to be covered by
/// garbage collection and deleted, set this to true. This is used during merge.
#[serde(skip)]
#[serde(default = "default_temp_store")]
pub(crate) include_temp_doc_store: Arc<AtomicBool>,
}
fn default_temp_store() -> Arc<AtomicBool> {
Arc::new(AtomicBool::new(false))
}
impl InnerSegmentMeta {
@@ -321,8 +286,6 @@ pub struct IndexMeta {
/// This payload is entirely unused by tantivy.
#[serde(skip_serializing_if = "Option::is_none")]
pub payload: Option<String>,
/// Codec configuration for the index.
pub codec: CodecConfiguration,
}
#[derive(Deserialize, Debug)]
@@ -334,8 +297,6 @@ struct UntrackedIndexMeta {
pub opstamp: Opstamp,
#[serde(skip_serializing_if = "Option::is_none")]
pub payload: Option<String>,
#[serde(default)]
pub codec: CodecConfiguration,
}
impl UntrackedIndexMeta {
@@ -350,7 +311,6 @@ impl UntrackedIndexMeta {
schema: self.schema,
opstamp: self.opstamp,
payload: self.payload,
codec: self.codec,
}
}
}
@@ -361,14 +321,13 @@ impl IndexMeta {
///
/// This new index does not contains any segments.
/// Opstamp will the value `0u64`.
pub fn with_schema_and_codec<C: Codec>(schema: Schema, codec: &C) -> IndexMeta {
pub fn with_schema(schema: Schema) -> IndexMeta {
IndexMeta {
index_settings: IndexSettings::default(),
segments: vec![],
schema,
opstamp: 0u64,
payload: None,
codec: CodecConfiguration::from_codec(codec),
}
}
@@ -419,12 +378,11 @@ mod tests {
schema,
opstamp: 0u64,
payload: None,
codec: Default::default(),
};
let json = serde_json::ser::to_string(&index_metas).expect("serialization failed");
assert_eq!(
json,
r#"{"index_settings":{"docstore_compression":"none","docstore_blocksize":16384},"segments":[],"schema":[{"name":"text","type":"text","options":{"indexing":{"record":"position","fieldnorms":true,"tokenizer":"default"},"stored":false,"fast":false}}],"opstamp":0,"codec":{"name":"standard"}}"#
r#"{"index_settings":{"docstore_compression":"none","docstore_blocksize":16384},"segments":[],"schema":[{"name":"text","type":"text","options":{"indexing":{"record":"position","fieldnorms":true,"tokenizer":"default"},"stored":false,"fast":false}}],"opstamp":0}"#
);
let deser_meta: UntrackedIndexMeta = serde_json::from_str(&json).unwrap();

View File

@@ -1,8 +1,7 @@
use std::io;
use std::sync::Arc;
use common::json_path_writer::JSON_END_OF_PATH;
use common::{BinarySerializable, ByteCount, OwnedBytes};
use common::{BinarySerializable, ByteCount};
#[cfg(feature = "quickwit")]
use futures_util::{FutureExt, StreamExt, TryStreamExt};
#[cfg(feature = "quickwit")]
@@ -10,13 +9,9 @@ use itertools::Itertools;
#[cfg(feature = "quickwit")]
use tantivy_fst::automaton::{AlwaysMatch, Automaton};
use crate::codec::postings::PostingsCodec;
use crate::codec::{Codec, ObjectSafeCodec, StandardCodec};
use crate::directory::FileSlice;
use crate::fieldnorm::FieldNormReader;
use crate::postings::{Postings, TermInfo};
use crate::query::term_query::TermScorer;
use crate::query::{Bm25Weight, PhraseScorer, Scorer};
use crate::positions::PositionReader;
use crate::postings::{BlockSegmentPostings, SegmentPostings, TermInfo};
use crate::schema::{IndexRecordOption, Term, Type};
use crate::termdict::TermDictionary;
@@ -38,7 +33,6 @@ pub struct InvertedIndexReader {
positions_file_slice: FileSlice,
record_option: IndexRecordOption,
total_num_tokens: u64,
codec: Arc<dyn ObjectSafeCodec>,
}
/// Object that records the amount of space used by a field in an inverted index.
@@ -74,7 +68,6 @@ impl InvertedIndexReader {
postings_file_slice: FileSlice,
positions_file_slice: FileSlice,
record_option: IndexRecordOption,
codec: Arc<dyn ObjectSafeCodec>,
) -> io::Result<InvertedIndexReader> {
let (total_num_tokens_slice, postings_body) = postings_file_slice.split(8);
let total_num_tokens = u64::deserialize(&mut total_num_tokens_slice.read_bytes()?)?;
@@ -84,7 +77,6 @@ impl InvertedIndexReader {
positions_file_slice,
record_option,
total_num_tokens,
codec,
})
}
@@ -97,7 +89,6 @@ impl InvertedIndexReader {
positions_file_slice: FileSlice::empty(),
record_option,
total_num_tokens: 0u64,
codec: Arc::new(StandardCodec),
}
}
@@ -169,98 +160,61 @@ impl InvertedIndexReader {
Ok(fields)
}
pub(crate) fn new_term_scorer_specialized<C: Codec>(
&self,
term_info: &TermInfo,
option: IndexRecordOption,
fieldnorm_reader: FieldNormReader,
similarity_weight: Bm25Weight,
codec: &C,
) -> io::Result<TermScorer<<<C as Codec>::PostingsCodec as PostingsCodec>::Postings>> {
let postings = self.read_postings_from_terminfo_specialized(term_info, option, codec)?;
let term_scorer = TermScorer::new(postings, fieldnorm_reader, similarity_weight);
Ok(term_scorer)
}
pub(crate) fn new_phrase_scorer_type_specialized<C: Codec>(
&self,
term_infos: &[(usize, TermInfo)],
similarity_weight_opt: Option<Bm25Weight>,
fieldnorm_reader: FieldNormReader,
slop: u32,
codec: &C,
) -> io::Result<PhraseScorer<<<C as Codec>::PostingsCodec as PostingsCodec>::Postings>> {
let mut offset_and_term_postings: Vec<(
usize,
<<C as Codec>::PostingsCodec as PostingsCodec>::Postings,
)> = Vec::with_capacity(term_infos.len());
for (offset, term_info) in term_infos {
let postings = self.read_postings_from_terminfo_specialized(
term_info,
IndexRecordOption::WithFreqsAndPositions,
codec,
)?;
offset_and_term_postings.push((*offset, postings));
}
let phrase_scorer = PhraseScorer::new(
offset_and_term_postings,
similarity_weight_opt,
fieldnorm_reader,
slop,
);
Ok(phrase_scorer)
}
/// Build a new term scorer.
pub fn new_term_scorer(
&self,
term_info: &TermInfo,
option: IndexRecordOption,
fieldnorm_reader: FieldNormReader,
similarity_weight: Bm25Weight,
) -> io::Result<Box<dyn Scorer>> {
let term_scorer = self.codec.load_term_scorer_type_erased(
term_info,
option,
self,
fieldnorm_reader,
similarity_weight,
)?;
Ok(term_scorer)
}
/// Returns a postings object specific with a concrete type.
/// Resets the block segment to another position of the postings
/// file.
///
/// This requires you to provied the actual codec.
pub fn read_postings_from_terminfo_specialized<C: Codec>(
/// This is useful for enumerating through a list of terms,
/// and consuming the associated posting lists while avoiding
/// reallocating a [`BlockSegmentPostings`].
///
/// # Warning
///
/// This does not reset the positions list.
pub fn reset_block_postings_from_terminfo(
&self,
term_info: &TermInfo,
block_postings: &mut BlockSegmentPostings,
) -> io::Result<()> {
let postings_slice = self
.postings_file_slice
.slice(term_info.postings_range.clone());
let postings_bytes = postings_slice.read_bytes()?;
block_postings.reset(term_info.doc_freq, postings_bytes)?;
Ok(())
}
/// Returns a block postings given a `Term`.
/// This method is for an advanced usage only.
///
/// Most users should prefer using [`Self::read_postings()`] instead.
pub fn read_block_postings(
&self,
term: &Term,
option: IndexRecordOption,
codec: &C,
) -> io::Result<<<C as Codec>::PostingsCodec as PostingsCodec>::Postings> {
let option = option.downgrade(self.record_option);
) -> io::Result<Option<BlockSegmentPostings>> {
self.get_term_info(term)?
.map(move |term_info| self.read_block_postings_from_terminfo(&term_info, option))
.transpose()
}
/// Returns a block postings given a `term_info`.
/// This method is for an advanced usage only.
///
/// Most users should prefer using [`Self::read_postings()`] instead.
pub fn read_block_postings_from_terminfo(
&self,
term_info: &TermInfo,
requested_option: IndexRecordOption,
) -> io::Result<BlockSegmentPostings> {
let postings_data = self
.postings_file_slice
.slice(term_info.postings_range.clone())
.read_bytes()?;
let positions_data: Option<OwnedBytes> = if option.has_positions() {
let positions_data = self
.positions_file_slice
.slice(term_info.positions_range.clone())
.read_bytes()?;
Some(positions_data)
} else {
None
};
let postings: <<C as Codec>::PostingsCodec as PostingsCodec>::Postings =
codec.postings_codec().load_postings(
term_info.doc_freq,
postings_data,
self.record_option,
option,
positions_data,
)?;
Ok(postings)
.slice(term_info.postings_range.clone());
BlockSegmentPostings::open(
term_info.doc_freq,
postings_data,
self.record_option,
requested_option,
)
}
/// Returns a posting object given a `term_info`.
@@ -271,9 +225,25 @@ impl InvertedIndexReader {
&self,
term_info: &TermInfo,
option: IndexRecordOption,
) -> io::Result<Box<dyn Postings>> {
self.codec
.load_postings_type_erased(term_info, option, self)
) -> io::Result<SegmentPostings> {
let option = option.downgrade(self.record_option);
let block_postings = self.read_block_postings_from_terminfo(term_info, option)?;
let position_reader = {
if option.has_positions() {
let positions_data = self
.positions_file_slice
.read_bytes_slice(term_info.positions_range.clone())?;
let position_reader = PositionReader::open(positions_data)?;
Some(position_reader)
} else {
None
}
};
Ok(SegmentPostings::from_block_postings(
block_postings,
position_reader,
))
}
/// Returns the total number of tokens recorded for all documents
@@ -296,7 +266,7 @@ impl InvertedIndexReader {
&self,
term: &Term,
option: IndexRecordOption,
) -> io::Result<Option<Box<dyn Postings>>> {
) -> io::Result<Option<SegmentPostings>> {
self.get_term_info(term)?
.map(move |term_info| self.read_postings_from_terminfo(&term_info, option))
.transpose()

View File

@@ -2,7 +2,6 @@
//!
//! It contains `Index` and `Segment`, where a `Index` consists of one or more `Segment`s.
mod codec_configuration;
mod index;
mod index_meta;
mod inverted_index_reader;
@@ -11,7 +10,6 @@ mod segment_component;
mod segment_id;
mod segment_reader;
pub use self::codec_configuration::CodecConfiguration;
pub use self::index::{Index, IndexBuilder};
pub(crate) use self::index_meta::SegmentMetaInventory;
pub use self::index_meta::{IndexMeta, IndexSettings, Order, SegmentMeta};

View File

@@ -2,7 +2,6 @@ use std::fmt;
use std::path::PathBuf;
use super::SegmentComponent;
use crate::codec::StandardCodec;
use crate::directory::error::{OpenReadError, OpenWriteError};
use crate::directory::{Directory, FileSlice, WritePtr};
use crate::index::{Index, SegmentId, SegmentMeta};
@@ -11,25 +10,25 @@ use crate::Opstamp;
/// A segment is a piece of the index.
#[derive(Clone)]
pub struct Segment<C: crate::codec::Codec = StandardCodec> {
index: Index<C>,
pub struct Segment {
index: Index,
meta: SegmentMeta,
}
impl<C: crate::codec::Codec> fmt::Debug for Segment<C> {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
impl fmt::Debug for Segment {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "Segment({:?})", self.id().uuid_string())
}
}
impl<C: crate::codec::Codec> Segment<C> {
impl Segment {
/// Creates a new segment given an `Index` and a `SegmentId`
pub(crate) fn for_index(index: Index<C>, meta: SegmentMeta) -> Segment<C> {
pub(crate) fn for_index(index: Index, meta: SegmentMeta) -> Segment {
Segment { index, meta }
}
/// Returns the index the segment belongs to.
pub fn index(&self) -> &Index<C> {
pub fn index(&self) -> &Index {
&self.index
}
@@ -47,7 +46,7 @@ impl<C: crate::codec::Codec> Segment<C> {
///
/// This method is only used when updating `max_doc` from 0
/// as we finalize a fresh new segment.
pub fn with_max_doc(self, max_doc: u32) -> Segment<C> {
pub fn with_max_doc(self, max_doc: u32) -> Segment {
Segment {
index: self.index,
meta: self.meta.with_max_doc(max_doc),
@@ -56,7 +55,7 @@ impl<C: crate::codec::Codec> Segment<C> {
#[doc(hidden)]
#[must_use]
pub fn with_delete_meta(self, num_deleted_docs: u32, opstamp: Opstamp) -> Segment<C> {
pub fn with_delete_meta(self, num_deleted_docs: u32, opstamp: Opstamp) -> Segment {
Segment {
index: self.index,
meta: self.meta.with_delete_meta(num_deleted_docs, opstamp),

View File

@@ -23,8 +23,6 @@ pub enum SegmentComponent {
/// Accessing a document from the store is relatively slow, as it
/// requires to decompress the entire block it belongs to.
Store,
/// Temporary storage of the documents, before streamed to `Store`.
TempStore,
/// Bitset describing which document of the segment is alive.
/// (It was representing deleted docs but changed to represent alive docs from v0.17)
Delete,
@@ -33,14 +31,13 @@ pub enum SegmentComponent {
impl SegmentComponent {
/// Iterates through the components.
pub fn iterator() -> slice::Iter<'static, SegmentComponent> {
static SEGMENT_COMPONENTS: [SegmentComponent; 8] = [
static SEGMENT_COMPONENTS: [SegmentComponent; 7] = [
SegmentComponent::Postings,
SegmentComponent::Positions,
SegmentComponent::FastFields,
SegmentComponent::FieldNorms,
SegmentComponent::Terms,
SegmentComponent::Store,
SegmentComponent::TempStore,
SegmentComponent::Delete,
];
SEGMENT_COMPONENTS.iter()

View File

@@ -6,7 +6,6 @@ use common::{ByteCount, HasLen};
use fnv::FnvHashMap;
use itertools::Itertools;
use crate::codec::ObjectSafeCodec;
use crate::directory::{CompositeFile, FileSlice};
use crate::error::DataCorruption;
use crate::fastfield::{intersect_alive_bitsets, AliveBitSet, FacetReader, FastFieldReaders};
@@ -48,8 +47,6 @@ pub struct SegmentReader {
store_file: FileSlice,
alive_bitset_opt: Option<AliveBitSet>,
schema: Schema,
pub(crate) codec: Arc<dyn ObjectSafeCodec>,
}
impl SegmentReader {
@@ -143,16 +140,15 @@ impl SegmentReader {
}
/// Open a new segment for reading.
pub fn open<C: crate::codec::Codec>(segment: &Segment<C>) -> crate::Result<SegmentReader> {
pub fn open(segment: &Segment) -> crate::Result<SegmentReader> {
Self::open_with_custom_alive_set(segment, None)
}
/// Open a new segment for reading.
pub fn open_with_custom_alive_set<C: crate::codec::Codec>(
segment: &Segment<C>,
pub fn open_with_custom_alive_set(
segment: &Segment,
custom_bitset: Option<AliveBitSet>,
) -> crate::Result<SegmentReader> {
let codec: Arc<dyn ObjectSafeCodec> = Arc::new(segment.index().codec().clone());
let termdict_file = segment.open_read(SegmentComponent::Terms)?;
let termdict_composite = CompositeFile::open(&termdict_file)?;
@@ -208,7 +204,6 @@ impl SegmentReader {
alive_bitset_opt,
positions_composite,
schema,
codec,
})
}
@@ -278,7 +273,6 @@ impl SegmentReader {
postings_file,
positions_file,
record_option,
self.codec.clone(),
)?);
// by releasing the lock in between, we may end up opening the inverting index

View File

@@ -9,7 +9,6 @@ use smallvec::smallvec;
use super::operation::{AddOperation, UserOperation};
use super::segment_updater::SegmentUpdater;
use super::{AddBatch, AddBatchReceiver, AddBatchSender, PreparedCommit};
use crate::codec::{Codec, StandardCodec};
use crate::directory::{DirectoryLock, GarbageCollectionResult, TerminatingWrite};
use crate::error::TantivyError;
use crate::fastfield::write_alive_bitset;
@@ -69,12 +68,12 @@ pub struct IndexWriterOptions {
/// indexing queue.
/// Each indexing thread builds its own independent [`Segment`], via
/// a `SegmentWriter` object.
pub struct IndexWriter<C: Codec = StandardCodec, D: Document = TantivyDocument> {
pub struct IndexWriter<D: Document = TantivyDocument> {
// the lock is just used to bind the
// lifetime of the lock with that of the IndexWriter.
_directory_lock: Option<DirectoryLock>,
index: Index<C>,
index: Index,
options: IndexWriterOptions,
@@ -83,7 +82,7 @@ pub struct IndexWriter<C: Codec = StandardCodec, D: Document = TantivyDocument>
index_writer_status: IndexWriterStatus<D>,
operation_sender: AddBatchSender<D>,
segment_updater: SegmentUpdater<C>,
segment_updater: SegmentUpdater,
worker_id: usize,
@@ -129,8 +128,8 @@ fn compute_deleted_bitset(
/// is `==` target_opstamp.
/// For instance, there was no delete operation between the state of the `segment_entry` and
/// the `target_opstamp`, `segment_entry` is not updated.
pub fn advance_deletes<C: Codec>(
mut segment: Segment<C>,
pub fn advance_deletes(
mut segment: Segment,
segment_entry: &mut SegmentEntry,
target_opstamp: Opstamp,
) -> crate::Result<()> {
@@ -180,11 +179,11 @@ pub fn advance_deletes<C: Codec>(
Ok(())
}
fn index_documents<C: crate::codec::Codec, D: Document>(
fn index_documents<D: Document>(
memory_budget: usize,
segment: Segment<C>,
segment: Segment,
grouped_document_iterator: &mut dyn Iterator<Item = AddBatch<D>>,
segment_updater: &SegmentUpdater<C>,
segment_updater: &SegmentUpdater,
mut delete_cursor: DeleteCursor,
) -> crate::Result<()> {
let mut segment_writer = SegmentWriter::for_segment(memory_budget, segment.clone())?;
@@ -219,7 +218,7 @@ fn index_documents<C: crate::codec::Codec, D: Document>(
let alive_bitset_opt = apply_deletes(&segment_with_max_doc, &mut delete_cursor, &doc_opstamps)?;
let meta = segment_with_max_doc.meta().clone();
meta.untrack_temp_docstore();
// update segment_updater inventory to remove tempstore
let segment_entry = SegmentEntry::new(meta, delete_cursor, alive_bitset_opt);
segment_updater.schedule_add_segment(segment_entry).wait()?;
@@ -227,8 +226,8 @@ fn index_documents<C: crate::codec::Codec, D: Document>(
}
/// `doc_opstamps` is required to be non-empty.
fn apply_deletes<C: crate::codec::Codec>(
segment: &Segment<C>,
fn apply_deletes(
segment: &Segment,
delete_cursor: &mut DeleteCursor,
doc_opstamps: &[Opstamp],
) -> crate::Result<Option<BitSet>> {
@@ -263,7 +262,7 @@ fn apply_deletes<C: crate::codec::Codec>(
})
}
impl<C: Codec, D: Document> IndexWriter<C, D> {
impl<D: Document> IndexWriter<D> {
/// Create a new index writer. Attempts to acquire a lockfile.
///
/// The lockfile should be deleted on drop, but it is possible
@@ -279,7 +278,7 @@ impl<C: Codec, D: Document> IndexWriter<C, D> {
/// If the memory arena per thread is too small or too big, returns
/// `TantivyError::InvalidArgument`
pub(crate) fn new(
index: &Index<C>,
index: &Index,
options: IndexWriterOptions,
directory_lock: DirectoryLock,
) -> crate::Result<Self> {
@@ -346,7 +345,7 @@ impl<C: Codec, D: Document> IndexWriter<C, D> {
}
/// Accessor to the index.
pub fn index(&self) -> &Index<C> {
pub fn index(&self) -> &Index {
&self.index
}
@@ -394,7 +393,7 @@ impl<C: Codec, D: Document> IndexWriter<C, D> {
/// It is safe to start writing file associated with the new `Segment`.
/// These will not be garbage collected as long as an instance object of
/// `SegmentMeta` object associated with the new `Segment` is "alive".
pub fn new_segment(&self) -> Segment<C> {
pub fn new_segment(&self) -> Segment {
self.index.new_segment()
}
@@ -616,7 +615,7 @@ impl<C: Codec, D: Document> IndexWriter<C, D> {
/// It is also possible to add a payload to the `commit`
/// using this API.
/// See [`PreparedCommit::set_payload()`].
pub fn prepare_commit(&mut self) -> crate::Result<PreparedCommit<'_, C, D>> {
pub fn prepare_commit(&mut self) -> crate::Result<PreparedCommit<'_, D>> {
// Here, because we join all of the worker threads,
// all of the segment update for this commit have been
// sent.
@@ -666,7 +665,7 @@ impl<C: Codec, D: Document> IndexWriter<C, D> {
self.prepare_commit()?.commit()
}
pub(crate) fn segment_updater(&self) -> &SegmentUpdater<C> {
pub(crate) fn segment_updater(&self) -> &SegmentUpdater {
&self.segment_updater
}
@@ -805,7 +804,7 @@ impl<C: Codec, D: Document> IndexWriter<C, D> {
}
}
impl<C: Codec, D: Document> Drop for IndexWriter<C, D> {
impl<D: Document> Drop for IndexWriter<D> {
fn drop(&mut self) {
self.segment_updater.kill();
self.drop_sender();

View File

@@ -94,7 +94,7 @@ impl MergePolicy for LogMergePolicy {
fn compute_merge_candidates(&self, segments: &[SegmentMeta]) -> Vec<MergeCandidate> {
let size_sorted_segments = segments
.iter()
.filter(|seg| seg.num_docs() <= (self.max_docs_before_merge as u32))
.filter(|seg| (seg.num_docs() as usize) <= self.max_docs_before_merge)
.sorted_by_key(|seg| std::cmp::Reverse(seg.max_doc()))
.collect::<Vec<&SegmentMeta>>();
@@ -372,4 +372,21 @@ mod tests {
assert_eq!(merge_candidates[0].0.len(), 1);
assert_eq!(merge_candidates[0].0[0], test_input[1].id());
}
#[test]
fn test_max_docs_before_merge_large_value() {
// Regression test: (max_docs_before_merge as u32) truncates values > u32::MAX.
// Casting num_docs() to usize instead avoids the truncation.
let mut policy = LogMergePolicy::default();
policy.set_min_num_segments(2);
policy.set_max_docs_before_merge(5_000_000_000usize);
let test_input = vec![
create_random_segment_meta(100_000),
create_random_segment_meta(100_000),
];
let result = policy.compute_merge_candidates(&test_input);
// Both segments should be eligible (100_000 < 5_000_000_000)
assert_eq!(result.len(), 1);
assert_eq!(result[0].0.len(), 2);
}
}

View File

@@ -1,10 +1,9 @@
#[cfg(test)]
mod tests {
use crate::codec::StandardCodec;
use crate::collector::TopDocs;
use crate::fastfield::AliveBitSet;
use crate::index::Index;
use crate::postings::{DocFreq, Postings};
use crate::postings::Postings;
use crate::query::QueryParser;
use crate::schema::{
self, BytesOptions, Facet, FacetOptions, IndexRecordOption, NumericOptions,
@@ -122,26 +121,21 @@ mod tests {
let my_text_field = index.schema().get_field("text_field").unwrap();
let term_a = Term::from_field_text(my_text_field, "text");
let inverted_index = segment_reader.inverted_index(my_text_field).unwrap();
let term_info = inverted_index.get_term_info(&term_a).unwrap().unwrap();
let mut postings = inverted_index
.read_postings_from_terminfo_specialized(
&term_info,
IndexRecordOption::WithFreqsAndPositions,
&StandardCodec,
)
.read_postings(&term_a, IndexRecordOption::WithFreqsAndPositions)
.unwrap()
.unwrap();
assert_eq!(postings.doc_freq(), DocFreq::Exact(2));
assert_eq!(postings.doc_freq(), 2);
let fallback_bitset = AliveBitSet::for_test_from_deleted_docs(&[0], 100);
assert_eq!(
crate::indexer::merger::doc_freq_given_deletes(
&postings,
postings.doc_freq_given_deletes(
segment_reader.alive_bitset().unwrap_or(&fallback_bitset)
),
2
);
assert_eq!(postings.term_freq(), 1);
let mut output = Vec::new();
let mut output = vec![];
postings.positions(&mut output);
assert_eq!(output, vec![1]);
postings.advance();

View File

@@ -7,8 +7,6 @@ use common::ReadOnlyBitSet;
use itertools::Itertools;
use measure_time::debug_time;
use crate::codec::postings::PostingsCodec;
use crate::codec::{Codec, StandardCodec};
use crate::directory::WritePtr;
use crate::docset::{DocSet, TERMINATED};
use crate::error::DataCorruption;
@@ -17,7 +15,7 @@ use crate::fieldnorm::{FieldNormReader, FieldNormReaders, FieldNormsSerializer,
use crate::index::{Segment, SegmentComponent, SegmentReader};
use crate::indexer::doc_id_mapping::{MappingType, SegmentDocIdMapping};
use crate::indexer::SegmentSerializer;
use crate::postings::{InvertedIndexSerializer, Postings};
use crate::postings::{InvertedIndexSerializer, Postings, SegmentPostings};
use crate::schema::{value_type_to_column_type, Field, FieldType, Schema};
use crate::store::StoreWriter;
use crate::termdict::{TermMerger, TermOrdinal};
@@ -78,11 +76,10 @@ fn estimate_total_num_tokens(readers: &[SegmentReader], field: Field) -> crate::
Ok(total_num_tokens)
}
pub struct IndexMerger<C: Codec = StandardCodec> {
pub struct IndexMerger {
schema: Schema,
pub(crate) readers: Vec<SegmentReader>,
max_doc: u32,
codec: C,
}
struct DeltaComputer {
@@ -147,8 +144,8 @@ fn extract_fast_field_required_columns(schema: &Schema) -> Vec<(String, ColumnTy
.collect()
}
impl<C: Codec> IndexMerger<C> {
pub fn open(schema: Schema, segments: &[Segment<C>]) -> crate::Result<IndexMerger<C>> {
impl IndexMerger {
pub fn open(schema: Schema, segments: &[Segment]) -> crate::Result<IndexMerger> {
let alive_bitset = segments.iter().map(|_| None).collect_vec();
Self::open_with_custom_alive_set(schema, segments, alive_bitset)
}
@@ -165,15 +162,11 @@ impl<C: Codec> IndexMerger<C> {
// This can be used to merge but also apply an additional filter.
// One use case is demux, which is basically taking a list of
// segments and partitions them e.g. by a value in a field.
//
// # Panics if segments is empty.
pub fn open_with_custom_alive_set(
schema: Schema,
segments: &[Segment<C>],
segments: &[Segment],
alive_bitset_opt: Vec<Option<AliveBitSet>>,
) -> crate::Result<IndexMerger<C>> {
assert!(!segments.is_empty());
let codec = segments[0].index().codec().clone();
) -> crate::Result<IndexMerger> {
let mut readers = vec![];
for (segment, new_alive_bitset_opt) in segments.iter().zip(alive_bitset_opt) {
if segment.meta().num_docs() > 0 {
@@ -196,7 +189,6 @@ impl<C: Codec> IndexMerger<C> {
schema,
readers,
max_doc,
codec,
})
}
@@ -295,7 +287,7 @@ impl<C: Codec> IndexMerger<C> {
&self,
indexed_field: Field,
_field_type: &FieldType,
serializer: &mut InvertedIndexSerializer<C>,
serializer: &mut InvertedIndexSerializer,
fieldnorm_reader: Option<FieldNormReader>,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
@@ -363,10 +355,7 @@ impl<C: Codec> IndexMerger<C> {
indexed. Have you modified the schema?",
);
let mut segment_postings_containing_the_term: Vec<(
usize,
<C::PostingsCodec as PostingsCodec>::Postings,
)> = Vec::with_capacity(self.readers.len());
let mut segment_postings_containing_the_term: Vec<(usize, SegmentPostings)> = vec![];
while merged_terms.advance() {
segment_postings_containing_the_term.clear();
@@ -378,24 +367,17 @@ impl<C: Codec> IndexMerger<C> {
for (segment_ord, term_info) in merged_terms.current_segment_ords_and_term_infos() {
let segment_reader = &self.readers[segment_ord];
let inverted_index: &InvertedIndexReader = &field_readers[segment_ord];
let postings = inverted_index.read_postings_from_terminfo_specialized(
&term_info,
segment_postings_option,
&self.codec,
)?;
let segment_postings = inverted_index
.read_postings_from_terminfo(&term_info, segment_postings_option)?;
let alive_bitset_opt = segment_reader.alive_bitset();
let doc_freq = if let Some(alive_bitset) = alive_bitset_opt {
doc_freq_given_deletes(&postings, alive_bitset)
segment_postings.doc_freq_given_deletes(alive_bitset)
} else {
// We do not an exact document frequency here.
match postings.doc_freq() {
crate::postings::DocFreq::Approximate(_) => exact_doc_freq(&postings),
crate::postings::DocFreq::Exact(doc_freq) => doc_freq,
}
segment_postings.doc_freq()
};
if doc_freq > 0u32 {
total_doc_freq += doc_freq;
segment_postings_containing_the_term.push((segment_ord, postings));
segment_postings_containing_the_term.push((segment_ord, segment_postings));
}
}
@@ -413,7 +395,11 @@ impl<C: Codec> IndexMerger<C> {
assert!(!segment_postings_containing_the_term.is_empty());
let has_term_freq = {
let has_term_freq = segment_postings_containing_the_term[0].1.has_freq();
let has_term_freq = !segment_postings_containing_the_term[0]
.1
.block_cursor
.freqs()
.is_empty();
for (_, postings) in &segment_postings_containing_the_term[1..] {
// This may look at a strange way to test whether we have term freq or not.
// With JSON object, the schema is not sufficient to know whether a term
@@ -429,7 +415,7 @@ impl<C: Codec> IndexMerger<C> {
//
// Overall the reliable way to know if we have actual frequencies loaded or not
// is to check whether the actual decoded array is empty or not.
if postings.has_freq() != has_term_freq {
if has_term_freq == postings.block_cursor.freqs().is_empty() {
return Err(DataCorruption::comment_only(
"Term freqs are inconsistent across segments",
)
@@ -481,7 +467,7 @@ impl<C: Codec> IndexMerger<C> {
fn write_postings(
&self,
serializer: &mut InvertedIndexSerializer<C>,
serializer: &mut InvertedIndexSerializer,
fieldnorm_readers: FieldNormReaders,
doc_id_mapping: &SegmentDocIdMapping,
) -> crate::Result<()> {
@@ -539,7 +525,7 @@ impl<C: Codec> IndexMerger<C> {
///
/// # Returns
/// The number of documents in the resulting segment.
pub fn write(&self, mut serializer: SegmentSerializer<C>) -> crate::Result<u32> {
pub fn write(&self, mut serializer: SegmentSerializer) -> crate::Result<u32> {
let doc_id_mapping = self.get_doc_id_from_concatenated_data()?;
debug!("write-fieldnorms");
if let Some(fieldnorms_serializer) = serializer.extract_fieldnorms_serializer() {
@@ -567,43 +553,6 @@ impl<C: Codec> IndexMerger<C> {
}
}
/// Compute the number of non-deleted documents.
///
/// This method will clone and scan through the posting lists.
/// (this is a rather expensive operation).
pub(crate) fn doc_freq_given_deletes<P: Postings + Clone>(
postings: &P,
alive_bitset: &AliveBitSet,
) -> u32 {
let mut docset = postings.clone();
let mut doc_freq = 0;
loop {
let doc = docset.doc();
if doc == TERMINATED {
return doc_freq;
}
if alive_bitset.is_alive(doc) {
doc_freq += 1u32;
}
docset.advance();
}
}
/// If the postings is not able to inform us of the document frequency,
/// we just scan through it.
pub(crate) fn exact_doc_freq<P: Postings + Clone>(postings: &P) -> u32 {
let mut docset = postings.clone();
let mut doc_freq = 0;
loop {
let doc = docset.doc();
if doc == TERMINATED {
return doc_freq;
}
doc_freq += 1u32;
docset.advance();
}
}
#[cfg(test)]
mod tests {
@@ -612,16 +561,12 @@ mod tests {
use proptest::strategy::Strategy;
use schema::FAST;
use crate::codec::postings::PostingsCodec;
use crate::codec::standard::postings::StandardPostingsCodec;
use crate::collector::tests::{
BytesFastFieldTestCollector, FastFieldTestCollector, TEST_COLLECTOR_WITH_SCORE,
};
use crate::collector::{Count, FacetCollector};
use crate::fastfield::AliveBitSet;
use crate::index::{Index, SegmentId};
use crate::indexer::NoMergePolicy;
use crate::postings::{DocFreq, Postings as _};
use crate::query::{AllQuery, BooleanQuery, EnableScoring, Scorer, TermQuery};
use crate::schema::{
Facet, FacetOptions, IndexRecordOption, NumericOptions, TantivyDocument, Term,
@@ -1573,10 +1518,10 @@ mod tests {
let searcher = reader.searcher();
let mut term_scorer = term_query
.specialized_weight(EnableScoring::enabled_from_searcher(&searcher))?
.term_scorer_for_test(searcher.segment_reader(0u32), 1.0)
.term_scorer_for_test(searcher.segment_reader(0u32), 1.0)?
.unwrap();
assert_eq!(term_scorer.doc(), 0);
assert_nearly_equals!(term_scorer.seek_block_max(0), 0.0079681855);
assert_nearly_equals!(term_scorer.block_max_score(), 0.0079681855);
assert_nearly_equals!(term_scorer.score(), 0.0079681855);
for _ in 0..81 {
writer.add_document(doc!(text=>"hello happy tax payer"))?;
@@ -1589,13 +1534,13 @@ mod tests {
for segment_reader in searcher.segment_readers() {
let mut term_scorer = term_query
.specialized_weight(EnableScoring::enabled_from_searcher(&searcher))?
.term_scorer_for_test(segment_reader, 1.0)
.term_scorer_for_test(segment_reader, 1.0)?
.unwrap();
// the difference compared to before is intrinsic to the bm25 formula. no worries
// there.
for doc in segment_reader.doc_ids_alive() {
assert_eq!(term_scorer.doc(), doc);
assert_nearly_equals!(term_scorer.seek_block_max(doc), 0.003478312);
assert_nearly_equals!(term_scorer.block_max_score(), 0.003478312);
assert_nearly_equals!(term_scorer.score(), 0.003478312);
term_scorer.advance();
}
@@ -1615,12 +1560,12 @@ mod tests {
let segment_reader = searcher.segment_reader(0u32);
let mut term_scorer = term_query
.specialized_weight(EnableScoring::enabled_from_searcher(&searcher))?
.term_scorer_for_test(segment_reader, 1.0)
.term_scorer_for_test(segment_reader, 1.0)?
.unwrap();
// the difference compared to before is intrinsic to the bm25 formula. no worries there.
for doc in segment_reader.doc_ids_alive() {
assert_eq!(term_scorer.doc(), doc);
assert_nearly_equals!(term_scorer.seek_block_max(doc), 0.003478312);
assert_nearly_equals!(term_scorer.block_max_score(), 0.003478312);
assert_nearly_equals!(term_scorer.score(), 0.003478312);
term_scorer.advance();
}
@@ -1634,16 +1579,4 @@ mod tests {
assert!(((super::MAX_DOC_LIMIT - 1) as i32) >= 0);
assert!((super::MAX_DOC_LIMIT as i32) < 0);
}
#[test]
fn test_doc_freq_given_delete() {
let docs =
<StandardPostingsCodec as PostingsCodec>::Postings::create_from_docs(&[0, 2, 10]);
assert_eq!(docs.doc_freq(), DocFreq::Exact(3));
let alive_bitset = AliveBitSet::for_test_from_deleted_docs(&[2], 12);
assert_eq!(super::doc_freq_given_deletes(&docs, &alive_bitset), 2);
let all_deleted =
AliveBitSet::for_test_from_deleted_docs(&[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], 12);
assert_eq!(super::doc_freq_given_deletes(&docs, &all_deleted), 0);
}
}

View File

@@ -1,17 +1,16 @@
use super::IndexWriter;
use crate::codec::Codec;
use crate::schema::document::Document;
use crate::{FutureResult, Opstamp, TantivyDocument};
/// A prepared commit
pub struct PreparedCommit<'a, C: Codec, D: Document = TantivyDocument> {
index_writer: &'a mut IndexWriter<C, D>,
pub struct PreparedCommit<'a, D: Document = TantivyDocument> {
index_writer: &'a mut IndexWriter<D>,
payload: Option<String>,
opstamp: Opstamp,
}
impl<'a, C: Codec, D: Document> PreparedCommit<'a, C, D> {
pub(crate) fn new(index_writer: &'a mut IndexWriter<C, D>, opstamp: Opstamp) -> Self {
impl<'a, D: Document> PreparedCommit<'a, D> {
pub(crate) fn new(index_writer: &'a mut IndexWriter<D>, opstamp: Opstamp) -> Self {
Self {
index_writer,
payload: None,

View File

@@ -8,17 +8,17 @@ use crate::store::StoreWriter;
/// Segment serializer is in charge of laying out on disk
/// the data accumulated and sorted by the `SegmentWriter`.
pub struct SegmentSerializer<C: crate::codec::Codec> {
segment: Segment<C>,
pub struct SegmentSerializer {
segment: Segment,
pub(crate) store_writer: StoreWriter,
fast_field_write: WritePtr,
fieldnorms_serializer: Option<FieldNormsSerializer>,
postings_serializer: InvertedIndexSerializer<C>,
postings_serializer: InvertedIndexSerializer,
}
impl<C: crate::codec::Codec> SegmentSerializer<C> {
impl SegmentSerializer {
/// Creates a new `SegmentSerializer`.
pub fn for_segment(mut segment: Segment<C>) -> crate::Result<SegmentSerializer<C>> {
pub fn for_segment(mut segment: Segment) -> crate::Result<SegmentSerializer> {
let settings = segment.index().settings().clone();
let store_writer = {
let store_write = segment.open_write(SegmentComponent::Store)?;
@@ -50,12 +50,12 @@ impl<C: crate::codec::Codec> SegmentSerializer<C> {
self.store_writer.mem_usage()
}
pub fn segment(&self) -> &Segment<C> {
pub fn segment(&self) -> &Segment {
&self.segment
}
/// Accessor to the `PostingsSerializer`.
pub fn get_postings_serializer(&mut self) -> &mut InvertedIndexSerializer<C> {
pub fn get_postings_serializer(&mut self) -> &mut InvertedIndexSerializer {
&mut self.postings_serializer
}

View File

@@ -10,13 +10,10 @@ use std::sync::{Arc, RwLock};
use rayon::{ThreadPool, ThreadPoolBuilder};
use super::segment_manager::SegmentManager;
use crate::codec::Codec;
use crate::core::META_FILEPATH;
use crate::directory::{Directory, DirectoryClone, GarbageCollectionResult};
use crate::fastfield::AliveBitSet;
use crate::index::{
CodecConfiguration, Index, IndexMeta, IndexSettings, Segment, SegmentId, SegmentMeta,
};
use crate::index::{Index, IndexMeta, IndexSettings, Segment, SegmentId, SegmentMeta};
use crate::indexer::delete_queue::DeleteCursor;
use crate::indexer::index_writer::advance_deletes;
use crate::indexer::merge_operation::MergeOperationInventory;
@@ -64,10 +61,10 @@ pub(crate) fn save_metas(metas: &IndexMeta, directory: &dyn Directory) -> crate:
// We voluntarily pass a merge_operation ref to guarantee that
// the merge_operation is alive during the process
#[derive(Clone)]
pub(crate) struct SegmentUpdater<C: Codec>(Arc<InnerSegmentUpdater<C>>);
pub(crate) struct SegmentUpdater(Arc<InnerSegmentUpdater>);
impl<C: Codec> Deref for SegmentUpdater<C> {
type Target = InnerSegmentUpdater<C>;
impl Deref for SegmentUpdater {
type Target = InnerSegmentUpdater;
#[inline]
fn deref(&self) -> &Self::Target {
@@ -75,8 +72,8 @@ impl<C: Codec> Deref for SegmentUpdater<C> {
}
}
fn garbage_collect_files<C: Codec>(
segment_updater: SegmentUpdater<C>,
fn garbage_collect_files(
segment_updater: SegmentUpdater,
) -> crate::Result<GarbageCollectionResult> {
info!("Running garbage collection");
let mut index = segment_updater.index.clone();
@@ -87,8 +84,8 @@ fn garbage_collect_files<C: Codec>(
/// Merges a list of segments the list of segment givens in the `segment_entries`.
/// This function happens in the calling thread and is computationally expensive.
fn merge<Codec: crate::codec::Codec>(
index: &Index<Codec>,
fn merge(
index: &Index,
mut segment_entries: Vec<SegmentEntry>,
target_opstamp: Opstamp,
) -> crate::Result<Option<SegmentEntry>> {
@@ -111,13 +108,13 @@ fn merge<Codec: crate::codec::Codec>(
let delete_cursor = segment_entries[0].delete_cursor().clone();
let segments: Vec<Segment<Codec>> = segment_entries
let segments: Vec<Segment> = segment_entries
.iter()
.map(|segment_entry| index.segment(segment_entry.meta().clone()))
.collect();
// An IndexMerger is like a "view" of our merged segments.
let merger: IndexMerger<Codec> = IndexMerger::open(index.schema(), &segments[..])?;
let merger: IndexMerger = IndexMerger::open(index.schema(), &segments[..])?;
// ... we just serialize this index merger in our new segment to merge the segments.
let segment_serializer = SegmentSerializer::for_segment(merged_segment.clone())?;
@@ -142,10 +139,10 @@ fn merge<Codec: crate::codec::Codec>(
/// meant to work if you have an `IndexWriter` running for the origin indices, or
/// the destination `Index`.
#[doc(hidden)]
pub fn merge_indices<Codec: crate::codec::Codec>(
indices: &[Index<Codec>],
output_directory: Box<dyn Directory>,
) -> crate::Result<Index<Codec>> {
pub fn merge_indices<T: Into<Box<dyn Directory>>>(
indices: &[Index],
output_directory: T,
) -> crate::Result<Index> {
if indices.is_empty() {
// If there are no indices to merge, there is no need to do anything.
return Err(crate::TantivyError::InvalidArgument(
@@ -166,7 +163,7 @@ pub fn merge_indices<Codec: crate::codec::Codec>(
));
}
let mut segments: Vec<Segment<Codec>> = Vec::new();
let mut segments: Vec<Segment> = Vec::new();
for index in indices {
segments.extend(index.searchable_segments()?);
}
@@ -188,12 +185,12 @@ pub fn merge_indices<Codec: crate::codec::Codec>(
/// meant to work if you have an `IndexWriter` running for the origin indices, or
/// the destination `Index`.
#[doc(hidden)]
pub fn merge_filtered_segments<C: crate::codec::Codec, T: Into<Box<dyn Directory>>>(
segments: &[Segment<C>],
pub fn merge_filtered_segments<T: Into<Box<dyn Directory>>>(
segments: &[Segment],
target_settings: IndexSettings,
filter_doc_ids: Vec<Option<AliveBitSet>>,
output_directory: T,
) -> crate::Result<Index<C>> {
) -> crate::Result<Index> {
if segments.is_empty() {
// If there are no indices to merge, there is no need to do anything.
return Err(crate::TantivyError::InvalidArgument(
@@ -214,15 +211,14 @@ pub fn merge_filtered_segments<C: crate::codec::Codec, T: Into<Box<dyn Directory
));
}
let mut merged_index: Index<C> = Index::builder()
.schema(target_schema.clone())
.codec(segments[0].index().codec().clone())
.settings(target_settings.clone())
.create(output_directory.into())?;
let mut merged_index = Index::create(
output_directory,
target_schema.clone(),
target_settings.clone(),
)?;
let merged_segment = merged_index.new_segment();
let merged_segment_id = merged_segment.id();
let merger: IndexMerger<C> =
let merger: IndexMerger =
IndexMerger::open_with_custom_alive_set(merged_index.schema(), segments, filter_doc_ids)?;
let segment_serializer = SegmentSerializer::for_segment(merged_segment)?;
let num_docs = merger.write(segment_serializer)?;
@@ -239,7 +235,6 @@ pub fn merge_filtered_segments<C: crate::codec::Codec, T: Into<Box<dyn Directory
))
.trim_end()
);
let codec_configuration = CodecConfiguration::from_codec(segments[0].index().codec());
let index_meta = IndexMeta {
index_settings: target_settings, // index_settings of all segments should be the same
@@ -247,7 +242,6 @@ pub fn merge_filtered_segments<C: crate::codec::Codec, T: Into<Box<dyn Directory
schema: target_schema,
opstamp: 0u64,
payload: Some(stats),
codec: codec_configuration,
};
// save the meta.json
@@ -256,7 +250,7 @@ pub fn merge_filtered_segments<C: crate::codec::Codec, T: Into<Box<dyn Directory
Ok(merged_index)
}
pub(crate) struct InnerSegmentUpdater<C: Codec> {
pub(crate) struct InnerSegmentUpdater {
// we keep a copy of the current active IndexMeta to
// avoid loading the file every time we need it in the
// `SegmentUpdater`.
@@ -267,7 +261,7 @@ pub(crate) struct InnerSegmentUpdater<C: Codec> {
pool: ThreadPool,
merge_thread_pool: ThreadPool,
index: Index<C>,
index: Index,
segment_manager: SegmentManager,
merge_policy: RwLock<Arc<dyn MergePolicy>>,
killed: AtomicBool,
@@ -275,13 +269,13 @@ pub(crate) struct InnerSegmentUpdater<C: Codec> {
merge_operations: MergeOperationInventory,
}
impl<Codec: crate::codec::Codec> SegmentUpdater<Codec> {
impl SegmentUpdater {
pub fn create(
index: Index<Codec>,
index: Index,
stamper: Stamper,
delete_cursor: &DeleteCursor,
num_merge_threads: usize,
) -> crate::Result<Self> {
) -> crate::Result<SegmentUpdater> {
let segments = index.searchable_segment_metas()?;
let segment_manager = SegmentManager::from_segments(segments, delete_cursor);
let pool = ThreadPoolBuilder::new()
@@ -409,15 +403,14 @@ impl<Codec: crate::codec::Codec> SegmentUpdater<Codec> {
// from the different drives.
//
// Segment 1 from disk 1, Segment 1 from disk 2, etc.
committed_segment_metas.sort_by_key(|segment_meta| -(segment_meta.max_doc() as i32));
let codec = CodecConfiguration::from_codec(index.codec());
committed_segment_metas
.sort_by_key(|segment_meta| std::cmp::Reverse(segment_meta.max_doc()));
let index_meta = IndexMeta {
index_settings: index.settings().clone(),
segments: committed_segment_metas,
schema: index.schema(),
opstamp,
payload: commit_message,
codec,
};
// TODO add context to the error.
save_metas(&index_meta, directory.box_clone().borrow_mut())?;
@@ -451,7 +444,7 @@ impl<Codec: crate::codec::Codec> SegmentUpdater<Codec> {
opstamp: Opstamp,
payload: Option<String>,
) -> FutureResult<Opstamp> {
let segment_updater: SegmentUpdater<Codec> = self.clone();
let segment_updater: SegmentUpdater = self.clone();
self.schedule_task(move || {
let segment_entries = segment_updater.purge_deletes(opstamp)?;
segment_updater.segment_manager.commit(segment_entries);
@@ -710,10 +703,10 @@ impl<Codec: crate::codec::Codec> SegmentUpdater<Codec> {
#[cfg(test)]
mod tests {
use super::merge_indices;
use crate::codec::StandardCodec;
use crate::collector::TopDocs;
use crate::directory::RamDirectory;
use crate::fastfield::AliveBitSet;
use crate::index::{SegmentId, SegmentMetaInventory};
use crate::indexer::merge_policy::tests::MergeWheneverPossible;
use crate::indexer::merger::IndexMerger;
use crate::indexer::segment_updater::merge_filtered_segments;
@@ -721,6 +714,22 @@ mod tests {
use crate::schema::*;
use crate::{Directory, DocAddress, Index, Segment};
#[test]
fn test_segment_sort_large_max_doc() {
// Regression test: -(max_doc as i32) overflows for max_doc >= 2^31.
// Using std::cmp::Reverse avoids this.
let inventory = SegmentMetaInventory::default();
let mut metas = vec![
inventory.new_segment_meta(SegmentId::generate_random(), 100),
inventory.new_segment_meta(SegmentId::generate_random(), (1u32 << 31) - 1),
inventory.new_segment_meta(SegmentId::generate_random(), 50_000),
];
metas.sort_by_key(|m| std::cmp::Reverse(m.max_doc()));
assert_eq!(metas[0].max_doc(), (1u32 << 31) - 1);
assert_eq!(metas[1].max_doc(), 50_000);
assert_eq!(metas[2].max_doc(), 100);
}
#[test]
fn test_delete_during_merge() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
@@ -924,7 +933,7 @@ mod tests {
#[test]
fn test_merge_empty_indices_array() {
let merge_result = merge_indices::<StandardCodec>(&[], Box::new(RamDirectory::default()));
let merge_result = merge_indices(&[], RamDirectory::default());
assert!(merge_result.is_err());
}
@@ -951,10 +960,7 @@ mod tests {
};
// mismatched schema index list
let result = merge_indices(
&[first_index, second_index],
Box::new(RamDirectory::default()),
);
let result = merge_indices(&[first_index, second_index], RamDirectory::default());
assert!(result.is_err());
Ok(())

View File

@@ -4,7 +4,6 @@ use itertools::Itertools;
use tokenizer_api::BoxTokenStream;
use super::operation::AddOperation;
use crate::codec::Codec;
use crate::fastfield::FastFieldsWriter;
use crate::fieldnorm::{FieldNormReaders, FieldNormsWriter};
use crate::index::{Segment, SegmentComponent};
@@ -13,7 +12,7 @@ use crate::indexer::segment_serializer::SegmentSerializer;
use crate::json_utils::{index_json_value, IndexingPositionsPerPath};
use crate::postings::{
compute_table_memory_size, serialize_postings, IndexingContext, IndexingPosition,
PerFieldPostingsWriter, PostingsWriter, PostingsWriterEnum,
PerFieldPostingsWriter, PostingsWriter,
};
use crate::schema::document::{Document, Value};
use crate::schema::{FieldEntry, FieldType, Schema, DATE_TIME_PRECISION_INDEXED};
@@ -46,11 +45,11 @@ fn compute_initial_table_size(per_thread_memory_budget: usize) -> crate::Result<
///
/// They creates the postings list in anonymous memory.
/// The segment is laid on disk when the segment gets `finalized`.
pub struct SegmentWriter<Codec: crate::codec::Codec> {
pub struct SegmentWriter {
pub(crate) max_doc: DocId,
pub(crate) ctx: IndexingContext,
pub(crate) per_field_postings_writers: PerFieldPostingsWriter,
pub(crate) segment_serializer: SegmentSerializer<Codec>,
pub(crate) segment_serializer: SegmentSerializer,
pub(crate) fast_field_writers: FastFieldsWriter,
pub(crate) fieldnorms_writer: FieldNormsWriter,
pub(crate) json_path_writer: JsonPathWriter,
@@ -61,7 +60,7 @@ pub struct SegmentWriter<Codec: crate::codec::Codec> {
schema: Schema,
}
impl<Codec: crate::codec::Codec> SegmentWriter<Codec> {
impl SegmentWriter {
/// Creates a new `SegmentWriter`
///
/// The arguments are defined as follows
@@ -71,10 +70,7 @@ impl<Codec: crate::codec::Codec> SegmentWriter<Codec> {
/// behavior as a memory limit.
/// - segment: The segment being written
/// - schema
pub fn for_segment(
memory_budget_in_bytes: usize,
segment: Segment<Codec>,
) -> crate::Result<Self> {
pub fn for_segment(memory_budget_in_bytes: usize, segment: Segment) -> crate::Result<Self> {
let schema = segment.schema();
let tokenizer_manager = segment.index().tokenizers().clone();
let tokenizer_manager_fast_field = segment.index().fast_field_tokenizer().clone();
@@ -173,7 +169,7 @@ impl<Codec: crate::codec::Codec> SegmentWriter<Codec> {
}
let (term_buffer, ctx) = (&mut self.term_buffer, &mut self.ctx);
let postings_writer: &mut PostingsWriterEnum =
let postings_writer: &mut dyn PostingsWriter =
self.per_field_postings_writers.get_for_field_mut(field);
term_buffer.clear_with_field(field);
@@ -390,13 +386,13 @@ impl<Codec: crate::codec::Codec> SegmentWriter<Codec> {
/// to the `SegmentSerializer`.
///
/// `doc_id_map` is used to map to the new doc_id order.
fn remap_and_write<C: Codec>(
fn remap_and_write(
schema: Schema,
per_field_postings_writers: &PerFieldPostingsWriter,
ctx: IndexingContext,
fast_field_writers: FastFieldsWriter,
fieldnorms_writer: &FieldNormsWriter,
mut serializer: SegmentSerializer<C>,
mut serializer: SegmentSerializer,
) -> crate::Result<()> {
debug!("remap-and-write");
if let Some(fieldnorms_serializer) = serializer.extract_fieldnorms_serializer() {

View File

@@ -1,7 +1,5 @@
use std::marker::PhantomData;
use crate::codec::StandardCodec;
use crate::index::CodecConfiguration;
use crate::indexer::operation::AddOperation;
use crate::indexer::segment_updater::save_metas;
use crate::indexer::SegmentWriter;
@@ -9,25 +7,22 @@ use crate::schema::document::Document;
use crate::{Directory, Index, IndexMeta, Opstamp, Segment, TantivyDocument};
#[doc(hidden)]
pub struct SingleSegmentIndexWriter<
Codec: crate::codec::Codec = StandardCodec,
D: Document = TantivyDocument,
> {
segment_writer: SegmentWriter<Codec>,
segment: Segment<Codec>,
pub struct SingleSegmentIndexWriter<D: Document = TantivyDocument> {
segment_writer: SegmentWriter,
segment: Segment,
opstamp: Opstamp,
_doc: PhantomData<D>,
_phantom: PhantomData<D>,
}
impl<Codec: crate::codec::Codec, D: Document> SingleSegmentIndexWriter<Codec, D> {
pub fn new(index: Index<Codec>, mem_budget: usize) -> crate::Result<Self> {
impl<D: Document> SingleSegmentIndexWriter<D> {
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())?;
Ok(Self {
segment_writer,
segment,
opstamp: 0,
_doc: PhantomData,
_phantom: PhantomData,
})
}
@@ -42,10 +37,10 @@ impl<Codec: crate::codec::Codec, D: Document> SingleSegmentIndexWriter<Codec, D>
.add_document(AddOperation { opstamp, document })
}
pub fn finalize(self) -> crate::Result<Index<Codec>> {
pub fn finalize(self) -> crate::Result<Index> {
let max_doc = self.segment_writer.max_doc();
self.segment_writer.finalize()?;
let segment: Segment<Codec> = self.segment.with_max_doc(max_doc);
let segment: Segment = self.segment.with_max_doc(max_doc);
let index = segment.index();
let index_meta = IndexMeta {
index_settings: index.settings().clone(),
@@ -53,7 +48,6 @@ impl<Codec: crate::codec::Codec, D: Document> SingleSegmentIndexWriter<Codec, D>
schema: index.schema(),
opstamp: 0,
payload: None,
codec: CodecConfiguration::from_codec(index.codec()),
};
save_metas(&index_meta, index.directory())?;
index.directory().sync_directory()?;

View File

@@ -166,14 +166,13 @@ mod functional_test;
#[macro_use]
mod macros;
/// Tantivy codecs describes how data is layed out on disk.
pub mod codec;
mod future_result;
// Re-exports
pub use columnar;
pub use common::{ByteCount, DateTime};
pub use {columnar, query_grammar, time};
pub use query_grammar;
pub use time;
pub use crate::error::TantivyError;
pub use crate::future_result::FutureResult;
@@ -380,7 +379,7 @@ pub mod tests {
use common::{BinarySerializable, FixedSize};
use query_grammar::{UserInputAst, UserInputLeaf, UserInputLiteral};
use rand::distributions::{Bernoulli, Uniform};
use rand::distr::{Bernoulli, Uniform};
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use time::OffsetDateTime;
@@ -431,7 +430,7 @@ pub mod tests {
pub fn generate_nonunique_unsorted(max_value: u32, n_elems: usize) -> Vec<u32> {
let seed: [u8; 32] = [1; 32];
StdRng::from_seed(seed)
.sample_iter(&Uniform::new(0u32, max_value))
.sample_iter(&Uniform::new(0u32, max_value).unwrap())
.take(n_elems)
.collect::<Vec<u32>>()
}

View File

@@ -1,18 +1,28 @@
use std::io;
use common::{OwnedBytes, VInt};
use common::VInt;
use crate::codec::standard::postings::skip::{BlockInfo, SkipReader};
use crate::codec::standard::postings::FreqReadingOption;
use crate::postings::compression::{BlockDecoder, VIntDecoder as _, COMPRESSION_BLOCK_SIZE};
use crate::directory::{FileSlice, OwnedBytes};
use crate::fieldnorm::FieldNormReader;
use crate::postings::compression::{BlockDecoder, VIntDecoder, COMPRESSION_BLOCK_SIZE};
use crate::postings::{BlockInfo, FreqReadingOption, SkipReader};
use crate::query::Bm25Weight;
use crate::schema::IndexRecordOption;
use crate::{DocId, Score, TERMINATED};
fn max_score<I: Iterator<Item = Score>>(mut it: I) -> Option<Score> {
it.next().map(|first| it.fold(first, Score::max))
}
/// `BlockSegmentPostings` is a cursor iterating over blocks
/// of documents.
///
/// # Warning
///
/// While it is useful for some very specific high-performance
/// use cases, you should prefer using `SegmentPostings` for most usage.
#[derive(Clone)]
pub(crate) struct BlockSegmentPostings {
pub struct BlockSegmentPostings {
pub(crate) doc_decoder: BlockDecoder,
block_loaded: bool,
freq_decoder: BlockDecoder,
@@ -78,7 +88,7 @@ fn split_into_skips_and_postings(
}
impl BlockSegmentPostings {
/// Opens a `StandardPostingsReader`.
/// Opens a `BlockSegmentPostings`.
/// `doc_freq` is the number of documents in the posting list.
/// `record_option` represents the amount of data available according to the schema.
/// `requested_option` is the amount of data requested by the user.
@@ -86,10 +96,11 @@ impl BlockSegmentPostings {
/// term frequency blocks.
pub(crate) fn open(
doc_freq: u32,
bytes: OwnedBytes,
data: FileSlice,
mut record_option: IndexRecordOption,
requested_option: IndexRecordOption,
) -> io::Result<BlockSegmentPostings> {
let bytes = data.read_bytes()?;
let (skip_data_opt, postings_data) = split_into_skips_and_postings(doc_freq, bytes)?;
let skip_reader = match skip_data_opt {
Some(skip_data) => {
@@ -127,9 +138,76 @@ impl BlockSegmentPostings {
block_segment_postings.load_block();
Ok(block_segment_postings)
}
}
impl BlockSegmentPostings {
/// Returns the block_max_score for the current block.
/// It does not require the block to be loaded. For instance, it is ok to call this method
/// after having called `.shallow_advance(..)`.
///
/// See `TermScorer::block_max_score(..)` for more information.
pub fn block_max_score(
&mut self,
fieldnorm_reader: &FieldNormReader,
bm25_weight: &Bm25Weight,
) -> Score {
if let Some(score) = self.block_max_score_cache {
return score;
}
if let Some(skip_reader_max_score) = self.skip_reader.block_max_score(bm25_weight) {
// if we are on a full block, the skip reader should have the block max information
// for us
self.block_max_score_cache = Some(skip_reader_max_score);
return skip_reader_max_score;
}
// this is the last block of the segment posting list.
// If it is actually loaded, we can compute block max manually.
if self.block_is_loaded() {
let docs = self.doc_decoder.output_array().iter().cloned();
let freqs = self.freq_decoder.output_array().iter().cloned();
let bm25_scores = docs.zip(freqs).map(|(doc, term_freq)| {
let fieldnorm_id = fieldnorm_reader.fieldnorm_id(doc);
bm25_weight.score(fieldnorm_id, term_freq)
});
let block_max_score = max_score(bm25_scores).unwrap_or(0.0);
self.block_max_score_cache = Some(block_max_score);
return block_max_score;
}
// We do not have access to any good block max value. We return bm25_weight.max_score()
// as it is a valid upperbound.
//
// We do not cache it however, so that it gets computed when once block is loaded.
bm25_weight.max_score()
}
pub(crate) fn freq_reading_option(&self) -> FreqReadingOption {
self.freq_reading_option
}
// Resets the block segment postings on another position
// in the postings file.
//
// This is useful for enumerating through a list of terms,
// and consuming the associated posting lists while avoiding
// reallocating a `BlockSegmentPostings`.
//
// # Warning
//
// This does not reset the positions list.
pub(crate) fn reset(&mut self, doc_freq: u32, postings_data: OwnedBytes) -> io::Result<()> {
let (skip_data_opt, postings_data) =
split_into_skips_and_postings(doc_freq, postings_data)?;
self.data = postings_data;
self.block_max_score_cache = None;
self.block_loaded = false;
if let Some(skip_data) = skip_data_opt {
self.skip_reader.reset(skip_data, doc_freq);
} else {
self.skip_reader.reset(OwnedBytes::empty(), doc_freq);
}
self.doc_freq = doc_freq;
self.load_block();
Ok(())
}
/// Returns the overall number of documents in the block postings.
/// It does not take in account whether documents are deleted or not.
///
@@ -145,7 +223,7 @@ impl BlockSegmentPostings {
/// returned by `.docs()` is empty.
#[inline]
pub fn docs(&self) -> &[DocId] {
debug_assert!(self.block_loaded);
debug_assert!(self.block_is_loaded());
self.doc_decoder.output_array()
}
@@ -158,24 +236,35 @@ impl BlockSegmentPostings {
/// Return the array of `term freq` in the block.
#[inline]
pub fn freqs(&self) -> &[u32] {
debug_assert!(self.block_loaded);
debug_assert!(self.block_is_loaded());
self.freq_decoder.output_array()
}
/// Return the frequency at index `idx` of the block.
#[inline]
pub fn freq(&self, idx: usize) -> u32 {
debug_assert!(self.block_loaded);
debug_assert!(self.block_is_loaded());
self.freq_decoder.output(idx)
}
/// Returns the length of the current block.
///
/// All blocks have a length of `NUM_DOCS_PER_BLOCK`,
/// except the last block that may have a length
/// of any number between 1 and `NUM_DOCS_PER_BLOCK - 1`
#[inline]
pub fn block_len(&self) -> usize {
debug_assert!(self.block_is_loaded());
self.doc_decoder.output_len
}
/// Position on a block that may contains `target_doc`.
///
/// If all docs are smaller than target, the block loaded may be empty,
/// or be the last an incomplete VInt block.
pub fn seek(&mut self, target_doc: DocId) -> usize {
// Move to the block that might contain our document.
self.seek_block_without_loading(target_doc);
self.seek_block(target_doc);
self.load_block();
// At this point we are on the block that might contain our document.
@@ -192,76 +281,29 @@ impl BlockSegmentPostings {
doc
}
pub fn position_offset(&self) -> u64 {
pub(crate) fn position_offset(&self) -> u64 {
self.skip_reader.position_offset()
}
/// Advance to the next block.
pub fn advance(&mut self) {
self.skip_reader.advance();
self.block_loaded = false;
self.block_max_score_cache = None;
self.load_block();
}
/// Returns the block_max_score for the current block.
/// It does not require the block to be loaded. For instance, it is ok to call this method
/// after having called `.shallow_advance(..)`.
///
/// See `TermScorer::block_max_score(..)` for more information.
pub fn block_max_score(&mut self, bm25_weight: &Bm25Weight) -> Score {
if let Some(score) = self.block_max_score_cache {
return score;
}
if let Some(skip_reader_max_score) = self.skip_reader.block_max_score(bm25_weight) {
// if we are on a full block, the skip reader should have the block max information
// for us
self.block_max_score_cache = Some(skip_reader_max_score);
return skip_reader_max_score;
}
// We do not have access to any good block max value.
// It happens if this is the last block.
// We return bm25_weight.max_score() as it is a valid upperbound.
//
// We do not cache it however, so that it gets computed when once block is loaded.
bm25_weight.max_score()
}
}
impl BlockSegmentPostings {
/// Returns an empty segment postings object
pub fn empty() -> BlockSegmentPostings {
BlockSegmentPostings {
doc_decoder: BlockDecoder::with_val(TERMINATED),
block_loaded: true,
freq_decoder: BlockDecoder::with_val(1),
freq_reading_option: FreqReadingOption::NoFreq,
block_max_score_cache: None,
doc_freq: 0,
data: OwnedBytes::empty(),
skip_reader: SkipReader::new(OwnedBytes::empty(), 0, IndexRecordOption::Basic),
}
}
pub(crate) fn skip_reader(&self) -> &SkipReader {
&self.skip_reader
}
/// Dangerous API! This calls seeks the next block on the skip list,
/// but does not `.load_block()` afterwards.
///
/// `.load_block()` needs to be called manually afterwards.
/// If all docs are smaller than target, the block loaded may be empty,
/// or be the last an incomplete VInt block.
pub(crate) fn seek_block_without_loading(&mut self, target_doc: DocId) {
pub(crate) fn seek_block(&mut self, target_doc: DocId) {
if self.skip_reader.seek(target_doc) {
self.block_max_score_cache = None;
self.block_loaded = false;
}
}
pub(crate) fn block_is_loaded(&self) -> bool {
self.block_loaded
}
pub(crate) fn load_block(&mut self) {
if self.block_loaded {
if self.block_is_loaded() {
return;
}
let offset = self.skip_reader.byte_offset();
@@ -309,40 +351,68 @@ impl BlockSegmentPostings {
}
self.block_loaded = true;
}
/// Advance to the next block.
pub fn advance(&mut self) {
self.skip_reader.advance();
self.block_loaded = false;
self.block_max_score_cache = None;
self.load_block();
}
/// Returns an empty segment postings object
pub fn empty() -> BlockSegmentPostings {
BlockSegmentPostings {
doc_decoder: BlockDecoder::with_val(TERMINATED),
block_loaded: true,
freq_decoder: BlockDecoder::with_val(1),
freq_reading_option: FreqReadingOption::NoFreq,
block_max_score_cache: None,
doc_freq: 0,
data: OwnedBytes::empty(),
skip_reader: SkipReader::new(OwnedBytes::empty(), 0, IndexRecordOption::Basic),
}
}
pub(crate) fn skip_reader(&self) -> &SkipReader {
&self.skip_reader
}
}
#[cfg(test)]
mod tests {
use common::OwnedBytes;
use common::HasLen;
use super::BlockSegmentPostings;
use crate::codec::postings::PostingsSerializer;
use crate::codec::standard::postings::segment_postings::SegmentPostings;
use crate::codec::standard::postings::StandardPostingsSerializer;
use crate::docset::{DocSet, TERMINATED};
use crate::index::Index;
use crate::postings::compression::COMPRESSION_BLOCK_SIZE;
use crate::schema::IndexRecordOption;
use crate::postings::postings::Postings;
use crate::postings::SegmentPostings;
use crate::schema::{IndexRecordOption, Schema, Term, INDEXED};
use crate::DocId;
#[cfg(test)]
fn build_block_postings(docs: &[u32]) -> BlockSegmentPostings {
let doc_freq = docs.len() as u32;
let mut postings_serializer =
StandardPostingsSerializer::new(1.0f32, IndexRecordOption::Basic, None);
postings_serializer.new_term(docs.len() as u32, false);
for doc in docs {
postings_serializer.write_doc(*doc, 1u32);
}
let mut buffer: Vec<u8> = Vec::new();
postings_serializer
.close_term(doc_freq, &mut buffer)
.unwrap();
BlockSegmentPostings::open(
doc_freq,
OwnedBytes::new(buffer),
IndexRecordOption::Basic,
IndexRecordOption::Basic,
)
.unwrap()
#[test]
fn test_empty_segment_postings() {
let mut postings = SegmentPostings::empty();
assert_eq!(postings.doc(), TERMINATED);
assert_eq!(postings.advance(), TERMINATED);
assert_eq!(postings.advance(), TERMINATED);
assert_eq!(postings.doc_freq(), 0);
assert_eq!(postings.len(), 0);
}
#[test]
fn test_empty_postings_doc_returns_terminated() {
let mut postings = SegmentPostings::empty();
assert_eq!(postings.doc(), TERMINATED);
assert_eq!(postings.advance(), TERMINATED);
}
#[test]
fn test_empty_postings_doc_term_freq_returns_0() {
let postings = SegmentPostings::empty();
assert_eq!(postings.term_freq(), 1);
}
#[test]
@@ -357,7 +427,7 @@ mod tests {
#[test]
fn test_block_segment_postings() -> crate::Result<()> {
let mut block_segments = build_block_postings(&(0..100_000).collect::<Vec<u32>>());
let mut block_segments = build_block_postings(&(0..100_000).collect::<Vec<u32>>())?;
let mut offset: u32 = 0u32;
// checking that the `doc_freq` is correct
assert_eq!(block_segments.doc_freq(), 100_000);
@@ -382,7 +452,7 @@ mod tests {
doc_ids.push(129);
doc_ids.push(130);
{
let block_segments = build_block_postings(&doc_ids);
let block_segments = build_block_postings(&doc_ids)?;
let mut docset = SegmentPostings::from_block_postings(block_segments, None);
assert_eq!(docset.seek(128), 129);
assert_eq!(docset.doc(), 129);
@@ -391,7 +461,7 @@ mod tests {
assert_eq!(docset.advance(), TERMINATED);
}
{
let block_segments = build_block_postings(&doc_ids);
let block_segments = build_block_postings(&doc_ids).unwrap();
let mut docset = SegmentPostings::from_block_postings(block_segments, None);
assert_eq!(docset.seek(129), 129);
assert_eq!(docset.doc(), 129);
@@ -400,7 +470,7 @@ mod tests {
assert_eq!(docset.advance(), TERMINATED);
}
{
let block_segments = build_block_postings(&doc_ids);
let block_segments = build_block_postings(&doc_ids)?;
let mut docset = SegmentPostings::from_block_postings(block_segments, None);
assert_eq!(docset.doc(), 0);
assert_eq!(docset.seek(131), TERMINATED);
@@ -409,13 +479,38 @@ mod tests {
Ok(())
}
fn build_block_postings(docs: &[DocId]) -> crate::Result<BlockSegmentPostings> {
let mut schema_builder = Schema::builder();
let int_field = schema_builder.add_u64_field("id", INDEXED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_for_tests()?;
let mut last_doc = 0u32;
for &doc in docs {
for _ in last_doc..doc {
index_writer.add_document(doc!(int_field=>1u64))?;
}
index_writer.add_document(doc!(int_field=>0u64))?;
last_doc = doc + 1;
}
index_writer.commit()?;
let searcher = index.reader()?.searcher();
let segment_reader = searcher.segment_reader(0);
let inverted_index = segment_reader.inverted_index(int_field).unwrap();
let term = Term::from_field_u64(int_field, 0u64);
let term_info = inverted_index.get_term_info(&term)?.unwrap();
let block_postings = inverted_index
.read_block_postings_from_terminfo(&term_info, IndexRecordOption::Basic)?;
Ok(block_postings)
}
#[test]
fn test_block_segment_postings_seek() -> crate::Result<()> {
let mut docs = Vec::new();
let mut docs = vec![0];
for i in 0..1300 {
docs.push((i * i / 100) + i);
}
let mut block_postings = build_block_postings(&docs[..]);
let mut block_postings = build_block_postings(&docs[..])?;
for i in &[0, 424, 10000] {
block_postings.seek(*i);
let docs = block_postings.docs();
@@ -426,4 +521,40 @@ mod tests {
assert_eq!(block_postings.doc(COMPRESSION_BLOCK_SIZE - 1), TERMINATED);
Ok(())
}
#[test]
fn test_reset_block_segment_postings() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let int_field = schema_builder.add_u64_field("id", INDEXED);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
let mut index_writer = index.writer_for_tests()?;
// create two postings list, one containing even number,
// the other containing odd numbers.
for i in 0..6 {
let doc = doc!(int_field=> (i % 2) as u64);
index_writer.add_document(doc)?;
}
index_writer.commit()?;
let searcher = index.reader()?.searcher();
let segment_reader = searcher.segment_reader(0);
let mut block_segments;
{
let term = Term::from_field_u64(int_field, 0u64);
let inverted_index = segment_reader.inverted_index(int_field)?;
let term_info = inverted_index.get_term_info(&term)?.unwrap();
block_segments = inverted_index
.read_block_postings_from_terminfo(&term_info, IndexRecordOption::Basic)?;
}
assert_eq!(block_segments.docs(), &[0, 2, 4]);
{
let term = Term::from_field_u64(int_field, 1u64);
let inverted_index = segment_reader.inverted_index(int_field)?;
let term_info = inverted_index.get_term_info(&term)?.unwrap();
inverted_index.reset_block_postings_from_terminfo(&term_info, &mut block_segments)?;
}
assert_eq!(block_segments.docs(), &[1, 3, 5]);
Ok(())
}
}

View File

@@ -397,7 +397,10 @@ mod bench {
let mut seed: [u8; 32] = [0; 32];
seed[31] = seed_val;
let mut rng = StdRng::from_seed(seed);
(0u32..).filter(|_| rng.gen_bool(ratio)).take(n).collect()
(0u32..)
.filter(|_| rng.random_bool(ratio))
.take(n)
.collect()
}
pub fn generate_array(n: usize, ratio: f64) -> Vec<u32> {

View File

@@ -3,7 +3,6 @@ use std::io;
use common::json_path_writer::JSON_END_OF_PATH;
use stacker::Addr;
use crate::codec::Codec;
use crate::indexer::indexing_term::IndexingTerm;
use crate::indexer::path_to_unordered_id::OrderedPathId;
use crate::postings::postings_writer::SpecializedPostingsWriter;
@@ -23,6 +22,12 @@ pub(crate) struct JsonPostingsWriter<Rec: Recorder> {
non_str_posting_writer: SpecializedPostingsWriter<DocIdRecorder>,
}
impl<Rec: Recorder> From<JsonPostingsWriter<Rec>> for Box<dyn PostingsWriter> {
fn from(json_postings_writer: JsonPostingsWriter<Rec>) -> Box<dyn PostingsWriter> {
Box::new(json_postings_writer)
}
}
impl<Rec: Recorder> PostingsWriter for JsonPostingsWriter<Rec> {
#[inline]
fn subscribe(
@@ -53,12 +58,12 @@ impl<Rec: Recorder> PostingsWriter for JsonPostingsWriter<Rec> {
}
/// The actual serialization format is handled by the `PostingsSerializer`.
fn serialize<C: Codec>(
fn serialize(
&self,
ordered_term_addrs: &[(Field, OrderedPathId, &[u8], Addr)],
ordered_id_to_path: &[&str],
ctx: &IndexingContext,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer,
) -> io::Result<()> {
let mut term_buffer = JsonTermSerializer(Vec::with_capacity(48));
let mut buffer_lender = BufferLender::default();

View File

@@ -1,5 +1,5 @@
use crate::docset::{DocSet, TERMINATED};
use crate::postings::{DocFreq, Postings};
use crate::postings::{Postings, SegmentPostings};
use crate::DocId;
/// `LoadedPostings` is a `DocSet` and `Postings` implementation.
@@ -25,16 +25,16 @@ impl LoadedPostings {
/// Creates a new `LoadedPostings` from a `SegmentPostings`.
///
/// It will also preload positions, if positions are available in the SegmentPostings.
pub fn load(postings: &mut Box<dyn Postings>) -> LoadedPostings {
let num_docs: usize = u32::from(postings.doc_freq()) as usize;
pub fn load(segment_postings: &mut SegmentPostings) -> LoadedPostings {
let num_docs = segment_postings.doc_freq() as usize;
let mut doc_ids = Vec::with_capacity(num_docs);
let mut positions = Vec::with_capacity(num_docs);
let mut position_offsets = Vec::with_capacity(num_docs);
while postings.doc() != TERMINATED {
while segment_postings.doc() != TERMINATED {
position_offsets.push(positions.len() as u32);
doc_ids.push(postings.doc());
postings.append_positions_with_offset(0, &mut positions);
postings.advance();
doc_ids.push(segment_postings.doc());
segment_postings.append_positions_with_offset(0, &mut positions);
segment_postings.advance();
}
position_offsets.push(positions.len() as u32);
LoadedPostings {
@@ -101,14 +101,6 @@ impl Postings for LoadedPostings {
output.push(*pos + offset);
}
}
fn has_freq(&self) -> bool {
true
}
fn doc_freq(&self) -> DocFreq {
DocFreq::Exact(self.doc_ids.len() as u32)
}
}
#[cfg(test)]

View File

@@ -4,6 +4,7 @@ mod block_search;
pub(crate) use self::block_search::branchless_binary_search;
mod block_segment_postings;
pub(crate) mod compression;
mod indexing_context;
mod json_postings_writer;
@@ -12,22 +13,33 @@ mod per_field_postings_writer;
mod postings;
mod postings_writer;
mod recorder;
mod serializer;
mod segment_postings;
/// Serializer module for the inverted index
pub mod serializer;
mod skip;
mod term_info;
pub(crate) use loaded_postings::LoadedPostings;
pub use postings::DocFreq;
pub(crate) use stacker::compute_table_memory_size;
pub use self::block_segment_postings::BlockSegmentPostings;
pub(crate) use self::indexing_context::IndexingContext;
pub(crate) use self::per_field_postings_writer::PerFieldPostingsWriter;
pub use self::postings::Postings;
pub(crate) use self::postings_writer::{
serialize_postings, IndexingPosition, PostingsWriter, PostingsWriterEnum,
};
pub(crate) use self::postings_writer::{serialize_postings, IndexingPosition, PostingsWriter};
pub use self::segment_postings::SegmentPostings;
pub use self::serializer::{FieldSerializer, InvertedIndexSerializer};
pub(crate) use self::skip::{BlockInfo, SkipReader};
pub use self::term_info::TermInfo;
#[expect(clippy::enum_variant_names)]
#[derive(Debug, PartialEq, Clone, Copy, Eq)]
pub(crate) enum FreqReadingOption {
NoFreq,
SkipFreq,
ReadFreq,
}
#[cfg(test)]
pub(crate) mod tests {
use std::mem;
@@ -38,7 +50,6 @@ pub(crate) mod tests {
use crate::index::{Index, SegmentComponent, SegmentReader};
use crate::indexer::operation::AddOperation;
use crate::indexer::SegmentWriter;
use crate::postings::DocFreq;
use crate::query::Scorer;
use crate::schema::{
Field, IndexRecordOption, Schema, Term, TextFieldIndexing, TextOptions, INDEXED, TEXT,
@@ -269,11 +280,11 @@ pub(crate) mod tests {
}
{
let term_a = Term::from_field_text(text_field, "a");
let mut postings_a: Box<dyn Postings> = segment_reader
let mut postings_a = segment_reader
.inverted_index(term_a.field())?
.read_postings(&term_a, IndexRecordOption::WithFreqsAndPositions)?
.unwrap();
assert_eq!(postings_a.doc_freq(), DocFreq::Exact(1000));
assert_eq!(postings_a.len(), 1000);
assert_eq!(postings_a.doc(), 0);
assert_eq!(postings_a.term_freq(), 6);
postings_a.positions(&mut positions);
@@ -296,7 +307,7 @@ pub(crate) mod tests {
.inverted_index(term_e.field())?
.read_postings(&term_e, IndexRecordOption::WithFreqsAndPositions)?
.unwrap();
assert_eq!(postings_e.doc_freq(), DocFreq::Exact(1000 - 2));
assert_eq!(postings_e.len(), 1000 - 2);
for i in 2u32..1000u32 {
assert_eq!(postings_e.term_freq(), i);
postings_e.positions(&mut positions);
@@ -594,13 +605,13 @@ mod bench {
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
for _ in 0..posting_list_size {
let mut doc = TantivyDocument::default();
if rng.gen_bool(1f64 / 15f64) {
if rng.random_bool(1f64 / 15f64) {
doc.add_text(text_field, "a");
}
if rng.gen_bool(1f64 / 10f64) {
if rng.random_bool(1f64 / 10f64) {
doc.add_text(text_field, "b");
}
if rng.gen_bool(1f64 / 5f64) {
if rng.random_bool(1f64 / 5f64) {
doc.add_text(text_field, "c");
}
doc.add_text(text_field, "d");

View File

@@ -1,15 +1,16 @@
use crate::postings::json_postings_writer::JsonPostingsWriter;
use crate::postings::postings_writer::{PostingsWriterEnum, SpecializedPostingsWriter};
use crate::postings::postings_writer::SpecializedPostingsWriter;
use crate::postings::recorder::{DocIdRecorder, TermFrequencyRecorder, TfAndPositionRecorder};
use crate::postings::PostingsWriter;
use crate::schema::{Field, FieldEntry, FieldType, IndexRecordOption, Schema};
pub(crate) struct PerFieldPostingsWriter {
per_field_postings_writers: Vec<PostingsWriterEnum>,
per_field_postings_writers: Vec<Box<dyn PostingsWriter>>,
}
impl PerFieldPostingsWriter {
pub fn for_schema(schema: &Schema) -> Self {
let per_field_postings_writers: Vec<PostingsWriterEnum> = schema
let per_field_postings_writers = schema
.fields()
.map(|(_, field_entry)| posting_writer_from_field_entry(field_entry))
.collect();
@@ -18,16 +19,16 @@ impl PerFieldPostingsWriter {
}
}
pub(crate) fn get_for_field(&self, field: Field) -> &PostingsWriterEnum {
&self.per_field_postings_writers[field.field_id() as usize]
pub(crate) fn get_for_field(&self, field: Field) -> &dyn PostingsWriter {
self.per_field_postings_writers[field.field_id() as usize].as_ref()
}
pub(crate) fn get_for_field_mut(&mut self, field: Field) -> &mut PostingsWriterEnum {
&mut self.per_field_postings_writers[field.field_id() as usize]
pub(crate) fn get_for_field_mut(&mut self, field: Field) -> &mut dyn PostingsWriter {
self.per_field_postings_writers[field.field_id() as usize].as_mut()
}
}
fn posting_writer_from_field_entry(field_entry: &FieldEntry) -> PostingsWriterEnum {
fn posting_writer_from_field_entry(field_entry: &FieldEntry) -> Box<dyn PostingsWriter> {
match *field_entry.field_type() {
FieldType::Str(ref text_options) => text_options
.get_indexing_options()
@@ -50,7 +51,7 @@ fn posting_writer_from_field_entry(field_entry: &FieldEntry) -> PostingsWriterEn
| FieldType::Date(_)
| FieldType::Bytes(_)
| FieldType::IpAddr(_)
| FieldType::Facet(_) => <SpecializedPostingsWriter<DocIdRecorder>>::default().into(),
| FieldType::Facet(_) => Box::<SpecializedPostingsWriter<DocIdRecorder>>::default(),
FieldType::JsonObject(ref json_object_options) => {
if let Some(text_indexing_option) = json_object_options.get_text_indexing_options() {
match text_indexing_option.index_option() {

View File

@@ -1,25 +1,5 @@
use crate::docset::DocSet;
/// Result of the doc_freq method.
///
/// Postings can inform us that the document frequency is approximate.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum DocFreq {
/// The document frequency is approximate.
Approximate(u32),
/// The document frequency is exact.
Exact(u32),
}
impl From<DocFreq> for u32 {
fn from(doc_freq: DocFreq) -> Self {
match doc_freq {
DocFreq::Approximate(approximate_doc_freq) => approximate_doc_freq,
DocFreq::Exact(doc_freq) => doc_freq,
}
}
}
/// Postings (also called inverted list)
///
/// For a given term, it is the list of doc ids of the doc
@@ -34,9 +14,6 @@ pub trait Postings: DocSet + 'static {
/// The number of times the term appears in the document.
fn term_freq(&self) -> u32;
/// Returns the number of documents containing the term in the segment.
fn doc_freq(&self) -> DocFreq;
/// Returns the positions offsetted with a given value.
/// It is not necessary to clear the `output` before calling this method.
/// The output vector will be resized to the `term_freq`.
@@ -54,16 +31,6 @@ pub trait Postings: DocSet + 'static {
fn positions(&mut self, output: &mut Vec<u32>) {
self.positions_with_offset(0u32, output);
}
/// Returns true if the term_frequency is available.
///
/// This is a tricky question, because on JSON fields, it is possible
/// for a text term to have term freq, whereas a number term in the field has none.
///
/// This function returns whether the actual term has term frequencies or not.
/// In this above JSON field example, `has_freq` should return true for the
/// earlier and false for the latter.
fn has_freq(&self) -> bool;
}
impl Postings for Box<dyn Postings> {
@@ -74,12 +41,4 @@ impl Postings for Box<dyn Postings> {
fn append_positions_with_offset(&mut self, offset: u32, output: &mut Vec<u32>) {
(**self).append_positions_with_offset(offset, output);
}
fn has_freq(&self) -> bool {
(**self).has_freq()
}
fn doc_freq(&self) -> DocFreq {
(**self).doc_freq()
}
}

View File

@@ -4,14 +4,10 @@ use std::ops::Range;
use stacker::Addr;
use crate::codec::Codec;
use crate::fieldnorm::FieldNormReaders;
use crate::indexer::indexing_term::IndexingTerm;
use crate::indexer::path_to_unordered_id::OrderedPathId;
use crate::postings::json_postings_writer::JsonPostingsWriter;
use crate::postings::recorder::{
BufferLender, DocIdRecorder, Recorder, TermFrequencyRecorder, TfAndPositionRecorder,
};
use crate::postings::recorder::{BufferLender, Recorder};
use crate::postings::{
FieldSerializer, IndexingContext, InvertedIndexSerializer, PerFieldPostingsWriter,
};
@@ -49,12 +45,12 @@ fn make_field_partition(
/// Serialize the inverted index.
/// It pushes all term, one field at a time, towards the
/// postings serializer.
pub(crate) fn serialize_postings<C: Codec>(
pub(crate) fn serialize_postings(
ctx: IndexingContext,
schema: Schema,
per_field_postings_writers: &PerFieldPostingsWriter,
fieldnorm_readers: FieldNormReaders,
serializer: &mut InvertedIndexSerializer<C>,
serializer: &mut InvertedIndexSerializer,
) -> crate::Result<()> {
// Replace unordered ids by ordered ids to be able to sort
let unordered_id_to_ordered_id: Vec<OrderedPathId> =
@@ -104,141 +100,6 @@ pub(crate) struct IndexingPosition {
pub end_position: u32,
}
pub enum PostingsWriterEnum {
DocId(SpecializedPostingsWriter<DocIdRecorder>),
DocIdTf(SpecializedPostingsWriter<TermFrequencyRecorder>),
DocTfAndPosition(SpecializedPostingsWriter<TfAndPositionRecorder>),
JsonDocId(JsonPostingsWriter<DocIdRecorder>),
JsonDocIdTf(JsonPostingsWriter<TermFrequencyRecorder>),
JsonDocTfAndPosition(JsonPostingsWriter<TfAndPositionRecorder>),
}
impl From<SpecializedPostingsWriter<DocIdRecorder>> for PostingsWriterEnum {
fn from(doc_id_recorder_writer: SpecializedPostingsWriter<DocIdRecorder>) -> Self {
PostingsWriterEnum::DocId(doc_id_recorder_writer)
}
}
impl From<SpecializedPostingsWriter<TermFrequencyRecorder>> for PostingsWriterEnum {
fn from(doc_id_tf_recorder_writer: SpecializedPostingsWriter<TermFrequencyRecorder>) -> Self {
PostingsWriterEnum::DocIdTf(doc_id_tf_recorder_writer)
}
}
impl From<SpecializedPostingsWriter<TfAndPositionRecorder>> for PostingsWriterEnum {
fn from(
doc_id_tf_and_positions_recorder_writer: SpecializedPostingsWriter<TfAndPositionRecorder>,
) -> Self {
PostingsWriterEnum::DocTfAndPosition(doc_id_tf_and_positions_recorder_writer)
}
}
impl From<JsonPostingsWriter<DocIdRecorder>> for PostingsWriterEnum {
fn from(doc_id_recorder_writer: JsonPostingsWriter<DocIdRecorder>) -> Self {
PostingsWriterEnum::JsonDocId(doc_id_recorder_writer)
}
}
impl From<JsonPostingsWriter<TermFrequencyRecorder>> for PostingsWriterEnum {
fn from(doc_id_tf_recorder_writer: JsonPostingsWriter<TermFrequencyRecorder>) -> Self {
PostingsWriterEnum::JsonDocIdTf(doc_id_tf_recorder_writer)
}
}
impl From<JsonPostingsWriter<TfAndPositionRecorder>> for PostingsWriterEnum {
fn from(
doc_id_tf_and_positions_recorder_writer: JsonPostingsWriter<TfAndPositionRecorder>,
) -> Self {
PostingsWriterEnum::JsonDocTfAndPosition(doc_id_tf_and_positions_recorder_writer)
}
}
impl PostingsWriter for PostingsWriterEnum {
fn subscribe(&mut self, doc: DocId, pos: u32, term: &IndexingTerm, ctx: &mut IndexingContext) {
match self {
PostingsWriterEnum::DocId(writer) => writer.subscribe(doc, pos, term, ctx),
PostingsWriterEnum::DocIdTf(writer) => writer.subscribe(doc, pos, term, ctx),
PostingsWriterEnum::DocTfAndPosition(writer) => writer.subscribe(doc, pos, term, ctx),
PostingsWriterEnum::JsonDocId(writer) => writer.subscribe(doc, pos, term, ctx),
PostingsWriterEnum::JsonDocIdTf(writer) => writer.subscribe(doc, pos, term, ctx),
PostingsWriterEnum::JsonDocTfAndPosition(writer) => {
writer.subscribe(doc, pos, term, ctx)
}
}
}
fn serialize<C: Codec>(
&self,
term_addrs: &[(Field, OrderedPathId, &[u8], Addr)],
ordered_id_to_path: &[&str],
ctx: &IndexingContext,
serializer: &mut FieldSerializer<C>,
) -> io::Result<()> {
match self {
PostingsWriterEnum::DocId(writer) => {
writer.serialize(term_addrs, ordered_id_to_path, ctx, serializer)
}
PostingsWriterEnum::DocIdTf(writer) => {
writer.serialize(term_addrs, ordered_id_to_path, ctx, serializer)
}
PostingsWriterEnum::DocTfAndPosition(writer) => {
writer.serialize(term_addrs, ordered_id_to_path, ctx, serializer)
}
PostingsWriterEnum::JsonDocId(writer) => {
writer.serialize(term_addrs, ordered_id_to_path, ctx, serializer)
}
PostingsWriterEnum::JsonDocIdTf(writer) => {
writer.serialize(term_addrs, ordered_id_to_path, ctx, serializer)
}
PostingsWriterEnum::JsonDocTfAndPosition(writer) => {
writer.serialize(term_addrs, ordered_id_to_path, ctx, serializer)
}
}
}
/// Tokenize a text and subscribe all of its token.
fn index_text(
&mut self,
doc_id: DocId,
token_stream: &mut dyn TokenStream,
term_buffer: &mut IndexingTerm,
ctx: &mut IndexingContext,
indexing_position: &mut IndexingPosition,
) {
match self {
PostingsWriterEnum::DocId(writer) => {
writer.index_text(doc_id, token_stream, term_buffer, ctx, indexing_position)
}
PostingsWriterEnum::DocIdTf(writer) => {
writer.index_text(doc_id, token_stream, term_buffer, ctx, indexing_position)
}
PostingsWriterEnum::DocTfAndPosition(writer) => {
writer.index_text(doc_id, token_stream, term_buffer, ctx, indexing_position)
}
PostingsWriterEnum::JsonDocId(writer) => {
writer.index_text(doc_id, token_stream, term_buffer, ctx, indexing_position)
}
PostingsWriterEnum::JsonDocIdTf(writer) => {
writer.index_text(doc_id, token_stream, term_buffer, ctx, indexing_position)
}
PostingsWriterEnum::JsonDocTfAndPosition(writer) => {
writer.index_text(doc_id, token_stream, term_buffer, ctx, indexing_position)
}
}
}
fn total_num_tokens(&self) -> u64 {
match self {
PostingsWriterEnum::DocId(writer) => writer.total_num_tokens(),
PostingsWriterEnum::DocIdTf(writer) => writer.total_num_tokens(),
PostingsWriterEnum::DocTfAndPosition(writer) => writer.total_num_tokens(),
PostingsWriterEnum::JsonDocId(writer) => writer.total_num_tokens(),
PostingsWriterEnum::JsonDocIdTf(writer) => writer.total_num_tokens(),
PostingsWriterEnum::JsonDocTfAndPosition(writer) => writer.total_num_tokens(),
}
}
}
/// The `PostingsWriter` is in charge of receiving documenting
/// and building a `Segment` in anonymous memory.
///
@@ -255,12 +116,12 @@ pub(crate) trait PostingsWriter: Send + Sync {
/// Serializes the postings on disk.
/// The actual serialization format is handled by the `PostingsSerializer`.
fn serialize<C: Codec>(
fn serialize(
&self,
term_addrs: &[(Field, OrderedPathId, &[u8], Addr)],
ordered_id_to_path: &[&str],
ctx: &IndexingContext,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer,
) -> io::Result<()>;
/// Tokenize a text and subscribe all of its token.
@@ -310,14 +171,22 @@ pub(crate) struct SpecializedPostingsWriter<Rec: Recorder> {
_recorder_type: PhantomData<Rec>,
}
impl<Rec: Recorder> From<SpecializedPostingsWriter<Rec>> for Box<dyn PostingsWriter> {
fn from(
specialized_postings_writer: SpecializedPostingsWriter<Rec>,
) -> Box<dyn PostingsWriter> {
Box::new(specialized_postings_writer)
}
}
impl<Rec: Recorder> SpecializedPostingsWriter<Rec> {
#[inline]
pub(crate) fn serialize_one_term<C: Codec>(
pub(crate) fn serialize_one_term(
term: &[u8],
addr: Addr,
buffer_lender: &mut BufferLender,
ctx: &IndexingContext,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer,
) -> io::Result<()> {
let recorder: Rec = ctx.term_index.read(addr);
let term_doc_freq = recorder.term_doc_freq().unwrap_or(0u32);
@@ -358,12 +227,12 @@ impl<Rec: Recorder> PostingsWriter for SpecializedPostingsWriter<Rec> {
});
}
fn serialize<C: Codec>(
fn serialize(
&self,
term_addrs: &[(Field, OrderedPathId, &[u8], Addr)],
_ordered_id_to_path: &[&str],
ctx: &IndexingContext,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer,
) -> io::Result<()> {
let mut buffer_lender = BufferLender::default();
for (_field, _path_id, term, addr) in term_addrs {

View File

@@ -1,7 +1,6 @@
use common::read_u32_vint;
use stacker::{ExpUnrolledLinkedList, MemoryArena};
use crate::codec::Codec;
use crate::postings::FieldSerializer;
use crate::DocId;
@@ -68,10 +67,10 @@ pub(crate) trait Recorder: Copy + Default + Send + Sync + 'static {
/// Close the document. It will help record the term frequency.
fn close_doc(&mut self, arena: &mut MemoryArena);
/// Pushes the postings information to the serializer.
fn serialize<C: Codec>(
fn serialize(
&self,
arena: &MemoryArena,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer<'_>,
buffer_lender: &mut BufferLender,
);
/// Returns the number of document containing this term.
@@ -111,10 +110,10 @@ impl Recorder for DocIdRecorder {
#[inline]
fn close_doc(&mut self, _arena: &mut MemoryArena) {}
fn serialize<C: Codec>(
fn serialize(
&self,
arena: &MemoryArena,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer<'_>,
buffer_lender: &mut BufferLender,
) {
let buffer = buffer_lender.lend_u8();
@@ -179,10 +178,10 @@ impl Recorder for TermFrequencyRecorder {
self.current_tf = 0;
}
fn serialize<C: Codec>(
fn serialize(
&self,
arena: &MemoryArena,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer<'_>,
buffer_lender: &mut BufferLender,
) {
let buffer = buffer_lender.lend_u8();
@@ -236,10 +235,10 @@ impl Recorder for TfAndPositionRecorder {
self.stack.writer(arena).write_u32_vint(POSITION_END);
}
fn serialize<C: Codec>(
fn serialize(
&self,
arena: &MemoryArena,
serializer: &mut FieldSerializer<C>,
serializer: &mut FieldSerializer<'_>,
buffer_lender: &mut BufferLender,
) {
let (buffer_u8, buffer_positions) = buffer_lender.lend_all();

View File

@@ -1,13 +1,11 @@
use common::{BitSet, HasLen};
use common::HasLen;
use super::BlockSegmentPostings;
use crate::codec::postings::PostingsWithBlockMax;
use crate::docset::DocSet;
use crate::fastfield::AliveBitSet;
use crate::positions::PositionReader;
use crate::postings::compression::COMPRESSION_BLOCK_SIZE;
use crate::postings::{DocFreq, Postings};
use crate::query::Bm25Weight;
use crate::{DocId, Score};
use crate::postings::{BlockSegmentPostings, Postings};
use crate::{DocId, TERMINATED};
/// `SegmentPostings` represents the inverted list or postings associated with
/// a term in a `Segment`.
@@ -31,6 +29,31 @@ impl SegmentPostings {
}
}
/// Compute the number of non-deleted documents.
///
/// This method will clone and scan through the posting lists.
/// (this is a rather expensive operation).
pub fn doc_freq_given_deletes(&self, alive_bitset: &AliveBitSet) -> u32 {
let mut docset = self.clone();
let mut doc_freq = 0;
loop {
let doc = docset.doc();
if doc == TERMINATED {
return doc_freq;
}
if alive_bitset.is_alive(doc) {
doc_freq += 1u32;
}
docset.advance();
}
}
/// Returns the overall number of documents in the block postings.
/// It does not take in account whether documents are deleted or not.
pub fn doc_freq(&self) -> u32 {
self.block_cursor.doc_freq()
}
/// Creates a segment postings object with the given documents
/// and no frequency encoded.
///
@@ -41,19 +64,13 @@ impl SegmentPostings {
/// buffer with the serialized data.
#[cfg(test)]
pub fn create_from_docs(docs: &[u32]) -> SegmentPostings {
use common::OwnedBytes;
use crate::directory::FileSlice;
use crate::postings::serializer::PostingsSerializer;
use crate::schema::IndexRecordOption;
let mut buffer = Vec::new();
{
use crate::codec::postings::PostingsSerializer;
let mut postings_serializer =
crate::codec::standard::postings::StandardPostingsSerializer::new(
0.0,
IndexRecordOption::Basic,
None,
);
PostingsSerializer::new(0.0, IndexRecordOption::Basic, None);
postings_serializer.new_term(docs.len() as u32, false);
for &doc in docs {
postings_serializer.write_doc(doc, 1u32);
@@ -64,7 +81,7 @@ impl SegmentPostings {
}
let block_segment_postings = BlockSegmentPostings::open(
docs.len() as u32,
OwnedBytes::new(buffer),
FileSlice::from(buffer),
IndexRecordOption::Basic,
IndexRecordOption::Basic,
)
@@ -78,11 +95,9 @@ impl SegmentPostings {
doc_and_tfs: &[(u32, u32)],
fieldnorms: Option<&[u32]>,
) -> SegmentPostings {
use common::OwnedBytes;
use crate::codec::postings::PostingsSerializer as _;
use crate::codec::standard::postings::StandardPostingsSerializer;
use crate::directory::FileSlice;
use crate::fieldnorm::FieldNormReader;
use crate::postings::serializer::PostingsSerializer;
use crate::schema::IndexRecordOption;
use crate::Score;
let mut buffer: Vec<u8> = Vec::new();
@@ -99,7 +114,7 @@ impl SegmentPostings {
total_num_tokens as Score / fieldnorms.len() as Score
})
.unwrap_or(0.0);
let mut postings_serializer = StandardPostingsSerializer::new(
let mut postings_serializer = PostingsSerializer::new(
average_field_norm,
IndexRecordOption::WithFreqs,
fieldnorm_reader,
@@ -113,7 +128,7 @@ impl SegmentPostings {
.unwrap();
let block_segment_postings = BlockSegmentPostings::open(
doc_and_tfs.len() as u32,
OwnedBytes::new(buffer),
FileSlice::from(buffer),
IndexRecordOption::WithFreqs,
IndexRecordOption::WithFreqs,
)
@@ -143,6 +158,7 @@ impl DocSet for SegmentPostings {
// next needs to be called a first time to point to the correct element.
#[inline]
fn advance(&mut self) -> DocId {
debug_assert!(self.block_cursor.block_is_loaded());
if self.cur == COMPRESSION_BLOCK_SIZE - 1 {
self.cur = 0;
self.block_cursor.advance();
@@ -152,12 +168,20 @@ impl DocSet for SegmentPostings {
self.doc()
}
#[inline]
fn seek(&mut self, target: DocId) -> DocId {
debug_assert!(self.doc() <= target);
if self.doc() >= target {
return self.doc();
}
// As an optimization, if the block is already loaded, we can
// cheaply check the next doc.
self.cur = (self.cur + 1).min(COMPRESSION_BLOCK_SIZE - 1);
if self.doc() >= target {
return self.doc();
}
// Delegate block-local search to BlockSegmentPostings::seek, which returns
// the in-block index of the first doc >= target.
self.cur = self.block_cursor.seek(target);
@@ -175,19 +199,6 @@ impl DocSet for SegmentPostings {
fn size_hint(&self) -> u32 {
self.len() as u32
}
fn fill_bitset(&mut self, bitset: &mut BitSet) {
loop {
let docs = self.block_cursor.docs();
if docs.is_empty() {
break;
}
for &doc in docs {
bitset.insert(doc);
}
self.block_cursor.advance();
}
}
}
impl HasLen for SegmentPostings {
@@ -203,7 +214,7 @@ impl Postings for SegmentPostings {
///
/// # Panics
///
/// Will panics if called without having cagled advance before.
/// Will panics if called without having called advance before.
fn term_freq(&self) -> u32 {
debug_assert!(
// Here we do not use the len of `freqs()`
@@ -218,13 +229,6 @@ impl Postings for SegmentPostings {
self.block_cursor.freq(self.cur)
}
/// Returns the overall number of documents in the block postings.
/// It does not take in account whether documents are deleted or not.
#[inline(always)]
fn doc_freq(&self) -> DocFreq {
DocFreq::Exact(self.block_cursor.doc_freq())
}
fn append_positions_with_offset(&mut self, offset: u32, output: &mut Vec<u32>) {
let term_freq = self.term_freq();
let prev_len = output.len();
@@ -248,25 +252,6 @@ impl Postings for SegmentPostings {
}
}
}
fn has_freq(&self) -> bool {
!self.block_cursor.freqs().is_empty()
}
}
impl PostingsWithBlockMax for SegmentPostings {
fn seek_block_max(
&mut self,
target_doc: crate::DocId,
similarity_weight: &Bm25Weight,
) -> Score {
self.block_cursor.seek_block_without_loading(target_doc);
self.block_cursor.block_max_score(similarity_weight)
}
fn last_doc_in_block(&self) -> crate::DocId {
self.block_cursor.skip_reader().last_doc_in_block()
}
}
#[cfg(test)]
@@ -276,15 +261,14 @@ mod tests {
use super::SegmentPostings;
use crate::docset::{DocSet, TERMINATED};
use crate::postings::Postings;
use crate::fastfield::AliveBitSet;
use crate::postings::postings::Postings;
#[test]
fn test_empty_segment_postings() {
let mut postings = SegmentPostings::empty();
assert_eq!(postings.doc(), TERMINATED);
assert_eq!(postings.advance(), TERMINATED);
assert_eq!(postings.advance(), TERMINATED);
assert_eq!(postings.doc_freq(), crate::postings::DocFreq::Exact(0));
assert_eq!(postings.len(), 0);
}
@@ -300,4 +284,15 @@ mod tests {
let postings = SegmentPostings::empty();
assert_eq!(postings.term_freq(), 1);
}
#[test]
fn test_doc_freq() {
let docs = SegmentPostings::create_from_docs(&[0, 2, 10]);
assert_eq!(docs.doc_freq(), 3);
let alive_bitset = AliveBitSet::for_test_from_deleted_docs(&[2], 12);
assert_eq!(docs.doc_freq_given_deletes(&alive_bitset), 2);
let all_deleted =
AliveBitSet::for_test_from_deleted_docs(&[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], 12);
assert_eq!(docs.doc_freq_given_deletes(&all_deleted), 0);
}
}

View File

@@ -1,15 +1,17 @@
use std::cmp::Ordering;
use std::io::{self, Write};
use common::{BinarySerializable, CountingWriter};
use common::{BinarySerializable, CountingWriter, VInt};
use super::TermInfo;
use crate::codec::postings::PostingsSerializer;
use crate::codec::Codec;
use crate::directory::{CompositeWrite, WritePtr};
use crate::fieldnorm::FieldNormReader;
use crate::index::Segment;
use crate::positions::PositionSerializer;
use crate::schema::{Field, FieldEntry, FieldType, IndexRecordOption, Schema};
use crate::postings::compression::{BlockEncoder, VIntEncoder, COMPRESSION_BLOCK_SIZE};
use crate::postings::skip::SkipSerializer;
use crate::query::Bm25Weight;
use crate::schema::{Field, FieldEntry, IndexRecordOption, Schema};
use crate::termdict::TermDictionaryBuilder;
use crate::{DocId, Score};
@@ -44,27 +46,22 @@ use crate::{DocId, Score};
///
/// A description of the serialization format is
/// [available here](https://fulmicoton.gitbooks.io/tantivy-doc/content/inverted-index.html).
pub struct InvertedIndexSerializer<C: Codec> {
pub struct InvertedIndexSerializer {
terms_write: CompositeWrite<WritePtr>,
postings_write: CompositeWrite<WritePtr>,
positions_write: CompositeWrite<WritePtr>,
schema: Schema,
codec: C,
}
use crate::codec::postings::PostingsCodec;
impl<C: Codec> InvertedIndexSerializer<C> {
impl InvertedIndexSerializer {
/// Open a new `InvertedIndexSerializer` for the given segment
pub fn open(segment: &mut Segment<C>) -> crate::Result<InvertedIndexSerializer<C>> {
pub fn open(segment: &mut Segment) -> crate::Result<InvertedIndexSerializer> {
use crate::index::SegmentComponent::{Positions, Postings, Terms};
let codec = segment.index().codec().clone();
let inv_index_serializer = InvertedIndexSerializer {
terms_write: CompositeWrite::wrap(segment.open_write(Terms)?),
postings_write: CompositeWrite::wrap(segment.open_write(Postings)?),
positions_write: CompositeWrite::wrap(segment.open_write(Positions)?),
schema: segment.schema(),
codec,
};
Ok(inv_index_serializer)
}
@@ -78,20 +75,22 @@ impl<C: Codec> InvertedIndexSerializer<C> {
field: Field,
total_num_tokens: u64,
fieldnorm_reader: Option<FieldNormReader>,
) -> io::Result<FieldSerializer<'_, C>> {
) -> io::Result<FieldSerializer<'_>> {
let field_entry: &FieldEntry = self.schema.get_field_entry(field);
let term_dictionary_write = self.terms_write.for_field(field);
let postings_write = self.postings_write.for_field(field);
let positions_write = self.positions_write.for_field(field);
let field_type: FieldType = (*field_entry.field_type()).clone();
let index_record_option = field_entry
.field_type()
.index_record_option()
.unwrap_or(IndexRecordOption::Basic);
FieldSerializer::create(
&field_type,
index_record_option,
total_num_tokens,
term_dictionary_write,
postings_write,
positions_write,
fieldnorm_reader,
&self.codec,
)
}
@@ -106,40 +105,34 @@ impl<C: Codec> InvertedIndexSerializer<C> {
/// The field serializer is in charge of
/// the serialization of a specific field.
pub struct FieldSerializer<'a, C: Codec> {
term_dictionary_builder: TermDictionaryBuilder<&'a mut CountingWriter<WritePtr>>,
postings_serializer: <C::PostingsCodec as PostingsCodec>::PostingsSerializer,
positions_serializer_opt: Option<PositionSerializer<&'a mut CountingWriter<WritePtr>>>,
pub struct FieldSerializer<'a, W: Write = WritePtr> {
term_dictionary_builder: TermDictionaryBuilder<&'a mut CountingWriter<W>>,
postings_serializer: PostingsSerializer,
positions_serializer_opt: Option<PositionSerializer<&'a mut CountingWriter<W>>>,
current_term_info: TermInfo,
term_open: bool,
postings_write: &'a mut CountingWriter<WritePtr>,
postings_write: &'a mut CountingWriter<W>,
postings_start_offset: u64,
}
impl<'a, C: Codec> FieldSerializer<'a, C> {
fn create(
field_type: &FieldType,
impl<'a, W: Write> FieldSerializer<'a, W> {
/// Creates a new `FieldSerializer` for the given field type.
pub fn create(
index_record_option: IndexRecordOption,
total_num_tokens: u64,
term_dictionary_write: &'a mut CountingWriter<WritePtr>,
postings_write: &'a mut CountingWriter<WritePtr>,
positions_write: &'a mut CountingWriter<WritePtr>,
term_dictionary_write: &'a mut CountingWriter<W>,
postings_write: &'a mut CountingWriter<W>,
positions_write: &'a mut CountingWriter<W>,
fieldnorm_reader: Option<FieldNormReader>,
codec: &C,
) -> io::Result<FieldSerializer<'a, C>> {
) -> io::Result<FieldSerializer<'a, W>> {
total_num_tokens.serialize(postings_write)?;
let index_record_option = field_type
.index_record_option()
.unwrap_or(IndexRecordOption::Basic);
let term_dictionary_builder = TermDictionaryBuilder::create(term_dictionary_write)?;
let average_fieldnorm = fieldnorm_reader
.as_ref()
.map(|ff_reader| total_num_tokens as Score / ff_reader.num_docs() as Score)
.unwrap_or(0.0);
let postings_serializer = codec.postings_codec().new_serializer(
average_fieldnorm,
index_record_option,
fieldnorm_reader,
);
let postings_serializer =
PostingsSerializer::new(average_fieldnorm, index_record_option, fieldnorm_reader);
let positions_serializer_opt = if index_record_option.has_positions() {
Some(PositionSerializer::new(positions_write))
} else {
@@ -192,6 +185,7 @@ impl<'a, C: Codec> FieldSerializer<'a, C> {
"Called new_term, while the previous term was not closed."
);
self.term_open = true;
self.postings_serializer.clear();
self.current_term_info = self.current_term_info();
self.term_dictionary_builder.insert_key(term)?;
self.postings_serializer
@@ -199,6 +193,11 @@ impl<'a, C: Codec> FieldSerializer<'a, C> {
Ok(())
}
/// Starts the postings for a new term without recording term frequencies.
pub fn new_term_without_freq(&mut self, term: &[u8]) -> io::Result<()> {
self.new_term(term, 0, false)
}
/// Serialize the information that a document contains for the current term:
/// its term frequency, and the position deltas.
///
@@ -255,3 +254,234 @@ impl<'a, C: Codec> FieldSerializer<'a, C> {
Ok(())
}
}
struct Block {
doc_ids: [DocId; COMPRESSION_BLOCK_SIZE],
term_freqs: [u32; COMPRESSION_BLOCK_SIZE],
len: usize,
}
impl Block {
fn new() -> Self {
Block {
doc_ids: [0u32; COMPRESSION_BLOCK_SIZE],
term_freqs: [0u32; COMPRESSION_BLOCK_SIZE],
len: 0,
}
}
fn doc_ids(&self) -> &[DocId] {
&self.doc_ids[..self.len]
}
fn term_freqs(&self) -> &[u32] {
&self.term_freqs[..self.len]
}
fn clear(&mut self) {
self.len = 0;
}
fn append_doc(&mut self, doc: DocId, term_freq: u32) {
let len = self.len;
self.doc_ids[len] = doc;
self.term_freqs[len] = term_freq;
self.len = len + 1;
}
fn is_full(&self) -> bool {
self.len == COMPRESSION_BLOCK_SIZE
}
fn is_empty(&self) -> bool {
self.len == 0
}
fn last_doc(&self) -> DocId {
assert_eq!(self.len, COMPRESSION_BLOCK_SIZE);
self.doc_ids[COMPRESSION_BLOCK_SIZE - 1]
}
}
/// Serializer for postings lists.
pub struct PostingsSerializer {
last_doc_id_encoded: u32,
block_encoder: BlockEncoder,
block: Box<Block>,
postings_write: Vec<u8>,
skip_write: SkipSerializer,
mode: IndexRecordOption,
fieldnorm_reader: Option<FieldNormReader>,
bm25_weight: Option<Bm25Weight>,
avg_fieldnorm: Score, /* Average number of term in the field for that segment.
* this value is used to compute the block wand information. */
term_has_freq: bool,
}
impl PostingsSerializer {
/// Creates a new `PostingsSerializer`.
/// * avg_fieldnorm - average field norm for the field being serialized.
/// * mode - indexing options for the field being serialized.
pub fn new(
avg_fieldnorm: Score,
mode: IndexRecordOption,
fieldnorm_reader: Option<FieldNormReader>,
) -> PostingsSerializer {
PostingsSerializer {
block_encoder: BlockEncoder::new(),
block: Box::new(Block::new()),
postings_write: Vec::new(),
skip_write: SkipSerializer::new(),
last_doc_id_encoded: 0u32,
mode,
fieldnorm_reader,
bm25_weight: None,
avg_fieldnorm,
term_has_freq: false,
}
}
/// Starts the serialization for a new term.
/// * term_doc_freq - the number of documents containing the term.
pub fn new_term(&mut self, term_doc_freq: u32, record_term_freq: bool) {
self.bm25_weight = None;
self.term_has_freq = self.mode.has_freq() && record_term_freq;
if !self.term_has_freq {
return;
}
let num_docs_in_segment: u64 =
if let Some(fieldnorm_reader) = self.fieldnorm_reader.as_ref() {
fieldnorm_reader.num_docs() as u64
} else {
return;
};
if num_docs_in_segment == 0 {
return;
}
self.bm25_weight = Some(Bm25Weight::for_one_term_without_explain(
term_doc_freq as u64,
num_docs_in_segment,
self.avg_fieldnorm,
));
}
fn write_block(&mut self) {
{
// encode the doc ids
let (num_bits, block_encoded): (u8, &[u8]) = self
.block_encoder
.compress_block_sorted(self.block.doc_ids(), self.last_doc_id_encoded);
self.last_doc_id_encoded = self.block.last_doc();
self.skip_write
.write_doc(self.last_doc_id_encoded, num_bits);
// last el block 0, offset block 1,
self.postings_write.extend(block_encoded);
}
if self.term_has_freq {
// encode the term frequencies
let (num_bits, block_encoded): (u8, &[u8]) = self
.block_encoder
.compress_block_unsorted(self.block.term_freqs(), true);
self.postings_write.extend(block_encoded);
self.skip_write.write_term_freq(num_bits);
if self.mode.has_positions() {
// We serialize the sum of term freqs within the skip information
// in order to navigate through positions.
let sum_freq = self.block.term_freqs().iter().cloned().sum();
self.skip_write.write_total_term_freq(sum_freq);
}
let mut blockwand_params = (0u8, 0u32);
if let Some(bm25_weight) = self.bm25_weight.as_ref() {
if let Some(fieldnorm_reader) = self.fieldnorm_reader.as_ref() {
let docs = self.block.doc_ids().iter().cloned();
let term_freqs = self.block.term_freqs().iter().cloned();
let fieldnorms = docs.map(|doc| fieldnorm_reader.fieldnorm_id(doc));
blockwand_params = fieldnorms
.zip(term_freqs)
.max_by(
|(left_fieldnorm_id, left_term_freq),
(right_fieldnorm_id, right_term_freq)| {
let left_score =
bm25_weight.tf_factor(*left_fieldnorm_id, *left_term_freq);
let right_score =
bm25_weight.tf_factor(*right_fieldnorm_id, *right_term_freq);
left_score
.partial_cmp(&right_score)
.unwrap_or(Ordering::Equal)
},
)
.unwrap();
}
}
let (fieldnorm_id, term_freq) = blockwand_params;
self.skip_write.write_blockwand_max(fieldnorm_id, term_freq);
}
self.block.clear();
}
/// Register that the given document contains the current term.
/// * doc_id - the document id.
/// * term_freq - the term frequency within the document.
pub fn write_doc(&mut self, doc_id: DocId, term_freq: u32) {
self.block.append_doc(doc_id, term_freq);
if self.block.is_full() {
self.write_block();
}
}
/// Finish the serialization for this term.
pub fn close_term(
&mut self,
doc_freq: u32,
output_write: &mut impl std::io::Write,
) -> io::Result<()> {
if !self.block.is_empty() {
// we have doc ids waiting to be written
// this happens when the number of doc ids is
// not a perfect multiple of our block size.
//
// In that case, the remaining part is encoded
// using variable int encoding.
{
let block_encoded = self
.block_encoder
.compress_vint_sorted(self.block.doc_ids(), self.last_doc_id_encoded);
self.postings_write.write_all(block_encoded)?;
}
// ... Idem for term frequencies
if self.term_has_freq {
let block_encoded = self
.block_encoder
.compress_vint_unsorted(self.block.term_freqs());
self.postings_write.write_all(block_encoded)?;
}
self.block.clear();
}
if doc_freq >= COMPRESSION_BLOCK_SIZE as u32 {
let skip_data = self.skip_write.data();
VInt(skip_data.len() as u64).serialize(output_write)?;
output_write.write_all(skip_data)?;
}
output_write.write_all(&self.postings_write[..])?;
self.skip_write.clear();
self.postings_write.clear();
self.bm25_weight = None;
Ok(())
}
fn clear(&mut self) {
self.block.clear();
self.last_doc_id_encoded = 0;
}
}

View File

@@ -14,7 +14,11 @@ use crate::{DocId, Score, TERMINATED};
// (requiring a 6th bit), but the biggest doc_id we can want to encode is TERMINATED-1, which can
// be represented on 31b without delta encoding.
fn encode_bitwidth(bitwidth: u8, delta_1: bool) -> u8 {
assert!(bitwidth < 32);
assert!(
bitwidth < 32,
"bitwidth needs to be less than 32, but got {}",
bitwidth
);
bitwidth | ((delta_1 as u8) << 6)
}
@@ -142,6 +146,23 @@ impl SkipReader {
skip_reader
}
pub fn reset(&mut self, data: OwnedBytes, doc_freq: u32) {
self.last_doc_in_block = if doc_freq >= COMPRESSION_BLOCK_SIZE as u32 {
0
} else {
TERMINATED
};
self.last_doc_in_previous_block = 0u32;
self.owned_read = data;
self.block_info = BlockInfo::VInt { num_docs: doc_freq };
self.byte_offset = 0;
self.remaining_docs = doc_freq;
self.position_offset = 0u64;
if doc_freq >= COMPRESSION_BLOCK_SIZE as u32 {
self.read_block_info();
}
}
// Returns the block max score for this block if available.
//
// The block max score is available for all full bitpacked block,

View File

@@ -2,7 +2,7 @@ use crate::docset::{DocSet, COLLECT_BLOCK_BUFFER_LEN, TERMINATED};
use crate::index::SegmentReader;
use crate::query::boost_query::BoostScorer;
use crate::query::explanation::does_not_match;
use crate::query::{box_scorer, EnableScoring, Explanation, Query, Scorer, Weight};
use crate::query::{EnableScoring, Explanation, Query, Scorer, Weight};
use crate::{DocId, Score};
/// Query that matches all of the documents.
@@ -24,9 +24,9 @@ impl Weight for AllWeight {
fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>> {
let all_scorer = AllScorer::new(reader.max_doc());
if boost != 1.0 {
Ok(box_scorer(BoostScorer::new(all_scorer, boost)))
Ok(Box::new(BoostScorer::new(all_scorer, boost)))
} else {
Ok(box_scorer(all_scorer))
Ok(Box::new(all_scorer))
}
}

View File

@@ -10,7 +10,7 @@ use crate::postings::TermInfo;
use crate::query::{BitSetDocSet, ConstScorer, Explanation, Scorer, Weight};
use crate::schema::{Field, IndexRecordOption};
use crate::termdict::{TermDictionary, TermStreamer};
use crate::{DocId, DocSet, Score, TantivyError};
use crate::{DocId, Score, TantivyError};
/// A weight struct for Fuzzy Term and Regex Queries
pub struct AutomatonWeight<A> {
@@ -92,9 +92,18 @@ where
let mut term_stream = self.automaton_stream(term_dict)?;
while term_stream.advance() {
let term_info = term_stream.value();
let mut block_segment_postings =
inverted_index.read_postings_from_terminfo(term_info, IndexRecordOption::Basic)?;
block_segment_postings.fill_bitset(&mut doc_bitset);
let mut block_segment_postings = inverted_index
.read_block_postings_from_terminfo(term_info, IndexRecordOption::Basic)?;
loop {
let docs = block_segment_postings.docs();
if docs.is_empty() {
break;
}
for &doc in docs {
doc_bitset.insert(doc);
}
block_segment_postings.advance();
}
}
let doc_bitset = BitSetDocSet::from(doc_bitset);
let const_scorer = ConstScorer::new(doc_bitset, boost);

View File

@@ -24,13 +24,6 @@ impl BitSetDocSet {
self.cursor_bucket = bucket_addr;
self.cursor_tinybitset = self.docs.tinyset(bucket_addr);
}
/// Returns the number of documents in the bitset.
///
/// This call is not free: it will bitcount the number of bits in the bitset.
pub fn doc_freq(&self) -> u32 {
self.docs.len() as u32
}
}
impl From<BitSet> for BitSetDocSet {

View File

@@ -1,6 +1,5 @@
use std::ops::{Deref, DerefMut};
use crate::codec::postings::PostingsWithBlockMax;
use crate::query::term_query::TermScorer;
use crate::query::Scorer;
use crate::{DocId, DocSet, Score, TERMINATED};
@@ -14,8 +13,8 @@ use crate::{DocId, DocSet, Score, TERMINATED};
/// We always have `before_pivot_len` < `pivot_len`.
///
/// `None` is returned if we establish that no document can exceed the threshold.
fn find_pivot_doc<TPostings: PostingsWithBlockMax>(
term_scorers: &[TermScorerWithMaxScore<TPostings>],
fn find_pivot_doc(
term_scorers: &[TermScorerWithMaxScore],
threshold: Score,
) -> Option<(usize, usize, DocId)> {
let mut max_score = 0.0;
@@ -47,8 +46,8 @@ fn find_pivot_doc<TPostings: PostingsWithBlockMax>(
/// the next doc candidate defined by the min of `last_doc_in_block + 1` for
/// scorer in scorers[..pivot_len] and `scorer.doc()` for scorer in scorers[pivot_len..].
/// Note: before and after calling this method, scorers need to be sorted by their `.doc()`.
fn block_max_was_too_low_advance_one_scorer<TPostings: PostingsWithBlockMax>(
scorers: &mut [TermScorerWithMaxScore<TPostings>],
fn block_max_was_too_low_advance_one_scorer(
scorers: &mut [TermScorerWithMaxScore],
pivot_len: usize,
) {
debug_assert!(is_sorted(scorers.iter().map(|scorer| scorer.doc())));
@@ -83,10 +82,7 @@ fn block_max_was_too_low_advance_one_scorer<TPostings: PostingsWithBlockMax>(
// Given a list of term_scorers and a `ord` and assuming that `term_scorers[ord]` is sorted
// except term_scorers[ord] that might be in advance compared to its ranks,
// bubble up term_scorers[ord] in order to restore the ordering.
fn restore_ordering<TPostings: PostingsWithBlockMax>(
term_scorers: &mut [TermScorerWithMaxScore<TPostings>],
ord: usize,
) {
fn restore_ordering(term_scorers: &mut [TermScorerWithMaxScore], ord: usize) {
let doc = term_scorers[ord].doc();
for i in ord + 1..term_scorers.len() {
if term_scorers[i].doc() >= doc {
@@ -101,10 +97,9 @@ fn restore_ordering<TPostings: PostingsWithBlockMax>(
// If this works, return true.
// If this fails (ie: one of the term_scorer does not contain `pivot_doc` and seek goes past the
// pivot), reorder the term_scorers to ensure the list is still sorted and returns `false`.
// If a term_scorer reach TERMINATED in the process return false remove the term_scorer and
// return.
fn align_scorers<TPostings: PostingsWithBlockMax>(
term_scorers: &mut Vec<TermScorerWithMaxScore<TPostings>>,
// If a term_scorer reach TERMINATED in the process return false remove the term_scorer and return.
fn align_scorers(
term_scorers: &mut Vec<TermScorerWithMaxScore>,
pivot_doc: DocId,
before_pivot_len: usize,
) -> bool {
@@ -131,10 +126,7 @@ fn align_scorers<TPostings: PostingsWithBlockMax>(
// Assumes terms_scorers[..pivot_len] are positioned on the same doc (pivot_doc).
// Advance term_scorers[..pivot_len] and out of these removes the terminated scores.
// Restores the ordering of term_scorers.
fn advance_all_scorers_on_pivot<TPostings: PostingsWithBlockMax>(
term_scorers: &mut Vec<TermScorerWithMaxScore<TPostings>>,
pivot_len: usize,
) {
fn advance_all_scorers_on_pivot(term_scorers: &mut Vec<TermScorerWithMaxScore>, pivot_len: usize) {
for term_scorer in &mut term_scorers[..pivot_len] {
term_scorer.advance();
}
@@ -153,12 +145,12 @@ fn advance_all_scorers_on_pivot<TPostings: PostingsWithBlockMax>(
/// Implements the WAND (Weak AND) algorithm for dynamic pruning
/// described in the paper "Faster Top-k Document Retrieval Using Block-Max Indexes".
/// Link: <http://engineering.nyu.edu/~suel/papers/bmw.pdf>
pub fn block_wand<TPostings: PostingsWithBlockMax>(
mut scorers: Vec<TermScorer<TPostings>>,
pub fn block_wand(
mut scorers: Vec<TermScorer>,
mut threshold: Score,
callback: &mut dyn FnMut(u32, Score) -> Score,
) {
let mut scorers: Vec<TermScorerWithMaxScore<TPostings>> = scorers
let mut scorers: Vec<TermScorerWithMaxScore> = scorers
.iter_mut()
.map(TermScorerWithMaxScore::from)
.collect();
@@ -174,7 +166,10 @@ pub fn block_wand<TPostings: PostingsWithBlockMax>(
let block_max_score_upperbound: Score = scorers[..pivot_len]
.iter_mut()
.map(|scorer| scorer.seek_block_max(pivot_doc))
.map(|scorer| {
scorer.seek_block(pivot_doc);
scorer.block_max_score()
})
.sum();
// Beware after shallow advance, skip readers can be in advance compared to
@@ -225,22 +220,21 @@ pub fn block_wand<TPostings: PostingsWithBlockMax>(
/// - On a block, advance until the end and execute `callback` when the doc score is greater or
/// equal to the `threshold`.
pub fn block_wand_single_scorer(
mut scorer: TermScorer<impl PostingsWithBlockMax>,
mut scorer: TermScorer,
mut threshold: Score,
callback: &mut dyn FnMut(u32, Score) -> Score,
) {
let mut doc = scorer.doc();
let mut block_max_score = scorer.seek_block_max(doc);
loop {
// We position the scorer on a block that can reach
// the threshold.
while block_max_score < threshold {
while scorer.block_max_score() < threshold {
let last_doc_in_block = scorer.last_doc_in_block();
if last_doc_in_block == TERMINATED {
return;
}
doc = last_doc_in_block + 1;
block_max_score = scorer.seek_block_max(doc);
scorer.seek_block(doc);
}
// Seek will effectively load that block.
doc = scorer.seek(doc);
@@ -262,33 +256,31 @@ pub fn block_wand_single_scorer(
}
}
doc += 1;
block_max_score = scorer.seek_block_max(doc);
scorer.seek_block(doc);
}
}
struct TermScorerWithMaxScore<'a, TPostings: PostingsWithBlockMax> {
scorer: &'a mut TermScorer<TPostings>,
struct TermScorerWithMaxScore<'a> {
scorer: &'a mut TermScorer,
max_score: Score,
}
impl<'a, TPostings: PostingsWithBlockMax> From<&'a mut TermScorer<TPostings>>
for TermScorerWithMaxScore<'a, TPostings>
{
fn from(scorer: &'a mut TermScorer<TPostings>) -> Self {
impl<'a> From<&'a mut TermScorer> for TermScorerWithMaxScore<'a> {
fn from(scorer: &'a mut TermScorer) -> Self {
let max_score = scorer.max_score();
TermScorerWithMaxScore { scorer, max_score }
}
}
impl<TPostings: PostingsWithBlockMax> Deref for TermScorerWithMaxScore<'_, TPostings> {
type Target = TermScorer<TPostings>;
impl Deref for TermScorerWithMaxScore<'_> {
type Target = TermScorer;
fn deref(&self) -> &Self::Target {
self.scorer
}
}
impl<TPostings: PostingsWithBlockMax> DerefMut for TermScorerWithMaxScore<'_, TPostings> {
impl DerefMut for TermScorerWithMaxScore<'_> {
fn deref_mut(&mut self) -> &mut Self::Target {
self.scorer
}

View File

@@ -2,16 +2,23 @@ use std::collections::HashMap;
use crate::docset::COLLECT_BLOCK_BUFFER_LEN;
use crate::index::SegmentReader;
use crate::postings::FreqReadingOption;
use crate::query::disjunction::Disjunction;
use crate::query::explanation::does_not_match;
use crate::query::score_combiner::{DoNothingCombiner, ScoreCombiner};
use crate::query::weight::{for_each_docset_buffered, for_each_scorer};
use crate::query::term_query::TermScorer;
use crate::query::weight::{for_each_docset_buffered, for_each_pruning_scorer, for_each_scorer};
use crate::query::{
box_scorer, intersect_scorers, AllScorer, BufferedUnionScorer, EmptyScorer, Exclude,
Explanation, Occur, RequiredOptionalScorer, Scorer, Weight,
intersect_scorers, AllScorer, BufferedUnionScorer, EmptyScorer, Exclude, Explanation, Occur,
RequiredOptionalScorer, Scorer, Weight,
};
use crate::{DocId, Score};
enum SpecializedScorer {
TermUnion(Vec<TermScorer>),
Other(Box<dyn Scorer>),
}
fn scorer_disjunction<TScoreCombiner>(
scorers: Vec<Box<dyn Scorer>>,
score_combiner: TScoreCombiner,
@@ -25,7 +32,7 @@ where
if scorers.len() == 1 {
return scorers.into_iter().next().unwrap(); // Safe unwrap.
}
box_scorer(Disjunction::new(
Box::new(Disjunction::new(
scorers,
score_combiner,
minimum_match_required,
@@ -37,18 +44,56 @@ fn scorer_union<TScoreCombiner>(
scorers: Vec<Box<dyn Scorer>>,
score_combiner_fn: impl Fn() -> TScoreCombiner,
num_docs: u32,
) -> Box<dyn Scorer>
) -> SpecializedScorer
where
TScoreCombiner: ScoreCombiner,
{
match scorers.len() {
0 => box_scorer(EmptyScorer),
1 => scorers.into_iter().next().unwrap(),
_ => box_scorer(BufferedUnionScorer::build(
scorers,
score_combiner_fn,
num_docs,
)),
assert!(!scorers.is_empty());
if scorers.len() == 1 {
return SpecializedScorer::Other(scorers.into_iter().next().unwrap()); //< we checked the size beforehand
}
{
let is_all_term_queries = scorers.iter().all(|scorer| scorer.is::<TermScorer>());
if is_all_term_queries {
let scorers: Vec<TermScorer> = scorers
.into_iter()
.map(|scorer| *(scorer.downcast::<TermScorer>().map_err(|_| ()).unwrap()))
.collect();
if scorers
.iter()
.all(|scorer| scorer.freq_reading_option() == FreqReadingOption::ReadFreq)
{
// Block wand is only available if we read frequencies.
return SpecializedScorer::TermUnion(scorers);
} else {
return SpecializedScorer::Other(Box::new(BufferedUnionScorer::build(
scorers,
score_combiner_fn,
num_docs,
)));
}
}
}
SpecializedScorer::Other(Box::new(BufferedUnionScorer::build(
scorers,
score_combiner_fn,
num_docs,
)))
}
fn into_box_scorer<TScoreCombiner: ScoreCombiner>(
scorer: SpecializedScorer,
score_combiner_fn: impl Fn() -> TScoreCombiner,
num_docs: u32,
) -> Box<dyn Scorer> {
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
let union_scorer =
BufferedUnionScorer::build(term_scorers, score_combiner_fn, num_docs);
Box::new(union_scorer)
}
SpecializedScorer::Other(scorer) => scorer,
}
}
@@ -65,7 +110,7 @@ fn effective_must_scorer(
if must_scorers.is_empty() {
if removed_all_scorer_count > 0 {
// Had AllScorer(s) only - all docs match
Some(box_scorer(AllScorer::new(max_doc)))
Some(Box::new(AllScorer::new(max_doc)))
} else {
// No MUST constraint at all
None
@@ -83,26 +128,28 @@ fn effective_must_scorer(
/// When `scoring_enabled` is false, we can just return AllScorer alone since
/// we don't need score contributions from the should_scorer.
fn effective_should_scorer_for_union<TScoreCombiner: ScoreCombiner>(
should_scorer: Box<dyn Scorer>,
should_scorer: SpecializedScorer,
removed_all_scorer_count: usize,
max_doc: DocId,
num_docs: u32,
score_combiner_fn: impl Fn() -> TScoreCombiner,
scoring_enabled: bool,
) -> Box<dyn Scorer> {
) -> SpecializedScorer {
if removed_all_scorer_count > 0 {
if scoring_enabled {
// Need to union to get score contributions from both
let all_scorers: Vec<Box<dyn Scorer>> =
vec![should_scorer, box_scorer(AllScorer::new(max_doc))];
box_scorer(BufferedUnionScorer::build(
let all_scorers: Vec<Box<dyn Scorer>> = vec![
into_box_scorer(should_scorer, &score_combiner_fn, num_docs),
Box::new(AllScorer::new(max_doc)),
];
SpecializedScorer::Other(Box::new(BufferedUnionScorer::build(
all_scorers,
score_combiner_fn,
num_docs,
))
)))
} else {
// Scoring disabled - AllScorer alone is sufficient
box_scorer(AllScorer::new(max_doc))
SpecializedScorer::Other(Box::new(AllScorer::new(max_doc)))
}
} else {
should_scorer
@@ -113,9 +160,9 @@ enum ShouldScorersCombinationMethod {
// Should scorers are irrelevant.
Ignored,
// Only contributes to final score.
Optional(Box<dyn Scorer>),
Optional(SpecializedScorer),
// Regardless of score, the should scorers may impact whether a document is matching or not.
Required(Box<dyn Scorer>),
Required(SpecializedScorer),
}
/// Weight associated to the `BoolQuery`.
@@ -177,7 +224,7 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
reader: &SegmentReader,
boost: Score,
score_combiner_fn: impl Fn() -> TComplexScoreCombiner,
) -> crate::Result<Box<dyn Scorer>> {
) -> crate::Result<SpecializedScorer> {
let num_docs = reader.num_docs();
let mut per_occur_scorers = self.per_occur_scorers(reader, boost)?;
@@ -187,7 +234,7 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
let must_special_scorer_counts = remove_and_count_all_and_empty_scorers(&mut must_scorers);
if must_special_scorer_counts.num_empty_scorers > 0 {
return Ok(box_scorer(EmptyScorer));
return Ok(SpecializedScorer::Other(Box::new(EmptyScorer)));
}
let mut should_scorers = per_occur_scorers.remove(&Occur::Should).unwrap_or_default();
@@ -202,7 +249,7 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
if exclude_special_scorer_counts.num_all_scorers > 0 {
// We exclude all documents at one point.
return Ok(box_scorer(EmptyScorer));
return Ok(SpecializedScorer::Other(Box::new(EmptyScorer)));
}
let effective_minimum_number_should_match = self
@@ -214,7 +261,7 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
if effective_minimum_number_should_match > num_of_should_scorers {
// We don't have enough scorers to satisfy the minimum number of should matches.
// The request will match no documents.
return Ok(box_scorer(EmptyScorer));
return Ok(SpecializedScorer::Other(Box::new(EmptyScorer)));
}
match effective_minimum_number_should_match {
0 if num_of_should_scorers == 0 => ShouldScorersCombinationMethod::Ignored,
@@ -234,22 +281,16 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
must_scorers.append(&mut should_scorers);
ShouldScorersCombinationMethod::Ignored
}
_ => ShouldScorersCombinationMethod::Required(scorer_disjunction(
should_scorers,
score_combiner_fn(),
effective_minimum_number_should_match,
_ => ShouldScorersCombinationMethod::Required(SpecializedScorer::Other(
scorer_disjunction(
should_scorers,
score_combiner_fn(),
effective_minimum_number_should_match,
),
)),
}
};
let exclude_scorer_opt: Option<Box<dyn Scorer>> = if exclude_scorers.is_empty() {
None
} else {
let exclude_scorers_union: Box<dyn Scorer> =
scorer_union(exclude_scorers, DoNothingCombiner::default, num_docs);
Some(exclude_scorers_union)
};
let include_scorer = match (should_scorers, must_scorers) {
(ShouldScorersCombinationMethod::Ignored, must_scorers) => {
// No SHOULD clauses (or they were absorbed into MUST).
@@ -262,8 +303,8 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
reader.max_doc(),
num_docs,
)
.unwrap_or_else(|| box_scorer(EmptyScorer));
boxed_scorer
.unwrap_or_else(|| Box::new(EmptyScorer));
SpecializedScorer::Other(boxed_scorer)
}
(ShouldScorersCombinationMethod::Optional(should_scorer), must_scorers) => {
// Optional SHOULD: contributes to scoring but not required for matching.
@@ -288,12 +329,16 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
Some(must_scorer) => {
// Has MUST constraint: SHOULD only affects scoring.
if self.scoring_enabled {
box_scorer(RequiredOptionalScorer::<_, _, TScoreCombiner>::new(
SpecializedScorer::Other(Box::new(RequiredOptionalScorer::<
_,
_,
TScoreCombiner,
>::new(
must_scorer,
should_scorer,
))
into_box_scorer(should_scorer, &score_combiner_fn, num_docs),
)))
} else {
must_scorer
SpecializedScorer::Other(must_scorer)
}
}
}
@@ -313,16 +358,33 @@ impl<TScoreCombiner: ScoreCombiner> BooleanWeight<TScoreCombiner> {
}
Some(must_scorer) => {
// Has MUST constraint: intersect MUST with SHOULD.
intersect_scorers(vec![must_scorer, should_scorer], num_docs)
let should_boxed =
into_box_scorer(should_scorer, &score_combiner_fn, num_docs);
SpecializedScorer::Other(intersect_scorers(
vec![must_scorer, should_boxed],
num_docs,
))
}
}
}
};
if let Some(exclude_scorer) = exclude_scorer_opt {
Ok(box_scorer(Exclude::new(include_scorer, exclude_scorer)))
} else {
Ok(include_scorer)
if exclude_scorers.is_empty() {
return Ok(include_scorer);
}
let include_scorer_boxed = into_box_scorer(include_scorer, &score_combiner_fn, num_docs);
let scorer: Box<dyn Scorer> = if exclude_scorers.len() == 1 {
let exclude_scorer = exclude_scorers.pop().unwrap();
match exclude_scorer.downcast::<TermScorer>() {
// Cast to TermScorer succeeded
Ok(exclude_scorer) => Box::new(Exclude::new(include_scorer_boxed, *exclude_scorer)),
// We get back the original Box<dyn Scorer>
Err(exclude_scorer) => Box::new(Exclude::new(include_scorer_boxed, exclude_scorer)),
}
} else {
Box::new(Exclude::new(include_scorer_boxed, exclude_scorers))
};
Ok(SpecializedScorer::Other(scorer))
}
}
@@ -352,6 +414,7 @@ fn remove_and_count_all_and_empty_scorers(
impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombiner> {
fn scorer(&self, reader: &SegmentReader, boost: Score) -> crate::Result<Box<dyn Scorer>> {
let num_docs = reader.num_docs();
if self.weights.is_empty() {
Ok(Box::new(EmptyScorer))
} else if self.weights.len() == 1 {
@@ -363,8 +426,14 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
}
} else if self.scoring_enabled {
self.complex_scorer(reader, boost, &self.score_combiner_fn)
.map(|specialized_scorer| {
into_box_scorer(specialized_scorer, &self.score_combiner_fn, num_docs)
})
} else {
self.complex_scorer(reader, boost, DoNothingCombiner::default)
.map(|specialized_scorer| {
into_box_scorer(specialized_scorer, DoNothingCombiner::default, num_docs)
})
}
}
@@ -393,8 +462,20 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
reader: &SegmentReader,
callback: &mut dyn FnMut(DocId, Score),
) -> crate::Result<()> {
let mut scorer = self.complex_scorer(reader, 1.0, &self.score_combiner_fn)?;
for_each_scorer(scorer.as_mut(), callback);
let scorer = self.complex_scorer(reader, 1.0, &self.score_combiner_fn)?;
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
let mut union_scorer = BufferedUnionScorer::build(
term_scorers,
&self.score_combiner_fn,
reader.num_docs(),
);
for_each_scorer(&mut union_scorer, callback);
}
SpecializedScorer::Other(mut scorer) => {
for_each_scorer(scorer.as_mut(), callback);
}
}
Ok(())
}
@@ -403,9 +484,22 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
reader: &SegmentReader,
callback: &mut dyn FnMut(&[DocId]),
) -> crate::Result<()> {
let mut scorer = self.complex_scorer(reader, 1.0, || DoNothingCombiner)?;
let scorer = self.complex_scorer(reader, 1.0, || DoNothingCombiner)?;
let mut buffer = [0u32; COLLECT_BLOCK_BUFFER_LEN];
for_each_docset_buffered(scorer.as_mut(), &mut buffer, callback);
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
let mut union_scorer = BufferedUnionScorer::build(
term_scorers,
&self.score_combiner_fn,
reader.num_docs(),
);
for_each_docset_buffered(&mut union_scorer, &mut buffer, callback);
}
SpecializedScorer::Other(mut scorer) => {
for_each_docset_buffered(scorer.as_mut(), &mut buffer, callback);
}
}
Ok(())
}
@@ -426,7 +520,14 @@ impl<TScoreCombiner: ScoreCombiner + Sync> Weight for BooleanWeight<TScoreCombin
callback: &mut dyn FnMut(DocId, Score) -> Score,
) -> crate::Result<()> {
let scorer = self.complex_scorer(reader, 1.0, &self.score_combiner_fn)?;
reader.codec.for_each_pruning(threshold, scorer, callback);
match scorer {
SpecializedScorer::TermUnion(term_scorers) => {
super::block_wand(term_scorers, threshold, callback);
}
SpecializedScorer::Other(mut scorer) => {
for_each_pruning_scorer(scorer.as_mut(), threshold, callback);
}
}
Ok(())
}
}

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