mirror of
https://github.com/quickwit-oss/tantivy.git
synced 2025-12-28 04:52:55 +00:00
Compare commits
332 Commits
0.20.2
...
ownedbytes
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
c6e77d27c6 | ||
|
|
db6587ed9b | ||
|
|
3fa90e70e2 | ||
|
|
6ab4102253 | ||
|
|
11c6329ca5 | ||
|
|
ab8bb93928 | ||
|
|
2b668bd2bf | ||
|
|
97a7137ef8 | ||
|
|
ffa7cdf397 | ||
|
|
caf1275e60 | ||
|
|
fb12b7be28 | ||
|
|
6f77083493 | ||
|
|
cd7745da7a | ||
|
|
eb8304dee9 | ||
|
|
e5638112a9 | ||
|
|
81110152fb | ||
|
|
ae88a7ece5 | ||
|
|
bdd5f80fd9 | ||
|
|
3f62ef22e5 | ||
|
|
8102e19e48 | ||
|
|
175c853ea7 | ||
|
|
c992cf3f37 | ||
|
|
83f6c2f265 | ||
|
|
17bf8aa092 | ||
|
|
6fc0e96ff8 | ||
|
|
06d2dcf469 | ||
|
|
b681ec9335 | ||
|
|
da2ff5712a | ||
|
|
18da402e27 | ||
|
|
18ae3ffe94 | ||
|
|
0a37b7acaa | ||
|
|
1a9fd885dd | ||
|
|
3e660905a7 | ||
|
|
0c2b984cb4 | ||
|
|
a69b1c609c | ||
|
|
8d4a6fcaba | ||
|
|
feced4762f | ||
|
|
0149317c5a | ||
|
|
3fcb6f9597 | ||
|
|
388fcd763b | ||
|
|
e488f9e6a2 | ||
|
|
9426d5be7b | ||
|
|
d5d2d41264 | ||
|
|
80f5f1ecd4 | ||
|
|
519e5d2ed1 | ||
|
|
df2d52a84e | ||
|
|
371dba9414 | ||
|
|
0afabad494 | ||
|
|
89b052cd42 | ||
|
|
c48c649436 | ||
|
|
58c0739953 | ||
|
|
e7daf69de9 | ||
|
|
f060e86bc6 | ||
|
|
0368162ef0 | ||
|
|
e843c71015 | ||
|
|
5cea16ef9f | ||
|
|
4aa8cd2470 | ||
|
|
4d4ee1b0ac | ||
|
|
43c89b4360 | ||
|
|
d281ca3e65 | ||
|
|
be17daf658 | ||
|
|
6ca84a61fa | ||
|
|
037d12c9c9 | ||
|
|
71cf19870b | ||
|
|
175a529c41 | ||
|
|
fe0c7c5408 | ||
|
|
148594f0f9 | ||
|
|
8edb439440 | ||
|
|
dfff5f3bcb | ||
|
|
ebf4d84553 | ||
|
|
42efc7f7c8 | ||
|
|
192395c311 | ||
|
|
a1447cc9c2 | ||
|
|
c39d91f827 | ||
|
|
32b6e9711b | ||
|
|
24c5dc2398 | ||
|
|
9e2ddec4b3 | ||
|
|
1f6a8e74bb | ||
|
|
7e901f523b | ||
|
|
3c30a41c14 | ||
|
|
0f99d4f420 | ||
|
|
6e02c5cb25 | ||
|
|
876a579e5d | ||
|
|
4c52499622 | ||
|
|
0bac391291 | ||
|
|
52d4e81e70 | ||
|
|
c71ea7b2ef | ||
|
|
c35a782747 | ||
|
|
c66af2c0a9 | ||
|
|
f9ac055847 | ||
|
|
21d057059e | ||
|
|
dca508b4ca | ||
|
|
aebae9965d | ||
|
|
e7e3e3f44c | ||
|
|
2f2db16ec1 | ||
|
|
d152e29687 | ||
|
|
285bcc25c9 | ||
|
|
7b65ad922d | ||
|
|
99be20cedd | ||
|
|
5f026901b8 | ||
|
|
6dfa2df06f | ||
|
|
c17e513377 | ||
|
|
2f5a269c70 | ||
|
|
50532260e3 | ||
|
|
8bd6eb06e6 | ||
|
|
55b0b52457 | ||
|
|
56fc56c5b9 | ||
|
|
85395d942a | ||
|
|
a206c3ccd3 | ||
|
|
dc5d31c116 | ||
|
|
95a4ddea3e | ||
|
|
ab5125d3dc | ||
|
|
9f81d59ecd | ||
|
|
c71ec8086d | ||
|
|
27be6aed91 | ||
|
|
3d1c4b313a | ||
|
|
0d4e319965 | ||
|
|
75dc3eb298 | ||
|
|
3f6d225086 | ||
|
|
d8843c608c | ||
|
|
7ebcc15b17 | ||
|
|
1b4076691f | ||
|
|
eab660873a | ||
|
|
232f37126e | ||
|
|
13e9885dfd | ||
|
|
56d79cb203 | ||
|
|
0f4c2e27cf | ||
|
|
f9ae295507 | ||
|
|
d9db5302d9 | ||
|
|
e453848134 | ||
|
|
59084143ef | ||
|
|
511b027350 | ||
|
|
322f47eb47 | ||
|
|
72f61ff89c | ||
|
|
a141c3ec59 | ||
|
|
e90e7a25ae | ||
|
|
c3b92a5412 | ||
|
|
2f55511064 | ||
|
|
08b9fc0b31 | ||
|
|
714f363d43 | ||
|
|
93ff7365b0 | ||
|
|
8151925068 | ||
|
|
b960e40bc8 | ||
|
|
1095c9b073 | ||
|
|
c0686515a9 | ||
|
|
455156f51c | ||
|
|
4143d31865 | ||
|
|
0c634adbe1 | ||
|
|
2e3641c2ae | ||
|
|
b806122c81 | ||
|
|
e1679f3fb9 | ||
|
|
5a80420b10 | ||
|
|
aa26ff5029 | ||
|
|
e197b59258 | ||
|
|
5b7cca13e5 | ||
|
|
a79590477e | ||
|
|
6181c1eb5e | ||
|
|
1ee5f90761 | ||
|
|
71f3b4e4e3 | ||
|
|
8cd7ddc535 | ||
|
|
2b76335a95 | ||
|
|
c6b213d8f0 | ||
|
|
eea70030bf | ||
|
|
92b5526310 | ||
|
|
99a59ad37e | ||
|
|
6a66a71cbb | ||
|
|
ff40764204 | ||
|
|
047da20b5b | ||
|
|
1417eaf3a7 | ||
|
|
4f8493d2de | ||
|
|
8861366137 | ||
|
|
0e9fced336 | ||
|
|
b257b960b3 | ||
|
|
4708171a32 | ||
|
|
b493743f8d | ||
|
|
d2955a3fd2 | ||
|
|
17d5869ad6 | ||
|
|
dfa3aed32d | ||
|
|
398817ce7b | ||
|
|
74940e9345 | ||
|
|
1e9fc51535 | ||
|
|
92c32979d2 | ||
|
|
b644d78a32 | ||
|
|
4e79e11007 | ||
|
|
67ebba3c3c | ||
|
|
7ce950f141 | ||
|
|
0cffe5fb09 | ||
|
|
b0e65560a1 | ||
|
|
ec37295b2f | ||
|
|
f6b0cc1aab | ||
|
|
7e41d31c6e | ||
|
|
40aa4abfe5 | ||
|
|
2650317622 | ||
|
|
6739357314 | ||
|
|
d57622d54b | ||
|
|
f745dbc054 | ||
|
|
79b041f81f | ||
|
|
0e16ed9ef7 | ||
|
|
88a3275dbb | ||
|
|
1223a87eb2 | ||
|
|
48630ceec9 | ||
|
|
72002e8a89 | ||
|
|
3c9297dd64 | ||
|
|
0e04ec3136 | ||
|
|
9b7f3a55cf | ||
|
|
1dacdb6c85 | ||
|
|
30483310ca | ||
|
|
e1d18b5114 | ||
|
|
108f30ba23 | ||
|
|
5943ee46bd | ||
|
|
f95a76293f | ||
|
|
014328e378 | ||
|
|
53f2fe1fbe | ||
|
|
9c75942aaf | ||
|
|
bff7c58497 | ||
|
|
9ebc5ed053 | ||
|
|
0b56c88e69 | ||
|
|
24841f0b2a | ||
|
|
1a9fc10be9 | ||
|
|
07573a7f19 | ||
|
|
daad2dc151 | ||
|
|
054f49dc31 | ||
|
|
47009ed2d3 | ||
|
|
0aae31d7d7 | ||
|
|
9caab45136 | ||
|
|
6d9a7b7eb0 | ||
|
|
7a2c5804b1 | ||
|
|
5319977171 | ||
|
|
828632e8c4 | ||
|
|
6b59ec6fd5 | ||
|
|
b60d862150 | ||
|
|
4837c7811a | ||
|
|
5a2397d57e | ||
|
|
927b4432c9 | ||
|
|
7a0064db1f | ||
|
|
2e7327205d | ||
|
|
7bc5bf78e2 | ||
|
|
ef603c8c7e | ||
|
|
28dd6b6546 | ||
|
|
1dda2bb537 | ||
|
|
bf6544cf28 | ||
|
|
ccecf946f7 | ||
|
|
19a859d6fd | ||
|
|
83af14caa4 | ||
|
|
4feeb2323d | ||
|
|
07bf66a197 | ||
|
|
0d4589219b | ||
|
|
c2b0469180 | ||
|
|
7e1980b218 | ||
|
|
ecb9a89a9f | ||
|
|
5e06e504e6 | ||
|
|
182f58cea6 | ||
|
|
337ffadefd | ||
|
|
22aa4daf19 | ||
|
|
493f9b2f2a | ||
|
|
e246e5765d | ||
|
|
6097235eff | ||
|
|
b700c42246 | ||
|
|
5b1bf1a993 | ||
|
|
041d4fced7 | ||
|
|
166fc15239 | ||
|
|
514a6e7fef | ||
|
|
82d9127191 | ||
|
|
03a1f40767 | ||
|
|
1c7c6fd591 | ||
|
|
b525f653c0 | ||
|
|
90586bc1e2 | ||
|
|
832f1633de | ||
|
|
38db53c465 | ||
|
|
34920d31f5 | ||
|
|
0241a05b90 | ||
|
|
e125f3b041 | ||
|
|
c520ac46fc | ||
|
|
2d7390341c | ||
|
|
03fcdce016 | ||
|
|
e4e416ac42 | ||
|
|
19325132b7 | ||
|
|
389d36f760 | ||
|
|
49448b31c6 | ||
|
|
ebede0bed7 | ||
|
|
b1d8b072db | ||
|
|
ee6a7c2bbb | ||
|
|
c4e2708901 | ||
|
|
5c8cfa50eb | ||
|
|
73cb71762f | ||
|
|
267dfe58d7 | ||
|
|
131c10d318 | ||
|
|
e6cacc40a9 | ||
|
|
48d4847b38 | ||
|
|
59460c767f | ||
|
|
756156beaf | ||
|
|
480763db0d | ||
|
|
62ece86f24 | ||
|
|
52d9e6f298 | ||
|
|
47b315ff18 | ||
|
|
ed1deee902 | ||
|
|
2e109018b7 | ||
|
|
22c35b1e00 | ||
|
|
b92082b748 | ||
|
|
c2be6603a2 | ||
|
|
c805f08ca7 | ||
|
|
ccc0335158 | ||
|
|
42acd334f4 | ||
|
|
820f126075 | ||
|
|
7e6c4a1856 | ||
|
|
5fafe4b1ab | ||
|
|
1e7cd48cfa | ||
|
|
7f51d85bbd | ||
|
|
ad76e32398 | ||
|
|
7575f9bf1c | ||
|
|
67bdf3f5f6 | ||
|
|
3c300666ad | ||
|
|
b91d3f6be4 | ||
|
|
a8e76513bb | ||
|
|
0a23201338 | ||
|
|
81330aaf89 | ||
|
|
98a3b01992 | ||
|
|
d341520938 | ||
|
|
5c9af73e41 | ||
|
|
ad4c940fa3 | ||
|
|
910b0b0c61 | ||
|
|
3fef052bf1 | ||
|
|
040554f2f9 | ||
|
|
17186ca9c9 | ||
|
|
212d59c9ab | ||
|
|
1a1f252a3f | ||
|
|
d73706dede | ||
|
|
44850e1036 | ||
|
|
3b0cbf8102 | ||
|
|
4aa131c3db | ||
|
|
59962097d0 | ||
|
|
ebc78127f3 |
8
.github/workflows/coverage.yml
vendored
8
.github/workflows/coverage.yml
vendored
@@ -3,8 +3,6 @@ name: Coverage
|
||||
on:
|
||||
push:
|
||||
branches: [main]
|
||||
pull_request:
|
||||
branches: [main]
|
||||
|
||||
# Ensures that we cancel running jobs for the same PR / same workflow.
|
||||
concurrency:
|
||||
@@ -15,13 +13,13 @@ jobs:
|
||||
coverage:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install Rust
|
||||
run: rustup toolchain install nightly --profile minimal --component llvm-tools-preview
|
||||
run: rustup toolchain install nightly-2024-07-01 --profile minimal --component llvm-tools-preview
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
- uses: taiki-e/install-action@cargo-llvm-cov
|
||||
- name: Generate code coverage
|
||||
run: cargo +nightly llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
|
||||
run: cargo +nightly-2024-07-01 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
|
||||
- name: Upload coverage to Codecov
|
||||
uses: codecov/codecov-action@v3
|
||||
continue-on-error: true
|
||||
|
||||
2
.github/workflows/long_running.yml
vendored
2
.github/workflows/long_running.yml
vendored
@@ -19,7 +19,7 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install stable
|
||||
uses: actions-rs/toolchain@v1
|
||||
with:
|
||||
|
||||
13
.github/workflows/test.yml
vendored
13
.github/workflows/test.yml
vendored
@@ -20,7 +20,7 @@ jobs:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install nightly
|
||||
uses: actions-rs/toolchain@v1
|
||||
@@ -39,6 +39,13 @@ jobs:
|
||||
|
||||
- name: Check Formatting
|
||||
run: cargo +nightly fmt --all -- --check
|
||||
|
||||
- name: Check Stable Compilation
|
||||
run: cargo build --all-features
|
||||
|
||||
|
||||
- name: Check Bench Compilation
|
||||
run: cargo +nightly bench --no-run --profile=dev --all-features
|
||||
|
||||
- uses: actions-rs/clippy-check@v1
|
||||
with:
|
||||
@@ -53,14 +60,14 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
features: [
|
||||
{ label: "all", flags: "mmap,stopwords,brotli-compression,lz4-compression,snappy-compression,zstd-compression,failpoints" },
|
||||
{ label: "all", flags: "mmap,stopwords,lz4-compression,zstd-compression,failpoints" },
|
||||
{ label: "quickwit", flags: "mmap,quickwit,failpoints" }
|
||||
]
|
||||
|
||||
name: test-${{ matrix.features.label}}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install stable
|
||||
uses: actions-rs/toolchain@v1
|
||||
|
||||
@@ -46,7 +46,7 @@ The file of a segment has the format
|
||||
|
||||
```segment-id . ext```
|
||||
|
||||
The extension signals which data structure (or [`SegmentComponent`](src/core/segment_component.rs)) is stored in the file.
|
||||
The extension signals which data structure (or [`SegmentComponent`](src/index/segment_component.rs)) is stored in the file.
|
||||
|
||||
A small `meta.json` file is in charge of keeping track of the list of segments, as well as the schema.
|
||||
|
||||
@@ -102,7 +102,7 @@ but users can extend tantivy with their own implementation.
|
||||
|
||||
Tantivy's document follows a very strict schema, decided before building any index.
|
||||
|
||||
The schema defines all of the fields that the indexes [`Document`](src/schema/document.rs) may and should contain, their types (`text`, `i64`, `u64`, `Date`, ...) as well as how it should be indexed / represented in tantivy.
|
||||
The schema defines all of the fields that the indexes [`Document`](src/schema/document/mod.rs) may and should contain, their types (`text`, `i64`, `u64`, `Date`, ...) as well as how it should be indexed / represented in tantivy.
|
||||
|
||||
Depending on the type of the field, you can decide to
|
||||
|
||||
|
||||
206
CHANGELOG.md
206
CHANGELOG.md
@@ -1,5 +1,191 @@
|
||||
Tantivy 0.23 - Unreleased
|
||||
================================
|
||||
Tantivy 0.23 will be backwards compatible with indices created with v0.22 and v0.21. The new minimum rust version will be 1.75.
|
||||
|
||||
Tantivy 0.20 [Unreleased]
|
||||
#### Bugfixes
|
||||
- fix potential endless loop in merge [#2457](https://github.com/quickwit-oss/tantivy/pull/2457)(@PSeitz)
|
||||
- fix bug that causes out-of-order sstable key. [#2445](https://github.com/quickwit-oss/tantivy/pull/2445)(@fulmicoton)
|
||||
- fix ReferenceValue API flaw [#2372](https://github.com/quickwit-oss/tantivy/pull/2372)(@PSeitz)
|
||||
- fix `OwnedBytes` debug panic [#2512](https://github.com/quickwit-oss/tantivy/pull/2512)(@b41sh)
|
||||
- catch panics during merges [#2582](https://github.com/quickwit-oss/tantivy/pull/2582)(@rdettai)
|
||||
- switch from u32 to usize in bitpacker. This enables multivalued columns larger than 4GB, which crashed during merge before. [#2581](https://github.com/quickwit-oss/tantivy/pull/2581) [#2586](https://github.com/quickwit-oss/tantivy/pull/2586)(@fulmicoton-dd @PSeitz)
|
||||
|
||||
#### Breaking API Changes
|
||||
- remove index sorting [#2434](https://github.com/quickwit-oss/tantivy/pull/2434)(@PSeitz)
|
||||
|
||||
#### Features/Improvements
|
||||
- **Aggregation**
|
||||
- Support for cardinality aggregation [#2337](https://github.com/quickwit-oss/tantivy/pull/2337) [#2446](https://github.com/quickwit-oss/tantivy/pull/2446) (@raphaelcoeffic @PSeitz)
|
||||
- Support for extended stats aggregation [#2247](https://github.com/quickwit-oss/tantivy/pull/2247)(@giovannicuccu)
|
||||
- Add Key::I64 and Key::U64 variants in aggregation to avoid f64 precision issues [#2468](https://github.com/quickwit-oss/tantivy/pull/2468)(@PSeitz)
|
||||
- Faster term aggregation fetch terms [#2447](https://github.com/quickwit-oss/tantivy/pull/2447)(@PSeitz)
|
||||
- Improve custom order deserialization [#2451](https://github.com/quickwit-oss/tantivy/pull/2451)(@PSeitz)
|
||||
- Change AggregationLimits behavior [#2495](https://github.com/quickwit-oss/tantivy/pull/2495)(@PSeitz)
|
||||
- lower contention on AggregationLimits [#2394](https://github.com/quickwit-oss/tantivy/pull/2394)(@PSeitz)
|
||||
- fix postcard compatibility for top_hits, add postcard test [#2346](https://github.com/quickwit-oss/tantivy/pull/2346)(@PSeitz)
|
||||
- reduce top hits memory consumption [#2426](https://github.com/quickwit-oss/tantivy/pull/2426)(@PSeitz)
|
||||
- check unsupported parameters top_hits [#2351](https://github.com/quickwit-oss/tantivy/pull/2351)(@PSeitz)
|
||||
- Change AggregationLimits to AggregationLimitsGuard [#2495](https://github.com/quickwit-oss/tantivy/pull/2495)(@PSeitz)
|
||||
- add support for counting non integer in aggregation [#2547](https://github.com/quickwit-oss/tantivy/pull/2547)(@trinity-1686a)
|
||||
- **Range Queries**
|
||||
- Support fast field range queries on json fields [#2456](https://github.com/quickwit-oss/tantivy/pull/2456)(@PSeitz)
|
||||
- Add support for str fast field range query [#2460](https://github.com/quickwit-oss/tantivy/pull/2460) [#2452](https://github.com/quickwit-oss/tantivy/pull/2452) [#2453](https://github.com/quickwit-oss/tantivy/pull/2453)(@PSeitz)
|
||||
- modify fastfield range query heuristic [#2375](https://github.com/quickwit-oss/tantivy/pull/2375)(@trinity-1686a)
|
||||
- add FastFieldRangeQuery for explicit range queries on fast field (for `RangeQuery` it is autodetected) [#2477](https://github.com/quickwit-oss/tantivy/pull/2477)(@PSeitz)
|
||||
|
||||
- add format backwards-compatibility tests [#2485](https://github.com/quickwit-oss/tantivy/pull/2485)(@PSeitz)
|
||||
- add columnar format compatibility tests [#2433](https://github.com/quickwit-oss/tantivy/pull/2433)(@PSeitz)
|
||||
- Improved snippet ranges algorithm [#2474](https://github.com/quickwit-oss/tantivy/pull/2474)(@gezihuzi)
|
||||
- make find_field_with_default return json fields without path [#2476](https://github.com/quickwit-oss/tantivy/pull/2476)(@trinity-1686a)
|
||||
- Make `BooleanQuery` support `minimum_number_should_match` [#2405](https://github.com/quickwit-oss/tantivy/pull/2405)(@LebranceBW)
|
||||
- Make `NUM_MERGE_THREADS` configurable [#2535](https://github.com/quickwit-oss/tantivy/pull/2535)(@Barre)
|
||||
|
||||
- **RegexPhraseQuery**
|
||||
`RegexPhraseQuery` supports phrase queries with regex. E.g. query "b.* b.* wolf" matches "big bad wolf". Slop is supported as well: "b.* wolf"~2 matches "big bad wolf" [#2516](https://github.com/quickwit-oss/tantivy/pull/2516)(@PSeitz)
|
||||
|
||||
- **Optional Index in Multivalue Columnar Index**
|
||||
For mostly empty multivalued indices there was a large overhead during creation when iterating all docids (merge case).
|
||||
This is alleviated by placing an optional index in the multivalued index to mark documents that have values.
|
||||
This will slightly increase space and access time. [#2439](https://github.com/quickwit-oss/tantivy/pull/2439)(@PSeitz)
|
||||
|
||||
- **Store DateTime as nanoseconds in doc store** DateTime in the doc store was truncated to microseconds previously. This removes this truncation, while still keeping backwards compatibility. [#2486](https://github.com/quickwit-oss/tantivy/pull/2486)(@PSeitz)
|
||||
|
||||
- **Performace/Memory**
|
||||
- lift clauses in LogicalAst for optimized ast during execution [#2449](https://github.com/quickwit-oss/tantivy/pull/2449)(@PSeitz)
|
||||
- Use Vec instead of BTreeMap to back OwnedValue object [#2364](https://github.com/quickwit-oss/tantivy/pull/2364)(@fulmicoton)
|
||||
- Replace TantivyDocument with CompactDoc. CompactDoc is much smaller and provides similar performance. [#2402](https://github.com/quickwit-oss/tantivy/pull/2402)(@PSeitz)
|
||||
- Recycling buffer in PrefixPhraseScorer [#2443](https://github.com/quickwit-oss/tantivy/pull/2443)(@fulmicoton)
|
||||
|
||||
- **Json Type**
|
||||
- JSON supports now all values on the root level. Previously an object was required. This enables support for flat mixed types. allow more JSON values, fix i64 special case [#2383](https://github.com/quickwit-oss/tantivy/pull/2383)(@PSeitz)
|
||||
- add json path constructor to term [#2367](https://github.com/quickwit-oss/tantivy/pull/2367)(@PSeitz)
|
||||
|
||||
- **QueryParser**
|
||||
- fix de-escaping too much in query parser [#2427](https://github.com/quickwit-oss/tantivy/pull/2427)(@trinity-1686a)
|
||||
- improve query parser [#2416](https://github.com/quickwit-oss/tantivy/pull/2416)(@trinity-1686a)
|
||||
- Support field grouping `title:(return AND "pink panther")` [#2333](https://github.com/quickwit-oss/tantivy/pull/2333)(@trinity-1686a)
|
||||
- allow term starting with wildcard [#2568](https://github.com/quickwit-oss/tantivy/pull/2568)(@trinity-1686a)
|
||||
|
||||
- Exist queries match subpath fields [#2558](https://github.com/quickwit-oss/tantivy/pull/2558)(@rdettai)
|
||||
- add access benchmark for columnar [#2432](https://github.com/quickwit-oss/tantivy/pull/2432)(@PSeitz)
|
||||
- extend indexwriter proptests [#2342](https://github.com/quickwit-oss/tantivy/pull/2342)(@PSeitz)
|
||||
- add bench & test for columnar merging [#2428](https://github.com/quickwit-oss/tantivy/pull/2428)(@PSeitz)
|
||||
- Change in Executor API [#2391](https://github.com/quickwit-oss/tantivy/pull/2391)(@fulmicoton)
|
||||
- Removed usage of num_cpus [#2387](https://github.com/quickwit-oss/tantivy/pull/2387)(@fulmicoton)
|
||||
- use bingang for agg and stacker benchmark [#2378](https://github.com/quickwit-oss/tantivy/pull/2378)[#2492](https://github.com/quickwit-oss/tantivy/pull/2492)(@PSeitz)
|
||||
- cleanup top level exports [#2382](https://github.com/quickwit-oss/tantivy/pull/2382)(@PSeitz)
|
||||
- make convert_to_fast_value_and_append_to_json_term pub [#2370](https://github.com/quickwit-oss/tantivy/pull/2370)(@PSeitz)
|
||||
- remove JsonTermWriter [#2238](https://github.com/quickwit-oss/tantivy/pull/2238)(@PSeitz)
|
||||
- validate sort by field type [#2336](https://github.com/quickwit-oss/tantivy/pull/2336)(@PSeitz)
|
||||
- Fix trait bound of StoreReader::iter [#2360](https://github.com/quickwit-oss/tantivy/pull/2360)(@adamreichold)
|
||||
- remove read_postings_no_deletes [#2526](https://github.com/quickwit-oss/tantivy/pull/2526)(@PSeitz)
|
||||
|
||||
Tantivy 0.22
|
||||
================================
|
||||
|
||||
Tantivy 0.22 will be able to read indices created with Tantivy 0.21.
|
||||
|
||||
#### Bugfixes
|
||||
- Fix null byte handling in JSON paths (null bytes in json keys caused panic during indexing) [#2345](https://github.com/quickwit-oss/tantivy/pull/2345)(@PSeitz)
|
||||
- Fix bug that can cause `get_docids_for_value_range` to panic. [#2295](https://github.com/quickwit-oss/tantivy/pull/2295)(@fulmicoton)
|
||||
- Avoid 1 document indices by increase min memory to 15MB for indexing [#2176](https://github.com/quickwit-oss/tantivy/pull/2176)(@PSeitz)
|
||||
- Fix merge panic for JSON fields [#2284](https://github.com/quickwit-oss/tantivy/pull/2284)(@PSeitz)
|
||||
- Fix bug occurring when merging JSON object indexed with positions. [#2253](https://github.com/quickwit-oss/tantivy/pull/2253)(@fulmicoton)
|
||||
- Fix empty DateHistogram gap bug [#2183](https://github.com/quickwit-oss/tantivy/pull/2183)(@PSeitz)
|
||||
- Fix range query end check (fields with less than 1 value per doc are affected) [#2226](https://github.com/quickwit-oss/tantivy/pull/2226)(@PSeitz)
|
||||
- Handle exclusive out of bounds ranges on fastfield range queries [#2174](https://github.com/quickwit-oss/tantivy/pull/2174)(@PSeitz)
|
||||
|
||||
#### Breaking API Changes
|
||||
- rename ReloadPolicy onCommit to onCommitWithDelay [#2235](https://github.com/quickwit-oss/tantivy/pull/2235)(@giovannicuccu)
|
||||
- Move exports from the root into modules [#2220](https://github.com/quickwit-oss/tantivy/pull/2220)(@PSeitz)
|
||||
- Accept field name instead of `Field` in FilterCollector [#2196](https://github.com/quickwit-oss/tantivy/pull/2196)(@PSeitz)
|
||||
- remove deprecated IntOptions and DateTime [#2353](https://github.com/quickwit-oss/tantivy/pull/2353)(@PSeitz)
|
||||
|
||||
#### Features/Improvements
|
||||
- Tantivy documents as a trait: Index data directly without converting to tantivy types first [#2071](https://github.com/quickwit-oss/tantivy/pull/2071)(@ChillFish8)
|
||||
- encode some part of posting list as -1 instead of direct values (smaller inverted indices) [#2185](https://github.com/quickwit-oss/tantivy/pull/2185)(@trinity-1686a)
|
||||
- **Aggregation**
|
||||
- Support to deserialize f64 from string [#2311](https://github.com/quickwit-oss/tantivy/pull/2311)(@PSeitz)
|
||||
- Add a top_hits aggregator [#2198](https://github.com/quickwit-oss/tantivy/pull/2198)(@ditsuke)
|
||||
- Support bool type in term aggregation [#2318](https://github.com/quickwit-oss/tantivy/pull/2318)(@PSeitz)
|
||||
- Support ip addresses in term aggregation [#2319](https://github.com/quickwit-oss/tantivy/pull/2319)(@PSeitz)
|
||||
- Support date type in term aggregation [#2172](https://github.com/quickwit-oss/tantivy/pull/2172)(@PSeitz)
|
||||
- Support escaped dot when addressing field [#2250](https://github.com/quickwit-oss/tantivy/pull/2250)(@PSeitz)
|
||||
|
||||
- Add ExistsQuery to check documents that have a value [#2160](https://github.com/quickwit-oss/tantivy/pull/2160)(@imotov)
|
||||
- Expose TopDocs::order_by_u64_field again [#2282](https://github.com/quickwit-oss/tantivy/pull/2282)(@ditsuke)
|
||||
|
||||
- **Memory/Performance**
|
||||
- Faster TopN: replace BinaryHeap with TopNComputer [#2186](https://github.com/quickwit-oss/tantivy/pull/2186)(@PSeitz)
|
||||
- reduce number of allocations during indexing [#2257](https://github.com/quickwit-oss/tantivy/pull/2257)(@PSeitz)
|
||||
- Less Memory while indexing: docid deltas while indexing [#2249](https://github.com/quickwit-oss/tantivy/pull/2249)(@PSeitz)
|
||||
- Faster indexing: use term hashmap in fastfield [#2243](https://github.com/quickwit-oss/tantivy/pull/2243)(@PSeitz)
|
||||
- term hashmap remove copy in is_empty, unused unordered_id [#2229](https://github.com/quickwit-oss/tantivy/pull/2229)(@PSeitz)
|
||||
- add method to fetch block of first values in columnar [#2330](https://github.com/quickwit-oss/tantivy/pull/2330)(@PSeitz)
|
||||
- Faster aggregations: add fast path for full columns in fetch_block [#2328](https://github.com/quickwit-oss/tantivy/pull/2328)(@PSeitz)
|
||||
- Faster sstable loading: use fst for sstable index [#2268](https://github.com/quickwit-oss/tantivy/pull/2268)(@trinity-1686a)
|
||||
|
||||
- **QueryParser**
|
||||
- allow newline where we allow space in query parser [#2302](https://github.com/quickwit-oss/tantivy/pull/2302)(@trinity-1686a)
|
||||
- allow some mixing of occur and bool in strict query parser [#2323](https://github.com/quickwit-oss/tantivy/pull/2323)(@trinity-1686a)
|
||||
- handle * inside term in lenient query parser [#2228](https://github.com/quickwit-oss/tantivy/pull/2228)(@trinity-1686a)
|
||||
- add support for exists query syntax in query parser [#2170](https://github.com/quickwit-oss/tantivy/pull/2170)(@trinity-1686a)
|
||||
- Add shared search executor [#2312](https://github.com/quickwit-oss/tantivy/pull/2312)(@MochiXu)
|
||||
- Truncate keys to u16::MAX in term hashmap [#2299](https://github.com/quickwit-oss/tantivy/pull/2299)(@PSeitz)
|
||||
- report if a term matched when warming up posting list [#2309](https://github.com/quickwit-oss/tantivy/pull/2309)(@trinity-1686a)
|
||||
- Support json fields in FuzzyTermQuery [#2173](https://github.com/quickwit-oss/tantivy/pull/2173)(@PingXia-at)
|
||||
- Read list of fields encoded in term dictionary for JSON fields [#2184](https://github.com/quickwit-oss/tantivy/pull/2184)(@PSeitz)
|
||||
- add collect_block to BoxableSegmentCollector [#2331](https://github.com/quickwit-oss/tantivy/pull/2331)(@PSeitz)
|
||||
- expose collect_block buffer size [#2326](https://github.com/quickwit-oss/tantivy/pull/2326)(@PSeitz)
|
||||
- Forward regex parser errors [#2288](https://github.com/quickwit-oss/tantivy/pull/2288)(@adamreichold)
|
||||
- Make FacetCounts defaultable and cloneable. [#2322](https://github.com/quickwit-oss/tantivy/pull/2322)(@adamreichold)
|
||||
- Derive Debug for SchemaBuilder [#2254](https://github.com/quickwit-oss/tantivy/pull/2254)(@GodTamIt)
|
||||
- add missing inlines to tantivy options [#2245](https://github.com/quickwit-oss/tantivy/pull/2245)(@PSeitz)
|
||||
|
||||
Tantivy 0.21.1
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Range queries on fast fields with less values on that field than documents had an invalid end condition, leading to missing results. [#2226](https://github.com/quickwit-oss/tantivy/issues/2226)(@appaquet @PSeitz)
|
||||
- Increase the minimum memory budget from 3MB to 15MB to avoid single doc segments (API fix). [#2176](https://github.com/quickwit-oss/tantivy/issues/2176)(@PSeitz)
|
||||
|
||||
Tantivy 0.21
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Fix track fast field memory consumption, which led to higher memory consumption than the budget allowed during indexing [#2148](https://github.com/quickwit-oss/tantivy/issues/2148)[#2147](https://github.com/quickwit-oss/tantivy/issues/2147)(@PSeitz)
|
||||
- Fix a regression from 0.20 where sort index by date wasn't working anymore [#2124](https://github.com/quickwit-oss/tantivy/issues/2124)(@PSeitz)
|
||||
- Fix getting the root facet on the `FacetCollector`. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086)(@adamreichold)
|
||||
- Align numerical type priority order of columnar and query. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088)(@fmassot)
|
||||
#### Breaking Changes
|
||||
- Remove support for Brotli and Snappy compression [#2123](https://github.com/quickwit-oss/tantivy/issues/2123)(@adamreichold)
|
||||
#### Features/Improvements
|
||||
- Implement lenient query parser [#2129](https://github.com/quickwit-oss/tantivy/pull/2129)(@trinity-1686a)
|
||||
- order_by_u64_field and order_by_fast_field allow sorting in ascending and descending order [#2111](https://github.com/quickwit-oss/tantivy/issues/2111)(@naveenann)
|
||||
- Allow dynamic filters in text analyzer builder [#2110](https://github.com/quickwit-oss/tantivy/issues/2110)(@fulmicoton @fmassot)
|
||||
- **Aggregation**
|
||||
- Add missing parameter for term aggregation [#2149](https://github.com/quickwit-oss/tantivy/issues/2149)[#2103](https://github.com/quickwit-oss/tantivy/issues/2103)(@PSeitz)
|
||||
- Add missing parameter for percentiles [#2157](https://github.com/quickwit-oss/tantivy/issues/2157)(@PSeitz)
|
||||
- Add missing parameter for stats,min,max,count,sum,avg [#2151](https://github.com/quickwit-oss/tantivy/issues/2151)(@PSeitz)
|
||||
- Improve aggregation deserialization error message [#2150](https://github.com/quickwit-oss/tantivy/issues/2150)(@PSeitz)
|
||||
- Add validation for type Bytes to term_agg [#2077](https://github.com/quickwit-oss/tantivy/issues/2077)(@PSeitz)
|
||||
- Alternative mixed field collection [#2135](https://github.com/quickwit-oss/tantivy/issues/2135)(@PSeitz)
|
||||
- Add missing query_terms impl for TermSetQuery. [#2120](https://github.com/quickwit-oss/tantivy/issues/2120)(@adamreichold)
|
||||
- Minor improvements to OwnedBytes [#2134](https://github.com/quickwit-oss/tantivy/issues/2134)(@adamreichold)
|
||||
- Remove allocations in split compound words [#2080](https://github.com/quickwit-oss/tantivy/issues/2080)(@PSeitz)
|
||||
- Ngram tokenizer now returns an error with invalid arguments [#2102](https://github.com/quickwit-oss/tantivy/issues/2102)(@fmassot)
|
||||
- Make TextAnalyzerBuilder public [#2097](https://github.com/quickwit-oss/tantivy/issues/2097)(@adamreichold)
|
||||
- Return an error when tokenizer is not found while indexing [#2093](https://github.com/quickwit-oss/tantivy/issues/2093)(@naveenann)
|
||||
- Delayed column opening during merge [#2132](https://github.com/quickwit-oss/tantivy/issues/2132)(@PSeitz)
|
||||
|
||||
Tantivy 0.20.2
|
||||
================================
|
||||
- Align numerical type priority order on the search side. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088) (@fmassot)
|
||||
- Fix is_child_of function not considering the root facet. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086) (@adamreichhold)
|
||||
|
||||
Tantivy 0.20.1
|
||||
================================
|
||||
- Fix building on windows with mmap [#2070](https://github.com/quickwit-oss/tantivy/issues/2070) (@ChillFish8)
|
||||
|
||||
Tantivy 0.20
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Fix phrase queries with slop (slop supports now transpositions, algorithm that carries slop so far for num terms > 2) [#2031](https://github.com/quickwit-oss/tantivy/issues/2031)[#2020](https://github.com/quickwit-oss/tantivy/issues/2020)(@PSeitz)
|
||||
@@ -12,7 +198,7 @@ Tantivy 0.20 [Unreleased]
|
||||
- Add PhrasePrefixQuery [#1842](https://github.com/quickwit-oss/tantivy/issues/1842) (@trinity-1686a)
|
||||
- Add `coerce` option for text and numbers types (convert the value instead of returning an error during indexing) [#1904](https://github.com/quickwit-oss/tantivy/issues/1904) (@PSeitz)
|
||||
- Add regex tokenizer [#1759](https://github.com/quickwit-oss/tantivy/issues/1759)(@mkleen)
|
||||
- Move tokenizer API to seperate crate. Having a seperate crate with a stable API will allow us to use tokenizers with different tantivy versions. [#1767](https://github.com/quickwit-oss/tantivy/issues/1767) (@PSeitz)
|
||||
- Move tokenizer API to separate crate. Having a separate crate with a stable API will allow us to use tokenizers with different tantivy versions. [#1767](https://github.com/quickwit-oss/tantivy/issues/1767) (@PSeitz)
|
||||
- **Columnar crate**: New fast field handling (@fulmicoton @PSeitz) [#1806](https://github.com/quickwit-oss/tantivy/issues/1806)[#1809](https://github.com/quickwit-oss/tantivy/issues/1809)
|
||||
- Support for fast fields with optional values. Previously tantivy supported only single-valued and multi-value fast fields. The encoding of optional fast fields is now very compact.
|
||||
- Fast field Support for JSON (schemaless fast fields). Support multiple types on the same column. [#1876](https://github.com/quickwit-oss/tantivy/issues/1876) (@fulmicoton)
|
||||
@@ -38,12 +224,14 @@ Tantivy 0.20 [Unreleased]
|
||||
- Add aggregation support for JSON type [#1888](https://github.com/quickwit-oss/tantivy/issues/1888) (@PSeitz)
|
||||
- Mixed types support on JSON fields in aggs [#1971](https://github.com/quickwit-oss/tantivy/issues/1971) (@PSeitz)
|
||||
- Perf: Fetch blocks of vals in aggregation for all cardinality [#1950](https://github.com/quickwit-oss/tantivy/issues/1950) (@PSeitz)
|
||||
- Allow histogram bounds to be passed as Rfc3339 [#2076](https://github.com/quickwit-oss/tantivy/issues/2076) (@PSeitz)
|
||||
- `Searcher` with disabled scoring via `EnableScoring::Disabled` [#1780](https://github.com/quickwit-oss/tantivy/issues/1780) (@shikhar)
|
||||
- Enable tokenizer on json fields [#2053](https://github.com/quickwit-oss/tantivy/issues/2053) (@PSeitz)
|
||||
- Enforcing "NOT" and "-" queries consistency in UserInputAst [#1609](https://github.com/quickwit-oss/tantivy/issues/1609) (@bazhenov)
|
||||
- Faster indexing
|
||||
- Refactor tokenization pipeline to use GATs [#1924](https://github.com/quickwit-oss/tantivy/issues/1924) (@trinity-1686a)
|
||||
- Faster term hash map [#2058](https://github.com/quickwit-oss/tantivy/issues/2058)[#1940](https://github.com/quickwit-oss/tantivy/issues/1940) (@PSeitz)
|
||||
- tokenizer-api: reduce Tokenizer allocation overhead [#2062](https://github.com/quickwit-oss/tantivy/issues/2062) (@PSeitz)
|
||||
- Refactor vint [#2010](https://github.com/quickwit-oss/tantivy/issues/2010) (@PSeitz)
|
||||
- Faster search
|
||||
- Work in batches of docs on the SegmentCollector (Only for cases without score for now) [#1937](https://github.com/quickwit-oss/tantivy/issues/1937) (@PSeitz)
|
||||
@@ -57,13 +245,13 @@ Tantivy 0.20 [Unreleased]
|
||||
- Auto downgrade index record option, instead of vint error [#1857](https://github.com/quickwit-oss/tantivy/issues/1857) (@PSeitz)
|
||||
- Enable range query on fast field for u64 compatible types [#1762](https://github.com/quickwit-oss/tantivy/issues/1762) (@PSeitz) [#1876]
|
||||
- sstable
|
||||
- Isolating sstable and stacker in independant crates. [#1718](https://github.com/quickwit-oss/tantivy/issues/1718) (@fulmicoton)
|
||||
- Isolating sstable and stacker in independent crates. [#1718](https://github.com/quickwit-oss/tantivy/issues/1718) (@fulmicoton)
|
||||
- New sstable format [#1943](https://github.com/quickwit-oss/tantivy/issues/1943)[#1953](https://github.com/quickwit-oss/tantivy/issues/1953) (@trinity-1686a)
|
||||
- Use DeltaReader directly to implement Dictionnary::ord_to_term [#1928](https://github.com/quickwit-oss/tantivy/issues/1928) (@trinity-1686a)
|
||||
- Use DeltaReader directly to implement Dictionnary::term_ord [#1925](https://github.com/quickwit-oss/tantivy/issues/1925) (@trinity-1686a)
|
||||
- Add seperate tokenizer manager for fast fields [#2019](https://github.com/quickwit-oss/tantivy/issues/2019) (@PSeitz)
|
||||
- Use DeltaReader directly to implement Dictionary::ord_to_term [#1928](https://github.com/quickwit-oss/tantivy/issues/1928) (@trinity-1686a)
|
||||
- Use DeltaReader directly to implement Dictionary::term_ord [#1925](https://github.com/quickwit-oss/tantivy/issues/1925) (@trinity-1686a)
|
||||
- Add separate tokenizer manager for fast fields [#2019](https://github.com/quickwit-oss/tantivy/issues/2019) (@PSeitz)
|
||||
- Make construction of LevenshteinAutomatonBuilder for FuzzyTermQuery instances lazy. [#1756](https://github.com/quickwit-oss/tantivy/issues/1756) (@adamreichold)
|
||||
- Added support for madvise when opening an mmaped Index [#2036](https://github.com/quickwit-oss/tantivy/issues/2036) (@fulmicoton)
|
||||
- Added support for madvise when opening an mmapped Index [#2036](https://github.com/quickwit-oss/tantivy/issues/2036) (@fulmicoton)
|
||||
- Rename `DatePrecision` to `DateTimePrecision` [#2051](https://github.com/quickwit-oss/tantivy/issues/2051) (@guilload)
|
||||
- Query Parser
|
||||
- Quotation mark can now be used for phrase queries. [#2050](https://github.com/quickwit-oss/tantivy/issues/2050) (@fulmicoton)
|
||||
@@ -102,7 +290,7 @@ Tantivy 0.19
|
||||
- Add support for phrase slop in query language [#1393](https://github.com/quickwit-oss/tantivy/pull/1393) (@saroh)
|
||||
- Aggregation
|
||||
- Add aggregation support for date type [#1693](https://github.com/quickwit-oss/tantivy/pull/1693)(@PSeitz)
|
||||
- Add support for keyed parameter in range and histgram aggregations [#1424](https://github.com/quickwit-oss/tantivy/pull/1424) (@k-yomo)
|
||||
- Add support for keyed parameter in range and histogram aggregations [#1424](https://github.com/quickwit-oss/tantivy/pull/1424) (@k-yomo)
|
||||
- Add aggregation bucket limit [#1363](https://github.com/quickwit-oss/tantivy/pull/1363) (@PSeitz)
|
||||
- Faster indexing
|
||||
- [#1610](https://github.com/quickwit-oss/tantivy/pull/1610) (@PSeitz)
|
||||
@@ -545,7 +733,7 @@ Tantivy 0.4.0
|
||||
- Raise the limit of number of fields (previously 256 fields) (@fulmicoton)
|
||||
- Removed u32 fields. They are replaced by u64 and i64 fields (#65) (@fulmicoton)
|
||||
- Optimized skip in SegmentPostings (#130) (@lnicola)
|
||||
- Replacing rustc_serialize by serde. Kudos to @KodrAus and @lnicola
|
||||
- Replacing rustc_serialize by serde. Kudos to benchmark@KodrAus and @lnicola
|
||||
- Using error-chain (@KodrAus)
|
||||
- QueryParser: (@fulmicoton)
|
||||
- Explicit error returned when searched for a term that is not indexed
|
||||
|
||||
10
CITATION.cff
Normal file
10
CITATION.cff
Normal file
@@ -0,0 +1,10 @@
|
||||
cff-version: 1.2.0
|
||||
message: "If you use this software, please cite it as below."
|
||||
authors:
|
||||
- alias: Quickwit Inc.
|
||||
website: "https://quickwit.io"
|
||||
title: "tantivy"
|
||||
version: 0.22.0
|
||||
doi: 10.5281/zenodo.13942948
|
||||
date-released: 2024-10-17
|
||||
url: "https://github.com/quickwit-oss/tantivy"
|
||||
117
Cargo.toml
117
Cargo.toml
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy"
|
||||
version = "0.20.2"
|
||||
version = "0.24.0"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
categories = ["database-implementations", "data-structures"]
|
||||
@@ -11,78 +11,87 @@ repository = "https://github.com/quickwit-oss/tantivy"
|
||||
readme = "README.md"
|
||||
keywords = ["search", "information", "retrieval"]
|
||||
edition = "2021"
|
||||
rust-version = "1.62"
|
||||
rust-version = "1.75"
|
||||
exclude = ["benches/*.json", "benches/*.txt"]
|
||||
|
||||
[dependencies]
|
||||
oneshot = "0.1.5"
|
||||
base64 = "0.21.0"
|
||||
oneshot = "0.1.7"
|
||||
base64 = "0.22.0"
|
||||
byteorder = "1.4.3"
|
||||
crc32fast = "1.3.2"
|
||||
once_cell = "1.10.0"
|
||||
regex = { version = "1.5.5", default-features = false, features = ["std", "unicode"] }
|
||||
regex = { version = "1.5.5", default-features = false, features = [
|
||||
"std",
|
||||
"unicode",
|
||||
] }
|
||||
aho-corasick = "1.0"
|
||||
tantivy-fst = "0.4.0"
|
||||
memmap2 = { version = "0.6.0", optional = true }
|
||||
lz4_flex = { version = "0.10", default-features = false, features = ["checked-decode"], optional = true }
|
||||
brotli = { version = "3.3.4", optional = true }
|
||||
zstd = { version = "0.12", optional = true, default-features = false }
|
||||
snap = { version = "1.0.5", optional = true }
|
||||
tempfile = { version = "3.3.0", optional = true }
|
||||
tantivy-fst = "0.5"
|
||||
memmap2 = { version = "0.9.0", optional = true }
|
||||
lz4_flex = { version = "0.11", default-features = false, optional = true }
|
||||
zstd = { version = "0.13", optional = true, default-features = false }
|
||||
tempfile = { version = "3.12.0", optional = true }
|
||||
log = "0.4.16"
|
||||
serde = { version = "1.0.136", features = ["derive"] }
|
||||
serde_json = "1.0.79"
|
||||
num_cpus = "1.13.1"
|
||||
fs4 = { version = "0.6.3", optional = true }
|
||||
serde = { version = "1.0.219", features = ["derive"] }
|
||||
serde_json = "1.0.140"
|
||||
fs4 = { version = "0.8.0", optional = true }
|
||||
levenshtein_automata = "0.2.1"
|
||||
uuid = { version = "1.0.0", features = ["v4", "serde"] }
|
||||
crossbeam-channel = "0.5.4"
|
||||
rust-stemmers = "1.2.0"
|
||||
downcast-rs = "1.2.0"
|
||||
bitpacking = { version = "0.8.4", default-features = false, features = ["bitpacker4x"] }
|
||||
census = "0.4.0"
|
||||
rustc-hash = "1.1.0"
|
||||
thiserror = "1.0.30"
|
||||
downcast-rs = "2.0.1"
|
||||
bitpacking = { version = "0.9.2", default-features = false, features = [
|
||||
"bitpacker4x",
|
||||
] }
|
||||
census = "0.4.2"
|
||||
rustc-hash = "2.0.0"
|
||||
thiserror = "2.0.1"
|
||||
htmlescape = "0.3.1"
|
||||
fail = "0.5.0"
|
||||
murmurhash32 = "0.3.0"
|
||||
time = { version = "0.3.10", features = ["serde-well-known"] }
|
||||
fail = { version = "0.5.0", optional = true }
|
||||
time = { version = "0.3.35", features = ["serde-well-known"] }
|
||||
smallvec = "1.8.0"
|
||||
rayon = "1.5.2"
|
||||
lru = "0.10.0"
|
||||
lru = "0.12.0"
|
||||
fastdivide = "0.4.0"
|
||||
itertools = "0.10.3"
|
||||
measure_time = "0.8.2"
|
||||
async-trait = "0.1.53"
|
||||
itertools = "0.14.0"
|
||||
measure_time = "0.9.0"
|
||||
arc-swap = "1.5.0"
|
||||
bon = "3.3.1"
|
||||
|
||||
columnar = { version= "0.1", path="./columnar", package ="tantivy-columnar" }
|
||||
sstable = { version= "0.1", path="./sstable", package ="tantivy-sstable", optional = true }
|
||||
stacker = { version= "0.1", path="./stacker", package ="tantivy-stacker" }
|
||||
query-grammar = { version= "0.20.0", path="./query-grammar", package = "tantivy-query-grammar" }
|
||||
tantivy-bitpacker = { version= "0.4", path="./bitpacker" }
|
||||
common = { version= "0.5", path = "./common/", package = "tantivy-common" }
|
||||
tokenizer-api = { version= "0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
|
||||
sketches-ddsketch = { version = "0.2.1", features = ["use_serde"] }
|
||||
columnar = { version = "0.5", path = "./columnar", package = "tantivy-columnar" }
|
||||
sstable = { version = "0.5", path = "./sstable", package = "tantivy-sstable", optional = true }
|
||||
stacker = { version = "0.5", path = "./stacker", package = "tantivy-stacker" }
|
||||
query-grammar = { version = "0.24.0", path = "./query-grammar", package = "tantivy-query-grammar" }
|
||||
tantivy-bitpacker = { version = "0.8", path = "./bitpacker" }
|
||||
common = { version = "0.9", path = "./common/", package = "tantivy-common" }
|
||||
tokenizer-api = { version = "0.5", path = "./tokenizer-api", package = "tantivy-tokenizer-api" }
|
||||
sketches-ddsketch = { version = "0.3.0", features = ["use_serde"] }
|
||||
hyperloglogplus = { version = "0.4.1", features = ["const-loop"] }
|
||||
futures-util = { version = "0.3.28", optional = true }
|
||||
futures-channel = { version = "0.3.28", optional = true }
|
||||
fnv = "1.0.7"
|
||||
|
||||
[target.'cfg(windows)'.dependencies]
|
||||
winapi = "0.3.9"
|
||||
|
||||
[dev-dependencies]
|
||||
binggan = "0.14.0"
|
||||
rand = "0.8.5"
|
||||
maplit = "1.0.2"
|
||||
matches = "0.1.9"
|
||||
pretty_assertions = "1.2.1"
|
||||
proptest = "1.0.0"
|
||||
criterion = "0.5"
|
||||
test-log = "0.2.10"
|
||||
env_logger = "0.10.0"
|
||||
pprof = { git = "https://github.com/PSeitz/pprof-rs/", rev = "53af24b", features = ["flamegraph", "criterion"] } # temp fork that works with criterion 0.5
|
||||
futures = "0.3.21"
|
||||
paste = "1.0.11"
|
||||
more-asserts = "0.3.1"
|
||||
rand_distr = "0.4.3"
|
||||
time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
|
||||
postcard = { version = "1.0.4", features = [
|
||||
"use-std",
|
||||
], default-features = false }
|
||||
|
||||
[target.'cfg(not(windows))'.dev-dependencies]
|
||||
criterion = { version = "0.5", default-features = false }
|
||||
|
||||
[dev-dependencies.fail]
|
||||
version = "0.5.0"
|
||||
@@ -107,18 +116,30 @@ default = ["mmap", "stopwords", "lz4-compression"]
|
||||
mmap = ["fs4", "tempfile", "memmap2"]
|
||||
stopwords = []
|
||||
|
||||
brotli-compression = ["brotli"]
|
||||
lz4-compression = ["lz4_flex"]
|
||||
snappy-compression = ["snap"]
|
||||
zstd-compression = ["zstd"]
|
||||
|
||||
failpoints = ["fail/failpoints"]
|
||||
unstable = [] # useful for benches.
|
||||
failpoints = ["fail", "fail/failpoints"]
|
||||
unstable = [] # useful for benches.
|
||||
|
||||
quickwit = ["sstable", "futures-util"]
|
||||
quickwit = ["sstable", "futures-util", "futures-channel"]
|
||||
|
||||
# Compares only the hash of a string when indexing data.
|
||||
# Increases indexing speed, but may lead to extremely rare missing terms, when there's a hash collision.
|
||||
# Uses 64bit ahash.
|
||||
compare_hash_only = ["stacker/compare_hash_only"]
|
||||
|
||||
[workspace]
|
||||
members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sstable", "tokenizer-api", "columnar"]
|
||||
members = [
|
||||
"query-grammar",
|
||||
"bitpacker",
|
||||
"common",
|
||||
"ownedbytes",
|
||||
"stacker",
|
||||
"sstable",
|
||||
"tokenizer-api",
|
||||
"columnar",
|
||||
]
|
||||
|
||||
# Following the "fail" crate best practises, we isolate
|
||||
# tests that define specific behavior in fail check points
|
||||
@@ -130,7 +151,7 @@ members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sst
|
||||
[[test]]
|
||||
name = "failpoints"
|
||||
path = "tests/failpoints/mod.rs"
|
||||
required-features = ["fail/failpoints"]
|
||||
required-features = ["failpoints"]
|
||||
|
||||
[[bench]]
|
||||
name = "analyzer"
|
||||
@@ -139,3 +160,7 @@ harness = false
|
||||
[[bench]]
|
||||
name = "index-bench"
|
||||
harness = false
|
||||
|
||||
[[bench]]
|
||||
name = "agg_bench"
|
||||
harness = false
|
||||
|
||||
40
README.md
40
README.md
@@ -5,21 +5,20 @@
|
||||
[](https://opensource.org/licenses/MIT)
|
||||
[](https://crates.io/crates/tantivy)
|
||||
|
||||

|
||||
<img src="https://tantivy-search.github.io/logo/tantivy-logo.png" alt="Tantivy, the fastest full-text search engine library written in Rust" height="250">
|
||||
|
||||
**Tantivy** is a **full-text search engine library** written in Rust.
|
||||
## Fast full-text search engine library written in Rust
|
||||
|
||||
It is closer to [Apache Lucene](https://lucene.apache.org/) than to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Apache Solr](https://lucene.apache.org/solr/) in the sense it is not
|
||||
an off-the-shelf search engine server, but rather a crate that can be used
|
||||
to build such a search engine.
|
||||
**If you are looking for an alternative to Elasticsearch or Apache Solr, check out [Quickwit](https://github.com/quickwit-oss/quickwit), our distributed search engine built on top of Tantivy.**
|
||||
|
||||
Tantivy is closer to [Apache Lucene](https://lucene.apache.org/) than to [Elasticsearch](https://www.elastic.co/products/elasticsearch) or [Apache Solr](https://lucene.apache.org/solr/) in the sense it is not
|
||||
an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine.
|
||||
|
||||
Tantivy is, in fact, strongly inspired by Lucene's design.
|
||||
|
||||
If you are looking for an alternative to Elasticsearch or Apache Solr, check out [Quickwit](https://github.com/quickwit-oss/quickwit), our search engine built on top of Tantivy.
|
||||
## Benchmark
|
||||
|
||||
# Benchmark
|
||||
|
||||
The following [benchmark](https://tantivy-search.github.io/bench/) breakdowns
|
||||
The following [benchmark](https://tantivy-search.github.io/bench/) breaks down the
|
||||
performance for different types of queries/collections.
|
||||
|
||||
Your mileage WILL vary depending on the nature of queries and their load.
|
||||
@@ -28,7 +27,7 @@ Your mileage WILL vary depending on the nature of queries and their load.
|
||||
|
||||
Details about the benchmark can be found at this [repository](https://github.com/quickwit-oss/search-benchmark-game).
|
||||
|
||||
# Features
|
||||
## Features
|
||||
|
||||
- Full-text search
|
||||
- Configurable tokenizer (stemming available for 17 Latin languages) with third party support for Chinese ([tantivy-jieba](https://crates.io/crates/tantivy-jieba) and [cang-jie](https://crates.io/crates/cang-jie)), Japanese ([lindera](https://github.com/lindera-morphology/lindera-tantivy), [Vaporetto](https://crates.io/crates/vaporetto_tantivy), and [tantivy-tokenizer-tiny-segmenter](https://crates.io/crates/tantivy-tokenizer-tiny-segmenter)) and Korean ([lindera](https://github.com/lindera-morphology/lindera-tantivy) + [lindera-ko-dic-builder](https://github.com/lindera-morphology/lindera-ko-dic-builder))
|
||||
@@ -44,7 +43,7 @@ Details about the benchmark can be found at this [repository](https://github.com
|
||||
- Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene)
|
||||
- `&[u8]` fast fields
|
||||
- Text, i64, u64, f64, dates, ip, bool, and hierarchical facet fields
|
||||
- Compressed document store (LZ4, Zstd, None, Brotli, Snap)
|
||||
- Compressed document store (LZ4, Zstd, None)
|
||||
- Range queries
|
||||
- Faceted search
|
||||
- Configurable indexing (optional term frequency and position indexing)
|
||||
@@ -54,11 +53,11 @@ Details about the benchmark can be found at this [repository](https://github.com
|
||||
- Searcher Warmer API
|
||||
- Cheesy logo with a horse
|
||||
|
||||
## Non-features
|
||||
### Non-features
|
||||
|
||||
Distributed search is out of the scope of Tantivy, but if you are looking for this feature, check out [Quickwit](https://github.com/quickwit-oss/quickwit/).
|
||||
|
||||
# Getting started
|
||||
## Getting started
|
||||
|
||||
Tantivy works on stable Rust and supports Linux, macOS, and Windows.
|
||||
|
||||
@@ -68,7 +67,7 @@ index documents, and search via the CLI or a small server with a REST API.
|
||||
It walks you through getting a Wikipedia search engine up and running in a few minutes.
|
||||
- [Reference doc for the last released version](https://docs.rs/tantivy/)
|
||||
|
||||
# How can I support this project?
|
||||
## How can I support this project?
|
||||
|
||||
There are many ways to support this project.
|
||||
|
||||
@@ -79,16 +78,16 @@ There are many ways to support this project.
|
||||
- Contribute code (you can join [our Discord server](https://discord.gg/MT27AG5EVE))
|
||||
- Talk about Tantivy around you
|
||||
|
||||
# Contributing code
|
||||
## Contributing code
|
||||
|
||||
We use the GitHub Pull Request workflow: reference a GitHub ticket and/or include a comprehensive commit message when opening a PR.
|
||||
Feel free to update CHANGELOG.md with your contribution.
|
||||
|
||||
## Tokenizer
|
||||
### Tokenizer
|
||||
|
||||
When implementing a tokenizer for tantivy depend on the `tantivy-tokenizer-api` crate.
|
||||
|
||||
## Clone and build locally
|
||||
### Clone and build locally
|
||||
|
||||
Tantivy compiles on stable Rust.
|
||||
To check out and run tests, you can simply run:
|
||||
@@ -99,10 +98,11 @@ cd tantivy
|
||||
cargo test
|
||||
```
|
||||
|
||||
# Companies Using Tantivy
|
||||
## Companies Using Tantivy
|
||||
|
||||
<p align="left">
|
||||
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />
|
||||
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />
|
||||
<img align="center" src="doc/assets/images/paradedb.png" alt="ParadeDB" height="25" width="auto" />
|
||||
<img align="center" src="doc/assets/images/Nuclia.png#gh-light-mode-only" alt="Nuclia" height="25" width="auto" />
|
||||
<img align="center" src="doc/assets/images/humanfirst.png#gh-light-mode-only" alt="Humanfirst.ai" height="30" width="auto" />
|
||||
<img align="center" src="doc/assets/images/element.io.svg#gh-light-mode-only" alt="Element.io" height="25" width="auto" />
|
||||
@@ -111,7 +111,7 @@ cargo test
|
||||
<img align="center" src="doc/assets/images/element-dark-theme.png#gh-dark-mode-only" alt="Element.io" height="25" width="auto" />
|
||||
</p>
|
||||
|
||||
# FAQ
|
||||
## FAQ
|
||||
|
||||
### Can I use Tantivy in other languages?
|
||||
|
||||
|
||||
2
TODO.txt
2
TODO.txt
@@ -1,7 +1,7 @@
|
||||
Make schema_builder API fluent.
|
||||
fix doc serialization and prevent compression problems
|
||||
|
||||
u64 , etc. shoudl return Resutl<Option> now that we support optional missing a column is really not an error
|
||||
u64 , etc. should return Result<Option> now that we support optional missing a column is really not an error
|
||||
remove fastfield codecs
|
||||
ditch the first_or_default trick. if it is still useful, improve its implementation.
|
||||
rename FastFieldReaders::open to load
|
||||
|
||||
462
benches/agg_bench.rs
Normal file
462
benches/agg_bench.rs
Normal file
@@ -0,0 +1,462 @@
|
||||
use binggan::plugins::PeakMemAllocPlugin;
|
||||
use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
|
||||
use rand::prelude::SliceRandom;
|
||||
use rand::rngs::StdRng;
|
||||
use rand::{Rng, SeedableRng};
|
||||
use rand_distr::Distribution;
|
||||
use serde_json::json;
|
||||
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};
|
||||
|
||||
#[global_allocator]
|
||||
pub static GLOBAL: &PeakMemAlloc<std::alloc::System> = &INSTRUMENTED_SYSTEM;
|
||||
|
||||
/// Mini macro to register a function via its name
|
||||
/// runner.register("average_u64", move |index| average_u64(index));
|
||||
macro_rules! register {
|
||||
($runner:expr, $func:ident) => {
|
||||
$runner.register(stringify!($func), move |index| {
|
||||
$func(index);
|
||||
})
|
||||
};
|
||||
}
|
||||
|
||||
fn main() {
|
||||
let inputs = vec![
|
||||
("full", get_test_index_bench(Cardinality::Full).unwrap()),
|
||||
(
|
||||
"dense",
|
||||
get_test_index_bench(Cardinality::OptionalDense).unwrap(),
|
||||
),
|
||||
(
|
||||
"sparse",
|
||||
get_test_index_bench(Cardinality::OptionalSparse).unwrap(),
|
||||
),
|
||||
(
|
||||
"multivalue",
|
||||
get_test_index_bench(Cardinality::Multivalued).unwrap(),
|
||||
),
|
||||
];
|
||||
|
||||
bench_agg(InputGroup::new_with_inputs(inputs));
|
||||
}
|
||||
|
||||
fn bench_agg(mut group: InputGroup<Index>) {
|
||||
group.add_plugin(PeakMemAllocPlugin::new(GLOBAL));
|
||||
|
||||
register!(group, average_u64);
|
||||
register!(group, average_f64);
|
||||
register!(group, average_f64_u64);
|
||||
register!(group, stats_f64);
|
||||
register!(group, extendedstats_f64);
|
||||
register!(group, percentiles_f64);
|
||||
register!(group, terms_few);
|
||||
register!(group, terms_many);
|
||||
register!(group, terms_many_top_1000);
|
||||
register!(group, terms_many_order_by_term);
|
||||
register!(group, terms_many_with_top_hits);
|
||||
register!(group, terms_many_with_avg_sub_agg);
|
||||
register!(group, terms_many_json_mixed_type_with_avg_sub_agg);
|
||||
|
||||
register!(group, cardinality_agg);
|
||||
register!(group, terms_few_with_cardinality_agg);
|
||||
|
||||
register!(group, range_agg);
|
||||
register!(group, range_agg_with_avg_sub_agg);
|
||||
register!(group, range_agg_with_term_agg_few);
|
||||
register!(group, range_agg_with_term_agg_many);
|
||||
register!(group, histogram);
|
||||
register!(group, histogram_hard_bounds);
|
||||
register!(group, histogram_with_avg_sub_agg);
|
||||
register!(group, avg_and_range_with_avg_sub_agg);
|
||||
|
||||
group.run();
|
||||
}
|
||||
|
||||
fn exec_term_with_agg(index: &Index, agg_req: serde_json::Value) {
|
||||
let agg_req: Aggregations = serde_json::from_value(agg_req).unwrap();
|
||||
|
||||
let reader = index.reader().unwrap();
|
||||
let text_field = reader.searcher().schema().get_field("text").unwrap();
|
||||
let term_query = TermQuery::new(
|
||||
Term::from_field_text(text_field, "cool"),
|
||||
IndexRecordOption::Basic,
|
||||
);
|
||||
let collector = get_collector(agg_req);
|
||||
let searcher = reader.searcher();
|
||||
black_box(searcher.search(&term_query, &collector).unwrap());
|
||||
}
|
||||
|
||||
fn average_u64(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"average": { "avg": { "field": "score", } }
|
||||
});
|
||||
exec_term_with_agg(index, agg_req)
|
||||
}
|
||||
fn average_f64(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"average": { "avg": { "field": "score_f64", } }
|
||||
});
|
||||
exec_term_with_agg(index, agg_req)
|
||||
}
|
||||
fn average_f64_u64(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"average_f64": { "avg": { "field": "score_f64" } },
|
||||
"average": { "avg": { "field": "score" } },
|
||||
});
|
||||
exec_term_with_agg(index, agg_req)
|
||||
}
|
||||
fn stats_f64(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"average_f64": { "stats": { "field": "score_f64", } }
|
||||
});
|
||||
exec_term_with_agg(index, agg_req)
|
||||
}
|
||||
fn extendedstats_f64(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"extendedstats_f64": { "extended_stats": { "field": "score_f64", } }
|
||||
});
|
||||
exec_term_with_agg(index, agg_req)
|
||||
}
|
||||
fn percentiles_f64(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"mypercentiles": {
|
||||
"percentiles": {
|
||||
"field": "score_f64",
|
||||
"percents": [ 95, 99, 99.9 ]
|
||||
}
|
||||
}
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
|
||||
fn cardinality_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"cardinality": {
|
||||
"cardinality": {
|
||||
"field": "text_many_terms"
|
||||
},
|
||||
}
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_few_with_cardinality_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": {
|
||||
"terms": { "field": "text_few_terms" },
|
||||
"aggs": {
|
||||
"cardinality": {
|
||||
"cardinality": {
|
||||
"field": "text_many_terms"
|
||||
},
|
||||
}
|
||||
}
|
||||
},
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
|
||||
fn terms_few(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": { "terms": { "field": "text_few_terms" } },
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_many(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": { "terms": { "field": "text_many_terms" } },
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_many_top_1000(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": { "terms": { "field": "text_many_terms", "size": 1000 } },
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_many_order_by_term(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": { "terms": { "field": "text_many_terms", "order": { "_key": "desc" } } },
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_many_with_top_hits(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": {
|
||||
"terms": { "field": "text_many_terms" },
|
||||
"aggs": {
|
||||
"top_hits": { "top_hits":
|
||||
{
|
||||
"sort": [
|
||||
{ "score": "desc" }
|
||||
],
|
||||
"size": 2,
|
||||
"doc_value_fields": ["score_f64"]
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_many_with_avg_sub_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": {
|
||||
"terms": { "field": "text_many_terms" },
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
},
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn terms_many_json_mixed_type_with_avg_sub_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"my_texts": {
|
||||
"terms": { "field": "json.mixed_type" },
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
},
|
||||
});
|
||||
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);
|
||||
|
||||
let reader = index.reader().unwrap();
|
||||
let searcher = reader.searcher();
|
||||
black_box(searcher.search(&AllQuery, &collector).unwrap());
|
||||
}
|
||||
fn range_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"range_f64": { "range": { "field": "score_f64", "ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 30000 },
|
||||
{ "from": 30000, "to": 40000 },
|
||||
{ "from": 40000, "to": 50000 },
|
||||
{ "from": 50000, "to": 60000 }
|
||||
] } },
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn range_agg_with_avg_sub_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": {
|
||||
"range": {
|
||||
"field": "score_f64",
|
||||
"ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 30000 },
|
||||
{ "from": 30000, "to": 40000 },
|
||||
{ "from": 40000, "to": 50000 },
|
||||
{ "from": 50000, "to": 60000 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
},
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
|
||||
fn range_agg_with_term_agg_few(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": {
|
||||
"range": {
|
||||
"field": "score_f64",
|
||||
"ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 30000 },
|
||||
{ "from": 30000, "to": 40000 },
|
||||
{ "from": 40000, "to": 50000 },
|
||||
{ "from": 50000, "to": 60000 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"my_texts": { "terms": { "field": "text_few_terms" } },
|
||||
}
|
||||
},
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn range_agg_with_term_agg_many(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": {
|
||||
"range": {
|
||||
"field": "score_f64",
|
||||
"ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 30000 },
|
||||
{ "from": 30000, "to": 40000 },
|
||||
{ "from": 40000, "to": 50000 },
|
||||
{ "from": 50000, "to": 60000 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"my_texts": { "terms": { "field": "text_many_terms" } },
|
||||
}
|
||||
},
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
|
||||
fn histogram(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": {
|
||||
"histogram": {
|
||||
"field": "score_f64",
|
||||
"interval": 100 // 1000 buckets
|
||||
},
|
||||
}
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn histogram_hard_bounds(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": { "histogram": { "field": "score_f64", "interval": 100, "hard_bounds": { "min": 1000, "max": 300000 } } },
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn histogram_with_avg_sub_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": {
|
||||
"histogram": { "field": "score_f64", "interval": 100 },
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
}
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
fn avg_and_range_with_avg_sub_agg(index: &Index) {
|
||||
let agg_req = json!({
|
||||
"rangef64": {
|
||||
"range": {
|
||||
"field": "score_f64",
|
||||
"ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 60000 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"average_in_range": { "avg": { "field": "score" } }
|
||||
}
|
||||
},
|
||||
"average": { "avg": { "field": "score" } }
|
||||
});
|
||||
execute_agg(index, agg_req);
|
||||
}
|
||||
|
||||
#[derive(Clone, Copy, Hash, Default, Debug, PartialEq, Eq, PartialOrd, Ord)]
|
||||
enum Cardinality {
|
||||
/// All documents contain exactly one value.
|
||||
/// `Full` is the default for auto-detecting the Cardinality, since it is the most strict.
|
||||
#[default]
|
||||
Full = 0,
|
||||
/// All documents contain at most one value.
|
||||
OptionalDense = 1,
|
||||
/// All documents may contain any number of values.
|
||||
Multivalued = 2,
|
||||
/// 1 / 20 documents has a value
|
||||
OptionalSparse = 3,
|
||||
}
|
||||
|
||||
fn get_collector(agg_req: Aggregations) -> AggregationCollector {
|
||||
AggregationCollector::from_aggs(agg_req, Default::default())
|
||||
}
|
||||
|
||||
fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let text_fieldtype = tantivy::schema::TextOptions::default()
|
||||
.set_indexing_options(
|
||||
TextFieldIndexing::default().set_index_option(IndexRecordOption::WithFreqs),
|
||||
)
|
||||
.set_stored();
|
||||
let text_field = schema_builder.add_text_field("text", text_fieldtype);
|
||||
let json_field = schema_builder.add_json_field("json", 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 score_fieldtype = tantivy::schema::NumericOptions::default().set_fast();
|
||||
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 index = Index::create_from_tempdir(schema_builder.build())?;
|
||||
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)
|
||||
.map(|num| format!("author{num}"))
|
||||
.collect::<Vec<_>>();
|
||||
{
|
||||
let mut rng = StdRng::from_seed([1u8; 32]);
|
||||
let mut index_writer = index.writer_with_num_threads(1, 200_000_000)?;
|
||||
// To make the different test cases comparable we just change one doc to force the
|
||||
// cardinality
|
||||
if cardinality == Cardinality::OptionalDense {
|
||||
index_writer.add_document(doc!())?;
|
||||
}
|
||||
if cardinality == Cardinality::Multivalued {
|
||||
index_writer.add_document(doc!(
|
||||
json_field => json!({"mixed_type": 10.0}),
|
||||
json_field => json!({"mixed_type": 10.0}),
|
||||
text_field => "cool",
|
||||
text_field => "cool",
|
||||
text_field_many_terms => "cool",
|
||||
text_field_many_terms => "cool",
|
||||
text_field_few_terms => "cool",
|
||||
text_field_few_terms => "cool",
|
||||
score_field => 1u64,
|
||||
score_field => 1u64,
|
||||
score_field_f64 => lg_norm.sample(&mut rng),
|
||||
score_field_f64 => lg_norm.sample(&mut rng),
|
||||
score_field_i64 => 1i64,
|
||||
score_field_i64 => 1i64,
|
||||
))?;
|
||||
}
|
||||
let mut doc_with_value = 1_000_000;
|
||||
if cardinality == Cardinality::OptionalSparse {
|
||||
doc_with_value /= 20;
|
||||
}
|
||||
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) {
|
||||
// 10% are numeric values
|
||||
json!({ "mixed_type": val })
|
||||
} else {
|
||||
json!({"mixed_type": many_terms_data.choose(&mut rng).unwrap().to_string()})
|
||||
};
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "cool",
|
||||
json_field => json,
|
||||
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(),
|
||||
score_field => val as u64,
|
||||
score_field_f64 => lg_norm.sample(&mut rng),
|
||||
score_field_i64 => val as i64,
|
||||
))?;
|
||||
if cardinality == Cardinality::OptionalSparse {
|
||||
for _ in 0..20 {
|
||||
index_writer.add_document(doc!(text_field => "cool"))?;
|
||||
}
|
||||
}
|
||||
}
|
||||
// writing the segment
|
||||
index_writer.commit()?;
|
||||
}
|
||||
|
||||
Ok(index)
|
||||
}
|
||||
@@ -1,5 +1,7 @@
|
||||
use criterion::{criterion_group, criterion_main, Criterion};
|
||||
use tantivy::tokenizer::TokenizerManager;
|
||||
use tantivy::tokenizer::{
|
||||
LowerCaser, RemoveLongFilter, SimpleTokenizer, TextAnalyzer, TokenizerManager,
|
||||
};
|
||||
|
||||
const ALICE_TXT: &str = include_str!("alice.txt");
|
||||
|
||||
@@ -16,7 +18,26 @@ pub fn criterion_benchmark(c: &mut Criterion) {
|
||||
assert_eq!(word_count, 30_731);
|
||||
})
|
||||
});
|
||||
let mut dynamic_analyzer = TextAnalyzer::builder(SimpleTokenizer::default())
|
||||
.dynamic()
|
||||
.filter_dynamic(RemoveLongFilter::limit(40))
|
||||
.filter_dynamic(LowerCaser)
|
||||
.build();
|
||||
c.bench_function("dynamic-tokenize-alice", |b| {
|
||||
b.iter(|| {
|
||||
let mut word_count = 0;
|
||||
let mut token_stream = dynamic_analyzer.token_stream(ALICE_TXT);
|
||||
while token_stream.advance() {
|
||||
word_count += 1;
|
||||
}
|
||||
assert_eq!(word_count, 30_731);
|
||||
})
|
||||
});
|
||||
}
|
||||
|
||||
criterion_group!(benches, criterion_benchmark);
|
||||
criterion_group! {
|
||||
name = benches;
|
||||
config = Criterion::default().sample_size(200);
|
||||
targets = criterion_benchmark
|
||||
}
|
||||
criterion_main!(benches);
|
||||
|
||||
@@ -1,14 +1,98 @@
|
||||
use criterion::{criterion_group, criterion_main, Criterion, Throughput};
|
||||
use pprof::criterion::{Output, PProfProfiler};
|
||||
use tantivy::schema::{FAST, INDEXED, STORED, STRING, TEXT};
|
||||
use tantivy::Index;
|
||||
use criterion::{criterion_group, criterion_main, BatchSize, Bencher, Criterion, Throughput};
|
||||
use tantivy::schema::{TantivyDocument, FAST, INDEXED, STORED, STRING, TEXT};
|
||||
use tantivy::{tokenizer, Index, IndexWriter};
|
||||
|
||||
const HDFS_LOGS: &str = include_str!("hdfs.json");
|
||||
const GH_LOGS: &str = include_str!("gh.json");
|
||||
const WIKI: &str = include_str!("wiki.json");
|
||||
|
||||
fn get_lines(input: &str) -> Vec<&str> {
|
||||
input.trim().split('\n').collect()
|
||||
fn benchmark(
|
||||
b: &mut Bencher,
|
||||
input: &str,
|
||||
schema: tantivy::schema::Schema,
|
||||
commit: bool,
|
||||
parse_json: bool,
|
||||
is_dynamic: bool,
|
||||
) {
|
||||
if is_dynamic {
|
||||
benchmark_dynamic_json(b, input, schema, commit, parse_json)
|
||||
} else {
|
||||
_benchmark(b, input, schema, commit, parse_json, |schema, doc_json| {
|
||||
TantivyDocument::parse_json(schema, doc_json).unwrap()
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
fn get_index(schema: tantivy::schema::Schema) -> Index {
|
||||
let mut index = Index::create_in_ram(schema.clone());
|
||||
let ff_tokenizer_manager = tokenizer::TokenizerManager::default();
|
||||
ff_tokenizer_manager.register(
|
||||
"raw",
|
||||
tokenizer::TextAnalyzer::builder(tokenizer::RawTokenizer::default())
|
||||
.filter(tokenizer::RemoveLongFilter::limit(255))
|
||||
.build(),
|
||||
);
|
||||
index.set_fast_field_tokenizers(ff_tokenizer_manager.clone());
|
||||
index
|
||||
}
|
||||
|
||||
fn _benchmark(
|
||||
b: &mut Bencher,
|
||||
input: &str,
|
||||
schema: tantivy::schema::Schema,
|
||||
commit: bool,
|
||||
include_json_parsing: bool,
|
||||
create_doc: impl Fn(&tantivy::schema::Schema, &str) -> TantivyDocument,
|
||||
) {
|
||||
if include_json_parsing {
|
||||
let lines: Vec<&str> = input.trim().split('\n').collect();
|
||||
b.iter(|| {
|
||||
let index = get_index(schema.clone());
|
||||
let mut index_writer: IndexWriter =
|
||||
index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = create_doc(&schema, doc_json);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
if commit {
|
||||
index_writer.commit().unwrap();
|
||||
}
|
||||
})
|
||||
} else {
|
||||
let docs: Vec<_> = input
|
||||
.trim()
|
||||
.split('\n')
|
||||
.map(|doc_json| create_doc(&schema, doc_json))
|
||||
.collect();
|
||||
b.iter_batched(
|
||||
|| docs.clone(),
|
||||
|docs| {
|
||||
let index = get_index(schema.clone());
|
||||
let mut index_writer: IndexWriter =
|
||||
index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc in docs {
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
if commit {
|
||||
index_writer.commit().unwrap();
|
||||
}
|
||||
},
|
||||
BatchSize::SmallInput,
|
||||
)
|
||||
}
|
||||
}
|
||||
fn benchmark_dynamic_json(
|
||||
b: &mut Bencher,
|
||||
input: &str,
|
||||
schema: tantivy::schema::Schema,
|
||||
commit: bool,
|
||||
parse_json: bool,
|
||||
) {
|
||||
let json_field = schema.get_field("json").unwrap();
|
||||
_benchmark(b, input, schema, commit, parse_json, |_schema, doc_json| {
|
||||
let json_val: serde_json::Value = serde_json::from_str(doc_json).unwrap();
|
||||
tantivy::doc!(json_field=>json_val)
|
||||
})
|
||||
}
|
||||
|
||||
pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
@@ -19,7 +103,14 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
schema_builder.add_text_field("severity", STRING);
|
||||
schema_builder.build()
|
||||
};
|
||||
let schema_with_store = {
|
||||
let schema_only_fast = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_u64_field("timestamp", FAST);
|
||||
schema_builder.add_text_field("body", FAST);
|
||||
schema_builder.add_text_field("severity", FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
let _schema_with_store = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_u64_field("timestamp", INDEXED | STORED);
|
||||
schema_builder.add_text_field("body", TEXT | STORED);
|
||||
@@ -28,74 +119,40 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
};
|
||||
let dynamic_schema = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_json_field("json", TEXT);
|
||||
schema_builder.add_json_field("json", TEXT | FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-hdfs");
|
||||
group.throughput(Throughput::Bytes(HDFS_LOGS.len() as u64));
|
||||
group.sample_size(20);
|
||||
group.bench_function("index-hdfs-no-commit", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
|
||||
let benches = [
|
||||
("only-indexed-".to_string(), schema, false),
|
||||
//("stored-".to_string(), _schema_with_store, false),
|
||||
("only-fast-".to_string(), schema_only_fast, false),
|
||||
("dynamic-".to_string(), dynamic_schema, true),
|
||||
];
|
||||
|
||||
for (prefix, schema, is_dynamic) in benches {
|
||||
for commit in [false, true] {
|
||||
let suffix = if commit { "with-commit" } else { "no-commit" };
|
||||
{
|
||||
let parse_json = false;
|
||||
// for parse_json in [false, true] {
|
||||
let suffix = if parse_json {
|
||||
format!("{suffix}-with-json-parsing")
|
||||
} else {
|
||||
suffix.to_string()
|
||||
};
|
||||
|
||||
let bench_name = format!("{prefix}{suffix}");
|
||||
group.bench_function(bench_name, |b| {
|
||||
benchmark(b, HDFS_LOGS, schema.clone(), commit, parse_json, is_dynamic)
|
||||
});
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-no-commit-with-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema_with_store.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit-with-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema_with_store.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-no-commit-json-without-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub fn gh_index_benchmark(c: &mut Criterion) {
|
||||
@@ -104,38 +161,24 @@ pub fn gh_index_benchmark(c: &mut Criterion) {
|
||||
schema_builder.add_json_field("json", TEXT | FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
let dynamic_schema_fast = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_json_field("json", FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-gh");
|
||||
group.throughput(Throughput::Bytes(GH_LOGS.len() as u64));
|
||||
|
||||
group.bench_function("index-gh-no-commit", |b| {
|
||||
let lines = get_lines(GH_LOGS);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema.clone(), false, false)
|
||||
});
|
||||
group.bench_function("index-gh-with-commit", |b| {
|
||||
let lines = get_lines(GH_LOGS);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
group.bench_function("index-gh-fast", |b| {
|
||||
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema_fast.clone(), false, false)
|
||||
});
|
||||
|
||||
group.bench_function("index-gh-fast-with-commit", |b| {
|
||||
benchmark_dynamic_json(b, GH_LOGS, dynamic_schema_fast.clone(), true, false)
|
||||
});
|
||||
}
|
||||
|
||||
@@ -150,33 +193,10 @@ pub fn wiki_index_benchmark(c: &mut Criterion) {
|
||||
group.throughput(Throughput::Bytes(WIKI.len() as u64));
|
||||
|
||||
group.bench_function("index-wiki-no-commit", |b| {
|
||||
let lines = get_lines(WIKI);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
benchmark_dynamic_json(b, WIKI, dynamic_schema.clone(), false, false)
|
||||
});
|
||||
group.bench_function("index-wiki-with-commit", |b| {
|
||||
let lines = get_lines(WIKI);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
benchmark_dynamic_json(b, WIKI, dynamic_schema.clone(), true, false)
|
||||
});
|
||||
}
|
||||
|
||||
@@ -187,12 +207,12 @@ criterion_group! {
|
||||
}
|
||||
criterion_group! {
|
||||
name = gh_benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
config = Criterion::default();
|
||||
targets = gh_index_benchmark
|
||||
}
|
||||
criterion_group! {
|
||||
name = wiki_benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
config = Criterion::default();
|
||||
targets = wiki_index_benchmark
|
||||
}
|
||||
criterion_main!(benches, gh_benches, wiki_benches);
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-bitpacker"
|
||||
version = "0.4.0"
|
||||
version = "0.8.0"
|
||||
edition = "2021"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
@@ -15,7 +15,7 @@ homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
|
||||
|
||||
[dependencies]
|
||||
bitpacking = {version="0.8", default-features=false, features = ["bitpacker1x"]}
|
||||
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker1x"] }
|
||||
|
||||
[dev-dependencies]
|
||||
rand = "0.8"
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io;
|
||||
use std::ops::{Range, RangeInclusive};
|
||||
|
||||
@@ -66,7 +65,7 @@ impl BitPacker {
|
||||
|
||||
#[derive(Clone, Debug, Default, Copy)]
|
||||
pub struct BitUnpacker {
|
||||
num_bits: u32,
|
||||
num_bits: usize,
|
||||
mask: u64,
|
||||
}
|
||||
|
||||
@@ -84,7 +83,7 @@ impl BitUnpacker {
|
||||
(1u64 << num_bits) - 1u64
|
||||
};
|
||||
BitUnpacker {
|
||||
num_bits: u32::from(num_bits),
|
||||
num_bits: usize::from(num_bits),
|
||||
mask,
|
||||
}
|
||||
}
|
||||
@@ -95,14 +94,14 @@ impl BitUnpacker {
|
||||
|
||||
#[inline]
|
||||
pub fn get(&self, idx: u32, data: &[u8]) -> u64 {
|
||||
let addr_in_bits = idx * self.num_bits;
|
||||
let addr = (addr_in_bits >> 3) as usize;
|
||||
let addr_in_bits = idx as usize * self.num_bits;
|
||||
let addr = addr_in_bits >> 3;
|
||||
if addr + 8 > data.len() {
|
||||
if self.num_bits == 0 {
|
||||
return 0;
|
||||
}
|
||||
let bit_shift = addr_in_bits & 7;
|
||||
return self.get_slow_path(addr, bit_shift, data);
|
||||
return self.get_slow_path(addr, bit_shift as u32, data);
|
||||
}
|
||||
let bit_shift = addr_in_bits & 7;
|
||||
let bytes: [u8; 8] = (&data[addr..addr + 8]).try_into().unwrap();
|
||||
@@ -135,12 +134,13 @@ impl BitUnpacker {
|
||||
"Bitwidth must be <= 32 to use this method."
|
||||
);
|
||||
|
||||
let end_idx = start_idx + output.len() as u32;
|
||||
let end_idx: u32 = start_idx + output.len() as u32;
|
||||
|
||||
let end_bit_read = end_idx * self.num_bits;
|
||||
// We use `usize` here to avoid overflow issues.
|
||||
let end_bit_read = (end_idx as usize) * self.num_bits;
|
||||
let end_byte_read = (end_bit_read + 7) / 8;
|
||||
assert!(
|
||||
end_byte_read as usize <= data.len(),
|
||||
end_byte_read <= data.len(),
|
||||
"Requested index is out of bounds."
|
||||
);
|
||||
|
||||
@@ -160,24 +160,24 @@ impl BitUnpacker {
|
||||
// We want the start of the fast track to start align with bytes.
|
||||
// A sufficient condition is to start with an idx that is a multiple of 8,
|
||||
// so highway start is the closest multiple of 8 that is >= start_idx.
|
||||
let entrance_ramp_len = 8 - (start_idx % 8) % 8;
|
||||
let entrance_ramp_len: u32 = 8 - (start_idx % 8) % 8;
|
||||
|
||||
let highway_start: u32 = start_idx + entrance_ramp_len;
|
||||
|
||||
if highway_start + BitPacker1x::BLOCK_LEN as u32 > end_idx {
|
||||
if highway_start + (BitPacker1x::BLOCK_LEN as u32) > end_idx {
|
||||
// We don't have enough values to have even a single block of highway.
|
||||
// Let's just supply the values the simple way.
|
||||
get_batch_ramp(start_idx, output);
|
||||
return;
|
||||
}
|
||||
|
||||
let num_blocks: u32 = (end_idx - highway_start) / BitPacker1x::BLOCK_LEN as u32;
|
||||
let num_blocks: usize = (end_idx - highway_start) as usize / BitPacker1x::BLOCK_LEN;
|
||||
|
||||
// Entrance ramp
|
||||
get_batch_ramp(start_idx, &mut output[..entrance_ramp_len as usize]);
|
||||
|
||||
// Highway
|
||||
let mut offset = (highway_start * self.num_bits) as usize / 8;
|
||||
let mut offset = (highway_start as usize * self.num_bits) / 8;
|
||||
let mut output_cursor = (highway_start - start_idx) as usize;
|
||||
for _ in 0..num_blocks {
|
||||
offset += BitPacker1x.decompress(
|
||||
@@ -189,7 +189,7 @@ impl BitUnpacker {
|
||||
}
|
||||
|
||||
// Exit ramp
|
||||
let highway_end = highway_start + num_blocks * BitPacker1x::BLOCK_LEN as u32;
|
||||
let highway_end: u32 = highway_start + (num_blocks * BitPacker1x::BLOCK_LEN) as u32;
|
||||
get_batch_ramp(highway_end, &mut output[output_cursor..]);
|
||||
}
|
||||
|
||||
@@ -367,11 +367,11 @@ mod test {
|
||||
let mut output: Vec<u32> = Vec::new();
|
||||
for len in [0, 1, 2, 32, 33, 34, 64] {
|
||||
for start_idx in 0u32..32u32 {
|
||||
output.resize(len as usize, 0);
|
||||
output.resize(len, 0);
|
||||
bitunpacker.get_batch_u32s(start_idx, &buffer, &mut output);
|
||||
for i in 0..len {
|
||||
for (i, output_byte) in output.iter().enumerate() {
|
||||
let expected = (start_idx + i as u32) & mask;
|
||||
assert_eq!(output[i], expected);
|
||||
assert_eq!(*output_byte, expected);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -34,7 +34,7 @@ struct BlockedBitpackerEntryMetaData {
|
||||
|
||||
impl BlockedBitpackerEntryMetaData {
|
||||
fn new(offset: u64, num_bits: u8, base_value: u64) -> Self {
|
||||
let encoded = offset | (num_bits as u64) << (64 - 8);
|
||||
let encoded = offset | (u64::from(num_bits) << (64 - 8));
|
||||
Self {
|
||||
encoded,
|
||||
base_value,
|
||||
@@ -64,10 +64,8 @@ fn mem_usage<T>(items: &Vec<T>) -> usize {
|
||||
|
||||
impl BlockedBitpacker {
|
||||
pub fn new() -> Self {
|
||||
let mut compressed_blocks = vec![];
|
||||
compressed_blocks.resize(8, 0);
|
||||
Self {
|
||||
compressed_blocks,
|
||||
compressed_blocks: vec![0; 8],
|
||||
buffer: vec![],
|
||||
offset_and_bits: vec![],
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
use std::ops::RangeInclusive;
|
||||
|
||||
#[cfg(any(target_arch = "x86_64"))]
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
mod avx2;
|
||||
|
||||
mod scalar;
|
||||
@@ -35,8 +35,8 @@ const IMPLS: [FilterImplPerInstructionSet; 2] = [
|
||||
const IMPLS: [FilterImplPerInstructionSet; 1] = [FilterImplPerInstructionSet::Scalar];
|
||||
|
||||
impl FilterImplPerInstructionSet {
|
||||
#[allow(unused_variables)]
|
||||
#[inline]
|
||||
#[allow(unused_variables)] // on non-x86_64, code is unused.
|
||||
fn from(code: u8) -> FilterImplPerInstructionSet {
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
if code == FilterImplPerInstructionSet::AVX2 as u8 {
|
||||
|
||||
82
cliff.toml
82
cliff.toml
@@ -1,6 +1,10 @@
|
||||
# configuration file for git-cliff{ pattern = "foo", replace = "bar"}
|
||||
# see https://github.com/orhun/git-cliff#configuration-file
|
||||
|
||||
[remote.github]
|
||||
owner = "quickwit-oss"
|
||||
repo = "tantivy"
|
||||
|
||||
[changelog]
|
||||
# changelog header
|
||||
header = """
|
||||
@@ -8,15 +12,43 @@ header = """
|
||||
# template for the changelog body
|
||||
# https://tera.netlify.app/docs/#introduction
|
||||
body = """
|
||||
{% if version %}\
|
||||
{{ version | trim_start_matches(pat="v") }} ({{ timestamp | date(format="%Y-%m-%d") }})
|
||||
==================
|
||||
{% else %}\
|
||||
## [unreleased]
|
||||
{% endif %}\
|
||||
## What's Changed
|
||||
|
||||
{%- if version %} in {{ version }}{%- endif -%}
|
||||
{% for commit in commits %}
|
||||
- {% if commit.breaking %}[**breaking**] {% endif %}{{ commit.message | split(pat="\n") | first | trim | upper_first }}(@{{ commit.author.name }})\
|
||||
{% endfor %}
|
||||
{% if commit.remote.pr_title -%}
|
||||
{%- set commit_message = commit.remote.pr_title -%}
|
||||
{%- else -%}
|
||||
{%- set commit_message = commit.message -%}
|
||||
{%- endif -%}
|
||||
- {{ commit_message | split(pat="\n") | first | trim }}\
|
||||
{% if commit.remote.pr_number %} \
|
||||
[#{{ commit.remote.pr_number }}]({{ self::remote_url() }}/pull/{{ commit.remote.pr_number }}){% if commit.remote.username %}(@{{ commit.remote.username }}){%- endif -%} \
|
||||
{%- endif %}
|
||||
{%- endfor -%}
|
||||
|
||||
{% if github.contributors | filter(attribute="is_first_time", value=true) | length != 0 %}
|
||||
{% raw %}\n{% endraw -%}
|
||||
## New Contributors
|
||||
{%- endif %}\
|
||||
{% for contributor in github.contributors | filter(attribute="is_first_time", value=true) %}
|
||||
* @{{ contributor.username }} made their first contribution
|
||||
{%- if contributor.pr_number %} in \
|
||||
[#{{ contributor.pr_number }}]({{ self::remote_url() }}/pull/{{ contributor.pr_number }}) \
|
||||
{%- endif %}
|
||||
{%- endfor -%}
|
||||
|
||||
{% if version %}
|
||||
{% if previous.version %}
|
||||
**Full Changelog**: {{ self::remote_url() }}/compare/{{ previous.version }}...{{ version }}
|
||||
{% endif %}
|
||||
{% else -%}
|
||||
{% raw %}\n{% endraw %}
|
||||
{% endif %}
|
||||
|
||||
{%- macro remote_url() -%}
|
||||
https://github.com/{{ remote.github.owner }}/{{ remote.github.repo }}
|
||||
{%- endmacro -%}
|
||||
"""
|
||||
# remove the leading and trailing whitespace from the template
|
||||
trim = true
|
||||
@@ -25,52 +57,24 @@ footer = """
|
||||
"""
|
||||
|
||||
postprocessors = [
|
||||
{ pattern = 'Paul Masurel', replace = "fulmicoton"}, # replace with github user
|
||||
{ pattern = 'PSeitz', replace = "PSeitz"}, # replace with github user
|
||||
{ pattern = 'Adam Reichold', replace = "adamreichold"}, # replace with github user
|
||||
{ pattern = 'trinity-1686a', replace = "trinity-1686a"}, # replace with github user
|
||||
{ pattern = 'Michael Kleen', replace = "mkleen"}, # replace with github user
|
||||
{ pattern = 'Adrien Guillo', replace = "guilload"}, # replace with github user
|
||||
{ pattern = 'François Massot', replace = "fmassot"}, # replace with github user
|
||||
{ pattern = '', replace = ""}, # replace with github user
|
||||
]
|
||||
|
||||
[git]
|
||||
# parse the commits based on https://www.conventionalcommits.org
|
||||
# This is required or commit.message contains the whole commit message and not just the title
|
||||
conventional_commits = true
|
||||
conventional_commits = false
|
||||
# filter out the commits that are not conventional
|
||||
filter_unconventional = false
|
||||
filter_unconventional = true
|
||||
# process each line of a commit as an individual commit
|
||||
split_commits = false
|
||||
# regex for preprocessing the commit messages
|
||||
commit_preprocessors = [
|
||||
{ pattern = '\((\w+\s)?#([0-9]+)\)', replace = "[#${2}](https://github.com/quickwit-oss/tantivy/issues/${2})"}, # replace issue numbers
|
||||
{ pattern = '\((\w+\s)?#([0-9]+)\)', replace = ""},
|
||||
]
|
||||
#link_parsers = [
|
||||
#{ pattern = "#(\\d+)", href = "https://github.com/quickwit-oss/tantivy/pulls/$1"},
|
||||
#]
|
||||
# regex for parsing and grouping commits
|
||||
commit_parsers = [
|
||||
{ message = "^feat", group = "Features"},
|
||||
{ message = "^fix", group = "Bug Fixes"},
|
||||
{ message = "^doc", group = "Documentation"},
|
||||
{ message = "^perf", group = "Performance"},
|
||||
{ message = "^refactor", group = "Refactor"},
|
||||
{ message = "^style", group = "Styling"},
|
||||
{ message = "^test", group = "Testing"},
|
||||
{ message = "^chore\\(release\\): prepare for", skip = true},
|
||||
{ message = "(?i)clippy", skip = true},
|
||||
{ message = "(?i)dependabot", skip = true},
|
||||
{ message = "(?i)fmt", skip = true},
|
||||
{ message = "(?i)bump", skip = true},
|
||||
{ message = "(?i)readme", skip = true},
|
||||
{ message = "(?i)comment", skip = true},
|
||||
{ message = "(?i)spelling", skip = true},
|
||||
{ message = "^chore", group = "Miscellaneous Tasks"},
|
||||
{ body = ".*security", group = "Security"},
|
||||
{ message = ".*", group = "Other", default_scope = "other"},
|
||||
]
|
||||
# protect breaking changes from being skipped due to matching a skipping commit_parser
|
||||
protect_breaking_commits = false
|
||||
# filter out the commits that are not matched by commit parsers
|
||||
|
||||
@@ -1,28 +1,38 @@
|
||||
[package]
|
||||
name = "tantivy-columnar"
|
||||
version = "0.1.0"
|
||||
version = "0.5.0"
|
||||
edition = "2021"
|
||||
license = "MIT"
|
||||
homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
repository = "https://github.com/quickwit-oss/tantivy"
|
||||
desciption = "column oriented storage for tantivy"
|
||||
description = "column oriented storage for tantivy"
|
||||
categories = ["database-implementations", "data-structures", "compression"]
|
||||
|
||||
[dependencies]
|
||||
itertools = "0.10.5"
|
||||
fnv = "1.0.7"
|
||||
itertools = "0.14.0"
|
||||
fastdivide = "0.4.0"
|
||||
|
||||
stacker = { version= "0.1", path = "../stacker", package="tantivy-stacker"}
|
||||
sstable = { version= "0.1", path = "../sstable", package = "tantivy-sstable" }
|
||||
common = { version= "0.5", path = "../common", package = "tantivy-common" }
|
||||
tantivy-bitpacker = { version= "0.4", path = "../bitpacker/" }
|
||||
stacker = { version= "0.5", path = "../stacker", package="tantivy-stacker"}
|
||||
sstable = { version= "0.5", path = "../sstable", package = "tantivy-sstable" }
|
||||
common = { version= "0.9", path = "../common", package = "tantivy-common" }
|
||||
tantivy-bitpacker = { version= "0.8", path = "../bitpacker/" }
|
||||
serde = "1.0.152"
|
||||
downcast-rs = "2.0.1"
|
||||
|
||||
[dev-dependencies]
|
||||
proptest = "1"
|
||||
more-asserts = "0.3.1"
|
||||
rand = "0.8"
|
||||
binggan = "0.14.0"
|
||||
|
||||
[[bench]]
|
||||
name = "bench_merge"
|
||||
harness = false
|
||||
|
||||
[[bench]]
|
||||
name = "bench_access"
|
||||
harness = false
|
||||
|
||||
|
||||
[features]
|
||||
unstable = []
|
||||
|
||||
@@ -31,7 +31,7 @@ restriction on 50% of the values (e.g. a 64-bit hash). On the other hand, a lot
|
||||
# Columnar format
|
||||
|
||||
This columnar format may have more than one column (with different types) associated to the same `column_name` (see [Coercion rules](#coercion-rules) above).
|
||||
The `(column_name, columne_type)` couple however uniquely identifies a column.
|
||||
The `(column_name, column_type)` couple however uniquely identifies a column.
|
||||
That couple is serialized as a column `column_key`. The format of that key is:
|
||||
`[column_name][ZERO_BYTE][column_type_header: u8]`
|
||||
|
||||
|
||||
67
columnar/benches/bench_access.rs
Normal file
67
columnar/benches/bench_access.rs
Normal file
@@ -0,0 +1,67 @@
|
||||
use binggan::{black_box, InputGroup};
|
||||
use common::*;
|
||||
use tantivy_columnar::Column;
|
||||
|
||||
pub mod common;
|
||||
|
||||
const NUM_DOCS: u32 = 2_000_000;
|
||||
|
||||
pub fn generate_columnar_and_open(card: Card, num_docs: u32) -> Column {
|
||||
let reader = generate_columnar_with_name(card, num_docs, "price");
|
||||
reader.read_columns("price").unwrap()[0]
|
||||
.open_u64_lenient()
|
||||
.unwrap()
|
||||
.unwrap()
|
||||
}
|
||||
|
||||
fn main() {
|
||||
let mut inputs = Vec::new();
|
||||
|
||||
let mut add_card = |card1: Card| {
|
||||
inputs.push((
|
||||
format!("{card1}"),
|
||||
generate_columnar_and_open(card1, NUM_DOCS),
|
||||
));
|
||||
};
|
||||
|
||||
add_card(Card::MultiSparse);
|
||||
add_card(Card::Multi);
|
||||
add_card(Card::Sparse);
|
||||
add_card(Card::Dense);
|
||||
add_card(Card::Full);
|
||||
|
||||
bench_group(InputGroup::new_with_inputs(inputs));
|
||||
}
|
||||
|
||||
fn bench_group(mut runner: InputGroup<Column>) {
|
||||
runner.register("access_values_for_doc", |column| {
|
||||
let mut sum = 0;
|
||||
for i in 0..NUM_DOCS {
|
||||
for value in column.values_for_doc(i) {
|
||||
sum += value;
|
||||
}
|
||||
}
|
||||
black_box(sum);
|
||||
});
|
||||
runner.register("access_first_vals", |column| {
|
||||
let mut sum = 0;
|
||||
const BLOCK_SIZE: usize = 32;
|
||||
let mut docs = vec![0; BLOCK_SIZE];
|
||||
let mut buffer = vec![None; BLOCK_SIZE];
|
||||
for i in (0..NUM_DOCS).step_by(BLOCK_SIZE) {
|
||||
// fill docs
|
||||
for idx in 0..BLOCK_SIZE {
|
||||
docs[idx] = idx as u32 + i;
|
||||
}
|
||||
|
||||
column.first_vals(&docs, &mut buffer);
|
||||
for val in buffer.iter() {
|
||||
let Some(val) = val else { continue };
|
||||
sum += *val;
|
||||
}
|
||||
}
|
||||
|
||||
black_box(sum);
|
||||
});
|
||||
runner.run();
|
||||
}
|
||||
155
columnar/benches/bench_first_vals.rs
Normal file
155
columnar/benches/bench_first_vals.rs
Normal file
@@ -0,0 +1,155 @@
|
||||
#![feature(test)]
|
||||
extern crate test;
|
||||
|
||||
use std::sync::Arc;
|
||||
|
||||
use rand::prelude::*;
|
||||
use tantivy_columnar::column_values::{serialize_and_load_u64_based_column_values, CodecType};
|
||||
use tantivy_columnar::*;
|
||||
use test::{black_box, Bencher};
|
||||
|
||||
struct Columns {
|
||||
pub optional: Column,
|
||||
pub full: Column,
|
||||
pub multi: Column,
|
||||
}
|
||||
|
||||
fn get_test_columns() -> Columns {
|
||||
let data = generate_permutation();
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
for (idx, val) in data.iter().enumerate() {
|
||||
dataframe_writer.record_numerical(idx as u32, "full_values", NumericalValue::U64(*val));
|
||||
if idx % 2 == 0 {
|
||||
dataframe_writer.record_numerical(
|
||||
idx as u32,
|
||||
"optional_values",
|
||||
NumericalValue::U64(*val),
|
||||
);
|
||||
}
|
||||
dataframe_writer.record_numerical(idx as u32, "multi_values", NumericalValue::U64(*val));
|
||||
dataframe_writer.record_numerical(idx as u32, "multi_values", NumericalValue::U64(*val));
|
||||
}
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer
|
||||
.serialize(data.len() as u32, &mut buffer)
|
||||
.unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("optional_values").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
let optional = cols[0].open_u64_lenient().unwrap().unwrap();
|
||||
assert_eq!(optional.index.get_cardinality(), Cardinality::Optional);
|
||||
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("full_values").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
let column_full = cols[0].open_u64_lenient().unwrap().unwrap();
|
||||
assert_eq!(column_full.index.get_cardinality(), Cardinality::Full);
|
||||
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("multi_values").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
let multi = cols[0].open_u64_lenient().unwrap().unwrap();
|
||||
assert_eq!(multi.index.get_cardinality(), Cardinality::Multivalued);
|
||||
|
||||
Columns {
|
||||
optional,
|
||||
full: column_full,
|
||||
multi,
|
||||
}
|
||||
}
|
||||
|
||||
const NUM_VALUES: u64 = 100_000;
|
||||
fn generate_permutation() -> Vec<u64> {
|
||||
let mut permutation: Vec<u64> = (0u64..NUM_VALUES).collect();
|
||||
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
|
||||
permutation
|
||||
}
|
||||
|
||||
pub fn serialize_and_load(column: &[u64], codec_type: CodecType) -> Arc<dyn ColumnValues<u64>> {
|
||||
serialize_and_load_u64_based_column_values(&column, &[codec_type])
|
||||
}
|
||||
|
||||
fn run_bench_on_column_full_scan(b: &mut Bencher, column: Column) {
|
||||
let num_iter = black_box(NUM_VALUES);
|
||||
b.iter(|| {
|
||||
let mut sum = 0u64;
|
||||
for i in 0..num_iter as u32 {
|
||||
let val = column.first(i);
|
||||
sum += val.unwrap_or(0);
|
||||
}
|
||||
sum
|
||||
});
|
||||
}
|
||||
fn run_bench_on_column_block_fetch(b: &mut Bencher, column: Column) {
|
||||
let mut block: Vec<Option<u64>> = vec![None; 64];
|
||||
let fetch_docids = (0..64).collect::<Vec<_>>();
|
||||
b.iter(move || {
|
||||
column.first_vals(&fetch_docids, &mut block);
|
||||
block[0]
|
||||
});
|
||||
}
|
||||
fn run_bench_on_column_block_single_calls(b: &mut Bencher, column: Column) {
|
||||
let mut block: Vec<Option<u64>> = vec![None; 64];
|
||||
let fetch_docids = (0..64).collect::<Vec<_>>();
|
||||
b.iter(move || {
|
||||
for i in 0..fetch_docids.len() {
|
||||
block[i] = column.first(fetch_docids[i]);
|
||||
}
|
||||
block[0]
|
||||
});
|
||||
}
|
||||
|
||||
/// Column first method
|
||||
#[bench]
|
||||
fn bench_get_first_on_full_column_full_scan(b: &mut Bencher) {
|
||||
let column = get_test_columns().full;
|
||||
run_bench_on_column_full_scan(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_first_on_optional_column_full_scan(b: &mut Bencher) {
|
||||
let column = get_test_columns().optional;
|
||||
run_bench_on_column_full_scan(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_first_on_multi_column_full_scan(b: &mut Bencher) {
|
||||
let column = get_test_columns().multi;
|
||||
run_bench_on_column_full_scan(b, column);
|
||||
}
|
||||
|
||||
/// Block fetch column accessor
|
||||
#[bench]
|
||||
fn bench_get_block_first_on_optional_column(b: &mut Bencher) {
|
||||
let column = get_test_columns().optional;
|
||||
run_bench_on_column_block_fetch(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_block_first_on_multi_column(b: &mut Bencher) {
|
||||
let column = get_test_columns().multi;
|
||||
run_bench_on_column_block_fetch(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_block_first_on_full_column(b: &mut Bencher) {
|
||||
let column = get_test_columns().full;
|
||||
run_bench_on_column_block_fetch(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_block_first_on_optional_column_single_calls(b: &mut Bencher) {
|
||||
let column = get_test_columns().optional;
|
||||
run_bench_on_column_block_single_calls(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_block_first_on_multi_column_single_calls(b: &mut Bencher) {
|
||||
let column = get_test_columns().multi;
|
||||
run_bench_on_column_block_single_calls(b, column);
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_get_block_first_on_full_column_single_calls(b: &mut Bencher) {
|
||||
let column = get_test_columns().full;
|
||||
run_bench_on_column_block_single_calls(b, column);
|
||||
}
|
||||
49
columnar/benches/bench_merge.rs
Normal file
49
columnar/benches/bench_merge.rs
Normal file
@@ -0,0 +1,49 @@
|
||||
pub mod common;
|
||||
|
||||
use binggan::BenchRunner;
|
||||
use common::{generate_columnar_with_name, Card};
|
||||
use tantivy_columnar::*;
|
||||
|
||||
const NUM_DOCS: u32 = 100_000;
|
||||
|
||||
fn main() {
|
||||
let mut inputs = Vec::new();
|
||||
|
||||
let mut add_combo = |card1: Card, card2: Card| {
|
||||
inputs.push((
|
||||
format!("merge_{card1}_and_{card2}"),
|
||||
vec![
|
||||
generate_columnar_with_name(card1, NUM_DOCS, "price"),
|
||||
generate_columnar_with_name(card2, NUM_DOCS, "price"),
|
||||
],
|
||||
));
|
||||
};
|
||||
|
||||
add_combo(Card::Multi, Card::Multi);
|
||||
add_combo(Card::MultiSparse, Card::MultiSparse);
|
||||
add_combo(Card::Dense, Card::Dense);
|
||||
add_combo(Card::Sparse, Card::Sparse);
|
||||
add_combo(Card::Sparse, Card::Dense);
|
||||
add_combo(Card::MultiSparse, Card::Dense);
|
||||
add_combo(Card::MultiSparse, Card::Sparse);
|
||||
add_combo(Card::Multi, Card::Dense);
|
||||
add_combo(Card::Multi, Card::Sparse);
|
||||
|
||||
let mut runner: BenchRunner = BenchRunner::new();
|
||||
let mut group = runner.new_group();
|
||||
for (input_name, columnar_readers) in inputs.iter() {
|
||||
group.register_with_input(
|
||||
input_name,
|
||||
columnar_readers,
|
||||
move |columnar_readers: &Vec<ColumnarReader>| {
|
||||
let mut out = Vec::new();
|
||||
let columnar_readers = columnar_readers.iter().collect::<Vec<_>>();
|
||||
let merge_row_order = StackMergeOrder::stack(&columnar_readers[..]);
|
||||
|
||||
merge_columnar(&columnar_readers, &[], merge_row_order.into(), &mut out).unwrap();
|
||||
Some(out.len() as u64)
|
||||
},
|
||||
);
|
||||
}
|
||||
group.run();
|
||||
}
|
||||
@@ -16,14 +16,6 @@ fn generate_permutation() -> Vec<u64> {
|
||||
permutation
|
||||
}
|
||||
|
||||
fn generate_random() -> Vec<u64> {
|
||||
let mut permutation: Vec<u64> = (0u64..100_000u64)
|
||||
.map(|el| el + random::<u16>() as u64)
|
||||
.collect();
|
||||
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
|
||||
permutation
|
||||
}
|
||||
|
||||
// Warning: this generates the same permutation at each call
|
||||
fn generate_permutation_gcd() -> Vec<u64> {
|
||||
let mut permutation: Vec<u64> = (1u64..100_000u64).map(|el| el * 1000).collect();
|
||||
59
columnar/benches/common.rs
Normal file
59
columnar/benches/common.rs
Normal file
@@ -0,0 +1,59 @@
|
||||
extern crate tantivy_columnar;
|
||||
|
||||
use core::fmt;
|
||||
use std::fmt::{Display, Formatter};
|
||||
|
||||
use tantivy_columnar::{ColumnarReader, ColumnarWriter};
|
||||
|
||||
pub enum Card {
|
||||
MultiSparse,
|
||||
Multi,
|
||||
Sparse,
|
||||
Dense,
|
||||
Full,
|
||||
}
|
||||
impl Display for Card {
|
||||
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
|
||||
match self {
|
||||
Card::MultiSparse => write!(f, "multi sparse 1/13"),
|
||||
Card::Multi => write!(f, "multi 2x"),
|
||||
Card::Sparse => write!(f, "sparse 1/13"),
|
||||
Card::Dense => write!(f, "dense 1/12"),
|
||||
Card::Full => write!(f, "full"),
|
||||
}
|
||||
}
|
||||
}
|
||||
pub fn generate_columnar_with_name(card: Card, num_docs: u32, column_name: &str) -> ColumnarReader {
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
|
||||
if let Card::MultiSparse = card {
|
||||
columnar_writer.record_numerical(0, column_name, 10u64);
|
||||
columnar_writer.record_numerical(0, column_name, 10u64);
|
||||
}
|
||||
|
||||
for i in 0..num_docs {
|
||||
match card {
|
||||
Card::MultiSparse | Card::Sparse => {
|
||||
if i % 13 == 0 {
|
||||
columnar_writer.record_numerical(i, column_name, i as u64);
|
||||
}
|
||||
}
|
||||
Card::Dense => {
|
||||
if i % 12 == 0 {
|
||||
columnar_writer.record_numerical(i, column_name, i as u64);
|
||||
}
|
||||
}
|
||||
Card::Full => {
|
||||
columnar_writer.record_numerical(i, column_name, i as u64);
|
||||
}
|
||||
Card::Multi => {
|
||||
columnar_writer.record_numerical(i, column_name, i as u64);
|
||||
columnar_writer.record_numerical(i, column_name, i as u64);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
let mut wrt: Vec<u8> = Vec::new();
|
||||
columnar_writer.serialize(num_docs, &mut wrt).unwrap();
|
||||
ColumnarReader::open(wrt).unwrap()
|
||||
}
|
||||
18
columnar/columnar-cli-inspect/Cargo.toml
Normal file
18
columnar/columnar-cli-inspect/Cargo.toml
Normal file
@@ -0,0 +1,18 @@
|
||||
[package]
|
||||
name = "tantivy-columnar-inspect"
|
||||
version = "0.1.0"
|
||||
edition = "2021"
|
||||
license = "MIT"
|
||||
|
||||
[dependencies]
|
||||
tantivy = {path="../..", package="tantivy"}
|
||||
columnar = {path="../", package="tantivy-columnar"}
|
||||
common = {path="../../common", package="tantivy-common"}
|
||||
|
||||
[workspace]
|
||||
members = []
|
||||
|
||||
[profile.release]
|
||||
debug = true
|
||||
#debug-assertions = true
|
||||
#overflow-checks = true
|
||||
54
columnar/columnar-cli-inspect/src/main.rs
Normal file
54
columnar/columnar-cli-inspect/src/main.rs
Normal file
@@ -0,0 +1,54 @@
|
||||
use columnar::ColumnarReader;
|
||||
use common::file_slice::{FileSlice, WrapFile};
|
||||
use std::io;
|
||||
use std::path::Path;
|
||||
use tantivy::directory::footer::Footer;
|
||||
|
||||
fn main() -> io::Result<()> {
|
||||
println!("Opens a columnar file written by tantivy and validates it.");
|
||||
let path = std::env::args().nth(1).unwrap();
|
||||
|
||||
let path = Path::new(&path);
|
||||
println!("Reading {:?}", path);
|
||||
let _reader = open_and_validate_columnar(path.to_str().unwrap())?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub fn validate_columnar_reader(reader: &ColumnarReader) {
|
||||
let num_rows = reader.num_rows();
|
||||
println!("num_rows: {}", num_rows);
|
||||
let columns = reader.list_columns().unwrap();
|
||||
println!("num columns: {:?}", columns.len());
|
||||
for (col_name, dynamic_column_handle) in columns {
|
||||
let col = dynamic_column_handle.open().unwrap();
|
||||
match col {
|
||||
columnar::DynamicColumn::Bool(_)
|
||||
| columnar::DynamicColumn::I64(_)
|
||||
| columnar::DynamicColumn::U64(_)
|
||||
| columnar::DynamicColumn::F64(_)
|
||||
| columnar::DynamicColumn::IpAddr(_)
|
||||
| columnar::DynamicColumn::DateTime(_)
|
||||
| columnar::DynamicColumn::Bytes(_) => {}
|
||||
columnar::DynamicColumn::Str(str_column) => {
|
||||
let num_vals = str_column.ords().values.num_vals();
|
||||
let num_terms_dict = str_column.num_terms() as u64;
|
||||
let max_ord = str_column.ords().values.iter().max().unwrap_or_default();
|
||||
println!("{col_name:35} num_vals {num_vals:10} \t num_terms_dict {num_terms_dict:8} max_ord: {max_ord:8}",);
|
||||
for ord in str_column.ords().values.iter() {
|
||||
assert!(ord < num_terms_dict);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Opens a columnar file that was written by tantivy and validates it.
|
||||
pub fn open_and_validate_columnar(path: &str) -> io::Result<ColumnarReader> {
|
||||
let wrap_file = WrapFile::new(std::fs::File::open(path)?)?;
|
||||
let slice = FileSlice::new(std::sync::Arc::new(wrap_file));
|
||||
let (_footer, slice) = Footer::extract_footer(slice.clone()).unwrap();
|
||||
let reader = ColumnarReader::open(slice).unwrap();
|
||||
validate_columnar_reader(&reader);
|
||||
Ok(reader)
|
||||
}
|
||||
@@ -8,7 +8,6 @@ license = "MIT"
|
||||
columnar = {path="../", package="tantivy-columnar"}
|
||||
serde_json = "1"
|
||||
serde_json_borrow = {git="https://github.com/PSeitz/serde_json_borrow/"}
|
||||
serde = "1"
|
||||
|
||||
[workspace]
|
||||
members = []
|
||||
|
||||
BIN
columnar/compat_tests_data/v1.columnar
Normal file
BIN
columnar/compat_tests_data/v1.columnar
Normal file
Binary file not shown.
BIN
columnar/compat_tests_data/v2.columnar
Normal file
BIN
columnar/compat_tests_data/v2.columnar
Normal file
Binary file not shown.
@@ -10,7 +10,7 @@
|
||||
|
||||
# Perf and Size
|
||||
* remove alloc in `ord_to_term`
|
||||
+ multivaued range queries restrat frm the beginning all of the time.
|
||||
+ multivaued range queries restart from the beginning all of the time.
|
||||
* re-add ZSTD compression for dictionaries
|
||||
no systematic monotonic mapping
|
||||
consider removing multilinear
|
||||
@@ -30,7 +30,7 @@ investigate if should have better errors? io::Error is overused at the moment.
|
||||
rename rank/select in unit tests
|
||||
Review the public API via cargo doc
|
||||
go through TODOs
|
||||
remove all doc_id occurences -> row_id
|
||||
remove all doc_id occurrences -> row_id
|
||||
use the rank & select naming in unit tests branch.
|
||||
multi-linear -> blockwise
|
||||
linear codec -> simply a multiplication for the index column
|
||||
@@ -43,5 +43,5 @@ isolate u128_based and uniform naming
|
||||
# Other
|
||||
fix enhance column-cli
|
||||
|
||||
# Santa claus
|
||||
# Santa Claus
|
||||
autodetect datetime ipaddr, plug customizable tokenizer.
|
||||
|
||||
@@ -1,9 +1,12 @@
|
||||
use std::cmp::Ordering;
|
||||
|
||||
use crate::{Column, DocId, RowId};
|
||||
|
||||
#[derive(Debug, Default, Clone)]
|
||||
pub struct ColumnBlockAccessor<T> {
|
||||
val_cache: Vec<T>,
|
||||
docid_cache: Vec<DocId>,
|
||||
missing_docids_cache: Vec<DocId>,
|
||||
row_id_cache: Vec<RowId>,
|
||||
}
|
||||
|
||||
@@ -11,14 +14,40 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
|
||||
ColumnBlockAccessor<T>
|
||||
{
|
||||
#[inline]
|
||||
pub fn fetch_block(&mut self, docs: &[u32], accessor: &Column<T>) {
|
||||
self.docid_cache.clear();
|
||||
self.row_id_cache.clear();
|
||||
accessor.row_ids_for_docs(docs, &mut self.docid_cache, &mut self.row_id_cache);
|
||||
self.val_cache.resize(self.row_id_cache.len(), T::default());
|
||||
accessor
|
||||
.values
|
||||
.get_vals(&self.row_id_cache, &mut self.val_cache);
|
||||
pub fn fetch_block<'a>(&'a mut self, docs: &'a [u32], accessor: &Column<T>) {
|
||||
if accessor.index.get_cardinality().is_full() {
|
||||
self.val_cache.resize(docs.len(), T::default());
|
||||
accessor.values.get_vals(docs, &mut self.val_cache);
|
||||
} else {
|
||||
self.docid_cache.clear();
|
||||
self.row_id_cache.clear();
|
||||
accessor.row_ids_for_docs(docs, &mut self.docid_cache, &mut self.row_id_cache);
|
||||
self.val_cache.resize(self.row_id_cache.len(), T::default());
|
||||
accessor
|
||||
.values
|
||||
.get_vals(&self.row_id_cache, &mut self.val_cache);
|
||||
}
|
||||
}
|
||||
#[inline]
|
||||
pub fn fetch_block_with_missing(&mut self, docs: &[u32], accessor: &Column<T>, missing: T) {
|
||||
self.fetch_block(docs, accessor);
|
||||
// no missing values
|
||||
if accessor.index.get_cardinality().is_full() {
|
||||
return;
|
||||
}
|
||||
|
||||
// We can compare docid_cache length with docs to find missing docs
|
||||
// For multi value columns we can't rely on the length and always need to scan
|
||||
if accessor.index.get_cardinality().is_multivalue() || docs.len() != self.docid_cache.len()
|
||||
{
|
||||
self.missing_docids_cache.clear();
|
||||
find_missing_docs(docs, &self.docid_cache, |doc| {
|
||||
self.missing_docids_cache.push(doc);
|
||||
self.val_cache.push(missing);
|
||||
});
|
||||
self.docid_cache
|
||||
.extend_from_slice(&self.missing_docids_cache);
|
||||
}
|
||||
}
|
||||
|
||||
#[inline]
|
||||
@@ -27,10 +56,103 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn iter_docid_vals(&self) -> impl Iterator<Item = (DocId, T)> + '_ {
|
||||
self.docid_cache
|
||||
.iter()
|
||||
.cloned()
|
||||
.zip(self.val_cache.iter().cloned())
|
||||
/// Returns an iterator over the docids and values
|
||||
/// The passed in `docs` slice needs to be the same slice that was passed to `fetch_block` or
|
||||
/// `fetch_block_with_missing`.
|
||||
///
|
||||
/// The docs is used if the column is full (each docs has exactly one value), otherwise the
|
||||
/// internal docid vec is used for the iterator, which e.g. may contain duplicate docs.
|
||||
pub fn iter_docid_vals<'a>(
|
||||
&'a self,
|
||||
docs: &'a [u32],
|
||||
accessor: &Column<T>,
|
||||
) -> impl Iterator<Item = (DocId, T)> + 'a {
|
||||
if accessor.index.get_cardinality().is_full() {
|
||||
docs.iter().cloned().zip(self.val_cache.iter().cloned())
|
||||
} else {
|
||||
self.docid_cache
|
||||
.iter()
|
||||
.cloned()
|
||||
.zip(self.val_cache.iter().cloned())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Given two sorted lists of docids `docs` and `hits`, hits is a subset of `docs`.
|
||||
/// Return all docs that are not in `hits`.
|
||||
fn find_missing_docs<F>(docs: &[u32], hits: &[u32], mut callback: F)
|
||||
where F: FnMut(u32) {
|
||||
let mut docs_iter = docs.iter();
|
||||
let mut hits_iter = hits.iter();
|
||||
|
||||
let mut doc = docs_iter.next();
|
||||
let mut hit = hits_iter.next();
|
||||
|
||||
while let (Some(¤t_doc), Some(¤t_hit)) = (doc, hit) {
|
||||
match current_doc.cmp(¤t_hit) {
|
||||
Ordering::Less => {
|
||||
callback(current_doc);
|
||||
doc = docs_iter.next();
|
||||
}
|
||||
Ordering::Equal => {
|
||||
doc = docs_iter.next();
|
||||
hit = hits_iter.next();
|
||||
}
|
||||
Ordering::Greater => {
|
||||
hit = hits_iter.next();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
while let Some(¤t_doc) = doc {
|
||||
callback(current_doc);
|
||||
doc = docs_iter.next();
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs() {
|
||||
let docs: Vec<u32> = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
|
||||
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![1, 3, 5, 7, 9]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs_empty() {
|
||||
let docs: Vec<u32> = Vec::new();
|
||||
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, Vec::<u32>::new());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs_all_missing() {
|
||||
let docs: Vec<u32> = vec![1, 2, 3, 4, 5];
|
||||
let hits: Vec<u32> = Vec::new();
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![1, 2, 3, 4, 5]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -30,6 +30,13 @@ impl fmt::Debug for BytesColumn {
|
||||
}
|
||||
|
||||
impl BytesColumn {
|
||||
pub fn empty(num_docs: u32) -> BytesColumn {
|
||||
BytesColumn {
|
||||
dictionary: Arc::new(Dictionary::empty()),
|
||||
term_ord_column: Column::build_empty_column(num_docs),
|
||||
}
|
||||
}
|
||||
|
||||
/// Fills the given `output` buffer with the term associated to the ordinal `ord`.
|
||||
///
|
||||
/// Returns `false` if the term does not exist (e.g. `term_ord` is greater or equal to the
|
||||
@@ -77,7 +84,7 @@ impl From<StrColumn> for BytesColumn {
|
||||
}
|
||||
|
||||
impl StrColumn {
|
||||
pub(crate) fn wrap(bytes_column: BytesColumn) -> StrColumn {
|
||||
pub fn wrap(bytes_column: BytesColumn) -> StrColumn {
|
||||
StrColumn(bytes_column)
|
||||
}
|
||||
|
||||
|
||||
@@ -3,17 +3,17 @@ mod serialize;
|
||||
|
||||
use std::fmt::{self, Debug};
|
||||
use std::io::Write;
|
||||
use std::ops::{Deref, Range, RangeInclusive};
|
||||
use std::ops::{Range, RangeInclusive};
|
||||
use std::sync::Arc;
|
||||
|
||||
use common::BinarySerializable;
|
||||
pub use dictionary_encoded::{BytesColumn, StrColumn};
|
||||
pub use serialize::{
|
||||
open_column_bytes, open_column_str, open_column_u128, open_column_u64,
|
||||
serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
|
||||
open_column_bytes, open_column_str, open_column_u128, open_column_u128_as_compact_u64,
|
||||
open_column_u64, serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
|
||||
};
|
||||
|
||||
use crate::column_index::ColumnIndex;
|
||||
use crate::column_index::{ColumnIndex, Set};
|
||||
use crate::column_values::monotonic_mapping::StrictlyMonotonicMappingToInternal;
|
||||
use crate::column_values::{monotonic_map_column, ColumnValues};
|
||||
use crate::{Cardinality, DocId, EmptyColumnValues, MonotonicallyMappableToU64, RowId};
|
||||
@@ -83,10 +83,36 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
self.values.max_value()
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn first(&self, row_id: RowId) -> Option<T> {
|
||||
self.values_for_doc(row_id).next()
|
||||
}
|
||||
|
||||
/// Load the first value for each docid in the provided slice.
|
||||
#[inline]
|
||||
pub fn first_vals(&self, docids: &[DocId], output: &mut [Option<T>]) {
|
||||
match &self.index {
|
||||
ColumnIndex::Empty { .. } => {}
|
||||
ColumnIndex::Full => self.values.get_vals_opt(docids, output),
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
for (i, docid) in docids.iter().enumerate() {
|
||||
output[i] = optional_index
|
||||
.rank_if_exists(*docid)
|
||||
.map(|rowid| self.values.get_val(rowid));
|
||||
}
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => {
|
||||
for (i, docid) in docids.iter().enumerate() {
|
||||
let range = multivalued_index.range(*docid);
|
||||
let is_empty = range.start == range.end;
|
||||
if !is_empty {
|
||||
output[i] = Some(self.values.get_val(range.start));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Translates a block of docis to row_ids.
|
||||
///
|
||||
/// returns the row_ids and the matching docids on the same index
|
||||
@@ -105,11 +131,12 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
}
|
||||
|
||||
pub fn values_for_doc(&self, doc_id: DocId) -> impl Iterator<Item = T> + '_ {
|
||||
self.value_row_ids(doc_id)
|
||||
self.index
|
||||
.value_row_ids(doc_id)
|
||||
.map(|value_row_id: RowId| self.values.get_val(value_row_id))
|
||||
}
|
||||
|
||||
/// Get the docids of values which are in the provided value range.
|
||||
/// Get the docids of values which are in the provided value and docid range.
|
||||
#[inline]
|
||||
pub fn get_docids_for_value_range(
|
||||
&self,
|
||||
@@ -130,7 +157,7 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
.select_batch_in_place(selected_docid_range.start, doc_ids);
|
||||
}
|
||||
|
||||
/// Fils the output vector with the (possibly multiple values that are associated_with
|
||||
/// Fills the output vector with the (possibly multiple values that are associated_with
|
||||
/// `row_id`.
|
||||
///
|
||||
/// This method clears the `output` vector.
|
||||
@@ -147,14 +174,6 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<T> Deref for Column<T> {
|
||||
type Target = ColumnIndex;
|
||||
|
||||
fn deref(&self) -> &Self::Target {
|
||||
&self.index
|
||||
}
|
||||
}
|
||||
|
||||
impl BinarySerializable for Cardinality {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
|
||||
self.to_code().serialize(writer)
|
||||
@@ -176,6 +195,7 @@ struct FirstValueWithDefault<T: Copy> {
|
||||
impl<T: PartialOrd + Debug + Send + Sync + Copy + 'static> ColumnValues<T>
|
||||
for FirstValueWithDefault<T>
|
||||
{
|
||||
#[inline(always)]
|
||||
fn get_val(&self, idx: u32) -> T {
|
||||
self.column.first(idx).unwrap_or(self.default_value)
|
||||
}
|
||||
|
||||
@@ -12,7 +12,7 @@ use crate::column_values::{
|
||||
CodecType, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
|
||||
};
|
||||
use crate::iterable::Iterable;
|
||||
use crate::StrColumn;
|
||||
use crate::{StrColumn, Version};
|
||||
|
||||
pub fn serialize_column_mappable_to_u128<T: MonotonicallyMappableToU128>(
|
||||
column_index: SerializableColumnIndex<'_>,
|
||||
@@ -40,25 +40,9 @@ pub fn serialize_column_mappable_to_u64<T: MonotonicallyMappableToU64>(
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub fn open_column_u64<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::Result<Column<T>> {
|
||||
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
|
||||
let column_index_num_bytes = u32::from_le_bytes(
|
||||
column_index_num_bytes_payload
|
||||
.as_slice()
|
||||
.try_into()
|
||||
.unwrap(),
|
||||
);
|
||||
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
|
||||
let column_index = crate::column_index::open_column_index(column_index_data)?;
|
||||
let column_values = load_u64_based_column_values(column_values_data)?;
|
||||
Ok(Column {
|
||||
index: column_index,
|
||||
values: column_values,
|
||||
})
|
||||
}
|
||||
|
||||
pub fn open_column_u128<T: MonotonicallyMappableToU128>(
|
||||
pub fn open_column_u64<T: MonotonicallyMappableToU64>(
|
||||
bytes: OwnedBytes,
|
||||
format_version: Version,
|
||||
) -> io::Result<Column<T>> {
|
||||
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
|
||||
let column_index_num_bytes = u32::from_le_bytes(
|
||||
@@ -68,7 +52,27 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
|
||||
.unwrap(),
|
||||
);
|
||||
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
|
||||
let column_index = crate::column_index::open_column_index(column_index_data)?;
|
||||
let column_index = crate::column_index::open_column_index(column_index_data, format_version)?;
|
||||
let column_values = load_u64_based_column_values(column_values_data)?;
|
||||
Ok(Column {
|
||||
index: column_index,
|
||||
values: column_values,
|
||||
})
|
||||
}
|
||||
|
||||
pub fn open_column_u128<T: MonotonicallyMappableToU128>(
|
||||
bytes: OwnedBytes,
|
||||
format_version: Version,
|
||||
) -> io::Result<Column<T>> {
|
||||
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
|
||||
let column_index_num_bytes = u32::from_le_bytes(
|
||||
column_index_num_bytes_payload
|
||||
.as_slice()
|
||||
.try_into()
|
||||
.unwrap(),
|
||||
);
|
||||
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
|
||||
let column_index = crate::column_index::open_column_index(column_index_data, format_version)?;
|
||||
let column_values = crate::column_values::open_u128_mapped(column_values_data)?;
|
||||
Ok(Column {
|
||||
index: column_index,
|
||||
@@ -76,19 +80,42 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
|
||||
})
|
||||
}
|
||||
|
||||
pub fn open_column_bytes(data: OwnedBytes) -> io::Result<BytesColumn> {
|
||||
/// Open the column as u64.
|
||||
///
|
||||
/// See [`open_u128_as_compact_u64`] for more details.
|
||||
pub fn open_column_u128_as_compact_u64(
|
||||
bytes: OwnedBytes,
|
||||
format_version: Version,
|
||||
) -> io::Result<Column<u64>> {
|
||||
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
|
||||
let column_index_num_bytes = u32::from_le_bytes(
|
||||
column_index_num_bytes_payload
|
||||
.as_slice()
|
||||
.try_into()
|
||||
.unwrap(),
|
||||
);
|
||||
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
|
||||
let column_index = crate::column_index::open_column_index(column_index_data, format_version)?;
|
||||
let column_values = crate::column_values::open_u128_as_compact_u64(column_values_data)?;
|
||||
Ok(Column {
|
||||
index: column_index,
|
||||
values: column_values,
|
||||
})
|
||||
}
|
||||
|
||||
pub fn open_column_bytes(data: OwnedBytes, format_version: Version) -> io::Result<BytesColumn> {
|
||||
let (body, dictionary_len_bytes) = data.rsplit(4);
|
||||
let dictionary_len = u32::from_le_bytes(dictionary_len_bytes.as_slice().try_into().unwrap());
|
||||
let (dictionary_bytes, column_bytes) = body.split(dictionary_len as usize);
|
||||
let dictionary = Arc::new(Dictionary::from_bytes(dictionary_bytes)?);
|
||||
let term_ord_column = crate::column::open_column_u64::<u64>(column_bytes)?;
|
||||
let term_ord_column = crate::column::open_column_u64::<u64>(column_bytes, format_version)?;
|
||||
Ok(BytesColumn {
|
||||
dictionary,
|
||||
term_ord_column,
|
||||
})
|
||||
}
|
||||
|
||||
pub fn open_column_str(data: OwnedBytes) -> io::Result<StrColumn> {
|
||||
let bytes_column = open_column_bytes(data)?;
|
||||
pub fn open_column_str(data: OwnedBytes, format_version: Version) -> io::Result<StrColumn> {
|
||||
let bytes_column = open_column_bytes(data, format_version)?;
|
||||
Ok(StrColumn::wrap(bytes_column))
|
||||
}
|
||||
|
||||
@@ -95,8 +95,12 @@ pub fn merge_column_index<'a>(
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use common::OwnedBytes;
|
||||
|
||||
use crate::column_index::merge::detect_cardinality;
|
||||
use crate::column_index::multivalued_index::MultiValueIndex;
|
||||
use crate::column_index::multivalued_index::{
|
||||
open_multivalued_index, serialize_multivalued_index, MultiValueIndex,
|
||||
};
|
||||
use crate::column_index::{merge_column_index, OptionalIndex, SerializableColumnIndex};
|
||||
use crate::{
|
||||
Cardinality, ColumnIndex, MergeRowOrder, RowAddr, RowId, ShuffleMergeOrder, StackMergeOrder,
|
||||
@@ -168,9 +172,14 @@ mod tests {
|
||||
)
|
||||
.into();
|
||||
let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
|
||||
else { panic!("Excpected a multivalued index") };
|
||||
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
|
||||
panic!("Expected a multivalued index")
|
||||
};
|
||||
let mut output = Vec::new();
|
||||
serialize_multivalued_index(&start_index_iterable, &mut output).unwrap();
|
||||
let multivalue =
|
||||
open_multivalued_index(OwnedBytes::new(output), crate::Version::V2).unwrap();
|
||||
let start_indexes: Vec<RowId> = multivalue.get_start_index_column().iter().collect();
|
||||
assert_eq!(&start_indexes, &[0, 3, 5]);
|
||||
}
|
||||
|
||||
@@ -199,10 +208,16 @@ mod tests {
|
||||
],
|
||||
)
|
||||
.into();
|
||||
|
||||
let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
|
||||
else { panic!("Excpected a multivalued index") };
|
||||
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
|
||||
panic!("Expected a multivalued index")
|
||||
};
|
||||
let mut output = Vec::new();
|
||||
serialize_multivalued_index(&start_index_iterable, &mut output).unwrap();
|
||||
let multivalue =
|
||||
open_multivalued_index(OwnedBytes::new(output), crate::Version::V2).unwrap();
|
||||
let start_indexes: Vec<RowId> = multivalue.get_start_index_column().iter().collect();
|
||||
assert_eq!(&start_indexes, &[0, 3, 5, 6]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
use std::iter;
|
||||
|
||||
use crate::column_index::{SerializableColumnIndex, Set};
|
||||
use crate::column_index::{
|
||||
SerializableColumnIndex, SerializableMultivalueIndex, SerializableOptionalIndex, Set,
|
||||
};
|
||||
use crate::iterable::Iterable;
|
||||
use crate::{Cardinality, ColumnIndex, RowId, ShuffleMergeOrder};
|
||||
|
||||
@@ -14,15 +16,24 @@ pub fn merge_column_index_shuffled<'a>(
|
||||
Cardinality::Optional => {
|
||||
let non_null_row_ids =
|
||||
merge_column_index_shuffled_optional(column_indexes, shuffle_merge_order);
|
||||
SerializableColumnIndex::Optional {
|
||||
SerializableColumnIndex::Optional(SerializableOptionalIndex {
|
||||
non_null_row_ids,
|
||||
num_rows: shuffle_merge_order.num_rows(),
|
||||
}
|
||||
})
|
||||
}
|
||||
Cardinality::Multivalued => {
|
||||
let multivalue_start_index =
|
||||
merge_column_index_shuffled_multivalued(column_indexes, shuffle_merge_order);
|
||||
SerializableColumnIndex::Multivalued(multivalue_start_index)
|
||||
let non_null_row_ids =
|
||||
merge_column_index_shuffled_optional(column_indexes, shuffle_merge_order);
|
||||
SerializableColumnIndex::Multivalued(SerializableMultivalueIndex {
|
||||
doc_ids_with_values: SerializableOptionalIndex {
|
||||
non_null_row_ids,
|
||||
num_rows: shuffle_merge_order.num_rows(),
|
||||
},
|
||||
start_offsets: merge_column_index_shuffled_multivalued(
|
||||
column_indexes,
|
||||
shuffle_merge_order,
|
||||
),
|
||||
})
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -47,7 +58,7 @@ struct ShuffledIndex<'a> {
|
||||
merge_order: &'a ShuffleMergeOrder,
|
||||
}
|
||||
|
||||
impl<'a> Iterable<u32> for ShuffledIndex<'a> {
|
||||
impl Iterable<u32> for ShuffledIndex<'_> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
|
||||
Box::new(
|
||||
self.merge_order
|
||||
@@ -102,14 +113,21 @@ fn iter_num_values<'a>(
|
||||
|
||||
/// Transforms an iterator containing the number of vals per row (with `num_rows` elements)
|
||||
/// into a `start_offset` iterator starting at 0 and (with `num_rows + 1` element)
|
||||
///
|
||||
/// This will filter values with 0 values as these are covered by the optional index in the
|
||||
/// multivalue index.
|
||||
fn integrate_num_vals(num_vals: impl Iterator<Item = u32>) -> impl Iterator<Item = RowId> {
|
||||
iter::once(0u32).chain(num_vals.scan(0, |state, num_vals| {
|
||||
*state += num_vals;
|
||||
Some(*state)
|
||||
}))
|
||||
iter::once(0u32).chain(
|
||||
num_vals
|
||||
.filter(|num_vals| *num_vals != 0)
|
||||
.scan(0, |state, num_vals| {
|
||||
*state += num_vals;
|
||||
Some(*state)
|
||||
}),
|
||||
)
|
||||
}
|
||||
|
||||
impl<'a> Iterable<u32> for ShuffledMultivaluedIndex<'a> {
|
||||
impl Iterable<u32> for ShuffledMultivaluedIndex<'_> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
|
||||
let num_vals_per_row = iter_num_values(self.column_indexes, self.merge_order);
|
||||
Box::new(integrate_num_vals(num_vals_per_row))
|
||||
@@ -134,13 +152,13 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn test_integrate_num_vals_several() {
|
||||
assert!(integrate_num_vals([3, 0, 10, 20].into_iter()).eq([0, 3, 3, 13, 33].into_iter()));
|
||||
assert!(integrate_num_vals([3, 0, 10, 20].into_iter()).eq([0, 3, 13, 33].into_iter()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_merge_column_index_optional_shuffle() {
|
||||
let optional_index: ColumnIndex = OptionalIndex::for_test(2, &[0]).into();
|
||||
let column_indexes = vec![optional_index, ColumnIndex::Full];
|
||||
let column_indexes = [optional_index, ColumnIndex::Full];
|
||||
let row_addrs = vec![
|
||||
RowAddr {
|
||||
segment_ord: 0u32,
|
||||
@@ -157,7 +175,13 @@ mod tests {
|
||||
Cardinality::Optional,
|
||||
&shuffle_merge_order,
|
||||
);
|
||||
let SerializableColumnIndex::Optional { non_null_row_ids, num_rows } = serializable_index else { panic!() };
|
||||
let SerializableColumnIndex::Optional(SerializableOptionalIndex {
|
||||
non_null_row_ids,
|
||||
num_rows,
|
||||
}) = serializable_index
|
||||
else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(num_rows, 2);
|
||||
let non_null_rows: Vec<RowId> = non_null_row_ids.boxed_iter().collect();
|
||||
assert_eq!(&non_null_rows, &[1]);
|
||||
|
||||
@@ -1,6 +1,8 @@
|
||||
use std::iter;
|
||||
use std::ops::Range;
|
||||
|
||||
use crate::column_index::{SerializableColumnIndex, Set};
|
||||
use crate::column_index::multivalued_index::{MultiValueIndex, SerializableMultivalueIndex};
|
||||
use crate::column_index::serialize::SerializableOptionalIndex;
|
||||
use crate::column_index::SerializableColumnIndex;
|
||||
use crate::iterable::Iterable;
|
||||
use crate::{Cardinality, ColumnIndex, RowId, StackMergeOrder};
|
||||
|
||||
@@ -15,23 +17,149 @@ pub fn merge_column_index_stacked<'a>(
|
||||
) -> SerializableColumnIndex<'a> {
|
||||
match cardinality_after_merge {
|
||||
Cardinality::Full => SerializableColumnIndex::Full,
|
||||
Cardinality::Optional => SerializableColumnIndex::Optional {
|
||||
Cardinality::Optional => SerializableColumnIndex::Optional(SerializableOptionalIndex {
|
||||
non_null_row_ids: Box::new(StackedOptionalIndex {
|
||||
columns,
|
||||
stack_merge_order,
|
||||
}),
|
||||
num_rows: stack_merge_order.num_rows(),
|
||||
},
|
||||
}),
|
||||
Cardinality::Multivalued => {
|
||||
let stacked_multivalued_index = StackedMultivaluedIndex {
|
||||
columns,
|
||||
stack_merge_order,
|
||||
};
|
||||
SerializableColumnIndex::Multivalued(Box::new(stacked_multivalued_index))
|
||||
let serializable_multivalue_index =
|
||||
make_serializable_multivalued_index(columns, stack_merge_order);
|
||||
SerializableColumnIndex::Multivalued(serializable_multivalue_index)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
struct StackedDocIdsWithValues<'a> {
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
}
|
||||
|
||||
impl Iterable<u32> for StackedDocIdsWithValues<'_> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
|
||||
Box::new((0..self.column_indexes.len()).flat_map(|i| {
|
||||
let column_index = &self.column_indexes[i];
|
||||
let doc_range = self.stack_merge_order.columnar_range(i);
|
||||
get_doc_ids_with_values(column_index, doc_range)
|
||||
}))
|
||||
}
|
||||
}
|
||||
|
||||
fn get_doc_ids_with_values<'a>(
|
||||
column_index: &'a ColumnIndex,
|
||||
doc_range: Range<u32>,
|
||||
) -> Box<dyn Iterator<Item = u32> + 'a> {
|
||||
match column_index {
|
||||
ColumnIndex::Empty { .. } => Box::new(0..0),
|
||||
ColumnIndex::Full => Box::new(doc_range),
|
||||
ColumnIndex::Optional(optional_index) => Box::new(
|
||||
optional_index
|
||||
.iter_docs()
|
||||
.map(move |row| row + doc_range.start),
|
||||
),
|
||||
ColumnIndex::Multivalued(multivalued_index) => match multivalued_index {
|
||||
MultiValueIndex::MultiValueIndexV1(multivalued_index) => {
|
||||
Box::new((0..multivalued_index.num_docs()).filter_map(move |docid| {
|
||||
let range = multivalued_index.range(docid);
|
||||
if range.is_empty() {
|
||||
None
|
||||
} else {
|
||||
Some(docid + doc_range.start)
|
||||
}
|
||||
}))
|
||||
}
|
||||
MultiValueIndex::MultiValueIndexV2(multivalued_index) => Box::new(
|
||||
multivalued_index
|
||||
.optional_index
|
||||
.iter_docs()
|
||||
.map(move |row| row + doc_range.start),
|
||||
),
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
fn stack_doc_ids_with_values<'a>(
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
) -> SerializableOptionalIndex<'a> {
|
||||
let num_rows = stack_merge_order.num_rows();
|
||||
SerializableOptionalIndex {
|
||||
non_null_row_ids: Box::new(StackedDocIdsWithValues {
|
||||
column_indexes,
|
||||
stack_merge_order,
|
||||
}),
|
||||
num_rows,
|
||||
}
|
||||
}
|
||||
|
||||
struct StackedStartOffsets<'a> {
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
}
|
||||
|
||||
fn get_num_values_iterator<'a>(
|
||||
column_index: &'a ColumnIndex,
|
||||
num_docs: u32,
|
||||
) -> Box<dyn Iterator<Item = u32> + 'a> {
|
||||
match column_index {
|
||||
ColumnIndex::Empty { .. } => Box::new(std::iter::empty()),
|
||||
ColumnIndex::Full => Box::new(std::iter::repeat(1u32).take(num_docs as usize)),
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
Box::new(std::iter::repeat(1u32).take(optional_index.num_non_nulls() as usize))
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => Box::new(
|
||||
multivalued_index
|
||||
.get_start_index_column()
|
||||
.iter()
|
||||
.scan(0u32, |previous_start_offset, current_start_offset| {
|
||||
let num_vals = current_start_offset - *previous_start_offset;
|
||||
*previous_start_offset = current_start_offset;
|
||||
Some(num_vals)
|
||||
})
|
||||
.skip(1),
|
||||
),
|
||||
}
|
||||
}
|
||||
|
||||
impl Iterable<u32> for StackedStartOffsets<'_> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
|
||||
let num_values_it = (0..self.column_indexes.len()).flat_map(|columnar_id| {
|
||||
let num_docs = self.stack_merge_order.columnar_range(columnar_id).len() as u32;
|
||||
let column_index = &self.column_indexes[columnar_id];
|
||||
get_num_values_iterator(column_index, num_docs)
|
||||
});
|
||||
Box::new(std::iter::once(0u32).chain(num_values_it.into_iter().scan(
|
||||
0u32,
|
||||
|cumulated, el| {
|
||||
*cumulated += el;
|
||||
Some(*cumulated)
|
||||
},
|
||||
)))
|
||||
}
|
||||
}
|
||||
|
||||
fn stack_start_offsets<'a>(
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
) -> Box<dyn Iterable<u32> + 'a> {
|
||||
Box::new(StackedStartOffsets {
|
||||
column_indexes,
|
||||
stack_merge_order,
|
||||
})
|
||||
}
|
||||
|
||||
fn make_serializable_multivalued_index<'a>(
|
||||
columns: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
) -> SerializableMultivalueIndex<'a> {
|
||||
SerializableMultivalueIndex {
|
||||
doc_ids_with_values: stack_doc_ids_with_values(columns, stack_merge_order),
|
||||
start_offsets: stack_start_offsets(columns, stack_merge_order),
|
||||
}
|
||||
}
|
||||
|
||||
struct StackedOptionalIndex<'a> {
|
||||
columns: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
@@ -49,7 +177,7 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
|
||||
ColumnIndex::Full => Box::new(columnar_row_range),
|
||||
ColumnIndex::Optional(optional_index) => Box::new(
|
||||
optional_index
|
||||
.iter_rows()
|
||||
.iter_docs()
|
||||
.map(move |row_id: RowId| columnar_row_range.start + row_id),
|
||||
),
|
||||
ColumnIndex::Multivalued(_) => {
|
||||
@@ -62,90 +190,3 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Clone, Copy)]
|
||||
struct StackedMultivaluedIndex<'a> {
|
||||
columns: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
}
|
||||
|
||||
fn convert_column_opt_to_multivalued_index<'a>(
|
||||
column_index_opt: &'a ColumnIndex,
|
||||
num_rows: RowId,
|
||||
) -> Box<dyn Iterator<Item = RowId> + 'a> {
|
||||
match column_index_opt {
|
||||
ColumnIndex::Empty { .. } => Box::new(iter::repeat(0u32).take(num_rows as usize + 1)),
|
||||
ColumnIndex::Full => Box::new(0..num_rows + 1),
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
Box::new(
|
||||
(0..num_rows)
|
||||
// TODO optimize
|
||||
.map(|row_id| optional_index.rank(row_id))
|
||||
.chain(std::iter::once(optional_index.num_non_nulls())),
|
||||
)
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => multivalued_index.start_index_column.iter(),
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> Iterable<RowId> for StackedMultivaluedIndex<'a> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = RowId> + '_> {
|
||||
let multivalued_indexes =
|
||||
self.columns
|
||||
.iter()
|
||||
.enumerate()
|
||||
.map(|(columnar_id, column_opt)| {
|
||||
let num_rows =
|
||||
self.stack_merge_order.columnar_range(columnar_id).len() as RowId;
|
||||
convert_column_opt_to_multivalued_index(column_opt, num_rows)
|
||||
});
|
||||
stack_multivalued_indexes(multivalued_indexes)
|
||||
}
|
||||
}
|
||||
|
||||
// Refactor me
|
||||
fn stack_multivalued_indexes<'a>(
|
||||
mut multivalued_indexes: impl Iterator<Item = Box<dyn Iterator<Item = RowId> + 'a>> + 'a,
|
||||
) -> Box<dyn Iterator<Item = RowId> + 'a> {
|
||||
let mut offset = 0;
|
||||
let mut last_row_id = 0;
|
||||
let mut current_it = multivalued_indexes.next();
|
||||
Box::new(std::iter::from_fn(move || loop {
|
||||
let Some(multivalued_index) = current_it.as_mut() else {
|
||||
return None;
|
||||
};
|
||||
if let Some(row_id) = multivalued_index.next() {
|
||||
last_row_id = offset + row_id;
|
||||
return Some(last_row_id);
|
||||
}
|
||||
offset = last_row_id;
|
||||
loop {
|
||||
current_it = multivalued_indexes.next();
|
||||
if current_it.as_mut()?.next().is_some() {
|
||||
break;
|
||||
}
|
||||
}
|
||||
}))
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::RowId;
|
||||
|
||||
fn it<'a>(row_ids: &'a [RowId]) -> Box<dyn Iterator<Item = RowId> + 'a> {
|
||||
Box::new(row_ids.iter().copied())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_stack() {
|
||||
let columns = [
|
||||
it(&[0u32, 0u32]),
|
||||
it(&[0u32, 1u32, 1u32, 4u32]),
|
||||
it(&[0u32, 3u32, 5u32]),
|
||||
it(&[0u32, 4u32]),
|
||||
]
|
||||
.into_iter();
|
||||
let start_offsets: Vec<RowId> = super::stack_multivalued_indexes(columns).collect();
|
||||
assert_eq!(start_offsets, &[0, 0, 1, 1, 4, 7, 9, 13]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,3 +1,8 @@
|
||||
//! # `column_index`
|
||||
//!
|
||||
//! `column_index` provides rank and select operations to associate positions when not all
|
||||
//! documents have exactly one element.
|
||||
|
||||
mod merge;
|
||||
mod multivalued_index;
|
||||
mod optional_index;
|
||||
@@ -6,8 +11,11 @@ mod serialize;
|
||||
use std::ops::Range;
|
||||
|
||||
pub use merge::merge_column_index;
|
||||
pub(crate) use multivalued_index::SerializableMultivalueIndex;
|
||||
pub use optional_index::{OptionalIndex, Set};
|
||||
pub use serialize::{open_column_index, serialize_column_index, SerializableColumnIndex};
|
||||
pub use serialize::{
|
||||
open_column_index, serialize_column_index, SerializableColumnIndex, SerializableOptionalIndex,
|
||||
};
|
||||
|
||||
use crate::column_index::multivalued_index::MultiValueIndex;
|
||||
use crate::{Cardinality, DocId, RowId};
|
||||
@@ -20,7 +28,7 @@ pub enum ColumnIndex {
|
||||
Full,
|
||||
Optional(OptionalIndex),
|
||||
/// In addition, at index num_rows, an extra value is added
|
||||
/// containing the overal number of values.
|
||||
/// containing the overall number of values.
|
||||
Multivalued(MultiValueIndex),
|
||||
}
|
||||
|
||||
@@ -37,10 +45,10 @@ impl From<MultiValueIndex> for ColumnIndex {
|
||||
}
|
||||
|
||||
impl ColumnIndex {
|
||||
// Returns the cardinality of the column index.
|
||||
//
|
||||
// By convention, if the column contains no docs, we consider that it is
|
||||
// full.
|
||||
/// Returns the cardinality of the column index.
|
||||
///
|
||||
/// By convention, if the column contains no docs, we consider that it is
|
||||
/// full.
|
||||
#[inline]
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
match self {
|
||||
@@ -117,24 +125,50 @@ impl ColumnIndex {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
|
||||
pub fn docid_range_to_rowids(&self, doc_id_range: Range<DocId>) -> Range<RowId> {
|
||||
match self {
|
||||
ColumnIndex::Empty { .. } => 0..0,
|
||||
ColumnIndex::Full => doc_id,
|
||||
ColumnIndex::Full => doc_id_range,
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
let row_start = optional_index.rank(doc_id.start);
|
||||
let row_end = optional_index.rank(doc_id.end);
|
||||
let row_start = optional_index.rank(doc_id_range.start);
|
||||
let row_end = optional_index.rank(doc_id_range.end);
|
||||
row_start..row_end
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => {
|
||||
let end_docid = doc_id.end.min(multivalued_index.num_docs() - 1) + 1;
|
||||
let start_docid = doc_id.start.min(end_docid);
|
||||
ColumnIndex::Multivalued(multivalued_index) => match multivalued_index {
|
||||
MultiValueIndex::MultiValueIndexV1(index) => {
|
||||
let row_start = index.start_index_column.get_val(doc_id_range.start);
|
||||
let row_end = index.start_index_column.get_val(doc_id_range.end);
|
||||
row_start..row_end
|
||||
}
|
||||
MultiValueIndex::MultiValueIndexV2(index) => {
|
||||
// In this case we will use the optional_index select the next values
|
||||
// that are valid. There are different cases to consider:
|
||||
// Not exists below means does not exist in the optional
|
||||
// index, because it has no values.
|
||||
// * doc_id_range may cover a range of docids which are non existent
|
||||
// => rank
|
||||
// will give us the next document outside the range with a value. They both
|
||||
// get the same rank and therefore return a zero range
|
||||
//
|
||||
// * doc_id_range.start and doc_id_range.end may not exist, but docids in
|
||||
// between may have values
|
||||
// => rank will give us the next document outside the range with a value.
|
||||
//
|
||||
// * doc_id_range.start may be not existent but doc_id_range.end may exist
|
||||
// * doc_id_range.start may exist but doc_id_range.end may not exist
|
||||
// * doc_id_range.start and doc_id_range.end may exist
|
||||
// => rank on doc_id_range.end will give use the next value, which matches
|
||||
// how the `start_index_column` works, so we get the value start of the next
|
||||
// docid which we use to create the exclusive range.
|
||||
//
|
||||
let rank_start = index.optional_index.rank(doc_id_range.start);
|
||||
let row_start = index.start_index_column.get_val(rank_start);
|
||||
let rank_end = index.optional_index.rank(doc_id_range.end);
|
||||
let row_end = index.start_index_column.get_val(rank_end);
|
||||
|
||||
let row_start = multivalued_index.start_index_column.get_val(start_docid);
|
||||
let row_end = multivalued_index.start_index_column.get_val(end_docid);
|
||||
|
||||
row_start..row_end
|
||||
}
|
||||
row_start..row_end
|
||||
}
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -3,64 +3,98 @@ use std::io::Write;
|
||||
use std::ops::Range;
|
||||
use std::sync::Arc;
|
||||
|
||||
use common::OwnedBytes;
|
||||
use common::{CountingWriter, OwnedBytes};
|
||||
|
||||
use super::optional_index::{open_optional_index, serialize_optional_index};
|
||||
use super::{OptionalIndex, SerializableOptionalIndex, Set};
|
||||
use crate::column_values::{
|
||||
load_u64_based_column_values, serialize_u64_based_column_values, CodecType, ColumnValues,
|
||||
};
|
||||
use crate::iterable::Iterable;
|
||||
use crate::{DocId, RowId};
|
||||
use crate::{DocId, RowId, Version};
|
||||
|
||||
pub struct SerializableMultivalueIndex<'a> {
|
||||
pub doc_ids_with_values: SerializableOptionalIndex<'a>,
|
||||
pub start_offsets: Box<dyn Iterable<u32> + 'a>,
|
||||
}
|
||||
|
||||
pub fn serialize_multivalued_index(
|
||||
multivalued_index: &dyn Iterable<RowId>,
|
||||
multivalued_index: &SerializableMultivalueIndex,
|
||||
output: &mut impl Write,
|
||||
) -> io::Result<()> {
|
||||
let SerializableMultivalueIndex {
|
||||
doc_ids_with_values,
|
||||
start_offsets,
|
||||
} = multivalued_index;
|
||||
let mut count_writer = CountingWriter::wrap(output);
|
||||
let SerializableOptionalIndex {
|
||||
non_null_row_ids,
|
||||
num_rows,
|
||||
} = doc_ids_with_values;
|
||||
serialize_optional_index(&**non_null_row_ids, *num_rows, &mut count_writer)?;
|
||||
let optional_len = count_writer.written_bytes() as u32;
|
||||
let output = count_writer.finish();
|
||||
serialize_u64_based_column_values(
|
||||
multivalued_index,
|
||||
&**start_offsets,
|
||||
&[CodecType::Bitpacked, CodecType::Linear],
|
||||
output,
|
||||
)?;
|
||||
output.write_all(&optional_len.to_le_bytes())?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub fn open_multivalued_index(bytes: OwnedBytes) -> io::Result<MultiValueIndex> {
|
||||
let start_index_column: Arc<dyn ColumnValues<RowId>> = load_u64_based_column_values(bytes)?;
|
||||
Ok(MultiValueIndex { start_index_column })
|
||||
pub fn open_multivalued_index(
|
||||
bytes: OwnedBytes,
|
||||
format_version: Version,
|
||||
) -> io::Result<MultiValueIndex> {
|
||||
match format_version {
|
||||
Version::V1 => {
|
||||
let start_index_column: Arc<dyn ColumnValues<RowId>> =
|
||||
load_u64_based_column_values(bytes)?;
|
||||
Ok(MultiValueIndex::MultiValueIndexV1(MultiValueIndexV1 {
|
||||
start_index_column,
|
||||
}))
|
||||
}
|
||||
Version::V2 => {
|
||||
let (body_bytes, optional_index_len) = bytes.rsplit(4);
|
||||
let optional_index_len =
|
||||
u32::from_le_bytes(optional_index_len.as_slice().try_into().unwrap());
|
||||
let (optional_index_bytes, start_index_bytes) =
|
||||
body_bytes.split(optional_index_len as usize);
|
||||
let optional_index = open_optional_index(optional_index_bytes)?;
|
||||
let start_index_column: Arc<dyn ColumnValues<RowId>> =
|
||||
load_u64_based_column_values(start_index_bytes)?;
|
||||
Ok(MultiValueIndex::MultiValueIndexV2(MultiValueIndexV2 {
|
||||
optional_index,
|
||||
start_index_column,
|
||||
}))
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Clone)]
|
||||
/// Index to resolve value range for given doc_id.
|
||||
/// Starts at 0.
|
||||
pub struct MultiValueIndex {
|
||||
pub enum MultiValueIndex {
|
||||
MultiValueIndexV1(MultiValueIndexV1),
|
||||
MultiValueIndexV2(MultiValueIndexV2),
|
||||
}
|
||||
|
||||
#[derive(Clone)]
|
||||
/// Index to resolve value range for given doc_id.
|
||||
/// Starts at 0.
|
||||
pub struct MultiValueIndexV1 {
|
||||
pub start_index_column: Arc<dyn crate::ColumnValues<RowId>>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for MultiValueIndex {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
|
||||
f.debug_struct("MultiValuedIndex")
|
||||
.field("num_rows", &self.start_index_column.num_vals())
|
||||
.finish_non_exhaustive()
|
||||
}
|
||||
}
|
||||
|
||||
impl From<Arc<dyn ColumnValues<RowId>>> for MultiValueIndex {
|
||||
fn from(start_index_column: Arc<dyn ColumnValues<RowId>>) -> Self {
|
||||
MultiValueIndex { start_index_column }
|
||||
}
|
||||
}
|
||||
|
||||
impl MultiValueIndex {
|
||||
pub fn for_test(start_offsets: &[RowId]) -> MultiValueIndex {
|
||||
let mut buffer = Vec::new();
|
||||
serialize_multivalued_index(&start_offsets, &mut buffer).unwrap();
|
||||
let bytes = OwnedBytes::new(buffer);
|
||||
open_multivalued_index(bytes).unwrap()
|
||||
}
|
||||
|
||||
impl MultiValueIndexV1 {
|
||||
/// Returns `[start, end)`, such that the values associated with
|
||||
/// the given document are `start..end`.
|
||||
#[inline]
|
||||
pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
|
||||
if doc_id >= self.num_docs() {
|
||||
return 0..0;
|
||||
}
|
||||
let start = self.start_index_column.get_val(doc_id);
|
||||
let end = self.start_index_column.get_val(doc_id + 1);
|
||||
start..end
|
||||
@@ -83,7 +117,6 @@ impl MultiValueIndex {
|
||||
///
|
||||
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
|
||||
/// match a docid to its value position.
|
||||
#[allow(clippy::bool_to_int_with_if)]
|
||||
pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
|
||||
if ranks.is_empty() {
|
||||
return;
|
||||
@@ -111,11 +144,170 @@ impl MultiValueIndex {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Clone)]
|
||||
/// Index to resolve value range for given doc_id.
|
||||
/// Starts at 0.
|
||||
pub struct MultiValueIndexV2 {
|
||||
pub optional_index: OptionalIndex,
|
||||
pub start_index_column: Arc<dyn crate::ColumnValues<RowId>>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for MultiValueIndex {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
|
||||
let index = match self {
|
||||
MultiValueIndex::MultiValueIndexV1(idx) => &idx.start_index_column,
|
||||
MultiValueIndex::MultiValueIndexV2(idx) => &idx.start_index_column,
|
||||
};
|
||||
f.debug_struct("MultiValuedIndex")
|
||||
.field("num_rows", &index.num_vals())
|
||||
.finish_non_exhaustive()
|
||||
}
|
||||
}
|
||||
|
||||
impl MultiValueIndex {
|
||||
pub fn for_test(start_offsets: &[RowId]) -> MultiValueIndex {
|
||||
assert!(!start_offsets.is_empty());
|
||||
assert_eq!(start_offsets[0], 0);
|
||||
let mut doc_with_values = Vec::new();
|
||||
let mut compact_start_offsets: Vec<u32> = vec![0];
|
||||
for doc in 0..start_offsets.len() - 1 {
|
||||
if start_offsets[doc] < start_offsets[doc + 1] {
|
||||
doc_with_values.push(doc as RowId);
|
||||
compact_start_offsets.push(start_offsets[doc + 1]);
|
||||
}
|
||||
}
|
||||
let serializable_multivalued_index = SerializableMultivalueIndex {
|
||||
doc_ids_with_values: SerializableOptionalIndex {
|
||||
non_null_row_ids: Box::new(&doc_with_values[..]),
|
||||
num_rows: start_offsets.len() as u32 - 1,
|
||||
},
|
||||
start_offsets: Box::new(&compact_start_offsets[..]),
|
||||
};
|
||||
let mut buffer = Vec::new();
|
||||
serialize_multivalued_index(&serializable_multivalued_index, &mut buffer).unwrap();
|
||||
let bytes = OwnedBytes::new(buffer);
|
||||
open_multivalued_index(bytes, Version::V2).unwrap()
|
||||
}
|
||||
|
||||
pub fn get_start_index_column(&self) -> &Arc<dyn crate::ColumnValues<RowId>> {
|
||||
match self {
|
||||
MultiValueIndex::MultiValueIndexV1(idx) => &idx.start_index_column,
|
||||
MultiValueIndex::MultiValueIndexV2(idx) => &idx.start_index_column,
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns `[start, end)` values range, such that the values associated with
|
||||
/// the given document are `start..end`.
|
||||
#[inline]
|
||||
pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
|
||||
match self {
|
||||
MultiValueIndex::MultiValueIndexV1(idx) => idx.range(doc_id),
|
||||
MultiValueIndex::MultiValueIndexV2(idx) => idx.range(doc_id),
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the number of documents in the index.
|
||||
#[inline]
|
||||
pub fn num_docs(&self) -> u32 {
|
||||
match self {
|
||||
MultiValueIndex::MultiValueIndexV1(idx) => idx.start_index_column.num_vals() - 1,
|
||||
MultiValueIndex::MultiValueIndexV2(idx) => idx.optional_index.num_docs(),
|
||||
}
|
||||
}
|
||||
|
||||
/// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
|
||||
/// docids. Positions are converted inplace to docids.
|
||||
///
|
||||
/// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
|
||||
/// index.
|
||||
///
|
||||
/// Correctness: positions needs to be sorted. idx_reader needs to contain monotonically
|
||||
/// increasing positions.
|
||||
///
|
||||
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
|
||||
/// match a docid to its value position.
|
||||
pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
|
||||
match self {
|
||||
MultiValueIndex::MultiValueIndexV1(idx) => {
|
||||
idx.select_batch_in_place(docid_start, ranks)
|
||||
}
|
||||
MultiValueIndex::MultiValueIndexV2(idx) => {
|
||||
idx.select_batch_in_place(docid_start, ranks)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
impl MultiValueIndexV2 {
|
||||
/// Returns `[start, end)`, such that the values associated with
|
||||
/// the given document are `start..end`.
|
||||
#[inline]
|
||||
pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
|
||||
let Some(rank) = self.optional_index.rank_if_exists(doc_id) else {
|
||||
return 0..0;
|
||||
};
|
||||
let start = self.start_index_column.get_val(rank);
|
||||
let end = self.start_index_column.get_val(rank + 1);
|
||||
start..end
|
||||
}
|
||||
|
||||
/// Returns the number of documents in the index.
|
||||
#[inline]
|
||||
pub fn num_docs(&self) -> u32 {
|
||||
self.optional_index.num_docs()
|
||||
}
|
||||
|
||||
/// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
|
||||
/// docids. Positions are converted inplace to docids.
|
||||
///
|
||||
/// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
|
||||
/// index.
|
||||
///
|
||||
/// Correctness: positions needs to be sorted. idx_reader needs to contain monotonically
|
||||
/// increasing positions.
|
||||
///
|
||||
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
|
||||
/// match a docid to its value position.
|
||||
pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
|
||||
if ranks.is_empty() {
|
||||
return;
|
||||
}
|
||||
let mut cur_pos_in_idx = self.optional_index.rank(docid_start);
|
||||
let mut last_doc = None;
|
||||
|
||||
assert!(cur_pos_in_idx <= ranks[0]);
|
||||
|
||||
let mut write_doc_pos = 0;
|
||||
for i in 0..ranks.len() {
|
||||
let pos = ranks[i];
|
||||
loop {
|
||||
let end = self.start_index_column.get_val(cur_pos_in_idx + 1);
|
||||
if end > pos {
|
||||
ranks[write_doc_pos] = cur_pos_in_idx;
|
||||
write_doc_pos += if last_doc == Some(cur_pos_in_idx) {
|
||||
0
|
||||
} else {
|
||||
1
|
||||
};
|
||||
last_doc = Some(cur_pos_in_idx);
|
||||
break;
|
||||
}
|
||||
cur_pos_in_idx += 1;
|
||||
}
|
||||
}
|
||||
ranks.truncate(write_doc_pos);
|
||||
|
||||
for rank in ranks.iter_mut() {
|
||||
*rank = self.optional_index.select(*rank);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::ops::Range;
|
||||
|
||||
use super::MultiValueIndex;
|
||||
use crate::{ColumnarReader, DynamicColumn};
|
||||
|
||||
fn index_to_pos_helper(
|
||||
index: &MultiValueIndex,
|
||||
@@ -134,6 +326,7 @@ mod tests {
|
||||
let positions = &[10u32, 11, 15, 20, 21, 22];
|
||||
assert_eq!(index_to_pos_helper(&index, 0..5, positions), vec![1, 3, 4]);
|
||||
assert_eq!(index_to_pos_helper(&index, 1..5, positions), vec![1, 3, 4]);
|
||||
|
||||
assert_eq!(index_to_pos_helper(&index, 0..5, &[9]), vec![0]);
|
||||
assert_eq!(index_to_pos_helper(&index, 1..5, &[10]), vec![1]);
|
||||
assert_eq!(index_to_pos_helper(&index, 1..5, &[11]), vec![1]);
|
||||
@@ -141,4 +334,67 @@ mod tests {
|
||||
assert_eq!(index_to_pos_helper(&index, 2..5, &[12, 14]), vec![2]);
|
||||
assert_eq!(index_to_pos_helper(&index, 2..5, &[12, 14, 15]), vec![2, 3]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_range_to_rowids() {
|
||||
use crate::ColumnarWriter;
|
||||
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
|
||||
// This column gets coerced to u64
|
||||
columnar_writer.record_numerical(1, "full", u64::MAX);
|
||||
columnar_writer.record_numerical(1, "full", u64::MAX);
|
||||
|
||||
columnar_writer.record_numerical(5, "full", u64::MAX);
|
||||
columnar_writer.record_numerical(5, "full", u64::MAX);
|
||||
|
||||
let mut wrt: Vec<u8> = Vec::new();
|
||||
columnar_writer.serialize(7, &mut wrt).unwrap();
|
||||
|
||||
let reader = ColumnarReader::open(wrt).unwrap();
|
||||
// Open the column as u64
|
||||
let column = reader.read_columns("full").unwrap()[0]
|
||||
.open()
|
||||
.unwrap()
|
||||
.coerce_numerical(crate::NumericalType::U64)
|
||||
.unwrap();
|
||||
let DynamicColumn::U64(column) = column else {
|
||||
panic!();
|
||||
};
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(1..2);
|
||||
assert_eq!(row_id_range, 0..2);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(0..2);
|
||||
assert_eq!(row_id_range, 0..2);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(0..4);
|
||||
assert_eq!(row_id_range, 0..2);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(3..4);
|
||||
assert_eq!(row_id_range, 2..2);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(1..6);
|
||||
assert_eq!(row_id_range, 0..4);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(3..6);
|
||||
assert_eq!(row_id_range, 2..4);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(0..6);
|
||||
assert_eq!(row_id_range, 0..4);
|
||||
|
||||
let row_id_range = column.index.docid_range_to_rowids(0..6);
|
||||
assert_eq!(row_id_range, 0..4);
|
||||
|
||||
let check = |range, expected| {
|
||||
let full_range = 0..=u64::MAX;
|
||||
let mut docids = Vec::new();
|
||||
column.get_docids_for_value_range(full_range, range, &mut docids);
|
||||
assert_eq!(docids, expected);
|
||||
};
|
||||
|
||||
// check(0..1, vec![]);
|
||||
// check(0..2, vec![1]);
|
||||
check(1..2, vec![1]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -21,8 +21,6 @@ const DENSE_BLOCK_THRESHOLD: u32 =
|
||||
|
||||
const ELEMENTS_PER_BLOCK: u32 = u16::MAX as u32 + 1;
|
||||
|
||||
const BLOCK_SIZE: RowId = 1 << 16;
|
||||
|
||||
#[derive(Copy, Clone, Debug)]
|
||||
struct BlockMeta {
|
||||
non_null_rows_before_block: u32,
|
||||
@@ -82,17 +80,23 @@ impl BlockVariant {
|
||||
/// index is the block index. For each block `byte_start` and `offset` is computed.
|
||||
#[derive(Clone)]
|
||||
pub struct OptionalIndex {
|
||||
num_rows: RowId,
|
||||
num_non_null_rows: RowId,
|
||||
num_docs: RowId,
|
||||
num_non_null_docs: RowId,
|
||||
block_data: OwnedBytes,
|
||||
block_metas: Arc<[BlockMeta]>,
|
||||
}
|
||||
|
||||
impl Iterable<u32> for &OptionalIndex {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
|
||||
Box::new(self.iter_docs())
|
||||
}
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for OptionalIndex {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
|
||||
f.debug_struct("OptionalIndex")
|
||||
.field("num_rows", &self.num_rows)
|
||||
.field("num_non_null_rows", &self.num_non_null_rows)
|
||||
.field("num_docs", &self.num_docs)
|
||||
.field("num_non_null_docs", &self.num_non_null_docs)
|
||||
.finish_non_exhaustive()
|
||||
}
|
||||
}
|
||||
@@ -109,8 +113,8 @@ struct RowAddr {
|
||||
#[inline(always)]
|
||||
fn row_addr_from_row_id(row_id: RowId) -> RowAddr {
|
||||
RowAddr {
|
||||
block_id: (row_id / BLOCK_SIZE) as u16,
|
||||
in_block_row_id: (row_id % BLOCK_SIZE) as u16,
|
||||
block_id: (row_id / ELEMENTS_PER_BLOCK) as u16,
|
||||
in_block_row_id: (row_id % ELEMENTS_PER_BLOCK) as u16,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -119,7 +123,7 @@ enum BlockSelectCursor<'a> {
|
||||
Sparse(<SparseBlock<'a> as Set<u16>>::SelectCursor<'a>),
|
||||
}
|
||||
|
||||
impl<'a> BlockSelectCursor<'a> {
|
||||
impl BlockSelectCursor<'_> {
|
||||
fn select(&mut self, rank: u16) -> u16 {
|
||||
match self {
|
||||
BlockSelectCursor::Dense(dense_select_cursor) => dense_select_cursor.select(rank),
|
||||
@@ -137,7 +141,7 @@ pub struct OptionalIndexSelectCursor<'a> {
|
||||
num_null_rows_before_block: RowId,
|
||||
}
|
||||
|
||||
impl<'a> OptionalIndexSelectCursor<'a> {
|
||||
impl OptionalIndexSelectCursor<'_> {
|
||||
fn search_and_load_block(&mut self, rank: RowId) {
|
||||
if rank < self.current_block_end_rank {
|
||||
// we are already in the right block
|
||||
@@ -161,7 +165,7 @@ impl<'a> OptionalIndexSelectCursor<'a> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> SelectCursor<RowId> for OptionalIndexSelectCursor<'a> {
|
||||
impl SelectCursor<RowId> for OptionalIndexSelectCursor<'_> {
|
||||
fn select(&mut self, rank: RowId) -> RowId {
|
||||
self.search_and_load_block(rank);
|
||||
let index_in_block = (rank - self.num_null_rows_before_block) as u16;
|
||||
@@ -170,7 +174,9 @@ impl<'a> SelectCursor<RowId> for OptionalIndexSelectCursor<'a> {
|
||||
}
|
||||
|
||||
impl Set<RowId> for OptionalIndex {
|
||||
type SelectCursor<'b> = OptionalIndexSelectCursor<'b> where Self: 'b;
|
||||
type SelectCursor<'b>
|
||||
= OptionalIndexSelectCursor<'b>
|
||||
where Self: 'b;
|
||||
// Check if value at position is not null.
|
||||
#[inline]
|
||||
fn contains(&self, row_id: RowId) -> bool {
|
||||
@@ -185,14 +191,20 @@ impl Set<RowId> for OptionalIndex {
|
||||
}
|
||||
}
|
||||
|
||||
/// Any value doc_id is allowed.
|
||||
/// In particular, doc_id = num_rows.
|
||||
#[inline]
|
||||
fn rank(&self, doc_id: DocId) -> RowId {
|
||||
if doc_id >= self.num_docs() {
|
||||
return self.num_non_nulls();
|
||||
}
|
||||
let RowAddr {
|
||||
block_id,
|
||||
in_block_row_id,
|
||||
} = row_addr_from_row_id(doc_id);
|
||||
let block_meta = self.block_metas[block_id as usize];
|
||||
let block = self.block(block_meta);
|
||||
|
||||
let block_offset_row_id = match block {
|
||||
Block::Dense(dense_block) => dense_block.rank(in_block_row_id),
|
||||
Block::Sparse(sparse_block) => sparse_block.rank(in_block_row_id),
|
||||
@@ -200,13 +212,15 @@ impl Set<RowId> for OptionalIndex {
|
||||
block_meta.non_null_rows_before_block + block_offset_row_id
|
||||
}
|
||||
|
||||
/// Any value doc_id is allowed.
|
||||
/// In particular, doc_id = num_rows.
|
||||
#[inline]
|
||||
fn rank_if_exists(&self, doc_id: DocId) -> Option<RowId> {
|
||||
let RowAddr {
|
||||
block_id,
|
||||
in_block_row_id,
|
||||
} = row_addr_from_row_id(doc_id);
|
||||
let block_meta = self.block_metas[block_id as usize];
|
||||
let block_meta = *self.block_metas.get(block_id as usize)?;
|
||||
let block = self.block(block_meta);
|
||||
let block_offset_row_id = match block {
|
||||
Block::Dense(dense_block) => dense_block.rank_if_exists(in_block_row_id),
|
||||
@@ -257,17 +271,17 @@ impl OptionalIndex {
|
||||
}
|
||||
|
||||
pub fn num_docs(&self) -> RowId {
|
||||
self.num_rows
|
||||
self.num_docs
|
||||
}
|
||||
|
||||
pub fn num_non_nulls(&self) -> RowId {
|
||||
self.num_non_null_rows
|
||||
self.num_non_null_docs
|
||||
}
|
||||
|
||||
pub fn iter_rows(&self) -> impl Iterator<Item = RowId> + '_ {
|
||||
pub fn iter_docs(&self) -> impl Iterator<Item = RowId> + '_ {
|
||||
// TODO optimize
|
||||
let mut select_batch = self.select_cursor();
|
||||
(0..self.num_non_null_rows).map(move |rank| select_batch.select(rank))
|
||||
(0..self.num_non_null_docs).map(move |rank| select_batch.select(rank))
|
||||
}
|
||||
pub fn select_batch(&self, ranks: &mut [RowId]) {
|
||||
let mut select_cursor = self.select_cursor();
|
||||
@@ -491,7 +505,7 @@ fn deserialize_optional_index_block_metadatas(
|
||||
non_null_rows_before_block += num_non_null_rows;
|
||||
}
|
||||
block_metas.resize(
|
||||
((num_rows + BLOCK_SIZE - 1) / BLOCK_SIZE) as usize,
|
||||
num_rows.div_ceil(ELEMENTS_PER_BLOCK) as usize,
|
||||
BlockMeta {
|
||||
non_null_rows_before_block,
|
||||
start_byte_offset,
|
||||
@@ -505,15 +519,15 @@ pub fn open_optional_index(bytes: OwnedBytes) -> io::Result<OptionalIndex> {
|
||||
let (mut bytes, num_non_empty_blocks_bytes) = bytes.rsplit(2);
|
||||
let num_non_empty_block_bytes =
|
||||
u16::from_le_bytes(num_non_empty_blocks_bytes.as_slice().try_into().unwrap());
|
||||
let num_rows = VInt::deserialize_u64(&mut bytes)? as u32;
|
||||
let num_docs = VInt::deserialize_u64(&mut bytes)? as u32;
|
||||
let block_metas_num_bytes =
|
||||
num_non_empty_block_bytes as usize * SERIALIZED_BLOCK_META_NUM_BYTES;
|
||||
let (block_data, block_metas) = bytes.rsplit(block_metas_num_bytes);
|
||||
let (block_metas, num_non_null_rows) =
|
||||
deserialize_optional_index_block_metadatas(block_metas.as_slice(), num_rows);
|
||||
let (block_metas, num_non_null_docs) =
|
||||
deserialize_optional_index_block_metadatas(block_metas.as_slice(), num_docs);
|
||||
let optional_index = OptionalIndex {
|
||||
num_rows,
|
||||
num_non_null_rows,
|
||||
num_docs,
|
||||
num_non_null_docs,
|
||||
block_data,
|
||||
block_metas: block_metas.into(),
|
||||
};
|
||||
|
||||
@@ -28,10 +28,11 @@ pub trait Set<T> {
|
||||
/// Returns true if the elements is contained in the Set
|
||||
fn contains(&self, el: T) -> bool;
|
||||
|
||||
/// Returns the number of rows in the set that are < `el`
|
||||
/// Returns the element's rank (its position in the set).
|
||||
/// If the set does not contain the element, it will return the next existing elements rank.
|
||||
fn rank(&self, el: T) -> T;
|
||||
|
||||
/// If the set contains `el` returns the element rank.
|
||||
/// If the set contains `el`, returns the element's rank (its position in the set).
|
||||
/// If the set does not contain the element, it returns `None`.
|
||||
fn rank_if_exists(&self, el: T) -> Option<T>;
|
||||
|
||||
@@ -39,7 +40,8 @@ pub trait Set<T> {
|
||||
///
|
||||
/// # Panics
|
||||
///
|
||||
/// May panic if rank is greater than the number of elements in the Set.
|
||||
/// May panic if rank is greater or equal to the number of
|
||||
/// elements in the Set.
|
||||
fn select(&self, rank: T) -> T;
|
||||
|
||||
/// Creates a brand new select cursor.
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io::{self, Write};
|
||||
|
||||
use common::BinarySerializable;
|
||||
@@ -24,7 +23,6 @@ fn set_bit_at(input: &mut u64, n: u16) {
|
||||
///
|
||||
/// When translating a dense index to the original index, we can use the offset to find the correct
|
||||
/// block. Direct computation is not possible, but we can employ a linear or binary search.
|
||||
|
||||
const ELEMENTS_PER_MINI_BLOCK: u16 = 64;
|
||||
const MINI_BLOCK_BITVEC_NUM_BYTES: usize = 8;
|
||||
const MINI_BLOCK_OFFSET_NUM_BYTES: usize = 2;
|
||||
@@ -110,7 +108,7 @@ pub struct DenseBlockSelectCursor<'a> {
|
||||
dense_block: DenseBlock<'a>,
|
||||
}
|
||||
|
||||
impl<'a> SelectCursor<u16> for DenseBlockSelectCursor<'a> {
|
||||
impl SelectCursor<u16> for DenseBlockSelectCursor<'_> {
|
||||
#[inline]
|
||||
fn select(&mut self, rank: u16) -> u16 {
|
||||
self.block_id = self
|
||||
@@ -124,7 +122,9 @@ impl<'a> SelectCursor<u16> for DenseBlockSelectCursor<'a> {
|
||||
}
|
||||
|
||||
impl<'a> Set<u16> for DenseBlock<'a> {
|
||||
type SelectCursor<'b> = DenseBlockSelectCursor<'a> where Self: 'b;
|
||||
type SelectCursor<'b>
|
||||
= DenseBlockSelectCursor<'a>
|
||||
where Self: 'b;
|
||||
|
||||
#[inline(always)]
|
||||
fn contains(&self, el: u16) -> bool {
|
||||
@@ -174,7 +174,7 @@ impl<'a> Set<u16> for DenseBlock<'a> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> DenseBlock<'a> {
|
||||
impl DenseBlock<'_> {
|
||||
#[inline]
|
||||
fn mini_block(&self, mini_block_id: u16) -> DenseMiniBlock {
|
||||
let data_start_pos = mini_block_id as usize * MINI_BLOCK_NUM_BYTES;
|
||||
|
||||
@@ -31,8 +31,10 @@ impl<'a> SelectCursor<u16> for SparseBlock<'a> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> Set<u16> for SparseBlock<'a> {
|
||||
type SelectCursor<'b> = Self where Self: 'b;
|
||||
impl Set<u16> for SparseBlock<'_> {
|
||||
type SelectCursor<'b>
|
||||
= Self
|
||||
where Self: 'b;
|
||||
|
||||
#[inline(always)]
|
||||
fn contains(&self, el: u16) -> bool {
|
||||
@@ -67,7 +69,7 @@ fn get_u16(data: &[u8], byte_position: usize) -> u16 {
|
||||
u16::from_le_bytes(bytes)
|
||||
}
|
||||
|
||||
impl<'a> SparseBlock<'a> {
|
||||
impl SparseBlock<'_> {
|
||||
#[inline(always)]
|
||||
fn value_at_idx(&self, data: &[u8], idx: u16) -> u16 {
|
||||
let start_offset: usize = idx as usize * 2;
|
||||
@@ -80,7 +82,7 @@ impl<'a> SparseBlock<'a> {
|
||||
}
|
||||
|
||||
#[inline]
|
||||
#[allow(clippy::comparison_chain)]
|
||||
#[expect(clippy::comparison_chain)]
|
||||
// Looks for the element in the block. Returns the positions if found.
|
||||
fn binary_search(&self, target: u16) -> Result<u16, u16> {
|
||||
let data = &self.0;
|
||||
|
||||
@@ -22,8 +22,8 @@ fn test_set_helper<C: SetCodec<Item = u16>>(vals: &[u16]) -> usize {
|
||||
vals.iter().cloned().take_while(|v| *v < val).count() as u16
|
||||
);
|
||||
}
|
||||
for rank in 0..vals.len() {
|
||||
assert_eq!(tested_set.select(rank as u16), vals[rank]);
|
||||
for (rank, val) in vals.iter().enumerate() {
|
||||
assert_eq!(tested_set.select(rank as u16), *val);
|
||||
}
|
||||
buffer.len()
|
||||
}
|
||||
@@ -107,3 +107,41 @@ fn test_simple_translate_codec_idx_to_original_idx_dense() {
|
||||
assert_eq!(i, select_cursor.select(i));
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_simple_translate_idx_to_value_idx_dense() {
|
||||
let mut buffer = Vec::new();
|
||||
DenseBlockCodec::serialize([1, 10].iter().copied(), &mut buffer).unwrap();
|
||||
let tested_set = DenseBlockCodec::open(buffer.as_slice());
|
||||
assert!(tested_set.contains(1));
|
||||
assert!(!tested_set.contains(2));
|
||||
assert_eq!(tested_set.rank(0), 0);
|
||||
assert_eq!(tested_set.rank(1), 0);
|
||||
for rank in 2..10 {
|
||||
// ranks that don't exist select the next highest one
|
||||
assert_eq!(tested_set.rank_if_exists(rank), None);
|
||||
assert_eq!(tested_set.rank(rank), 1);
|
||||
}
|
||||
assert_eq!(tested_set.rank(10), 1);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_simple_translate_idx_to_value_idx_sparse() {
|
||||
let mut buffer = Vec::new();
|
||||
SparseBlockCodec::serialize([1, 10].iter().copied(), &mut buffer).unwrap();
|
||||
let tested_set = SparseBlockCodec::open(buffer.as_slice());
|
||||
assert!(tested_set.contains(1));
|
||||
assert!(!tested_set.contains(2));
|
||||
assert_eq!(tested_set.rank(0), 0);
|
||||
assert_eq!(tested_set.select(tested_set.rank(0)), 1);
|
||||
assert_eq!(tested_set.rank(1), 0);
|
||||
assert_eq!(tested_set.select(tested_set.rank(1)), 1);
|
||||
for rank in 2..10 {
|
||||
// ranks that don't exist select the next highest one
|
||||
assert_eq!(tested_set.rank_if_exists(rank), None);
|
||||
assert_eq!(tested_set.rank(rank), 1);
|
||||
assert_eq!(tested_set.select(tested_set.rank(rank)), 10);
|
||||
}
|
||||
assert_eq!(tested_set.rank(10), 1);
|
||||
assert_eq!(tested_set.select(tested_set.rank(10)), 10);
|
||||
}
|
||||
|
||||
@@ -1,8 +1,29 @@
|
||||
use proptest::prelude::{any, prop, *};
|
||||
use proptest::strategy::Strategy;
|
||||
use proptest::prelude::*;
|
||||
use proptest::{prop_oneof, proptest};
|
||||
|
||||
use super::*;
|
||||
use crate::{ColumnarReader, ColumnarWriter, DynamicColumnHandle};
|
||||
|
||||
#[test]
|
||||
fn test_optional_index_bug_2293() {
|
||||
// tests for panic in docid_range_to_rowids for docid == num_docs
|
||||
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK - 1);
|
||||
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK);
|
||||
test_optional_index_with_num_docs(ELEMENTS_PER_BLOCK + 1);
|
||||
}
|
||||
fn test_optional_index_with_num_docs(num_docs: u32) {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
dataframe_writer.record_numerical(100, "score", 80i64);
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(num_docs, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("score").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
|
||||
let col = cols[0].open().unwrap();
|
||||
col.column_index().docid_range_to_rowids(0..num_docs);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dense_block_threshold() {
|
||||
@@ -35,7 +56,7 @@ proptest! {
|
||||
|
||||
#[test]
|
||||
fn test_with_random_sets_simple() {
|
||||
let vals = 10..BLOCK_SIZE * 2;
|
||||
let vals = 10..ELEMENTS_PER_BLOCK * 2;
|
||||
let mut out: Vec<u8> = Vec::new();
|
||||
serialize_optional_index(&vals, 100, &mut out).unwrap();
|
||||
let null_index = open_optional_index(OwnedBytes::new(out)).unwrap();
|
||||
@@ -89,8 +110,8 @@ fn test_null_index(data: &[bool]) {
|
||||
.map(|(pos, _val)| pos as u32)
|
||||
.collect();
|
||||
let mut select_iter = null_index.select_cursor();
|
||||
for i in 0..orig_idx_with_value.len() {
|
||||
assert_eq!(select_iter.select(i as u32), orig_idx_with_value[i]);
|
||||
for (i, expected) in orig_idx_with_value.iter().enumerate() {
|
||||
assert_eq!(select_iter.select(i as u32), *expected);
|
||||
}
|
||||
|
||||
let step_size = (orig_idx_with_value.len() / 100).max(1);
|
||||
@@ -143,7 +164,7 @@ fn test_optional_index_large() {
|
||||
fn test_optional_index_iter_aux(row_ids: &[RowId], num_rows: RowId) {
|
||||
let optional_index = OptionalIndex::for_test(num_rows, row_ids);
|
||||
assert_eq!(optional_index.num_docs(), num_rows);
|
||||
assert!(optional_index.iter_rows().eq(row_ids.iter().copied()));
|
||||
assert!(optional_index.iter_docs().eq(row_ids.iter().copied()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -171,7 +192,7 @@ fn test_optional_index_rank() {
|
||||
test_optional_index_rank_aux(&[0u32, 1u32]);
|
||||
let mut block = Vec::new();
|
||||
block.push(3u32);
|
||||
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
|
||||
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
|
||||
test_optional_index_rank_aux(&block);
|
||||
}
|
||||
|
||||
@@ -185,8 +206,8 @@ fn test_optional_index_iter_empty_one() {
|
||||
fn test_optional_index_iter_dense_block() {
|
||||
let mut block = Vec::new();
|
||||
block.push(3u32);
|
||||
block.extend((0..BLOCK_SIZE).map(|i| i + BLOCK_SIZE + 1));
|
||||
test_optional_index_iter_aux(&block, 3 * BLOCK_SIZE);
|
||||
block.extend((0..ELEMENTS_PER_BLOCK).map(|i| i + ELEMENTS_PER_BLOCK + 1));
|
||||
test_optional_index_iter_aux(&block, 3 * ELEMENTS_PER_BLOCK);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -215,12 +236,12 @@ mod bench {
|
||||
let vals: Vec<RowId> = (0..TOTAL_NUM_VALUES)
|
||||
.map(|_| rng.gen_bool(fill_ratio))
|
||||
.enumerate()
|
||||
.filter(|(pos, val)| *val)
|
||||
.filter(|(_pos, val)| *val)
|
||||
.map(|(pos, _)| pos as RowId)
|
||||
.collect();
|
||||
serialize_optional_index(&&vals[..], TOTAL_NUM_VALUES, &mut out).unwrap();
|
||||
let codec = open_optional_index(OwnedBytes::new(out)).unwrap();
|
||||
codec
|
||||
|
||||
open_optional_index(OwnedBytes::new(out)).unwrap()
|
||||
}
|
||||
|
||||
fn random_range_iterator(
|
||||
@@ -242,7 +263,7 @@ mod bench {
|
||||
}
|
||||
|
||||
fn n_percent_step_iterator(percent: f32, num_values: u32) -> impl Iterator<Item = u32> {
|
||||
let ratio = percent as f32 / 100.0;
|
||||
let ratio = percent / 100.0;
|
||||
let step_size = (1f32 / ratio) as u32;
|
||||
let deviation = step_size - 1;
|
||||
random_range_iterator(0, num_values, step_size, deviation)
|
||||
|
||||
@@ -3,33 +3,45 @@ use std::io::Write;
|
||||
|
||||
use common::{CountingWriter, OwnedBytes};
|
||||
|
||||
use super::multivalued_index::SerializableMultivalueIndex;
|
||||
use super::OptionalIndex;
|
||||
use crate::column_index::multivalued_index::serialize_multivalued_index;
|
||||
use crate::column_index::optional_index::serialize_optional_index;
|
||||
use crate::column_index::ColumnIndex;
|
||||
use crate::iterable::Iterable;
|
||||
use crate::{Cardinality, RowId};
|
||||
use crate::{Cardinality, RowId, Version};
|
||||
|
||||
pub struct SerializableOptionalIndex<'a> {
|
||||
pub non_null_row_ids: Box<dyn Iterable<RowId> + 'a>,
|
||||
pub num_rows: RowId,
|
||||
}
|
||||
|
||||
impl<'a> From<&'a OptionalIndex> for SerializableOptionalIndex<'a> {
|
||||
fn from(optional_index: &'a OptionalIndex) -> Self {
|
||||
SerializableOptionalIndex {
|
||||
non_null_row_ids: Box::new(optional_index),
|
||||
num_rows: optional_index.num_docs(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub enum SerializableColumnIndex<'a> {
|
||||
Full,
|
||||
Optional {
|
||||
non_null_row_ids: Box<dyn Iterable<RowId> + 'a>,
|
||||
num_rows: RowId,
|
||||
},
|
||||
// TODO remove the Arc<dyn> apart from serialization this is not
|
||||
// dynamic at all.
|
||||
Multivalued(Box<dyn Iterable<RowId> + 'a>),
|
||||
Optional(SerializableOptionalIndex<'a>),
|
||||
Multivalued(SerializableMultivalueIndex<'a>),
|
||||
}
|
||||
|
||||
impl<'a> SerializableColumnIndex<'a> {
|
||||
impl SerializableColumnIndex<'_> {
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
match self {
|
||||
SerializableColumnIndex::Full => Cardinality::Full,
|
||||
SerializableColumnIndex::Optional { .. } => Cardinality::Optional,
|
||||
SerializableColumnIndex::Optional(_) => Cardinality::Optional,
|
||||
SerializableColumnIndex::Multivalued(_) => Cardinality::Multivalued,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Serialize a column index.
|
||||
pub fn serialize_column_index(
|
||||
column_index: SerializableColumnIndex,
|
||||
output: &mut impl Write,
|
||||
@@ -39,19 +51,23 @@ pub fn serialize_column_index(
|
||||
output.write_all(&[cardinality])?;
|
||||
match column_index {
|
||||
SerializableColumnIndex::Full => {}
|
||||
SerializableColumnIndex::Optional {
|
||||
SerializableColumnIndex::Optional(SerializableOptionalIndex {
|
||||
non_null_row_ids,
|
||||
num_rows,
|
||||
} => serialize_optional_index(non_null_row_ids.as_ref(), num_rows, &mut output)?,
|
||||
}) => serialize_optional_index(non_null_row_ids.as_ref(), num_rows, &mut output)?,
|
||||
SerializableColumnIndex::Multivalued(multivalued_index) => {
|
||||
serialize_multivalued_index(&*multivalued_index, &mut output)?
|
||||
serialize_multivalued_index(&multivalued_index, &mut output)?
|
||||
}
|
||||
}
|
||||
let column_index_num_bytes = output.written_bytes() as u32;
|
||||
Ok(column_index_num_bytes)
|
||||
}
|
||||
|
||||
pub fn open_column_index(mut bytes: OwnedBytes) -> io::Result<ColumnIndex> {
|
||||
/// Open a serialized column index.
|
||||
pub fn open_column_index(
|
||||
mut bytes: OwnedBytes,
|
||||
format_version: Version,
|
||||
) -> io::Result<ColumnIndex> {
|
||||
if bytes.is_empty() {
|
||||
return Err(io::Error::new(
|
||||
io::ErrorKind::UnexpectedEof,
|
||||
@@ -68,7 +84,8 @@ pub fn open_column_index(mut bytes: OwnedBytes) -> io::Result<ColumnIndex> {
|
||||
Ok(ColumnIndex::Optional(optional_index))
|
||||
}
|
||||
Cardinality::Multivalued => {
|
||||
let multivalue_index = super::multivalued_index::open_multivalued_index(bytes)?;
|
||||
let multivalue_index =
|
||||
super::multivalued_index::open_multivalued_index(bytes, format_version)?;
|
||||
Ok(ColumnIndex::Multivalued(multivalue_index))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -34,6 +34,7 @@ fn compute_stats(vals: impl Iterator<Item = u64>) -> ColumnStats {
|
||||
fn value_iter() -> impl Iterator<Item = u64> {
|
||||
0..20_000
|
||||
}
|
||||
|
||||
fn get_reader_for_bench<Codec: ColumnCodec>(data: &[u64]) -> Codec::ColumnValues {
|
||||
let mut bytes = Vec::new();
|
||||
let stats = compute_stats(data.iter().cloned());
|
||||
@@ -41,10 +42,13 @@ fn get_reader_for_bench<Codec: ColumnCodec>(data: &[u64]) -> Codec::ColumnValues
|
||||
for val in data {
|
||||
codec_serializer.collect(*val);
|
||||
}
|
||||
codec_serializer.serialize(&stats, Box::new(data.iter().copied()).as_mut(), &mut bytes);
|
||||
codec_serializer
|
||||
.serialize(&stats, Box::new(data.iter().copied()).as_mut(), &mut bytes)
|
||||
.unwrap();
|
||||
|
||||
Codec::load(OwnedBytes::new(bytes)).unwrap()
|
||||
}
|
||||
|
||||
fn bench_get<Codec: ColumnCodec>(b: &mut Bencher, data: &[u64]) {
|
||||
let col = get_reader_for_bench::<Codec>(data);
|
||||
b.iter(|| {
|
||||
|
||||
@@ -10,7 +10,7 @@ pub(crate) struct MergedColumnValues<'a, T> {
|
||||
pub(crate) merge_row_order: &'a MergeRowOrder,
|
||||
}
|
||||
|
||||
impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T> {
|
||||
impl<T: Copy + PartialOrd + Debug + 'static> Iterable<T> for MergedColumnValues<'_, T> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
|
||||
match self.merge_row_order {
|
||||
MergeRowOrder::Stack(_) => Box::new(
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
//! # `fastfield_codecs`
|
||||
//!
|
||||
//! - Columnar storage of data for tantivy [`Column`].
|
||||
//! - Columnar storage of data for tantivy [`crate::Column`].
|
||||
//! - Encode data in different codecs.
|
||||
//! - Monotonically map values to u64/u128
|
||||
|
||||
@@ -10,6 +10,7 @@ use std::fmt::Debug;
|
||||
use std::ops::{Range, RangeInclusive};
|
||||
use std::sync::Arc;
|
||||
|
||||
use downcast_rs::DowncastSync;
|
||||
pub use monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
|
||||
pub use monotonic_mapping_u128::MonotonicallyMappableToU128;
|
||||
|
||||
@@ -25,7 +26,10 @@ mod monotonic_column;
|
||||
|
||||
pub(crate) use merge::MergedColumnValues;
|
||||
pub use stats::ColumnStats;
|
||||
pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
|
||||
pub use u128_based::{
|
||||
open_u128_as_compact_u64, open_u128_mapped, serialize_column_values_u128,
|
||||
CompactSpaceU64Accessor,
|
||||
};
|
||||
pub use u64_based::{
|
||||
load_u64_based_column_values, serialize_and_load_u64_based_column_values,
|
||||
serialize_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
|
||||
@@ -41,7 +45,7 @@ use crate::RowId;
|
||||
///
|
||||
/// Any methods with a default and specialized implementation need to be called in the
|
||||
/// wrappers that implement the trait: Arc and MonotonicMappingColumn
|
||||
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
|
||||
/// Return the value associated with the given idx.
|
||||
///
|
||||
/// This accessor should return as fast as possible.
|
||||
@@ -68,11 +72,40 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
out_x4[3] = self.get_val(idx_x4[3]);
|
||||
}
|
||||
|
||||
let step_size = 4;
|
||||
let cutoff = indexes.len() - indexes.len() % step_size;
|
||||
let out_and_idx_chunks = output
|
||||
.chunks_exact_mut(4)
|
||||
.into_remainder()
|
||||
.iter_mut()
|
||||
.zip(indexes.chunks_exact(4).remainder());
|
||||
for (out, idx) in out_and_idx_chunks {
|
||||
*out = self.get_val(*idx);
|
||||
}
|
||||
}
|
||||
|
||||
for idx in cutoff..indexes.len() {
|
||||
output[idx] = self.get_val(indexes[idx]);
|
||||
/// Allows to push down multiple fetch calls, to avoid dynamic dispatch overhead.
|
||||
/// The slightly weird `Option<T>` in output allows pushdown to full columns.
|
||||
///
|
||||
/// idx and output should have the same length
|
||||
///
|
||||
/// # Panics
|
||||
///
|
||||
/// May panic if `idx` is greater than the column length.
|
||||
fn get_vals_opt(&self, indexes: &[u32], output: &mut [Option<T>]) {
|
||||
assert!(indexes.len() == output.len());
|
||||
let out_and_idx_chunks = output.chunks_exact_mut(4).zip(indexes.chunks_exact(4));
|
||||
for (out_x4, idx_x4) in out_and_idx_chunks {
|
||||
out_x4[0] = Some(self.get_val(idx_x4[0]));
|
||||
out_x4[1] = Some(self.get_val(idx_x4[1]));
|
||||
out_x4[2] = Some(self.get_val(idx_x4[2]));
|
||||
out_x4[3] = Some(self.get_val(idx_x4[3]));
|
||||
}
|
||||
let out_and_idx_chunks = output
|
||||
.chunks_exact_mut(4)
|
||||
.into_remainder()
|
||||
.iter_mut()
|
||||
.zip(indexes.chunks_exact(4).remainder());
|
||||
for (out, idx) in out_and_idx_chunks {
|
||||
*out = Some(self.get_val(*idx));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -101,7 +134,7 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
row_id_hits: &mut Vec<RowId>,
|
||||
) {
|
||||
let row_id_range = row_id_range.start..row_id_range.end.min(self.num_vals());
|
||||
for idx in row_id_range.start..row_id_range.end {
|
||||
for idx in row_id_range {
|
||||
let val = self.get_val(idx);
|
||||
if value_range.contains(&val) {
|
||||
row_id_hits.push(idx);
|
||||
@@ -139,6 +172,7 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
|
||||
}
|
||||
}
|
||||
downcast_rs::impl_downcast!(sync ColumnValues<T> where T: PartialOrd);
|
||||
|
||||
/// Empty column of values.
|
||||
pub struct EmptyColumnValues;
|
||||
@@ -161,12 +195,17 @@ impl<T: PartialOrd + Default> ColumnValues<T> for EmptyColumnValues {
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
|
||||
impl<T: Copy + PartialOrd + Debug + 'static> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
|
||||
#[inline(always)]
|
||||
fn get_val(&self, idx: u32) -> T {
|
||||
self.as_ref().get_val(idx)
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn get_vals_opt(&self, indexes: &[u32], output: &mut [Option<T>]) {
|
||||
self.as_ref().get_vals_opt(indexes, output)
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn min_value(&self) -> T {
|
||||
self.as_ref().min_value()
|
||||
|
||||
@@ -31,10 +31,10 @@ pub fn monotonic_map_column<C, T, Input, Output>(
|
||||
monotonic_mapping: T,
|
||||
) -> impl ColumnValues<Output>
|
||||
where
|
||||
C: ColumnValues<Input>,
|
||||
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
|
||||
Input: PartialOrd + Debug + Send + Sync + Clone,
|
||||
Output: PartialOrd + Debug + Send + Sync + Clone,
|
||||
C: ColumnValues<Input> + 'static,
|
||||
T: StrictlyMonotonicFn<Input, Output> + Send + Sync + 'static,
|
||||
Input: PartialOrd + Debug + Send + Sync + Clone + 'static,
|
||||
Output: PartialOrd + Debug + Send + Sync + Clone + 'static,
|
||||
{
|
||||
MonotonicMappingColumn {
|
||||
from_column,
|
||||
@@ -45,10 +45,10 @@ where
|
||||
|
||||
impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
|
||||
where
|
||||
C: ColumnValues<Input>,
|
||||
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
|
||||
Input: PartialOrd + Send + Debug + Sync + Clone,
|
||||
Output: PartialOrd + Send + Debug + Sync + Clone,
|
||||
C: ColumnValues<Input> + 'static,
|
||||
T: StrictlyMonotonicFn<Input, Output> + Send + Sync + 'static,
|
||||
Input: PartialOrd + Send + Debug + Sync + Clone + 'static,
|
||||
Output: PartialOrd + Send + Debug + Sync + Clone + 'static,
|
||||
{
|
||||
#[inline(always)]
|
||||
fn get_val(&self, idx: u32) -> Output {
|
||||
@@ -107,7 +107,7 @@ mod tests {
|
||||
#[test]
|
||||
fn test_monotonic_mapping_iter() {
|
||||
let vals: Vec<u64> = (0..100u64).map(|el| el * 10).collect();
|
||||
let col = VecColumn::from(&vals);
|
||||
let col = VecColumn::from(vals);
|
||||
let mapped = monotonic_map_column(
|
||||
col,
|
||||
StrictlyMonotonicMappingInverter::from(StrictlyMonotonicMappingToInternal::<i64>::new()),
|
||||
|
||||
@@ -38,6 +38,6 @@ impl Ord for BlankRange {
|
||||
}
|
||||
impl PartialOrd for BlankRange {
|
||||
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
|
||||
Some(self.blank_size().cmp(&other.blank_size()))
|
||||
Some(self.cmp(other))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -184,7 +184,7 @@ impl CompactSpaceBuilder {
|
||||
|
||||
let mut covered_space = Vec::with_capacity(self.blanks.len());
|
||||
|
||||
// begining of the blanks
|
||||
// beginning of the blanks
|
||||
if let Some(first_blank_start) = self.blanks.first().map(RangeInclusive::start) {
|
||||
if *first_blank_start != 0 {
|
||||
covered_space.push(0..=first_blank_start - 1);
|
||||
|
||||
@@ -22,7 +22,7 @@ mod build_compact_space;
|
||||
|
||||
use build_compact_space::get_compact_space;
|
||||
use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt, VIntU128};
|
||||
use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
|
||||
use tantivy_bitpacker::{BitPacker, BitUnpacker};
|
||||
|
||||
use crate::column_values::ColumnValues;
|
||||
use crate::RowId;
|
||||
@@ -148,7 +148,7 @@ impl CompactSpace {
|
||||
.binary_search_by_key(&compact, |range_mapping| range_mapping.compact_start)
|
||||
// Correctness: Overflow. The first range starts at compact space 0, the error from
|
||||
// binary search can never be 0
|
||||
.map_or_else(|e| e - 1, |v| v);
|
||||
.unwrap_or_else(|e| e - 1);
|
||||
|
||||
let range_mapping = &self.ranges_mapping[pos];
|
||||
let diff = compact - range_mapping.compact_start;
|
||||
@@ -292,6 +292,63 @@ impl BinarySerializable for IPCodecParams {
|
||||
}
|
||||
}
|
||||
|
||||
/// Exposes the compact space compressed values as u64.
|
||||
///
|
||||
/// This allows faster access to the values, as u64 is faster to work with than u128.
|
||||
/// It also allows to handle u128 values like u64, via the `open_u64_lenient` as a uniform
|
||||
/// access interface.
|
||||
///
|
||||
/// When converting from the internal u64 to u128 `compact_to_u128` can be used.
|
||||
pub struct CompactSpaceU64Accessor(CompactSpaceDecompressor);
|
||||
impl CompactSpaceU64Accessor {
|
||||
pub(crate) fn open(data: OwnedBytes) -> io::Result<CompactSpaceU64Accessor> {
|
||||
let decompressor = CompactSpaceU64Accessor(CompactSpaceDecompressor::open(data)?);
|
||||
Ok(decompressor)
|
||||
}
|
||||
/// Convert a compact space value to u128
|
||||
pub fn compact_to_u128(&self, compact: u32) -> u128 {
|
||||
self.0.compact_to_u128(compact)
|
||||
}
|
||||
}
|
||||
|
||||
impl ColumnValues<u64> for CompactSpaceU64Accessor {
|
||||
#[inline]
|
||||
fn get_val(&self, doc: u32) -> u64 {
|
||||
let compact = self.0.get_compact(doc);
|
||||
compact as u64
|
||||
}
|
||||
|
||||
fn min_value(&self) -> u64 {
|
||||
self.0.u128_to_compact(self.0.min_value()).unwrap() as u64
|
||||
}
|
||||
|
||||
fn max_value(&self) -> u64 {
|
||||
self.0.u128_to_compact(self.0.max_value()).unwrap() as u64
|
||||
}
|
||||
|
||||
fn num_vals(&self) -> u32 {
|
||||
self.0.params.num_vals
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
|
||||
Box::new(self.0.iter_compact().map(|el| el as u64))
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn get_row_ids_for_value_range(
|
||||
&self,
|
||||
value_range: RangeInclusive<u64>,
|
||||
position_range: Range<u32>,
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
let value_range = self.0.compact_to_u128(*value_range.start() as u32)
|
||||
..=self.0.compact_to_u128(*value_range.end() as u32);
|
||||
self.0
|
||||
.get_row_ids_for_value_range(value_range, position_range, positions)
|
||||
}
|
||||
}
|
||||
|
||||
impl ColumnValues<u128> for CompactSpaceDecompressor {
|
||||
#[inline]
|
||||
fn get_val(&self, doc: u32) -> u128 {
|
||||
@@ -402,9 +459,14 @@ impl CompactSpaceDecompressor {
|
||||
.map(|compact| self.compact_to_u128(compact))
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn get_compact(&self, idx: u32) -> u32 {
|
||||
self.params.bit_unpacker.get(idx, &self.data) as u32
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn get(&self, idx: u32) -> u128 {
|
||||
let compact = self.params.bit_unpacker.get(idx, &self.data) as u32;
|
||||
let compact = self.get_compact(idx);
|
||||
self.compact_to_u128(compact)
|
||||
}
|
||||
|
||||
|
||||
@@ -6,7 +6,9 @@ use std::sync::Arc;
|
||||
mod compact_space;
|
||||
|
||||
use common::{BinarySerializable, OwnedBytes, VInt};
|
||||
use compact_space::{CompactSpaceCompressor, CompactSpaceDecompressor};
|
||||
pub use compact_space::{
|
||||
CompactSpaceCompressor, CompactSpaceDecompressor, CompactSpaceU64Accessor,
|
||||
};
|
||||
|
||||
use crate::column_values::monotonic_map_column;
|
||||
use crate::column_values::monotonic_mapping::{
|
||||
@@ -108,8 +110,25 @@ pub fn open_u128_mapped<T: MonotonicallyMappableToU128 + Debug>(
|
||||
StrictlyMonotonicMappingToInternal::<T>::new().into();
|
||||
Ok(Arc::new(monotonic_map_column(reader, inverted)))
|
||||
}
|
||||
|
||||
/// Returns the u64 representation of the u128 data.
|
||||
/// The internal representation of the data as u64 is useful for faster processing.
|
||||
///
|
||||
/// In order to convert to u128 back cast to `CompactSpaceU64Accessor` and call
|
||||
/// `compact_to_u128`.
|
||||
///
|
||||
/// # Notice
|
||||
/// In case there are new codecs added, check for usages of `CompactSpaceDecompressorU64` and
|
||||
/// also handle the new codecs.
|
||||
pub fn open_u128_as_compact_u64(mut bytes: OwnedBytes) -> io::Result<Arc<dyn ColumnValues<u64>>> {
|
||||
let header = U128Header::deserialize(&mut bytes)?;
|
||||
assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
|
||||
let reader = CompactSpaceU64Accessor::open(bytes)?;
|
||||
Ok(Arc::new(reader))
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
pub mod tests {
|
||||
pub(crate) mod tests {
|
||||
use super::*;
|
||||
use crate::column_values::u64_based::{
|
||||
serialize_and_load_u64_based_column_values, serialize_u64_based_column_values,
|
||||
|
||||
@@ -63,7 +63,6 @@ impl ColumnValues for BitpackedReader {
|
||||
fn get_val(&self, doc: u32) -> u64 {
|
||||
self.stats.min_value + self.stats.gcd.get() * self.bit_unpacker.get(doc, &self.data)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn min_value(&self) -> u64 {
|
||||
self.stats.min_value
|
||||
@@ -83,7 +82,8 @@ impl ColumnValues for BitpackedReader {
|
||||
doc_id_range: Range<u32>,
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
let Some(transformed_range) = transform_range_before_linear_transformation(&self.stats, range)
|
||||
let Some(transformed_range) =
|
||||
transform_range_before_linear_transformation(&self.stats, range)
|
||||
else {
|
||||
positions.clear();
|
||||
return;
|
||||
|
||||
@@ -39,7 +39,7 @@ impl BinarySerializable for Block {
|
||||
}
|
||||
|
||||
fn compute_num_blocks(num_vals: u32) -> u32 {
|
||||
(num_vals + BLOCK_SIZE - 1) / BLOCK_SIZE
|
||||
num_vals.div_ceil(BLOCK_SIZE)
|
||||
}
|
||||
|
||||
pub struct BlockwiseLinearEstimator {
|
||||
@@ -63,7 +63,10 @@ impl BlockwiseLinearEstimator {
|
||||
if self.block.is_empty() {
|
||||
return;
|
||||
}
|
||||
let line = Line::train(&VecColumn::from(&self.block));
|
||||
let column = VecColumn::from(std::mem::take(&mut self.block));
|
||||
let line = Line::train(&column);
|
||||
self.block = column.into();
|
||||
|
||||
let mut max_value = 0u64;
|
||||
for (i, buffer_val) in self.block.iter().enumerate() {
|
||||
let interpolated_val = line.eval(i as u32);
|
||||
@@ -125,7 +128,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
|
||||
*buffer_val = gcd_divider.divide(*buffer_val - stats.min_value);
|
||||
}
|
||||
|
||||
let line = Line::train(&VecColumn::from(&buffer));
|
||||
let line = Line::train(&VecColumn::from(buffer.to_vec()));
|
||||
|
||||
assert!(!buffer.is_empty());
|
||||
|
||||
|
||||
@@ -122,12 +122,11 @@ impl Line {
|
||||
line
|
||||
}
|
||||
|
||||
/// Returns a line that attemps to approximate a function
|
||||
/// Returns a line that attempts to approximate a function
|
||||
/// f: i in 0..[ys.num_vals()) -> ys[i].
|
||||
///
|
||||
/// - The approximation is always lower than the actual value.
|
||||
/// Or more rigorously, formally `f(i).wrapping_sub(ys[i])` is small
|
||||
/// for any i in [0..ys.len()).
|
||||
/// - The approximation is always lower than the actual value. Or more rigorously, formally
|
||||
/// `f(i).wrapping_sub(ys[i])` is small for any i in [0..ys.len()).
|
||||
/// - It computes without panicking for any value of it.
|
||||
///
|
||||
/// This function is only invariable by translation if all of the
|
||||
@@ -184,7 +183,7 @@ mod tests {
|
||||
}
|
||||
|
||||
fn test_eval_max_err(ys: &[u64]) -> Option<u64> {
|
||||
let line = Line::train(&VecColumn::from(&ys));
|
||||
let line = Line::train(&VecColumn::from(ys.to_vec()));
|
||||
ys.iter()
|
||||
.enumerate()
|
||||
.map(|(x, y)| y.wrapping_sub(line.eval(x as u32)))
|
||||
|
||||
@@ -173,7 +173,9 @@ impl LinearCodecEstimator {
|
||||
fn collect_before_line_estimation(&mut self, value: u64) {
|
||||
self.block.push(value);
|
||||
if self.block.len() == LINE_ESTIMATION_BLOCK_LEN {
|
||||
let line = Line::train(&VecColumn::from(&self.block));
|
||||
let column = VecColumn::from(std::mem::take(&mut self.block));
|
||||
let line = Line::train(&column);
|
||||
self.block = column.into();
|
||||
let block = std::mem::take(&mut self.block);
|
||||
for val in block {
|
||||
self.collect_after_line_estimation(&line, val);
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
use proptest::prelude::*;
|
||||
use proptest::strategy::Strategy;
|
||||
use proptest::{prop_oneof, proptest};
|
||||
|
||||
#[test]
|
||||
|
||||
@@ -4,14 +4,14 @@ use tantivy_bitpacker::minmax;
|
||||
|
||||
use crate::ColumnValues;
|
||||
|
||||
/// VecColumn provides `Column` over a slice.
|
||||
pub struct VecColumn<'a, T = u64> {
|
||||
pub(crate) values: &'a [T],
|
||||
/// VecColumn provides `Column` over a `Vec<T>`.
|
||||
pub struct VecColumn<T = u64> {
|
||||
pub(crate) values: Vec<T>,
|
||||
pub(crate) min_value: T,
|
||||
pub(crate) max_value: T,
|
||||
}
|
||||
|
||||
impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
|
||||
impl<T: Copy + PartialOrd + Send + Sync + Debug + 'static> ColumnValues<T> for VecColumn<T> {
|
||||
fn get_val(&self, position: u32) -> T {
|
||||
self.values[position as usize]
|
||||
}
|
||||
@@ -37,11 +37,8 @@ impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColu
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
|
||||
where V: AsRef<[T]> + ?Sized
|
||||
{
|
||||
fn from(values: &'a V) -> Self {
|
||||
let values = values.as_ref();
|
||||
impl<T: Copy + PartialOrd + Default> From<Vec<T>> for VecColumn<T> {
|
||||
fn from(values: Vec<T>) -> Self {
|
||||
let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
|
||||
Self {
|
||||
values,
|
||||
@@ -50,3 +47,8 @@ where V: AsRef<[T]> + ?Sized
|
||||
}
|
||||
}
|
||||
}
|
||||
impl From<VecColumn> for Vec<u64> {
|
||||
fn from(column: VecColumn) -> Self {
|
||||
column.values
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,3 +1,6 @@
|
||||
use core::fmt;
|
||||
use std::fmt::{Display, Formatter};
|
||||
|
||||
use crate::InvalidData;
|
||||
|
||||
pub const VERSION_FOOTER_NUM_BYTES: usize = MAGIC_BYTES.len() + std::mem::size_of::<u32>();
|
||||
@@ -8,7 +11,7 @@ const MAGIC_BYTES: [u8; 4] = [2, 113, 119, 66];
|
||||
|
||||
pub fn footer() -> [u8; VERSION_FOOTER_NUM_BYTES] {
|
||||
let mut footer_bytes = [0u8; VERSION_FOOTER_NUM_BYTES];
|
||||
footer_bytes[0..4].copy_from_slice(&Version::V1.to_bytes());
|
||||
footer_bytes[0..4].copy_from_slice(&CURRENT_VERSION.to_bytes());
|
||||
footer_bytes[4..8].copy_from_slice(&MAGIC_BYTES[..]);
|
||||
footer_bytes
|
||||
}
|
||||
@@ -20,10 +23,22 @@ pub fn parse_footer(footer_bytes: [u8; VERSION_FOOTER_NUM_BYTES]) -> Result<Vers
|
||||
Version::try_from_bytes(footer_bytes[0..4].try_into().unwrap())
|
||||
}
|
||||
|
||||
pub const CURRENT_VERSION: Version = Version::V2;
|
||||
|
||||
#[derive(Debug, Copy, Clone, Eq, PartialEq)]
|
||||
#[repr(u32)]
|
||||
pub enum Version {
|
||||
V1 = 1u32,
|
||||
V2 = 2u32,
|
||||
}
|
||||
|
||||
impl Display for Version {
|
||||
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
|
||||
match self {
|
||||
Version::V1 => write!(f, "v1"),
|
||||
Version::V2 => write!(f, "v2"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Version {
|
||||
@@ -35,6 +50,7 @@ impl Version {
|
||||
let code = u32::from_le_bytes(bytes);
|
||||
match code {
|
||||
1u32 => Ok(Version::V1),
|
||||
2u32 => Ok(Version::V2),
|
||||
_ => Err(InvalidData),
|
||||
}
|
||||
}
|
||||
@@ -47,9 +63,9 @@ mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_footer_dserialization() {
|
||||
fn test_footer_deserialization() {
|
||||
let parsed_version: Version = parse_footer(footer()).unwrap();
|
||||
assert_eq!(Version::V1, parsed_version);
|
||||
assert_eq!(Version::V2, parsed_version);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -63,11 +79,10 @@ mod tests {
|
||||
for &i in &version_to_tests {
|
||||
let version_res = Version::try_from_bytes(i.to_le_bytes());
|
||||
if let Ok(version) = version_res {
|
||||
assert_eq!(version, Version::V1);
|
||||
assert_eq!(version.to_bytes(), i.to_le_bytes());
|
||||
valid_versions.insert(i);
|
||||
}
|
||||
}
|
||||
assert_eq!(valid_versions.len(), 1);
|
||||
assert_eq!(valid_versions.len(), 2);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -3,7 +3,7 @@ use std::io::{self, Write};
|
||||
use common::{BitSet, CountingWriter, ReadOnlyBitSet};
|
||||
use sstable::{SSTable, Streamer, TermOrdinal, VoidSSTable};
|
||||
|
||||
use super::term_merger::TermMerger;
|
||||
use super::term_merger::{TermMerger, TermsWithSegmentOrd};
|
||||
use crate::column::serialize_column_mappable_to_u64;
|
||||
use crate::column_index::SerializableColumnIndex;
|
||||
use crate::iterable::Iterable;
|
||||
@@ -39,7 +39,7 @@ struct RemappedTermOrdinalsValues<'a> {
|
||||
merge_row_order: &'a MergeRowOrder,
|
||||
}
|
||||
|
||||
impl<'a> Iterable for RemappedTermOrdinalsValues<'a> {
|
||||
impl Iterable for RemappedTermOrdinalsValues<'_> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
|
||||
match self.merge_row_order {
|
||||
MergeRowOrder::Stack(_) => self.boxed_iter_stacked(),
|
||||
@@ -50,7 +50,7 @@ impl<'a> Iterable for RemappedTermOrdinalsValues<'a> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> RemappedTermOrdinalsValues<'a> {
|
||||
impl RemappedTermOrdinalsValues<'_> {
|
||||
fn boxed_iter_stacked(&self) -> Box<dyn Iterator<Item = u64> + '_> {
|
||||
let iter = self
|
||||
.bytes_columns
|
||||
@@ -126,14 +126,17 @@ fn serialize_merged_dict(
|
||||
let mut term_ord_mapping = TermOrdinalMapping::default();
|
||||
|
||||
let mut field_term_streams = Vec::new();
|
||||
for column_opt in bytes_columns.iter() {
|
||||
for (segment_ord, column_opt) in bytes_columns.iter().enumerate() {
|
||||
if let Some(column) = column_opt {
|
||||
term_ord_mapping.add_segment(column.dictionary.num_terms());
|
||||
let terms: Streamer<VoidSSTable> = column.dictionary.stream()?;
|
||||
field_term_streams.push(terms);
|
||||
field_term_streams.push(TermsWithSegmentOrd { terms, segment_ord });
|
||||
} else {
|
||||
term_ord_mapping.add_segment(0);
|
||||
field_term_streams.push(Streamer::empty());
|
||||
field_term_streams.push(TermsWithSegmentOrd {
|
||||
terms: Streamer::empty(),
|
||||
segment_ord,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
@@ -191,6 +194,7 @@ fn serialize_merged_dict(
|
||||
|
||||
#[derive(Default, Debug)]
|
||||
struct TermOrdinalMapping {
|
||||
/// Contains the new term ordinals for each segment.
|
||||
per_segment_new_term_ordinals: Vec<Vec<TermOrdinal>>,
|
||||
}
|
||||
|
||||
@@ -205,6 +209,6 @@ impl TermOrdinalMapping {
|
||||
}
|
||||
|
||||
fn get_segment(&self, segment_ord: u32) -> &[TermOrdinal] {
|
||||
&(self.per_segment_new_term_ordinals[segment_ord as usize])[..]
|
||||
&self.per_segment_new_term_ordinals[segment_ord as usize]
|
||||
}
|
||||
}
|
||||
|
||||
@@ -26,7 +26,7 @@ impl StackMergeOrder {
|
||||
let mut cumulated_row_ids: Vec<RowId> = Vec::with_capacity(columnars.len());
|
||||
let mut cumulated_row_id = 0;
|
||||
for columnar in columnars {
|
||||
cumulated_row_id += columnar.num_rows();
|
||||
cumulated_row_id += columnar.num_docs();
|
||||
cumulated_row_ids.push(cumulated_row_id);
|
||||
}
|
||||
StackMergeOrder { cumulated_row_ids }
|
||||
@@ -52,8 +52,8 @@ pub enum MergeRowOrder {
|
||||
/// Columnar tables are simply stacked one above the other.
|
||||
/// If the i-th columnar_readers has n_rows_i rows, then
|
||||
/// in the resulting columnar,
|
||||
/// rows [r0..n_row_0) contains the row of columnar_readers[0], in ordder
|
||||
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of columnar_readers[1], in order.
|
||||
/// rows [r0..n_row_0) contains the row of `columnar_readers[0]`, in ordder
|
||||
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of `columnar_readers[1]`, in order.
|
||||
/// ..
|
||||
/// No documents is deleted.
|
||||
Stack(StackMergeOrder),
|
||||
|
||||
@@ -2,12 +2,11 @@ mod merge_dict_column;
|
||||
mod merge_mapping;
|
||||
mod term_merger;
|
||||
|
||||
use std::collections::{BTreeMap, HashMap, HashSet};
|
||||
use std::collections::{BTreeMap, HashSet};
|
||||
use std::io;
|
||||
use std::net::Ipv6Addr;
|
||||
use std::sync::Arc;
|
||||
|
||||
use itertools::Itertools;
|
||||
pub use merge_mapping::{MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};
|
||||
|
||||
use super::writer::ColumnarSerializer;
|
||||
@@ -18,24 +17,27 @@ use crate::columnar::writer::CompatibleNumericalTypes;
|
||||
use crate::columnar::ColumnarReader;
|
||||
use crate::dynamic_column::DynamicColumn;
|
||||
use crate::{
|
||||
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, NumericalType, NumericalValue,
|
||||
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, DynamicColumnHandle, NumericalType,
|
||||
NumericalValue,
|
||||
};
|
||||
|
||||
/// Column types are grouped into different categories.
|
||||
/// After merge, all columns belonging to the same category are coerced to
|
||||
/// the same column type.
|
||||
///
|
||||
/// In practise, today, only Numerical colummns are coerced into one type today.
|
||||
/// In practise, today, only Numerical columns are coerced into one type today.
|
||||
///
|
||||
/// See also [README.md].
|
||||
#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug)]
|
||||
///
|
||||
/// The ordering has to match the ordering of the variants in [ColumnType].
|
||||
#[derive(Copy, Clone, Eq, PartialOrd, Ord, PartialEq, Hash, Debug)]
|
||||
pub(crate) enum ColumnTypeCategory {
|
||||
Bool,
|
||||
Str,
|
||||
Numerical,
|
||||
DateTime,
|
||||
Bytes,
|
||||
Str,
|
||||
Bool,
|
||||
IpAddr,
|
||||
DateTime,
|
||||
}
|
||||
|
||||
impl From<ColumnType> for ColumnTypeCategory {
|
||||
@@ -61,11 +63,10 @@ impl From<ColumnType> for ColumnTypeCategory {
|
||||
/// `require_columns` makes it possible to ensure that some columns will be present in the
|
||||
/// resulting columnar. When a required column is a numerical column type, one of two things can
|
||||
/// happen:
|
||||
/// - If the required column type is compatible with all of the input columnar, the resulsting
|
||||
/// merged
|
||||
/// columnar will simply coerce the input column and use the required column type.
|
||||
/// - If the required column type is incompatible with one of the input columnar, the merged
|
||||
/// will fail with an InvalidData error.
|
||||
/// - If the required column type is compatible with all of the input columnar, the resulting merged
|
||||
/// columnar will simply coerce the input column and use the required column type.
|
||||
/// - If the required column type is incompatible with one of the input columnar, the merged will
|
||||
/// fail with an InvalidData error.
|
||||
///
|
||||
/// `merge_row_order` makes it possible to remove or reorder row in the resulting
|
||||
/// `Columnar` table.
|
||||
@@ -79,24 +80,38 @@ pub fn merge_columnar(
|
||||
output: &mut impl io::Write,
|
||||
) -> io::Result<()> {
|
||||
let mut serializer = ColumnarSerializer::new(output);
|
||||
let num_rows_per_columnar = columnar_readers
|
||||
let num_docs_per_columnar = columnar_readers
|
||||
.iter()
|
||||
.map(|reader| reader.num_rows())
|
||||
.map(|reader| reader.num_docs())
|
||||
.collect::<Vec<u32>>();
|
||||
let columns_to_merge =
|
||||
group_columns_for_merge(columnar_readers, required_columns, &merge_row_order)?;
|
||||
for ((column_name, column_type), columns) in columns_to_merge {
|
||||
|
||||
let columns_to_merge = group_columns_for_merge(columnar_readers, required_columns)?;
|
||||
for res in columns_to_merge {
|
||||
let ((column_name, _column_type_category), grouped_columns) = res;
|
||||
let grouped_columns = grouped_columns.open(&merge_row_order)?;
|
||||
if grouped_columns.is_empty() {
|
||||
continue;
|
||||
}
|
||||
|
||||
let column_type_after_merge = grouped_columns.column_type_after_merge();
|
||||
let mut columns = grouped_columns.columns;
|
||||
// Make sure the number of columns is the same as the number of columnar readers.
|
||||
// Or num_docs_per_columnar would be incorrect.
|
||||
assert_eq!(columns.len(), columnar_readers.len());
|
||||
coerce_columns(column_type_after_merge, &mut columns)?;
|
||||
|
||||
let mut column_serializer =
|
||||
serializer.start_serialize_column(column_name.as_bytes(), column_type);
|
||||
serializer.start_serialize_column(column_name.as_bytes(), column_type_after_merge);
|
||||
merge_column(
|
||||
column_type,
|
||||
&num_rows_per_columnar,
|
||||
column_type_after_merge,
|
||||
&num_docs_per_columnar,
|
||||
columns,
|
||||
&merge_row_order,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
|
||||
serializer.finalize(merge_row_order.num_rows())?;
|
||||
Ok(())
|
||||
}
|
||||
@@ -115,7 +130,7 @@ fn dynamic_column_to_u64_monotonic(dynamic_column: DynamicColumn) -> Option<Colu
|
||||
fn merge_column(
|
||||
column_type: ColumnType,
|
||||
num_docs_per_column: &[u32],
|
||||
columns: Vec<Option<DynamicColumn>>,
|
||||
columns_to_merge: Vec<Option<DynamicColumn>>,
|
||||
merge_row_order: &MergeRowOrder,
|
||||
wrt: &mut impl io::Write,
|
||||
) -> io::Result<()> {
|
||||
@@ -125,10 +140,10 @@ fn merge_column(
|
||||
| ColumnType::F64
|
||||
| ColumnType::DateTime
|
||||
| ColumnType::Bool => {
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns.len());
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns_to_merge.len());
|
||||
let mut column_values: Vec<Option<Arc<dyn ColumnValues>>> =
|
||||
Vec::with_capacity(columns.len());
|
||||
for (i, dynamic_column_opt) in columns.into_iter().enumerate() {
|
||||
Vec::with_capacity(columns_to_merge.len());
|
||||
for (i, dynamic_column_opt) in columns_to_merge.into_iter().enumerate() {
|
||||
if let Some(Column { index: idx, values }) =
|
||||
dynamic_column_opt.and_then(dynamic_column_to_u64_monotonic)
|
||||
{
|
||||
@@ -151,10 +166,10 @@ fn merge_column(
|
||||
serialize_column_mappable_to_u64(merged_column_index, &merge_column_values, wrt)?;
|
||||
}
|
||||
ColumnType::IpAddr => {
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns.len());
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns_to_merge.len());
|
||||
let mut column_values: Vec<Option<Arc<dyn ColumnValues<Ipv6Addr>>>> =
|
||||
Vec::with_capacity(columns.len());
|
||||
for (i, dynamic_column_opt) in columns.into_iter().enumerate() {
|
||||
Vec::with_capacity(columns_to_merge.len());
|
||||
for (i, dynamic_column_opt) in columns_to_merge.into_iter().enumerate() {
|
||||
if let Some(DynamicColumn::IpAddr(Column { index: idx, values })) =
|
||||
dynamic_column_opt
|
||||
{
|
||||
@@ -179,9 +194,10 @@ fn merge_column(
|
||||
serialize_column_mappable_to_u128(merged_column_index, &merge_column_values, wrt)?;
|
||||
}
|
||||
ColumnType::Bytes | ColumnType::Str => {
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns.len());
|
||||
let mut bytes_columns: Vec<Option<BytesColumn>> = Vec::with_capacity(columns.len());
|
||||
for (i, dynamic_column_opt) in columns.into_iter().enumerate() {
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns_to_merge.len());
|
||||
let mut bytes_columns: Vec<Option<BytesColumn>> =
|
||||
Vec::with_capacity(columns_to_merge.len());
|
||||
for (i, dynamic_column_opt) in columns_to_merge.into_iter().enumerate() {
|
||||
match dynamic_column_opt {
|
||||
Some(DynamicColumn::Str(str_column)) => {
|
||||
column_indexes.push(str_column.term_ord_column.index.clone());
|
||||
@@ -210,20 +226,80 @@ fn merge_column(
|
||||
struct GroupedColumns {
|
||||
required_column_type: Option<ColumnType>,
|
||||
columns: Vec<Option<DynamicColumn>>,
|
||||
column_category: ColumnTypeCategory,
|
||||
}
|
||||
|
||||
impl GroupedColumns {
|
||||
fn for_category(column_category: ColumnTypeCategory, num_columnars: usize) -> Self {
|
||||
GroupedColumns {
|
||||
/// Check is column group can be skipped during serialization.
|
||||
fn is_empty(&self) -> bool {
|
||||
self.required_column_type.is_none() && self.columns.iter().all(Option::is_none)
|
||||
}
|
||||
|
||||
/// Returns the column type after merge.
|
||||
///
|
||||
/// This method does not check if the column types can actually be coerced to
|
||||
/// this type.
|
||||
fn column_type_after_merge(&self) -> ColumnType {
|
||||
if let Some(required_type) = self.required_column_type {
|
||||
return required_type;
|
||||
}
|
||||
let column_type: HashSet<ColumnType> = self
|
||||
.columns
|
||||
.iter()
|
||||
.flatten()
|
||||
.map(|column| column.column_type())
|
||||
.collect();
|
||||
if column_type.len() == 1 {
|
||||
return column_type.into_iter().next().unwrap();
|
||||
}
|
||||
// At the moment, only the numerical column type category has more than one possible
|
||||
// column type.
|
||||
assert!(self
|
||||
.columns
|
||||
.iter()
|
||||
.flatten()
|
||||
.all(|el| ColumnTypeCategory::from(el.column_type()) == ColumnTypeCategory::Numerical));
|
||||
merged_numerical_columns_type(self.columns.iter().flatten()).into()
|
||||
}
|
||||
}
|
||||
|
||||
struct GroupedColumnsHandle {
|
||||
required_column_type: Option<ColumnType>,
|
||||
columns: Vec<Option<DynamicColumnHandle>>,
|
||||
}
|
||||
|
||||
impl GroupedColumnsHandle {
|
||||
fn new(num_columnars: usize) -> Self {
|
||||
GroupedColumnsHandle {
|
||||
required_column_type: None,
|
||||
columns: vec![None; num_columnars],
|
||||
column_category,
|
||||
}
|
||||
}
|
||||
fn open(self, merge_row_order: &MergeRowOrder) -> io::Result<GroupedColumns> {
|
||||
let mut columns: Vec<Option<DynamicColumn>> = Vec::new();
|
||||
for (columnar_id, column) in self.columns.iter().enumerate() {
|
||||
if let Some(column) = column {
|
||||
let column = column.open()?;
|
||||
// We skip columns that end up with 0 documents.
|
||||
// That way, we make sure they don't end up influencing the merge type or
|
||||
// creating empty columns.
|
||||
|
||||
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
|
||||
columns.push(None);
|
||||
} else {
|
||||
columns.push(Some(column));
|
||||
}
|
||||
} else {
|
||||
columns.push(None);
|
||||
}
|
||||
}
|
||||
Ok(GroupedColumns {
|
||||
required_column_type: self.required_column_type,
|
||||
columns,
|
||||
})
|
||||
}
|
||||
|
||||
/// Set the dynamic column for a given columnar.
|
||||
fn set_column(&mut self, columnar_id: usize, column: DynamicColumn) {
|
||||
fn set_column(&mut self, columnar_id: usize, column: DynamicColumnHandle) {
|
||||
self.columns[columnar_id] = Some(column);
|
||||
}
|
||||
|
||||
@@ -245,29 +321,6 @@ impl GroupedColumns {
|
||||
self.required_column_type = Some(required_type);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
/// Returns the column type after merge.
|
||||
///
|
||||
/// This method does not check if the column types can actually be coerced to
|
||||
/// this type.
|
||||
fn column_type_after_merge(&self) -> ColumnType {
|
||||
if let Some(required_type) = self.required_column_type {
|
||||
return required_type;
|
||||
}
|
||||
let column_type: HashSet<ColumnType> = self
|
||||
.columns
|
||||
.iter()
|
||||
.flatten()
|
||||
.map(|column| column.column_type())
|
||||
.collect();
|
||||
if column_type.len() == 1 {
|
||||
return column_type.into_iter().next().unwrap();
|
||||
}
|
||||
// At the moment, only the numerical categorical column type has more than one possible
|
||||
// column type.
|
||||
assert_eq!(self.column_category, ColumnTypeCategory::Numerical);
|
||||
merged_numerical_columns_type(self.columns.iter().flatten()).into()
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the type of the merged numerical column.
|
||||
@@ -293,7 +346,7 @@ fn merged_numerical_columns_type<'a>(
|
||||
fn is_empty_after_merge(
|
||||
merge_row_order: &MergeRowOrder,
|
||||
column: &DynamicColumn,
|
||||
columnar_id: usize,
|
||||
columnar_ord: usize,
|
||||
) -> bool {
|
||||
if column.num_values() == 0u32 {
|
||||
// It was empty before the merge.
|
||||
@@ -305,13 +358,13 @@ fn is_empty_after_merge(
|
||||
false
|
||||
}
|
||||
MergeRowOrder::Shuffled(shuffled) => {
|
||||
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_id] {
|
||||
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_ord] {
|
||||
let column_index = column.column_index();
|
||||
match column_index {
|
||||
ColumnIndex::Empty { .. } => true,
|
||||
ColumnIndex::Full => alive_bitset.len() == 0,
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
for doc in optional_index.iter_rows() {
|
||||
for doc in optional_index.iter_docs() {
|
||||
if alive_bitset.contains(doc) {
|
||||
return false;
|
||||
}
|
||||
@@ -319,20 +372,8 @@ fn is_empty_after_merge(
|
||||
true
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => {
|
||||
for (doc_id, (start_index, end_index)) in multivalued_index
|
||||
.start_index_column
|
||||
.iter()
|
||||
.tuple_windows()
|
||||
.enumerate()
|
||||
{
|
||||
let doc_id = doc_id as u32;
|
||||
if start_index == end_index {
|
||||
// There are no values in this document
|
||||
continue;
|
||||
}
|
||||
// The document contains values and is present in the alive bitset.
|
||||
// The column is therefore not empty.
|
||||
if alive_bitset.contains(doc_id) {
|
||||
for alive_docid in alive_bitset.iter() {
|
||||
if !multivalued_index.range(alive_docid).is_empty() {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
@@ -348,56 +389,33 @@ fn is_empty_after_merge(
|
||||
}
|
||||
}
|
||||
|
||||
#[allow(clippy::type_complexity)]
|
||||
fn group_columns_for_merge(
|
||||
columnar_readers: &[&ColumnarReader],
|
||||
required_columns: &[(String, ColumnType)],
|
||||
merge_row_order: &MergeRowOrder,
|
||||
) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
|
||||
// Each column name may have multiple types of column associated.
|
||||
// For merging we are interested in the same column type category since they can be merged.
|
||||
let mut columns_grouped: HashMap<(String, ColumnTypeCategory), GroupedColumns> = HashMap::new();
|
||||
/// Iterates over the columns of the columnar readers, grouped by column name.
|
||||
/// Key functionality is that `open` of the Columns is done lazy per group.
|
||||
fn group_columns_for_merge<'a>(
|
||||
columnar_readers: &'a [&'a ColumnarReader],
|
||||
required_columns: &'a [(String, ColumnType)],
|
||||
) -> io::Result<BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle>> {
|
||||
let mut columns: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> = BTreeMap::new();
|
||||
|
||||
for &(ref column_name, column_type) in required_columns {
|
||||
columns_grouped
|
||||
columns
|
||||
.entry((column_name.clone(), column_type.into()))
|
||||
.or_insert_with(|| {
|
||||
GroupedColumns::for_category(column_type.into(), columnar_readers.len())
|
||||
})
|
||||
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
|
||||
.require_type(column_type)?;
|
||||
}
|
||||
|
||||
for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
|
||||
let column_name_and_handle = columnar_reader.list_columns()?;
|
||||
// We skip columns that end up with 0 documents.
|
||||
// That way, we make sure they don't end up influencing the merge type or
|
||||
// creating empty columns.
|
||||
let column_name_and_handle = columnar_reader.iter_columns()?;
|
||||
|
||||
for (column_name, handle) in column_name_and_handle {
|
||||
let column_category: ColumnTypeCategory = handle.column_type().into();
|
||||
let column = handle.open()?;
|
||||
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
|
||||
continue;
|
||||
}
|
||||
columns_grouped
|
||||
columns
|
||||
.entry((column_name, column_category))
|
||||
.or_insert_with(|| {
|
||||
GroupedColumns::for_category(column_category, columnar_readers.len())
|
||||
})
|
||||
.set_column(columnar_id, column);
|
||||
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
|
||||
.set_column(columnar_id, handle);
|
||||
}
|
||||
}
|
||||
|
||||
let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
Default::default();
|
||||
|
||||
for ((column_name, _), mut grouped_columns) in columns_grouped {
|
||||
let column_type = grouped_columns.column_type_after_merge();
|
||||
coerce_columns(column_type, &mut grouped_columns.columns)?;
|
||||
merge_columns.insert((column_name, column_type), grouped_columns.columns);
|
||||
}
|
||||
|
||||
Ok(merge_columns)
|
||||
Ok(columns)
|
||||
}
|
||||
|
||||
fn coerce_columns(
|
||||
|
||||
@@ -5,28 +5,29 @@ use sstable::TermOrdinal;
|
||||
|
||||
use crate::Streamer;
|
||||
|
||||
pub struct HeapItem<'a> {
|
||||
pub streamer: Streamer<'a>,
|
||||
/// The terms of a column with the ordinal of the segment.
|
||||
pub struct TermsWithSegmentOrd<'a> {
|
||||
pub terms: Streamer<'a>,
|
||||
pub segment_ord: usize,
|
||||
}
|
||||
|
||||
impl<'a> PartialEq for HeapItem<'a> {
|
||||
impl PartialEq for TermsWithSegmentOrd<'_> {
|
||||
fn eq(&self, other: &Self) -> bool {
|
||||
self.segment_ord == other.segment_ord
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> Eq for HeapItem<'a> {}
|
||||
impl Eq for TermsWithSegmentOrd<'_> {}
|
||||
|
||||
impl<'a> PartialOrd for HeapItem<'a> {
|
||||
fn partial_cmp(&self, other: &HeapItem<'a>) -> Option<Ordering> {
|
||||
impl<'a> PartialOrd for TermsWithSegmentOrd<'a> {
|
||||
fn partial_cmp(&self, other: &TermsWithSegmentOrd<'a>) -> Option<Ordering> {
|
||||
Some(self.cmp(other))
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> Ord for HeapItem<'a> {
|
||||
fn cmp(&self, other: &HeapItem<'a>) -> Ordering {
|
||||
(&other.streamer.key(), &other.segment_ord).cmp(&(&self.streamer.key(), &self.segment_ord))
|
||||
impl<'a> Ord for TermsWithSegmentOrd<'a> {
|
||||
fn cmp(&self, other: &TermsWithSegmentOrd<'a>) -> Ordering {
|
||||
(&other.terms.key(), &other.segment_ord).cmp(&(&self.terms.key(), &self.segment_ord))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -35,42 +36,34 @@ impl<'a> Ord for HeapItem<'a> {
|
||||
///
|
||||
/// The item yield is actually a pair with
|
||||
/// - the term
|
||||
/// - a slice with the ordinal of the segments containing
|
||||
/// the terms.
|
||||
/// - a slice with the ordinal of the segments containing the terms.
|
||||
pub struct TermMerger<'a> {
|
||||
heap: BinaryHeap<HeapItem<'a>>,
|
||||
current_streamers: Vec<HeapItem<'a>>,
|
||||
heap: BinaryHeap<TermsWithSegmentOrd<'a>>,
|
||||
term_streams_with_segment: Vec<TermsWithSegmentOrd<'a>>,
|
||||
}
|
||||
|
||||
impl<'a> TermMerger<'a> {
|
||||
/// Stream of merged term dictionary
|
||||
pub fn new(streams: Vec<Streamer<'a>>) -> TermMerger<'a> {
|
||||
pub fn new(term_streams_with_segment: Vec<TermsWithSegmentOrd<'a>>) -> TermMerger<'a> {
|
||||
TermMerger {
|
||||
heap: BinaryHeap::new(),
|
||||
current_streamers: streams
|
||||
.into_iter()
|
||||
.enumerate()
|
||||
.map(|(ord, streamer)| HeapItem {
|
||||
streamer,
|
||||
segment_ord: ord,
|
||||
})
|
||||
.collect(),
|
||||
term_streams_with_segment,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn matching_segments<'b: 'a>(
|
||||
&'b self,
|
||||
) -> impl 'b + Iterator<Item = (usize, TermOrdinal)> {
|
||||
self.current_streamers
|
||||
self.term_streams_with_segment
|
||||
.iter()
|
||||
.map(|heap_item| (heap_item.segment_ord, heap_item.streamer.term_ord()))
|
||||
.map(|heap_item| (heap_item.segment_ord, heap_item.terms.term_ord()))
|
||||
}
|
||||
|
||||
fn advance_segments(&mut self) {
|
||||
let streamers = &mut self.current_streamers;
|
||||
let streamers = &mut self.term_streams_with_segment;
|
||||
let heap = &mut self.heap;
|
||||
for mut heap_item in streamers.drain(..) {
|
||||
if heap_item.streamer.advance() {
|
||||
if heap_item.terms.advance() {
|
||||
heap.push(heap_item);
|
||||
}
|
||||
}
|
||||
@@ -82,13 +75,13 @@ impl<'a> TermMerger<'a> {
|
||||
pub fn advance(&mut self) -> bool {
|
||||
self.advance_segments();
|
||||
if let Some(head) = self.heap.pop() {
|
||||
self.current_streamers.push(head);
|
||||
self.term_streams_with_segment.push(head);
|
||||
while let Some(next_streamer) = self.heap.peek() {
|
||||
if self.current_streamers[0].streamer.key() != next_streamer.streamer.key() {
|
||||
if self.term_streams_with_segment[0].terms.key() != next_streamer.terms.key() {
|
||||
break;
|
||||
}
|
||||
let next_heap_it = self.heap.pop().unwrap(); // safe : we peeked beforehand
|
||||
self.current_streamers.push(next_heap_it);
|
||||
self.term_streams_with_segment.push(next_heap_it);
|
||||
}
|
||||
true
|
||||
} else {
|
||||
@@ -102,6 +95,6 @@ impl<'a> TermMerger<'a> {
|
||||
/// if and only if advance() has been called before
|
||||
/// and "true" was returned.
|
||||
pub fn key(&self) -> &[u8] {
|
||||
self.current_streamers[0].streamer.key()
|
||||
self.term_streams_with_segment[0].terms.key()
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,7 +1,10 @@
|
||||
use itertools::Itertools;
|
||||
use proptest::collection::vec;
|
||||
use proptest::prelude::*;
|
||||
|
||||
use super::*;
|
||||
use crate::{Cardinality, ColumnarWriter, HasAssociatedColumnType, RowId};
|
||||
use crate::columnar::{merge_columnar, ColumnarReader, MergeRowOrder, StackMergeOrder};
|
||||
use crate::{Cardinality, ColumnarWriter, DynamicColumn, HasAssociatedColumnType, RowId};
|
||||
|
||||
fn make_columnar<T: Into<NumericalValue> + HasAssociatedColumnType + Copy>(
|
||||
column_name: &str,
|
||||
@@ -14,7 +17,7 @@ fn make_columnar<T: Into<NumericalValue> + HasAssociatedColumnType + Copy>(
|
||||
}
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer
|
||||
.serialize(vals.len() as RowId, None, &mut buffer)
|
||||
.serialize(vals.len() as RowId, &mut buffer)
|
||||
.unwrap();
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
@@ -26,23 +29,10 @@ fn test_column_coercion_to_u64() {
|
||||
// u64 type
|
||||
let columnar2 = make_columnar("numbers", &[u64::MAX]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[]).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_column_no_coercion_if_all_the_same() {
|
||||
let columnar1 = make_columnar("numbers", &[1u64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -50,41 +40,34 @@ fn test_column_coercion_to_i64() {
|
||||
let columnar1 = make_columnar("numbers", &[-1i64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[]).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_impossible_coercion_returns_an_error() {
|
||||
let columnar1 = make_columnar("numbers", &[u64::MAX]);
|
||||
let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
|
||||
let group_error = group_columns_for_merge(
|
||||
&[&columnar1],
|
||||
&[("numbers".to_string(), ColumnType::I64)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap_err();
|
||||
assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
|
||||
}
|
||||
//#[test]
|
||||
// fn test_impossible_coercion_returns_an_error() {
|
||||
// let columnar1 = make_columnar("numbers", &[u64::MAX]);
|
||||
// let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
|
||||
// let group_error = group_columns_for_merge_iter(
|
||||
//&[&columnar1],
|
||||
//&[("numbers".to_string(), ColumnType::I64)],
|
||||
//&merge_order,
|
||||
//)
|
||||
//.unwrap_err();
|
||||
// assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
|
||||
//}
|
||||
|
||||
#[test]
|
||||
fn test_group_columns_with_required_column() {
|
||||
let columnar1 = make_columnar("numbers", &[1i64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(
|
||||
&[&columnar1, &columnar2],
|
||||
&[("numbers".to_string(), ColumnType::U64)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[("numbers".to_string(), ColumnType::U64)]).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -92,18 +75,14 @@ fn test_group_columns_required_column_with_no_existing_columns() {
|
||||
let columnar1 = make_columnar("numbers", &[2u64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(
|
||||
columnars,
|
||||
&[("required_col".to_string(), ColumnType::Str)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
let column_map: BTreeMap<_, _> =
|
||||
group_columns_for_merge(columnars, &[("required_col".to_string(), ColumnType::Str)])
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 2);
|
||||
let columns = column_map
|
||||
.get(&("required_col".to_string(), ColumnType::Str))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("required_col".to_string(), ColumnTypeCategory::Str))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert_eq!(columns.len(), 2);
|
||||
assert!(columns[0].is_none());
|
||||
assert!(columns[1].is_none());
|
||||
@@ -114,16 +93,10 @@ fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_ru
|
||||
let columnar1 = make_columnar("numbers", &[2i64]);
|
||||
let columnar2 = make_columnar("numbers", &[2i64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(
|
||||
columnars,
|
||||
&[("numbers".to_string(), ColumnType::U64)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[("numbers".to_string(), ColumnType::U64)]).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -131,22 +104,23 @@ fn test_missing_column() {
|
||||
let columnar1 = make_columnar("numbers", &[-1i64]);
|
||||
let columnar2 = make_columnar("numbers2", &[2u64]);
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[]).unwrap();
|
||||
assert_eq!(column_map.len(), 2);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
{
|
||||
let columns = column_map
|
||||
.get(&("numbers".to_string(), ColumnType::I64))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("numbers".to_string(), ColumnTypeCategory::Numerical))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert!(columns[0].is_some());
|
||||
assert!(columns[1].is_none());
|
||||
}
|
||||
{
|
||||
let columns = column_map
|
||||
.get(&("numbers2".to_string(), ColumnType::U64))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("numbers2".to_string(), ColumnTypeCategory::Numerical))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert!(columns[0].is_none());
|
||||
assert!(columns[1].is_some());
|
||||
}
|
||||
@@ -169,9 +143,7 @@ fn make_numerical_columnar_multiple_columns(
|
||||
.max()
|
||||
.unwrap_or(0u32);
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer
|
||||
.serialize(num_rows, None, &mut buffer)
|
||||
.unwrap();
|
||||
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
@@ -194,9 +166,7 @@ fn make_byte_columnar_multiple_columns(
|
||||
}
|
||||
}
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer
|
||||
.serialize(num_rows, None, &mut buffer)
|
||||
.unwrap();
|
||||
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
@@ -215,9 +185,7 @@ fn make_text_columnar_multiple_columns(columns: &[(&str, &[&[&str]])]) -> Column
|
||||
.max()
|
||||
.unwrap_or(0u32);
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer
|
||||
.serialize(num_rows, None, &mut buffer)
|
||||
.unwrap();
|
||||
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
@@ -240,11 +208,13 @@ fn test_merge_columnar_numbers() {
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 3);
|
||||
assert_eq!(columnar_reader.num_docs(), 3);
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("numbers").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::F64(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::F64(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(vals.first(0u32), Some(-1f64));
|
||||
assert_eq!(vals.first(1u32), None);
|
||||
@@ -266,11 +236,13 @@ fn test_merge_columnar_texts() {
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 3);
|
||||
assert_eq!(columnar_reader.num_docs(), 3);
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("texts").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Str(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Str(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.ords().get_cardinality(), Cardinality::Optional);
|
||||
|
||||
let get_str_for_ord = |ord| {
|
||||
@@ -313,11 +285,13 @@ fn test_merge_columnar_byte() {
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 4);
|
||||
assert_eq!(columnar_reader.num_docs(), 4);
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("bytes").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
let get_bytes_for_ord = |ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(ord, &mut out).unwrap();
|
||||
@@ -367,11 +341,13 @@ fn test_merge_columnar_byte_with_missing() {
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 3 + 2 + 3);
|
||||
assert_eq!(columnar_reader.num_docs(), 3 + 2 + 3);
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("col").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
let get_bytes_for_ord = |ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(ord, &mut out).unwrap();
|
||||
@@ -417,23 +393,27 @@ fn test_merge_columnar_different_types() {
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 4);
|
||||
assert_eq!(columnar_reader.num_docs(), 4);
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("mixed").unwrap();
|
||||
|
||||
// numeric column
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::I64(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(vals.values_for_doc(0).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(1).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(2).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(0).collect_vec(), Vec::<i64>::new());
|
||||
assert_eq!(vals.values_for_doc(1).collect_vec(), Vec::<i64>::new());
|
||||
assert_eq!(vals.values_for_doc(2).collect_vec(), Vec::<i64>::new());
|
||||
assert_eq!(vals.values_for_doc(3).collect_vec(), vec![1]);
|
||||
assert_eq!(vals.values_for_doc(4).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(4).collect_vec(), Vec::<i64>::new());
|
||||
|
||||
// text column
|
||||
let dynamic_column = cols[1].open().unwrap();
|
||||
let DynamicColumn::Str(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Str(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.ords().get_cardinality(), Cardinality::Optional);
|
||||
let get_str_for_ord = |ord| {
|
||||
let mut out = String::new();
|
||||
@@ -478,7 +458,7 @@ fn test_merge_columnar_different_empty_cardinality() {
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 2);
|
||||
assert_eq!(columnar_reader.num_docs(), 2);
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("mixed").unwrap();
|
||||
|
||||
@@ -490,3 +470,119 @@ fn test_merge_columnar_different_empty_cardinality() {
|
||||
let dynamic_column = cols[1].open().unwrap();
|
||||
assert_eq!(dynamic_column.get_cardinality(), Cardinality::Optional);
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone)]
|
||||
struct ColumnSpec {
|
||||
column_name: String,
|
||||
/// (row_id, term)
|
||||
terms: Vec<(RowId, Vec<u8>)>,
|
||||
}
|
||||
|
||||
#[derive(Clone, Debug)]
|
||||
struct ColumnarSpec {
|
||||
columns: Vec<ColumnSpec>,
|
||||
}
|
||||
|
||||
/// Generate a random (row_id, term) pair:
|
||||
/// - row_id in [0..10]
|
||||
/// - term is either from POSSIBLE_TERMS or random bytes
|
||||
fn rowid_and_term_strategy() -> impl Strategy<Value = (RowId, Vec<u8>)> {
|
||||
const POSSIBLE_TERMS: &[&[u8]] = &[b"a", b"b", b"allo"];
|
||||
|
||||
let term_strat = prop_oneof![
|
||||
// pick from the fixed list
|
||||
(0..POSSIBLE_TERMS.len()).prop_map(|i| POSSIBLE_TERMS[i].to_vec()),
|
||||
// or random bytes (length 0..10)
|
||||
prop::collection::vec(any::<u8>(), 0..10),
|
||||
];
|
||||
|
||||
(0u32..11, term_strat)
|
||||
}
|
||||
|
||||
/// Generate one ColumnSpec, with a random name and a random list of (row_id, term).
|
||||
/// We sort it by row_id so that data is in ascending order.
|
||||
fn column_spec_strategy() -> impl Strategy<Value = ColumnSpec> {
|
||||
let column_name = prop_oneof![
|
||||
Just("col".to_string()),
|
||||
Just("col2".to_string()),
|
||||
"col.*".prop_map(|s| s),
|
||||
];
|
||||
|
||||
// We'll produce 0..8 (rowid,term) entries for this column
|
||||
let data_strat = vec(rowid_and_term_strategy(), 0..8).prop_map(|mut pairs| {
|
||||
// Sort by row_id
|
||||
pairs.sort_by_key(|(row_id, _)| *row_id);
|
||||
pairs
|
||||
});
|
||||
|
||||
(column_name, data_strat).prop_map(|(name, data)| ColumnSpec {
|
||||
column_name: name,
|
||||
terms: data,
|
||||
})
|
||||
}
|
||||
|
||||
/// Strategy to generate an ColumnarSpec
|
||||
fn columnar_strategy() -> impl Strategy<Value = ColumnarSpec> {
|
||||
vec(column_spec_strategy(), 0..3).prop_map(|columns| ColumnarSpec { columns })
|
||||
}
|
||||
|
||||
/// Strategy to generate multiple ColumnarSpecs, each of which we will treat
|
||||
/// as one "columnar" to be merged together.
|
||||
fn columnars_strategy() -> impl Strategy<Value = Vec<ColumnarSpec>> {
|
||||
vec(columnar_strategy(), 1..4)
|
||||
}
|
||||
|
||||
/// Build a `ColumnarReader` from a `ColumnarSpec`
|
||||
fn build_columnar(spec: &ColumnarSpec) -> ColumnarReader {
|
||||
let mut writer = ColumnarWriter::default();
|
||||
let mut max_row_id = 0;
|
||||
for col in &spec.columns {
|
||||
for &(row_id, ref term) in &col.terms {
|
||||
writer.record_bytes(row_id, &col.column_name, term);
|
||||
max_row_id = max_row_id.max(row_id);
|
||||
}
|
||||
}
|
||||
|
||||
let mut buffer = Vec::new();
|
||||
writer.serialize(max_row_id + 1, &mut buffer).unwrap();
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
proptest! {
|
||||
// We just test that the merge_columnar function doesn't crash.
|
||||
#![proptest_config(ProptestConfig::with_cases(256))]
|
||||
#[test]
|
||||
fn test_merge_columnar_bytes_no_crash(columnars in columnars_strategy(), second_merge_columnars in columnars_strategy()) {
|
||||
let columnars: Vec<ColumnarReader> = columnars.iter()
|
||||
.map(build_columnar)
|
||||
.collect();
|
||||
|
||||
let mut out = Vec::new();
|
||||
let columnar_refs: Vec<&ColumnarReader> = columnars.iter().collect();
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_refs);
|
||||
merge_columnar(
|
||||
&columnar_refs,
|
||||
&[],
|
||||
MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut out,
|
||||
).unwrap();
|
||||
|
||||
let merged_reader = ColumnarReader::open(out).unwrap();
|
||||
|
||||
// Merge the second set of columnars with the result of the first merge
|
||||
let mut columnars: Vec<ColumnarReader> = second_merge_columnars.iter()
|
||||
.map(build_columnar)
|
||||
.collect();
|
||||
columnars.push(merged_reader);
|
||||
let mut out = Vec::new();
|
||||
let columnar_refs: Vec<&ColumnarReader> = columnars.iter().collect();
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_refs);
|
||||
merge_columnar(
|
||||
&columnar_refs,
|
||||
&[],
|
||||
MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut out,
|
||||
).unwrap();
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
@@ -5,6 +5,7 @@ mod reader;
|
||||
mod writer;
|
||||
|
||||
pub use column_type::{ColumnType, HasAssociatedColumnType};
|
||||
pub use format_version::{Version, CURRENT_VERSION};
|
||||
#[cfg(test)]
|
||||
pub(crate) use merge::ColumnTypeCategory;
|
||||
pub use merge::{merge_columnar, MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};
|
||||
|
||||
@@ -1,12 +1,13 @@
|
||||
use std::{fmt, io, mem};
|
||||
|
||||
use common::file_slice::FileSlice;
|
||||
use common::json_path_writer::JSON_PATH_SEGMENT_SEP;
|
||||
use common::BinarySerializable;
|
||||
use sstable::{Dictionary, RangeSSTable};
|
||||
|
||||
use crate::columnar::{format_version, ColumnType};
|
||||
use crate::dynamic_column::DynamicColumnHandle;
|
||||
use crate::RowId;
|
||||
use crate::{RowId, Version};
|
||||
|
||||
fn io_invalid_data(msg: String) -> io::Error {
|
||||
io::Error::new(io::ErrorKind::InvalidData, msg)
|
||||
@@ -18,12 +19,13 @@ fn io_invalid_data(msg: String) -> io::Error {
|
||||
pub struct ColumnarReader {
|
||||
column_dictionary: Dictionary<RangeSSTable>,
|
||||
column_data: FileSlice,
|
||||
num_rows: RowId,
|
||||
num_docs: RowId,
|
||||
format_version: Version,
|
||||
}
|
||||
|
||||
impl fmt::Debug for ColumnarReader {
|
||||
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
|
||||
let num_rows = self.num_rows();
|
||||
let num_rows = self.num_docs();
|
||||
let columns = self.list_columns().unwrap();
|
||||
let num_cols = columns.len();
|
||||
let mut debug_struct = f.debug_struct("Columnar");
|
||||
@@ -53,6 +55,7 @@ impl fmt::Debug for ColumnarReader {
|
||||
fn read_all_columns_in_stream(
|
||||
mut stream: sstable::Streamer<'_, RangeSSTable>,
|
||||
column_data: &FileSlice,
|
||||
format_version: Version,
|
||||
) -> io::Result<Vec<DynamicColumnHandle>> {
|
||||
let mut results = Vec::new();
|
||||
while stream.advance() {
|
||||
@@ -67,12 +70,26 @@ fn read_all_columns_in_stream(
|
||||
let dynamic_column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
format_version,
|
||||
};
|
||||
results.push(dynamic_column_handle);
|
||||
}
|
||||
Ok(results)
|
||||
}
|
||||
|
||||
fn column_dictionary_prefix_for_column_name(column_name: &str) -> String {
|
||||
// Each column is a associated to a given `column_key`,
|
||||
// that starts by `column_name\0column_header`.
|
||||
//
|
||||
// Listing the columns associated to the given column name is therefore equivalent to
|
||||
// listing `column_key` with the prefix `column_name\0`.
|
||||
format!("{}{}", column_name, '\0')
|
||||
}
|
||||
|
||||
fn column_dictionary_prefix_for_subpath(root_path: &str) -> String {
|
||||
format!("{}{}", root_path, JSON_PATH_SEGMENT_SEP as char)
|
||||
}
|
||||
|
||||
impl ColumnarReader {
|
||||
/// Opens a new Columnar file.
|
||||
pub fn open<F>(file_slice: F) -> io::Result<ColumnarReader>
|
||||
@@ -88,75 +105,70 @@ impl ColumnarReader {
|
||||
let num_rows = u32::deserialize(&mut &footer_bytes[8..12])?;
|
||||
let version_footer_bytes: [u8; format_version::VERSION_FOOTER_NUM_BYTES] =
|
||||
footer_bytes[12..].try_into().unwrap();
|
||||
let _version = format_version::parse_footer(version_footer_bytes)?;
|
||||
let format_version = format_version::parse_footer(version_footer_bytes)?;
|
||||
let (column_data, sstable) =
|
||||
file_slice_without_sstable_len.split_from_end(sstable_len as usize);
|
||||
let column_dictionary = Dictionary::open(sstable)?;
|
||||
Ok(ColumnarReader {
|
||||
column_dictionary,
|
||||
column_data,
|
||||
num_rows,
|
||||
num_docs: num_rows,
|
||||
format_version,
|
||||
})
|
||||
}
|
||||
|
||||
pub fn num_rows(&self) -> RowId {
|
||||
self.num_rows
|
||||
pub fn num_docs(&self) -> RowId {
|
||||
self.num_docs
|
||||
}
|
||||
// Iterate over the columns in a sorted way
|
||||
pub fn iter_columns(
|
||||
&self,
|
||||
) -> io::Result<impl Iterator<Item = (String, DynamicColumnHandle)> + '_> {
|
||||
let mut stream = self.column_dictionary.stream()?;
|
||||
Ok(std::iter::from_fn(move || {
|
||||
if stream.advance() {
|
||||
let key_bytes: &[u8] = stream.key();
|
||||
let column_code: u8 = key_bytes.last().cloned().unwrap();
|
||||
// TODO Error Handling. The API gets quite ugly when returning the error here, so
|
||||
// instead we could just check the first N columns upfront.
|
||||
let column_type: ColumnType = ColumnType::try_from_code(column_code)
|
||||
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))
|
||||
.unwrap();
|
||||
let range = stream.value().clone();
|
||||
let column_name =
|
||||
// The last two bytes are respectively the 0u8 separator and the column_type.
|
||||
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
|
||||
let file_slice = self
|
||||
.column_data
|
||||
.slice(range.start as usize..range.end as usize);
|
||||
let column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
format_version: self.format_version,
|
||||
};
|
||||
Some((column_name, column_handle))
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}))
|
||||
}
|
||||
|
||||
// TODO Add unit tests
|
||||
pub fn list_columns(&self) -> io::Result<Vec<(String, DynamicColumnHandle)>> {
|
||||
let mut stream = self.column_dictionary.stream()?;
|
||||
let mut results = Vec::new();
|
||||
while stream.advance() {
|
||||
let key_bytes: &[u8] = stream.key();
|
||||
let column_code: u8 = key_bytes.last().cloned().unwrap();
|
||||
let column_type: ColumnType = ColumnType::try_from_code(column_code)
|
||||
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
|
||||
let range = stream.value().clone();
|
||||
let column_name =
|
||||
// The last two bytes are respectively the 0u8 separator and the column_type.
|
||||
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
|
||||
let file_slice = self
|
||||
.column_data
|
||||
.slice(range.start as usize..range.end as usize);
|
||||
let column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
};
|
||||
results.push((column_name, column_handle));
|
||||
}
|
||||
Ok(results)
|
||||
}
|
||||
|
||||
fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {
|
||||
// Each column is a associated to a given `column_key`,
|
||||
// that starts by `column_name\0column_header`.
|
||||
//
|
||||
// Listing the columns associated to the given column name is therefore equivalent to
|
||||
// listing `column_key` with the prefix `column_name\0`.
|
||||
//
|
||||
// This is in turn equivalent to searching for the range
|
||||
// `[column_name,\0`..column_name\1)`.
|
||||
// TODO can we get some more generic `prefix(..)` logic in the dictionary.
|
||||
let mut start_key = column_name.to_string();
|
||||
start_key.push('\0');
|
||||
let mut end_key = column_name.to_string();
|
||||
end_key.push(1u8 as char);
|
||||
self.column_dictionary
|
||||
.range()
|
||||
.ge(start_key.as_bytes())
|
||||
.lt(end_key.as_bytes())
|
||||
Ok(self.iter_columns()?.collect())
|
||||
}
|
||||
|
||||
pub async fn read_columns_async(
|
||||
&self,
|
||||
column_name: &str,
|
||||
) -> io::Result<Vec<DynamicColumnHandle>> {
|
||||
let prefix = column_dictionary_prefix_for_column_name(column_name);
|
||||
let stream = self
|
||||
.stream_for_column_range(column_name)
|
||||
.column_dictionary
|
||||
.prefix_range(prefix)
|
||||
.into_stream_async()
|
||||
.await?;
|
||||
read_all_columns_in_stream(stream, &self.column_data)
|
||||
read_all_columns_in_stream(stream, &self.column_data, self.format_version)
|
||||
}
|
||||
|
||||
/// Get all columns for the given column name.
|
||||
@@ -164,8 +176,36 @@ impl ColumnarReader {
|
||||
/// There can be more than one column associated to a given column name, provided they have
|
||||
/// different types.
|
||||
pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
|
||||
let stream = self.stream_for_column_range(column_name).into_stream()?;
|
||||
read_all_columns_in_stream(stream, &self.column_data)
|
||||
let prefix = column_dictionary_prefix_for_column_name(column_name);
|
||||
let stream = self.column_dictionary.prefix_range(prefix).into_stream()?;
|
||||
read_all_columns_in_stream(stream, &self.column_data, self.format_version)
|
||||
}
|
||||
|
||||
pub async fn read_subpath_columns_async(
|
||||
&self,
|
||||
root_path: &str,
|
||||
) -> io::Result<Vec<DynamicColumnHandle>> {
|
||||
let prefix = column_dictionary_prefix_for_subpath(root_path);
|
||||
let stream = self
|
||||
.column_dictionary
|
||||
.prefix_range(prefix)
|
||||
.into_stream_async()
|
||||
.await?;
|
||||
read_all_columns_in_stream(stream, &self.column_data, self.format_version)
|
||||
}
|
||||
|
||||
/// Get all inner columns for a given JSON prefix, i.e columns for which the name starts
|
||||
/// with the prefix then contain the [`JSON_PATH_SEGMENT_SEP`].
|
||||
///
|
||||
/// There can be more than one column associated to each path within the JSON structure,
|
||||
/// provided they have different types.
|
||||
pub fn read_subpath_columns(&self, root_path: &str) -> io::Result<Vec<DynamicColumnHandle>> {
|
||||
let prefix = column_dictionary_prefix_for_subpath(root_path);
|
||||
let stream = self
|
||||
.column_dictionary
|
||||
.prefix_range(prefix.as_bytes())
|
||||
.into_stream()?;
|
||||
read_all_columns_in_stream(stream, &self.column_data, self.format_version)
|
||||
}
|
||||
|
||||
/// Return the number of columns in the columnar.
|
||||
@@ -176,6 +216,8 @@ impl ColumnarReader {
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use common::json_path_writer::JSON_PATH_SEGMENT_SEP;
|
||||
|
||||
use crate::{ColumnType, ColumnarReader, ColumnarWriter};
|
||||
|
||||
#[test]
|
||||
@@ -184,7 +226,7 @@ mod tests {
|
||||
columnar_writer.record_column_type("col1", ColumnType::Str, false);
|
||||
columnar_writer.record_column_type("col2", ColumnType::U64, false);
|
||||
let mut buffer = Vec::new();
|
||||
columnar_writer.serialize(1, None, &mut buffer).unwrap();
|
||||
columnar_writer.serialize(1, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
let columns = columnar.list_columns().unwrap();
|
||||
assert_eq!(columns.len(), 2);
|
||||
@@ -200,7 +242,7 @@ mod tests {
|
||||
columnar_writer.record_column_type("count", ColumnType::U64, false);
|
||||
columnar_writer.record_numerical(1, "count", 1u64);
|
||||
let mut buffer = Vec::new();
|
||||
columnar_writer.serialize(2, None, &mut buffer).unwrap();
|
||||
columnar_writer.serialize(2, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
let columns = columnar.list_columns().unwrap();
|
||||
assert_eq!(columns.len(), 1);
|
||||
@@ -208,6 +250,64 @@ mod tests {
|
||||
assert_eq!(columns[0].1.column_type(), ColumnType::U64);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_read_columns() {
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
columnar_writer.record_column_type("col", ColumnType::U64, false);
|
||||
columnar_writer.record_numerical(1, "col", 1u64);
|
||||
let mut buffer = Vec::new();
|
||||
columnar_writer.serialize(2, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
{
|
||||
let columns = columnar.read_columns("col").unwrap();
|
||||
assert_eq!(columns.len(), 1);
|
||||
assert_eq!(columns[0].column_type(), ColumnType::U64);
|
||||
}
|
||||
{
|
||||
let columns = columnar.read_columns("other").unwrap();
|
||||
assert_eq!(columns.len(), 0);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_read_subpath_columns() {
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
columnar_writer.record_str(
|
||||
0,
|
||||
&format!("col1{}subcol1", JSON_PATH_SEGMENT_SEP as char),
|
||||
"hello",
|
||||
);
|
||||
columnar_writer.record_numerical(
|
||||
0,
|
||||
&format!("col1{}subcol2", JSON_PATH_SEGMENT_SEP as char),
|
||||
1i64,
|
||||
);
|
||||
columnar_writer.record_str(1, "col1", "hello");
|
||||
columnar_writer.record_str(0, "col2", "hello");
|
||||
let mut buffer = Vec::new();
|
||||
columnar_writer.serialize(2, &mut buffer).unwrap();
|
||||
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
{
|
||||
let columns = columnar.read_subpath_columns("col1").unwrap();
|
||||
assert_eq!(columns.len(), 2);
|
||||
assert_eq!(columns[0].column_type(), ColumnType::Str);
|
||||
assert_eq!(columns[1].column_type(), ColumnType::I64);
|
||||
}
|
||||
{
|
||||
let columns = columnar.read_subpath_columns("col1.subcol1").unwrap();
|
||||
assert_eq!(columns.len(), 0);
|
||||
}
|
||||
{
|
||||
let columns = columnar.read_subpath_columns("col2").unwrap();
|
||||
assert_eq!(columns.len(), 0);
|
||||
}
|
||||
{
|
||||
let columns = columnar.read_subpath_columns("other").unwrap();
|
||||
assert_eq!(columns.len(), 0);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[should_panic(expected = "Input type forbidden")]
|
||||
fn test_list_columns_strict_typing_panics_on_wrong_types() {
|
||||
|
||||
@@ -87,7 +87,7 @@ impl<V: SymbolValue> ColumnOperation<V> {
|
||||
minibuf
|
||||
}
|
||||
|
||||
/// Deserialize a colummn operation.
|
||||
/// Deserialize a column operation.
|
||||
/// Returns None if the buffer is empty.
|
||||
///
|
||||
/// Panics if the payload is invalid:
|
||||
@@ -122,7 +122,6 @@ impl<T> From<T> for ColumnOperation<T> {
|
||||
// In order to limit memory usage, and in order
|
||||
// to benefit from the stacker, we do this by serialization our data
|
||||
// as "Symbols".
|
||||
#[allow(clippy::from_over_into)]
|
||||
pub(super) trait SymbolValue: Clone + Copy {
|
||||
// Serializes the symbol into the given buffer.
|
||||
// Returns the number of bytes written into the buffer.
|
||||
|
||||
@@ -41,31 +41,10 @@ impl ColumnWriter {
|
||||
pub(super) fn operation_iterator<'a, V: SymbolValue>(
|
||||
&self,
|
||||
arena: &MemoryArena,
|
||||
old_to_new_ids_opt: Option<&[RowId]>,
|
||||
buffer: &'a mut Vec<u8>,
|
||||
) -> impl Iterator<Item = ColumnOperation<V>> + 'a {
|
||||
buffer.clear();
|
||||
self.values.read_to_end(arena, buffer);
|
||||
if let Some(old_to_new_ids) = old_to_new_ids_opt {
|
||||
// TODO avoid the extra deserialization / serialization.
|
||||
let mut sorted_ops: Vec<(RowId, ColumnOperation<V>)> = Vec::new();
|
||||
let mut new_doc = 0u32;
|
||||
let mut cursor = &buffer[..];
|
||||
for op in std::iter::from_fn(|| ColumnOperation::<V>::deserialize(&mut cursor)) {
|
||||
if let ColumnOperation::NewDoc(doc) = &op {
|
||||
new_doc = old_to_new_ids[*doc as usize];
|
||||
sorted_ops.push((new_doc, ColumnOperation::NewDoc(new_doc)));
|
||||
} else {
|
||||
sorted_ops.push((new_doc, op));
|
||||
}
|
||||
}
|
||||
// stable sort is crucial here.
|
||||
sorted_ops.sort_by_key(|(new_doc_id, _)| *new_doc_id);
|
||||
buffer.clear();
|
||||
for (_, op) in sorted_ops {
|
||||
buffer.extend_from_slice(op.serialize().as_ref());
|
||||
}
|
||||
}
|
||||
let mut cursor: &[u8] = &buffer[..];
|
||||
std::iter::from_fn(move || ColumnOperation::deserialize(&mut cursor))
|
||||
}
|
||||
@@ -231,11 +210,9 @@ impl NumericalColumnWriter {
|
||||
pub(super) fn operation_iterator<'a>(
|
||||
self,
|
||||
arena: &MemoryArena,
|
||||
old_to_new_ids: Option<&[RowId]>,
|
||||
buffer: &'a mut Vec<u8>,
|
||||
) -> impl Iterator<Item = ColumnOperation<NumericalValue>> + 'a {
|
||||
self.column_writer
|
||||
.operation_iterator(arena, old_to_new_ids, buffer)
|
||||
self.column_writer.operation_iterator(arena, buffer)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -269,18 +246,17 @@ impl StrOrBytesColumnWriter {
|
||||
dictionaries: &mut [DictionaryBuilder],
|
||||
arena: &mut MemoryArena,
|
||||
) {
|
||||
let unordered_id = dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes);
|
||||
let unordered_id =
|
||||
dictionaries[self.dictionary_id as usize].get_or_allocate_id(bytes, arena);
|
||||
self.column_writer.record(doc, unordered_id, arena);
|
||||
}
|
||||
|
||||
pub(super) fn operation_iterator<'a>(
|
||||
&self,
|
||||
arena: &MemoryArena,
|
||||
old_to_new_ids: Option<&[RowId]>,
|
||||
byte_buffer: &'a mut Vec<u8>,
|
||||
) -> impl Iterator<Item = ColumnOperation<UnorderedId>> + 'a {
|
||||
self.column_writer
|
||||
.operation_iterator(arena, old_to_new_ids, byte_buffer)
|
||||
self.column_writer.operation_iterator(arena, byte_buffer)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -8,14 +8,13 @@ use std::net::Ipv6Addr;
|
||||
|
||||
use column_operation::ColumnOperation;
|
||||
pub(crate) use column_writers::CompatibleNumericalTypes;
|
||||
use common::json_path_writer::JSON_END_OF_PATH;
|
||||
use common::CountingWriter;
|
||||
pub(crate) use serializer::ColumnarSerializer;
|
||||
use stacker::{Addr, ArenaHashMap, MemoryArena};
|
||||
|
||||
use crate::column_index::SerializableColumnIndex;
|
||||
use crate::column_values::{
|
||||
ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
|
||||
};
|
||||
use crate::column_index::{SerializableColumnIndex, SerializableOptionalIndex};
|
||||
use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
|
||||
use crate::columnar::column_type::ColumnType;
|
||||
use crate::columnar::writer::column_writers::{
|
||||
ColumnWriter, NumericalColumnWriter, StrOrBytesColumnWriter,
|
||||
@@ -45,7 +44,7 @@ struct SpareBuffers {
|
||||
/// columnar_writer.record_str(1u32 /* doc id */, "product_name", "Apple");
|
||||
/// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10.5f64); //< uh oh we ended up mixing integer and floats.
|
||||
/// let mut wrt: Vec<u8> = Vec::new();
|
||||
/// columnar_writer.serialize(2u32, None, &mut wrt).unwrap();
|
||||
/// columnar_writer.serialize(2u32, &mut wrt).unwrap();
|
||||
/// ```
|
||||
#[derive(Default)]
|
||||
pub struct ColumnarWriter {
|
||||
@@ -61,25 +60,8 @@ pub struct ColumnarWriter {
|
||||
buffers: SpareBuffers,
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn mutate_or_create_column<V, TMutator>(
|
||||
arena_hash_map: &mut ArenaHashMap,
|
||||
column_name: &str,
|
||||
updater: TMutator,
|
||||
) where
|
||||
V: Copy + 'static,
|
||||
TMutator: FnMut(Option<V>) -> V,
|
||||
{
|
||||
assert!(
|
||||
!column_name.as_bytes().contains(&0u8),
|
||||
"key may not contain the 0 byte"
|
||||
);
|
||||
arena_hash_map.mutate_or_create(column_name.as_bytes(), updater);
|
||||
}
|
||||
|
||||
impl ColumnarWriter {
|
||||
pub fn mem_usage(&self) -> usize {
|
||||
// TODO add dictionary builders.
|
||||
self.arena.mem_usage()
|
||||
+ self.numerical_field_hash_map.mem_usage()
|
||||
+ self.bool_field_hash_map.mem_usage()
|
||||
@@ -87,57 +69,11 @@ impl ColumnarWriter {
|
||||
+ self.str_field_hash_map.mem_usage()
|
||||
+ self.ip_addr_field_hash_map.mem_usage()
|
||||
+ self.datetime_field_hash_map.mem_usage()
|
||||
}
|
||||
|
||||
/// Returns the list of doc ids from 0..num_docs sorted by the `sort_field`
|
||||
/// column.
|
||||
///
|
||||
/// If the column is multivalued, use the first value for scoring.
|
||||
/// If no value is associated to a specific row, the document is assigned
|
||||
/// the lowest possible score.
|
||||
///
|
||||
/// The sort applied is stable.
|
||||
pub fn sort_order(&self, sort_field: &str, num_docs: RowId, reversed: bool) -> Vec<u32> {
|
||||
let Some(numerical_col_writer) =
|
||||
self.numerical_field_hash_map.get::<NumericalColumnWriter>(sort_field.as_bytes()) else {
|
||||
return Vec::new();
|
||||
};
|
||||
let mut symbols_buffer = Vec::new();
|
||||
let mut values = Vec::new();
|
||||
let mut start_doc_check_fill = 0;
|
||||
let mut current_doc_opt: Option<RowId> = None;
|
||||
// Assumption: NewDoc will never call the same doc twice and is strictly increasing between
|
||||
// calls
|
||||
for op in numerical_col_writer.operation_iterator(&self.arena, None, &mut symbols_buffer) {
|
||||
match op {
|
||||
ColumnOperation::NewDoc(doc) => {
|
||||
current_doc_opt = Some(doc);
|
||||
}
|
||||
ColumnOperation::Value(numerical_value) => {
|
||||
if let Some(current_doc) = current_doc_opt {
|
||||
// Fill up with 0.0 since last doc
|
||||
values.extend((start_doc_check_fill..current_doc).map(|doc| (0.0, doc)));
|
||||
start_doc_check_fill = current_doc + 1;
|
||||
// handle multi values
|
||||
current_doc_opt = None;
|
||||
|
||||
let score: f32 = f64::coerce(numerical_value) as f32;
|
||||
values.push((score, current_doc));
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
for doc in values.len() as u32..num_docs {
|
||||
values.push((0.0f32, doc));
|
||||
}
|
||||
values.sort_by(|(left_score, _), (right_score, _)| {
|
||||
if reversed {
|
||||
right_score.total_cmp(left_score)
|
||||
} else {
|
||||
left_score.total_cmp(right_score)
|
||||
}
|
||||
});
|
||||
values.into_iter().map(|(_score, doc)| doc).collect()
|
||||
+ self
|
||||
.dictionaries
|
||||
.iter()
|
||||
.map(|dict| dict.mem_usage())
|
||||
.sum::<usize>()
|
||||
}
|
||||
|
||||
/// Records a column type. This is useful to bypass the coercion process,
|
||||
@@ -167,9 +103,8 @@ impl ColumnarWriter {
|
||||
},
|
||||
&mut self.dictionaries,
|
||||
);
|
||||
mutate_or_create_column(
|
||||
hash_map,
|
||||
column_name,
|
||||
hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<StrOrBytesColumnWriter>| {
|
||||
let mut column_writer = if let Some(column_writer) = column_opt {
|
||||
column_writer
|
||||
@@ -184,24 +119,21 @@ impl ColumnarWriter {
|
||||
);
|
||||
}
|
||||
ColumnType::Bool => {
|
||||
mutate_or_create_column(
|
||||
&mut self.bool_field_hash_map,
|
||||
column_name,
|
||||
self.bool_field_hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
|
||||
);
|
||||
}
|
||||
ColumnType::DateTime => {
|
||||
mutate_or_create_column(
|
||||
&mut self.datetime_field_hash_map,
|
||||
column_name,
|
||||
self.datetime_field_hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
|
||||
);
|
||||
}
|
||||
ColumnType::I64 | ColumnType::F64 | ColumnType::U64 => {
|
||||
let numerical_type = column_type.numerical_type().unwrap();
|
||||
mutate_or_create_column(
|
||||
&mut self.numerical_field_hash_map,
|
||||
column_name,
|
||||
self.numerical_field_hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<NumericalColumnWriter>| {
|
||||
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
|
||||
column.force_numerical_type(numerical_type);
|
||||
@@ -209,9 +141,8 @@ impl ColumnarWriter {
|
||||
},
|
||||
);
|
||||
}
|
||||
ColumnType::IpAddr => mutate_or_create_column(
|
||||
&mut self.ip_addr_field_hash_map,
|
||||
column_name,
|
||||
ColumnType::IpAddr => self.ip_addr_field_hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
|
||||
),
|
||||
}
|
||||
@@ -224,9 +155,8 @@ impl ColumnarWriter {
|
||||
numerical_value: T,
|
||||
) {
|
||||
let (hash_map, arena) = (&mut self.numerical_field_hash_map, &mut self.arena);
|
||||
mutate_or_create_column(
|
||||
hash_map,
|
||||
column_name,
|
||||
hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<NumericalColumnWriter>| {
|
||||
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
|
||||
column.record_numerical_value(doc, numerical_value.into(), arena);
|
||||
@@ -236,10 +166,6 @@ impl ColumnarWriter {
|
||||
}
|
||||
|
||||
pub fn record_ip_addr(&mut self, doc: RowId, column_name: &str, ip_addr: Ipv6Addr) {
|
||||
assert!(
|
||||
!column_name.as_bytes().contains(&0u8),
|
||||
"key may not contain the 0 byte"
|
||||
);
|
||||
let (hash_map, arena) = (&mut self.ip_addr_field_hash_map, &mut self.arena);
|
||||
hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
@@ -253,24 +179,30 @@ impl ColumnarWriter {
|
||||
|
||||
pub fn record_bool(&mut self, doc: RowId, column_name: &str, val: bool) {
|
||||
let (hash_map, arena) = (&mut self.bool_field_hash_map, &mut self.arena);
|
||||
mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
|
||||
let mut column: ColumnWriter = column_opt.unwrap_or_default();
|
||||
column.record(doc, val, arena);
|
||||
column
|
||||
});
|
||||
hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<ColumnWriter>| {
|
||||
let mut column: ColumnWriter = column_opt.unwrap_or_default();
|
||||
column.record(doc, val, arena);
|
||||
column
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: common::DateTime) {
|
||||
let (hash_map, arena) = (&mut self.datetime_field_hash_map, &mut self.arena);
|
||||
mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
|
||||
let mut column: ColumnWriter = column_opt.unwrap_or_default();
|
||||
column.record(
|
||||
doc,
|
||||
NumericalValue::I64(datetime.into_timestamp_nanos()),
|
||||
arena,
|
||||
);
|
||||
column
|
||||
});
|
||||
hash_map.mutate_or_create(
|
||||
column_name.as_bytes(),
|
||||
|column_opt: Option<ColumnWriter>| {
|
||||
let mut column: ColumnWriter = column_opt.unwrap_or_default();
|
||||
column.record(
|
||||
doc,
|
||||
NumericalValue::I64(datetime.into_timestamp_nanos()),
|
||||
arena,
|
||||
);
|
||||
column
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
pub fn record_str(&mut self, doc: RowId, column_name: &str, value: &str) {
|
||||
@@ -295,10 +227,6 @@ impl ColumnarWriter {
|
||||
}
|
||||
|
||||
pub fn record_bytes(&mut self, doc: RowId, column_name: &str, value: &[u8]) {
|
||||
assert!(
|
||||
!column_name.as_bytes().contains(&0u8),
|
||||
"key may not contain the 0 byte"
|
||||
);
|
||||
let (hash_map, arena, dictionaries) = (
|
||||
&mut self.bytes_field_hash_map,
|
||||
&mut self.arena,
|
||||
@@ -318,17 +246,13 @@ impl ColumnarWriter {
|
||||
},
|
||||
);
|
||||
}
|
||||
pub fn serialize(
|
||||
&mut self,
|
||||
num_docs: RowId,
|
||||
old_to_new_row_ids: Option<&[RowId]>,
|
||||
wrt: &mut dyn io::Write,
|
||||
) -> io::Result<()> {
|
||||
pub fn serialize(&mut self, num_docs: RowId, wrt: &mut dyn io::Write) -> io::Result<()> {
|
||||
let mut serializer = ColumnarSerializer::new(wrt);
|
||||
|
||||
let mut columns: Vec<(&[u8], ColumnType, Addr)> = self
|
||||
.numerical_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| {
|
||||
.map(|(column_name, addr)| {
|
||||
let numerical_column_writer: NumericalColumnWriter =
|
||||
self.numerical_field_hash_map.read(addr);
|
||||
let column_type = numerical_column_writer.numerical_type().into();
|
||||
@@ -338,33 +262,38 @@ impl ColumnarWriter {
|
||||
columns.extend(
|
||||
self.bytes_field_hash_map
|
||||
.iter()
|
||||
.map(|(term, addr, _)| (term, ColumnType::Bytes, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::Bytes, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.str_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::Str, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::Str, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.bool_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::Bool, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::Bool, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.ip_addr_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::IpAddr, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::IpAddr, addr)),
|
||||
);
|
||||
columns.extend(
|
||||
self.datetime_field_hash_map
|
||||
.iter()
|
||||
.map(|(column_name, addr, _)| (column_name, ColumnType::DateTime, addr)),
|
||||
.map(|(column_name, addr)| (column_name, ColumnType::DateTime, addr)),
|
||||
);
|
||||
columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
|
||||
|
||||
let (arena, buffers, dictionaries) = (&self.arena, &mut self.buffers, &self.dictionaries);
|
||||
let mut symbol_byte_buffer: Vec<u8> = Vec::new();
|
||||
for (column_name, column_type, addr) in columns {
|
||||
if column_name.contains(&JSON_END_OF_PATH) {
|
||||
// Tantivy uses b'0' as a separator for nested fields in JSON.
|
||||
// Column names with a b'0' are not simply ignored by the columnar (and the inverted
|
||||
// index).
|
||||
continue;
|
||||
}
|
||||
match column_type {
|
||||
ColumnType::Bool => {
|
||||
let column_writer: ColumnWriter = self.bool_field_hash_map.read(addr);
|
||||
@@ -374,11 +303,7 @@ impl ColumnarWriter {
|
||||
serialize_bool_column(
|
||||
cardinality,
|
||||
num_docs,
|
||||
column_writer.operation_iterator(
|
||||
arena,
|
||||
old_to_new_row_ids,
|
||||
&mut symbol_byte_buffer,
|
||||
),
|
||||
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
@@ -392,11 +317,7 @@ impl ColumnarWriter {
|
||||
serialize_ip_addr_column(
|
||||
cardinality,
|
||||
num_docs,
|
||||
column_writer.operation_iterator(
|
||||
arena,
|
||||
old_to_new_row_ids,
|
||||
&mut symbol_byte_buffer,
|
||||
),
|
||||
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
@@ -421,12 +342,10 @@ impl ColumnarWriter {
|
||||
num_docs,
|
||||
str_or_bytes_column_writer.sort_values_within_row,
|
||||
dictionary_builder,
|
||||
str_or_bytes_column_writer.operation_iterator(
|
||||
arena,
|
||||
old_to_new_row_ids,
|
||||
&mut symbol_byte_buffer,
|
||||
),
|
||||
str_or_bytes_column_writer
|
||||
.operation_iterator(arena, &mut symbol_byte_buffer),
|
||||
buffers,
|
||||
&self.arena,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
@@ -442,11 +361,7 @@ impl ColumnarWriter {
|
||||
cardinality,
|
||||
num_docs,
|
||||
numerical_type,
|
||||
numerical_column_writer.operation_iterator(
|
||||
arena,
|
||||
old_to_new_row_ids,
|
||||
&mut symbol_byte_buffer,
|
||||
),
|
||||
numerical_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
@@ -461,11 +376,7 @@ impl ColumnarWriter {
|
||||
cardinality,
|
||||
num_docs,
|
||||
NumericalType::I64,
|
||||
column_writer.operation_iterator(
|
||||
arena,
|
||||
old_to_new_row_ids,
|
||||
&mut symbol_byte_buffer,
|
||||
),
|
||||
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
@@ -480,6 +391,7 @@ impl ColumnarWriter {
|
||||
|
||||
// Serialize [Dictionary, Column, dictionary num bytes U32::LE]
|
||||
// Column: [Column Index, Column Values, column index num bytes U32::LE]
|
||||
#[expect(clippy::too_many_arguments)]
|
||||
fn serialize_bytes_or_str_column(
|
||||
cardinality: Cardinality,
|
||||
num_docs: RowId,
|
||||
@@ -487,6 +399,7 @@ fn serialize_bytes_or_str_column(
|
||||
dictionary_builder: &DictionaryBuilder,
|
||||
operation_it: impl Iterator<Item = ColumnOperation<UnorderedId>>,
|
||||
buffers: &mut SpareBuffers,
|
||||
arena: &MemoryArena,
|
||||
wrt: impl io::Write,
|
||||
) -> io::Result<()> {
|
||||
let SpareBuffers {
|
||||
@@ -495,7 +408,8 @@ fn serialize_bytes_or_str_column(
|
||||
..
|
||||
} = buffers;
|
||||
let mut counting_writer = CountingWriter::wrap(wrt);
|
||||
let term_id_mapping: TermIdMapping = dictionary_builder.serialize(&mut counting_writer)?;
|
||||
let term_id_mapping: TermIdMapping =
|
||||
dictionary_builder.serialize(arena, &mut counting_writer)?;
|
||||
let dictionary_num_bytes: u32 = counting_writer.written_bytes() as u32;
|
||||
let mut wrt = counting_writer.finish();
|
||||
let operation_iterator = operation_it.map(|symbol: ColumnOperation<UnorderedId>| {
|
||||
@@ -631,10 +545,7 @@ fn send_to_serialize_column_mappable_to_u128<
|
||||
value_index_builders: &mut PreallocatedIndexBuilders,
|
||||
values: &mut Vec<T>,
|
||||
mut wrt: impl io::Write,
|
||||
) -> io::Result<()>
|
||||
where
|
||||
for<'a> VecColumn<'a, T>: ColumnValues<T>,
|
||||
{
|
||||
) -> io::Result<()> {
|
||||
values.clear();
|
||||
// TODO: split index and values
|
||||
let serializable_column_index = match cardinality {
|
||||
@@ -650,16 +561,16 @@ where
|
||||
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
|
||||
consume_operation_iterator(op_iterator, optional_index_builder, values);
|
||||
let optional_index = optional_index_builder.finish(num_rows);
|
||||
SerializableColumnIndex::Optional {
|
||||
SerializableColumnIndex::Optional(SerializableOptionalIndex {
|
||||
num_rows,
|
||||
non_null_row_ids: Box::new(optional_index),
|
||||
}
|
||||
})
|
||||
}
|
||||
Cardinality::Multivalued => {
|
||||
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
|
||||
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
|
||||
let multivalued_index = multivalued_index_builder.finish(num_rows);
|
||||
SerializableColumnIndex::Multivalued(Box::new(multivalued_index))
|
||||
let serializable_multivalued_index = multivalued_index_builder.finish(num_rows);
|
||||
SerializableColumnIndex::Multivalued(serializable_multivalued_index)
|
||||
}
|
||||
};
|
||||
crate::column::serialize_column_mappable_to_u128(
|
||||
@@ -670,15 +581,6 @@ where
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut [u64]) {
|
||||
let mut start_index: usize = 0;
|
||||
for end_index in multivalued_index.iter().copied() {
|
||||
let end_index = end_index as usize;
|
||||
values[start_index..end_index].sort_unstable();
|
||||
start_index = end_index;
|
||||
}
|
||||
}
|
||||
|
||||
fn send_to_serialize_column_mappable_to_u64(
|
||||
op_iterator: impl Iterator<Item = ColumnOperation<u64>>,
|
||||
cardinality: Cardinality,
|
||||
@@ -687,10 +589,7 @@ fn send_to_serialize_column_mappable_to_u64(
|
||||
value_index_builders: &mut PreallocatedIndexBuilders,
|
||||
values: &mut Vec<u64>,
|
||||
mut wrt: impl io::Write,
|
||||
) -> io::Result<()>
|
||||
where
|
||||
for<'a> VecColumn<'a, u64>: ColumnValues<u64>,
|
||||
{
|
||||
) -> io::Result<()> {
|
||||
values.clear();
|
||||
let serializable_column_index = match cardinality {
|
||||
Cardinality::Full => {
|
||||
@@ -705,19 +604,22 @@ where
|
||||
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
|
||||
consume_operation_iterator(op_iterator, optional_index_builder, values);
|
||||
let optional_index = optional_index_builder.finish(num_rows);
|
||||
SerializableColumnIndex::Optional {
|
||||
SerializableColumnIndex::Optional(SerializableOptionalIndex {
|
||||
non_null_row_ids: Box::new(optional_index),
|
||||
num_rows,
|
||||
}
|
||||
})
|
||||
}
|
||||
Cardinality::Multivalued => {
|
||||
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
|
||||
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
|
||||
let multivalued_index = multivalued_index_builder.finish(num_rows);
|
||||
let serializable_multivalued_index = multivalued_index_builder.finish(num_rows);
|
||||
if sort_values_within_row {
|
||||
sort_values_within_row_in_place(multivalued_index, values);
|
||||
sort_values_within_row_in_place(
|
||||
serializable_multivalued_index.start_offsets.boxed_iter(),
|
||||
values,
|
||||
);
|
||||
}
|
||||
SerializableColumnIndex::Multivalued(Box::new(multivalued_index))
|
||||
SerializableColumnIndex::Multivalued(serializable_multivalued_index)
|
||||
}
|
||||
};
|
||||
crate::column::serialize_column_mappable_to_u64(
|
||||
@@ -728,6 +630,18 @@ where
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn sort_values_within_row_in_place(
|
||||
multivalued_index: impl Iterator<Item = RowId>,
|
||||
values: &mut [u64],
|
||||
) {
|
||||
let mut start_index: usize = 0;
|
||||
for end_index in multivalued_index {
|
||||
let end_index = end_index as usize;
|
||||
values[start_index..end_index].sort_unstable();
|
||||
start_index = end_index;
|
||||
}
|
||||
}
|
||||
|
||||
fn coerce_numerical_symbol<T>(
|
||||
operation_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
|
||||
) -> impl Iterator<Item = ColumnOperation<u64>>
|
||||
@@ -775,7 +689,7 @@ mod tests {
|
||||
assert_eq!(column_writer.get_cardinality(3), Cardinality::Full);
|
||||
let mut buffer = Vec::new();
|
||||
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
|
||||
.operation_iterator(&arena, None, &mut buffer)
|
||||
.operation_iterator(&arena, &mut buffer)
|
||||
.collect();
|
||||
assert_eq!(symbols.len(), 6);
|
||||
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
|
||||
@@ -804,7 +718,7 @@ mod tests {
|
||||
assert_eq!(column_writer.get_cardinality(3), Cardinality::Optional);
|
||||
let mut buffer = Vec::new();
|
||||
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
|
||||
.operation_iterator(&arena, None, &mut buffer)
|
||||
.operation_iterator(&arena, &mut buffer)
|
||||
.collect();
|
||||
assert_eq!(symbols.len(), 4);
|
||||
assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
|
||||
@@ -827,7 +741,7 @@ mod tests {
|
||||
assert_eq!(column_writer.get_cardinality(2), Cardinality::Optional);
|
||||
let mut buffer = Vec::new();
|
||||
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
|
||||
.operation_iterator(&arena, None, &mut buffer)
|
||||
.operation_iterator(&arena, &mut buffer)
|
||||
.collect();
|
||||
assert_eq!(symbols.len(), 2);
|
||||
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
|
||||
@@ -846,7 +760,7 @@ mod tests {
|
||||
assert_eq!(column_writer.get_cardinality(1), Cardinality::Multivalued);
|
||||
let mut buffer = Vec::new();
|
||||
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
|
||||
.operation_iterator(&arena, None, &mut buffer)
|
||||
.operation_iterator(&arena, &mut buffer)
|
||||
.collect();
|
||||
assert_eq!(symbols.len(), 3);
|
||||
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
use std::io;
|
||||
use std::io::Write;
|
||||
|
||||
use common::json_path_writer::JSON_END_OF_PATH;
|
||||
use common::{BinarySerializable, CountingWriter};
|
||||
use sstable::value::RangeValueWriter;
|
||||
use sstable::RangeSSTable;
|
||||
@@ -19,7 +20,7 @@ pub struct ColumnarSerializer<W: io::Write> {
|
||||
fn prepare_key(key: &[u8], column_type: ColumnType, buffer: &mut Vec<u8>) {
|
||||
buffer.clear();
|
||||
buffer.extend_from_slice(key);
|
||||
buffer.push(0u8);
|
||||
buffer.push(JSON_END_OF_PATH);
|
||||
buffer.push(column_type.to_code());
|
||||
}
|
||||
|
||||
@@ -66,7 +67,7 @@ pub struct ColumnSerializer<'a, W: io::Write> {
|
||||
start_offset: u64,
|
||||
}
|
||||
|
||||
impl<'a, W: io::Write> ColumnSerializer<'a, W> {
|
||||
impl<W: io::Write> ColumnSerializer<'_, W> {
|
||||
pub fn finalize(self) -> io::Result<()> {
|
||||
let end_offset: u64 = self.columnar_serializer.wrt.written_bytes();
|
||||
let byte_range = self.start_offset..end_offset;
|
||||
@@ -79,7 +80,7 @@ impl<'a, W: io::Write> ColumnSerializer<'a, W> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a, W: io::Write> io::Write for ColumnSerializer<'a, W> {
|
||||
impl<W: io::Write> io::Write for ColumnSerializer<'_, W> {
|
||||
fn write(&mut self, buf: &[u8]) -> io::Result<usize> {
|
||||
self.columnar_serializer.wrt.write(buf)
|
||||
}
|
||||
@@ -92,19 +93,3 @@ impl<'a, W: io::Write> io::Write for ColumnSerializer<'a, W> {
|
||||
self.columnar_serializer.wrt.write_all(buf)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
use crate::columnar::column_type::ColumnType;
|
||||
|
||||
#[test]
|
||||
fn test_prepare_key_bytes() {
|
||||
let mut buffer: Vec<u8> = b"somegarbage".to_vec();
|
||||
prepare_key(b"root\0child", ColumnType::Str, &mut buffer);
|
||||
assert_eq!(buffer.len(), 12);
|
||||
assert_eq!(&buffer[..10], b"root\0child");
|
||||
assert_eq!(buffer[10], 0u8);
|
||||
assert_eq!(buffer[11], ColumnType::Str.to_code());
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
use crate::column_index::{SerializableMultivalueIndex, SerializableOptionalIndex};
|
||||
use crate::iterable::Iterable;
|
||||
use crate::RowId;
|
||||
|
||||
@@ -59,31 +60,47 @@ impl IndexBuilder for OptionalIndexBuilder {
|
||||
|
||||
#[derive(Default)]
|
||||
pub struct MultivaluedIndexBuilder {
|
||||
start_offsets: Vec<RowId>,
|
||||
doc_with_values: Vec<RowId>,
|
||||
start_offsets: Vec<u32>,
|
||||
total_num_vals_seen: u32,
|
||||
current_row: RowId,
|
||||
current_row_has_value: bool,
|
||||
}
|
||||
|
||||
impl MultivaluedIndexBuilder {
|
||||
pub fn finish(&mut self, num_docs: RowId) -> &[u32] {
|
||||
self.start_offsets
|
||||
.resize(num_docs as usize + 1, self.total_num_vals_seen);
|
||||
&self.start_offsets[..]
|
||||
pub fn finish(&mut self, num_docs: RowId) -> SerializableMultivalueIndex<'_> {
|
||||
self.start_offsets.push(self.total_num_vals_seen);
|
||||
let non_null_row_ids: Box<dyn Iterable<RowId>> = Box::new(&self.doc_with_values[..]);
|
||||
SerializableMultivalueIndex {
|
||||
doc_ids_with_values: SerializableOptionalIndex {
|
||||
non_null_row_ids,
|
||||
num_rows: num_docs,
|
||||
},
|
||||
start_offsets: Box::new(&self.start_offsets[..]),
|
||||
}
|
||||
}
|
||||
|
||||
fn reset(&mut self) {
|
||||
self.doc_with_values.clear();
|
||||
self.start_offsets.clear();
|
||||
self.start_offsets.push(0u32);
|
||||
self.total_num_vals_seen = 0;
|
||||
self.current_row = 0;
|
||||
self.current_row_has_value = false;
|
||||
}
|
||||
}
|
||||
|
||||
impl IndexBuilder for MultivaluedIndexBuilder {
|
||||
fn record_row(&mut self, row_id: RowId) {
|
||||
self.start_offsets
|
||||
.resize(row_id as usize + 1, self.total_num_vals_seen);
|
||||
self.current_row = row_id;
|
||||
self.current_row_has_value = false;
|
||||
}
|
||||
|
||||
fn record_value(&mut self) {
|
||||
if !self.current_row_has_value {
|
||||
self.current_row_has_value = true;
|
||||
self.doc_with_values.push(self.current_row);
|
||||
self.start_offsets.push(self.total_num_vals_seen);
|
||||
}
|
||||
self.total_num_vals_seen += 1;
|
||||
}
|
||||
}
|
||||
@@ -141,6 +158,32 @@ mod tests {
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_multivalued_value_index_builder_simple() {
|
||||
let mut multivalued_value_index_builder = MultivaluedIndexBuilder::default();
|
||||
{
|
||||
multivalued_value_index_builder.record_row(0u32);
|
||||
multivalued_value_index_builder.record_value();
|
||||
multivalued_value_index_builder.record_value();
|
||||
let serialized_multivalue_index = multivalued_value_index_builder.finish(1u32);
|
||||
let start_offsets: Vec<u32> = serialized_multivalue_index
|
||||
.start_offsets
|
||||
.boxed_iter()
|
||||
.collect();
|
||||
assert_eq!(&start_offsets, &[0, 2]);
|
||||
}
|
||||
multivalued_value_index_builder.reset();
|
||||
multivalued_value_index_builder.record_row(0u32);
|
||||
multivalued_value_index_builder.record_value();
|
||||
multivalued_value_index_builder.record_value();
|
||||
let serialized_multivalue_index = multivalued_value_index_builder.finish(1u32);
|
||||
let start_offsets: Vec<u32> = serialized_multivalue_index
|
||||
.start_offsets
|
||||
.boxed_iter()
|
||||
.collect();
|
||||
assert_eq!(&start_offsets, &[0, 2]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_multivalued_value_index_builder() {
|
||||
let mut multivalued_value_index_builder = MultivaluedIndexBuilder::default();
|
||||
@@ -149,17 +192,15 @@ mod tests {
|
||||
multivalued_value_index_builder.record_value();
|
||||
multivalued_value_index_builder.record_row(2u32);
|
||||
multivalued_value_index_builder.record_value();
|
||||
assert_eq!(
|
||||
multivalued_value_index_builder.finish(4u32).to_vec(),
|
||||
vec![0, 0, 2, 3, 3]
|
||||
);
|
||||
multivalued_value_index_builder.reset();
|
||||
multivalued_value_index_builder.record_row(2u32);
|
||||
multivalued_value_index_builder.record_value();
|
||||
multivalued_value_index_builder.record_value();
|
||||
assert_eq!(
|
||||
multivalued_value_index_builder.finish(4u32).to_vec(),
|
||||
vec![0, 0, 0, 2, 2]
|
||||
);
|
||||
let SerializableMultivalueIndex {
|
||||
doc_ids_with_values,
|
||||
start_offsets,
|
||||
} = multivalued_value_index_builder.finish(4u32);
|
||||
assert_eq!(doc_ids_with_values.num_rows, 4u32);
|
||||
let doc_ids_with_values: Vec<u32> =
|
||||
doc_ids_with_values.non_null_row_ids.boxed_iter().collect();
|
||||
assert_eq!(&doc_ids_with_values, &[1u32, 2u32]);
|
||||
let start_offsets: Vec<u32> = start_offsets.boxed_iter().collect();
|
||||
assert_eq!(&start_offsets[..], &[0, 2, 3]);
|
||||
}
|
||||
}
|
||||
|
||||
183
columnar/src/compat_tests.rs
Normal file
183
columnar/src/compat_tests.rs
Normal file
@@ -0,0 +1,183 @@
|
||||
use std::path::PathBuf;
|
||||
|
||||
use itertools::Itertools;
|
||||
|
||||
use crate::{
|
||||
merge_columnar, Cardinality, Column, ColumnarReader, DynamicColumn, StackMergeOrder,
|
||||
CURRENT_VERSION,
|
||||
};
|
||||
|
||||
const NUM_DOCS: u32 = u16::MAX as u32;
|
||||
|
||||
fn generate_columnar(num_docs: u32, value_offset: u64) -> Vec<u8> {
|
||||
use crate::ColumnarWriter;
|
||||
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
|
||||
for i in 0..num_docs {
|
||||
if i % 100 == 0 {
|
||||
columnar_writer.record_numerical(i, "sparse", value_offset + i as u64);
|
||||
}
|
||||
if i % 5 == 0 {
|
||||
columnar_writer.record_numerical(i, "dense", value_offset + i as u64);
|
||||
}
|
||||
columnar_writer.record_numerical(i, "full", value_offset + i as u64);
|
||||
columnar_writer.record_numerical(i, "multi", value_offset + i as u64);
|
||||
columnar_writer.record_numerical(i, "multi", value_offset + i as u64);
|
||||
}
|
||||
|
||||
let mut wrt: Vec<u8> = Vec::new();
|
||||
columnar_writer.serialize(num_docs, &mut wrt).unwrap();
|
||||
|
||||
wrt
|
||||
}
|
||||
|
||||
#[test]
|
||||
/// Writes a columnar for the CURRENT_VERSION to disk.
|
||||
fn create_format() {
|
||||
let version = CURRENT_VERSION.to_string();
|
||||
let file_path = path_for_version(&version);
|
||||
if PathBuf::from(file_path.clone()).exists() {
|
||||
return;
|
||||
}
|
||||
let columnar = generate_columnar(NUM_DOCS, 0);
|
||||
std::fs::write(file_path, columnar).unwrap();
|
||||
}
|
||||
|
||||
fn path_for_version(version: &str) -> String {
|
||||
format!("./compat_tests_data/{}.columnar", version)
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_format_v1() {
|
||||
let path = path_for_version("v1");
|
||||
test_format(&path);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_format_v2() {
|
||||
let path = path_for_version("v2");
|
||||
test_format(&path);
|
||||
}
|
||||
|
||||
fn test_format(path: &str) {
|
||||
let file_content = std::fs::read(path).unwrap();
|
||||
let reader = ColumnarReader::open(file_content).unwrap();
|
||||
|
||||
check_columns(&reader);
|
||||
|
||||
// Test merge
|
||||
let reader2 = ColumnarReader::open(generate_columnar(NUM_DOCS, NUM_DOCS as u64)).unwrap();
|
||||
let columnar_readers = vec![&reader, &reader2];
|
||||
let merge_row_order = StackMergeOrder::stack(&columnar_readers[..]);
|
||||
let mut out = Vec::new();
|
||||
merge_columnar(&columnar_readers, &[], merge_row_order.into(), &mut out).unwrap();
|
||||
let reader = ColumnarReader::open(out).unwrap();
|
||||
check_columns(&reader);
|
||||
}
|
||||
|
||||
fn check_columns(reader: &ColumnarReader) {
|
||||
let column = open_column(reader, "full");
|
||||
check_column(&column, |doc_id| vec![(doc_id, doc_id as u64).into()]);
|
||||
assert_eq!(column.get_cardinality(), Cardinality::Full);
|
||||
|
||||
let column = open_column(reader, "multi");
|
||||
check_column(&column, |doc_id| {
|
||||
vec![
|
||||
(doc_id * 2, doc_id as u64).into(),
|
||||
(doc_id * 2 + 1, doc_id as u64).into(),
|
||||
]
|
||||
});
|
||||
assert_eq!(column.get_cardinality(), Cardinality::Multivalued);
|
||||
|
||||
let column = open_column(reader, "sparse");
|
||||
check_column(&column, |doc_id| {
|
||||
if doc_id % 100 == 0 {
|
||||
vec![(doc_id / 100, doc_id as u64).into()]
|
||||
} else {
|
||||
vec![]
|
||||
}
|
||||
});
|
||||
assert_eq!(column.get_cardinality(), Cardinality::Optional);
|
||||
|
||||
let column = open_column(reader, "dense");
|
||||
check_column(&column, |doc_id| {
|
||||
if doc_id % 5 == 0 {
|
||||
vec![(doc_id / 5, doc_id as u64).into()]
|
||||
} else {
|
||||
vec![]
|
||||
}
|
||||
});
|
||||
assert_eq!(column.get_cardinality(), Cardinality::Optional);
|
||||
}
|
||||
|
||||
struct RowIdAndValue {
|
||||
row_id: u32,
|
||||
value: u64,
|
||||
}
|
||||
impl From<(u32, u64)> for RowIdAndValue {
|
||||
fn from((row_id, value): (u32, u64)) -> Self {
|
||||
Self { row_id, value }
|
||||
}
|
||||
}
|
||||
|
||||
fn check_column<F: Fn(u32) -> Vec<RowIdAndValue>>(column: &Column<u64>, expected: F) {
|
||||
let num_docs = column.num_docs();
|
||||
let test_doc = |doc: u32| {
|
||||
if expected(doc).is_empty() {
|
||||
assert_eq!(column.first(doc), None);
|
||||
} else {
|
||||
assert_eq!(column.first(doc), Some(expected(doc)[0].value));
|
||||
}
|
||||
let values = column.values_for_doc(doc).collect_vec();
|
||||
assert_eq!(values, expected(doc).iter().map(|x| x.value).collect_vec());
|
||||
let mut row_ids = Vec::new();
|
||||
column.row_ids_for_docs(&[doc], &mut vec![], &mut row_ids);
|
||||
assert_eq!(
|
||||
row_ids,
|
||||
expected(doc).iter().map(|x| x.row_id).collect_vec()
|
||||
);
|
||||
let values = column.values_for_doc(doc).collect_vec();
|
||||
assert_eq!(values, expected(doc).iter().map(|x| x.value).collect_vec());
|
||||
|
||||
// Docid rowid conversion
|
||||
let mut row_ids = Vec::new();
|
||||
let safe_next_doc = |doc: u32| (doc + 1).min(num_docs - 1);
|
||||
column
|
||||
.index
|
||||
.docids_to_rowids(&[doc, safe_next_doc(doc)], &mut vec![], &mut row_ids);
|
||||
let expected_rowids = expected(doc)
|
||||
.iter()
|
||||
.map(|x| x.row_id)
|
||||
.chain(expected(safe_next_doc(doc)).iter().map(|x| x.row_id))
|
||||
.collect_vec();
|
||||
assert_eq!(row_ids, expected_rowids);
|
||||
let rowid_range = column
|
||||
.index
|
||||
.docid_range_to_rowids(doc..safe_next_doc(doc) + 1);
|
||||
if expected_rowids.is_empty() {
|
||||
assert!(rowid_range.is_empty());
|
||||
} else {
|
||||
assert_eq!(
|
||||
rowid_range,
|
||||
expected_rowids[0]..expected_rowids.last().unwrap() + 1
|
||||
);
|
||||
}
|
||||
};
|
||||
test_doc(0);
|
||||
test_doc(num_docs - 1);
|
||||
test_doc(num_docs - 2);
|
||||
test_doc(65000);
|
||||
}
|
||||
|
||||
fn open_column(reader: &ColumnarReader, name: &str) -> Column<u64> {
|
||||
let column = reader.read_columns(name).unwrap()[0]
|
||||
.open()
|
||||
.unwrap()
|
||||
.coerce_numerical(crate::NumericalType::U64)
|
||||
.unwrap();
|
||||
let DynamicColumn::U64(column) = column else {
|
||||
panic!();
|
||||
};
|
||||
column
|
||||
}
|
||||
@@ -1,7 +1,7 @@
|
||||
use std::io;
|
||||
|
||||
use fnv::FnvHashMap;
|
||||
use sstable::SSTable;
|
||||
use stacker::{MemoryArena, SharedArenaHashMap};
|
||||
|
||||
pub(crate) struct TermIdMapping {
|
||||
unordered_to_ord: Vec<OrderedId>,
|
||||
@@ -31,26 +31,38 @@ pub struct OrderedId(pub u32);
|
||||
/// mapping.
|
||||
#[derive(Default)]
|
||||
pub(crate) struct DictionaryBuilder {
|
||||
dict: FnvHashMap<Vec<u8>, UnorderedId>,
|
||||
dict: SharedArenaHashMap,
|
||||
}
|
||||
|
||||
impl DictionaryBuilder {
|
||||
/// Get or allocate an unordered id.
|
||||
/// (This ID is simply an auto-incremented id.)
|
||||
pub fn get_or_allocate_id(&mut self, term: &[u8]) -> UnorderedId {
|
||||
if let Some(term_id) = self.dict.get(term) {
|
||||
return *term_id;
|
||||
}
|
||||
let new_id = UnorderedId(self.dict.len() as u32);
|
||||
self.dict.insert(term.to_vec(), new_id);
|
||||
new_id
|
||||
pub fn get_or_allocate_id(&mut self, term: &[u8], arena: &mut MemoryArena) -> UnorderedId {
|
||||
let next_id = self.dict.len() as u32;
|
||||
let unordered_id = self
|
||||
.dict
|
||||
.mutate_or_create(term, arena, |unordered_id: Option<u32>| {
|
||||
if let Some(unordered_id) = unordered_id {
|
||||
unordered_id
|
||||
} else {
|
||||
next_id
|
||||
}
|
||||
});
|
||||
UnorderedId(unordered_id)
|
||||
}
|
||||
|
||||
/// Serialize the dictionary into an fst, and returns the
|
||||
/// `UnorderedId -> TermOrdinal` map.
|
||||
pub fn serialize<'a, W: io::Write + 'a>(&self, wrt: &mut W) -> io::Result<TermIdMapping> {
|
||||
let mut terms: Vec<(&[u8], UnorderedId)> =
|
||||
self.dict.iter().map(|(k, v)| (k.as_slice(), *v)).collect();
|
||||
pub fn serialize<'a, W: io::Write + 'a>(
|
||||
&self,
|
||||
arena: &MemoryArena,
|
||||
wrt: &mut W,
|
||||
) -> io::Result<TermIdMapping> {
|
||||
let mut terms: Vec<(&[u8], UnorderedId)> = self
|
||||
.dict
|
||||
.iter(arena)
|
||||
.map(|(k, v)| (k, arena.read(v)))
|
||||
.collect();
|
||||
terms.sort_unstable_by_key(|(key, _)| *key);
|
||||
// TODO Remove the allocation.
|
||||
let mut unordered_to_ord: Vec<OrderedId> = vec![OrderedId(0u32); terms.len()];
|
||||
@@ -63,6 +75,10 @@ impl DictionaryBuilder {
|
||||
sstable_builder.finish()?;
|
||||
Ok(TermIdMapping { unordered_to_ord })
|
||||
}
|
||||
|
||||
pub(crate) fn mem_usage(&self) -> usize {
|
||||
self.dict.mem_usage()
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -71,12 +87,13 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn test_dictionary_builder() {
|
||||
let mut arena = MemoryArena::default();
|
||||
let mut dictionary_builder = DictionaryBuilder::default();
|
||||
let hello_uid = dictionary_builder.get_or_allocate_id(b"hello");
|
||||
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy");
|
||||
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax");
|
||||
let hello_uid = dictionary_builder.get_or_allocate_id(b"hello", &mut arena);
|
||||
let happy_uid = dictionary_builder.get_or_allocate_id(b"happy", &mut arena);
|
||||
let tax_uid = dictionary_builder.get_or_allocate_id(b"tax", &mut arena);
|
||||
let mut buffer = Vec::new();
|
||||
let id_mapping = dictionary_builder.serialize(&mut buffer).unwrap();
|
||||
let id_mapping = dictionary_builder.serialize(&arena, &mut buffer).unwrap();
|
||||
assert_eq!(id_mapping.to_ord(hello_uid), OrderedId(1));
|
||||
assert_eq!(id_mapping.to_ord(happy_uid), OrderedId(0));
|
||||
assert_eq!(id_mapping.to_ord(tax_uid), OrderedId(2));
|
||||
|
||||
@@ -8,7 +8,7 @@ use common::{ByteCount, DateTime, HasLen, OwnedBytes};
|
||||
use crate::column::{BytesColumn, Column, StrColumn};
|
||||
use crate::column_values::{monotonic_map_column, StrictlyMonotonicFn};
|
||||
use crate::columnar::ColumnType;
|
||||
use crate::{Cardinality, ColumnIndex, NumericalType};
|
||||
use crate::{Cardinality, ColumnIndex, ColumnValues, NumericalType, Version};
|
||||
|
||||
#[derive(Clone)]
|
||||
pub enum DynamicColumn {
|
||||
@@ -228,10 +228,11 @@ static_dynamic_conversions!(StrColumn, Str);
|
||||
static_dynamic_conversions!(BytesColumn, Bytes);
|
||||
static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
|
||||
|
||||
#[derive(Clone)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct DynamicColumnHandle {
|
||||
pub(crate) file_slice: FileSlice,
|
||||
pub(crate) column_type: ColumnType,
|
||||
pub(crate) format_version: Version,
|
||||
}
|
||||
|
||||
impl DynamicColumnHandle {
|
||||
@@ -247,7 +248,12 @@ impl DynamicColumnHandle {
|
||||
}
|
||||
|
||||
/// Returns the `u64` fast field reader reader associated with `fields` of types
|
||||
/// Str, u64, i64, f64, or datetime.
|
||||
/// Str, u64, i64, f64, bool, ip, or datetime.
|
||||
///
|
||||
/// Notice that for IpAddr, the fastfield reader will return the u64 representation of the
|
||||
/// IpAddr.
|
||||
/// In order to convert to u128 back cast to `CompactSpaceU64Accessor` and call
|
||||
/// `compact_to_u128`.
|
||||
///
|
||||
/// If not, the fastfield reader will returns the u64-value associated with the original
|
||||
/// FastValue.
|
||||
@@ -255,13 +261,24 @@ impl DynamicColumnHandle {
|
||||
let column_bytes = self.file_slice.read_bytes()?;
|
||||
match self.column_type {
|
||||
ColumnType::Str | ColumnType::Bytes => {
|
||||
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
|
||||
let column: BytesColumn =
|
||||
crate::column::open_column_bytes(column_bytes, self.format_version)?;
|
||||
Ok(Some(column.term_ord_column))
|
||||
}
|
||||
ColumnType::Bool => Ok(None),
|
||||
ColumnType::IpAddr => Ok(None),
|
||||
ColumnType::I64 | ColumnType::U64 | ColumnType::F64 | ColumnType::DateTime => {
|
||||
let column = crate::column::open_column_u64::<u64>(column_bytes)?;
|
||||
ColumnType::IpAddr => {
|
||||
let column = crate::column::open_column_u128_as_compact_u64(
|
||||
column_bytes,
|
||||
self.format_version,
|
||||
)?;
|
||||
Ok(Some(column))
|
||||
}
|
||||
ColumnType::Bool
|
||||
| ColumnType::I64
|
||||
| ColumnType::U64
|
||||
| ColumnType::F64
|
||||
| ColumnType::DateTime => {
|
||||
let column =
|
||||
crate::column::open_column_u64::<u64>(column_bytes, self.format_version)?;
|
||||
Ok(Some(column))
|
||||
}
|
||||
}
|
||||
@@ -269,15 +286,31 @@ impl DynamicColumnHandle {
|
||||
|
||||
fn open_internal(&self, column_bytes: OwnedBytes) -> io::Result<DynamicColumn> {
|
||||
let dynamic_column: DynamicColumn = match self.column_type {
|
||||
ColumnType::Bytes => crate::column::open_column_bytes(column_bytes)?.into(),
|
||||
ColumnType::Str => crate::column::open_column_str(column_bytes)?.into(),
|
||||
ColumnType::I64 => crate::column::open_column_u64::<i64>(column_bytes)?.into(),
|
||||
ColumnType::U64 => crate::column::open_column_u64::<u64>(column_bytes)?.into(),
|
||||
ColumnType::F64 => crate::column::open_column_u64::<f64>(column_bytes)?.into(),
|
||||
ColumnType::Bool => crate::column::open_column_u64::<bool>(column_bytes)?.into(),
|
||||
ColumnType::IpAddr => crate::column::open_column_u128::<Ipv6Addr>(column_bytes)?.into(),
|
||||
ColumnType::Bytes => {
|
||||
crate::column::open_column_bytes(column_bytes, self.format_version)?.into()
|
||||
}
|
||||
ColumnType::Str => {
|
||||
crate::column::open_column_str(column_bytes, self.format_version)?.into()
|
||||
}
|
||||
ColumnType::I64 => {
|
||||
crate::column::open_column_u64::<i64>(column_bytes, self.format_version)?.into()
|
||||
}
|
||||
ColumnType::U64 => {
|
||||
crate::column::open_column_u64::<u64>(column_bytes, self.format_version)?.into()
|
||||
}
|
||||
ColumnType::F64 => {
|
||||
crate::column::open_column_u64::<f64>(column_bytes, self.format_version)?.into()
|
||||
}
|
||||
ColumnType::Bool => {
|
||||
crate::column::open_column_u64::<bool>(column_bytes, self.format_version)?.into()
|
||||
}
|
||||
ColumnType::IpAddr => {
|
||||
crate::column::open_column_u128::<Ipv6Addr>(column_bytes, self.format_version)?
|
||||
.into()
|
||||
}
|
||||
ColumnType::DateTime => {
|
||||
crate::column::open_column_u64::<DateTime>(column_bytes)?.into()
|
||||
crate::column::open_column_u64::<DateTime>(column_bytes, self.format_version)?
|
||||
.into()
|
||||
}
|
||||
};
|
||||
Ok(dynamic_column)
|
||||
|
||||
@@ -1,10 +1,13 @@
|
||||
use std::ops::Range;
|
||||
use std::sync::Arc;
|
||||
|
||||
use crate::{ColumnValues, RowId};
|
||||
|
||||
pub trait Iterable<T = u64> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_>;
|
||||
}
|
||||
|
||||
impl<'a, T: Copy> Iterable<T> for &'a [T] {
|
||||
impl<T: Copy> Iterable<T> for &[T] {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
|
||||
Box::new(self.iter().copied())
|
||||
}
|
||||
@@ -17,3 +20,9 @@ where Range<T>: Iterator<Item = T>
|
||||
Box::new(self.clone())
|
||||
}
|
||||
}
|
||||
|
||||
impl Iterable for Arc<dyn crate::ColumnValues<RowId>> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
|
||||
Box::new(self.iter().map(|row_id| row_id as u64))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,3 +1,22 @@
|
||||
//! # Tantivy-Columnar
|
||||
//!
|
||||
//! `tantivy-columnar`provides a columnar storage for tantivy.
|
||||
//! The crate allows for efficient read operations on specific columns rather than entire records.
|
||||
//!
|
||||
//! ## Overview
|
||||
//!
|
||||
//! - **columnar**: Reading, writing, and merging multiple columns:
|
||||
//! - **[ColumnarWriter]**: Makes it possible to create a new columnar.
|
||||
//! - **[ColumnarReader]**: The ColumnarReader makes it possible to access a set of columns
|
||||
//! associated to field names.
|
||||
//! - **[merge_columnar]**: Contains the functionalities to merge multiple ColumnarReader or
|
||||
//! segments into a single one.
|
||||
//!
|
||||
//! - **column**: A single column, which contains
|
||||
//! - [column_index]: Resolves the rows for a document id. Manages the cardinality of the
|
||||
//! column.
|
||||
//! - [column_values]: Stores the values of a column in a dense format.
|
||||
|
||||
#![cfg_attr(all(feature = "unstable", test), feature(test))]
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -12,7 +31,7 @@ use std::io;
|
||||
|
||||
mod block_accessor;
|
||||
mod column;
|
||||
mod column_index;
|
||||
pub mod column_index;
|
||||
pub mod column_values;
|
||||
mod columnar;
|
||||
mod dictionary;
|
||||
@@ -29,7 +48,7 @@ pub use column_values::{
|
||||
};
|
||||
pub use columnar::{
|
||||
merge_columnar, ColumnType, ColumnarReader, ColumnarWriter, HasAssociatedColumnType,
|
||||
MergeRowOrder, ShuffleMergeOrder, StackMergeOrder,
|
||||
MergeRowOrder, ShuffleMergeOrder, StackMergeOrder, Version, CURRENT_VERSION,
|
||||
};
|
||||
use sstable::VoidSSTable;
|
||||
pub use value::{NumericalType, NumericalValue};
|
||||
@@ -94,6 +113,9 @@ impl Cardinality {
|
||||
pub fn is_multivalue(&self) -> bool {
|
||||
matches!(self, Cardinality::Multivalued)
|
||||
}
|
||||
pub fn is_full(&self) -> bool {
|
||||
matches!(self, Cardinality::Full)
|
||||
}
|
||||
pub(crate) fn to_code(self) -> u8 {
|
||||
self as u8
|
||||
}
|
||||
@@ -109,3 +131,6 @@ impl Cardinality {
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests;
|
||||
|
||||
#[cfg(test)]
|
||||
mod compat_tests;
|
||||
|
||||
@@ -21,12 +21,12 @@ fn test_dataframe_writer_str() {
|
||||
dataframe_writer.record_str(1u32, "my_string", "hello");
|
||||
dataframe_writer.record_str(3u32, "my_string", "helloeee");
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
|
||||
dataframe_writer.serialize(5, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 87);
|
||||
assert_eq!(cols[0].num_bytes(), 73);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -35,12 +35,12 @@ fn test_dataframe_writer_bytes() {
|
||||
dataframe_writer.record_bytes(1u32, "my_string", b"hello");
|
||||
dataframe_writer.record_bytes(3u32, "my_string", b"helloeee");
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
|
||||
dataframe_writer.serialize(5, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 87);
|
||||
assert_eq!(cols[0].num_bytes(), 73);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -49,7 +49,7 @@ fn test_dataframe_writer_bool() {
|
||||
dataframe_writer.record_bool(1u32, "bool.value", false);
|
||||
dataframe_writer.record_bool(3u32, "bool.value", true);
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
|
||||
dataframe_writer.serialize(5, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("bool.value").unwrap();
|
||||
@@ -57,7 +57,9 @@ fn test_dataframe_writer_bool() {
|
||||
assert_eq!(cols[0].num_bytes(), 22);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::Bool);
|
||||
let dyn_bool_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bool(bool_col) = dyn_bool_col else { panic!(); };
|
||||
let DynamicColumn::Bool(bool_col) = dyn_bool_col else {
|
||||
panic!();
|
||||
};
|
||||
let vals: Vec<Option<bool>> = (0..5).map(|row_id| bool_col.first(row_id)).collect();
|
||||
assert_eq!(&vals, &[None, Some(false), None, Some(true), None,]);
|
||||
}
|
||||
@@ -72,14 +74,16 @@ fn test_dataframe_writer_u64_multivalued() {
|
||||
dataframe_writer.record_numerical(6u32, "divisor", 2u64);
|
||||
dataframe_writer.record_numerical(6u32, "divisor", 3u64);
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(7, None, &mut buffer).unwrap();
|
||||
dataframe_writer.serialize(7, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("divisor").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 29);
|
||||
assert_eq!(cols[0].num_bytes(), 50);
|
||||
let dyn_i64_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(divisor_col) = dyn_i64_col else { panic!(); };
|
||||
let DynamicColumn::I64(divisor_col) = dyn_i64_col else {
|
||||
panic!();
|
||||
};
|
||||
assert_eq!(
|
||||
divisor_col.get_cardinality(),
|
||||
crate::Cardinality::Multivalued
|
||||
@@ -93,7 +97,7 @@ fn test_dataframe_writer_ip_addr() {
|
||||
dataframe_writer.record_ip_addr(1, "ip_addr", Ipv6Addr::from_u128(1001));
|
||||
dataframe_writer.record_ip_addr(3, "ip_addr", Ipv6Addr::from_u128(1050));
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
|
||||
dataframe_writer.serialize(5, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("ip_addr").unwrap();
|
||||
@@ -101,7 +105,9 @@ fn test_dataframe_writer_ip_addr() {
|
||||
assert_eq!(cols[0].num_bytes(), 42);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::IpAddr);
|
||||
let dyn_bool_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else { panic!(); };
|
||||
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else {
|
||||
panic!();
|
||||
};
|
||||
let vals: Vec<Option<Ipv6Addr>> = (0..5).map(|row_id| ip_col.first(row_id)).collect();
|
||||
assert_eq!(
|
||||
&vals,
|
||||
@@ -122,7 +128,7 @@ fn test_dataframe_writer_numerical() {
|
||||
dataframe_writer.record_numerical(2u32, "srical.value", NumericalValue::U64(13u64));
|
||||
dataframe_writer.record_numerical(4u32, "srical.value", NumericalValue::U64(15u64));
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer.serialize(6, None, &mut buffer).unwrap();
|
||||
dataframe_writer.serialize(6, &mut buffer).unwrap();
|
||||
let columnar = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("srical.value").unwrap();
|
||||
@@ -134,7 +140,9 @@ fn test_dataframe_writer_numerical() {
|
||||
// - null footer 6 bytes
|
||||
assert_eq!(cols[0].num_bytes(), 33);
|
||||
let column = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(column_i64) = column else { panic!(); };
|
||||
let DynamicColumn::I64(column_i64) = column else {
|
||||
panic!();
|
||||
};
|
||||
assert_eq!(column_i64.index.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(column_i64.first(0), None);
|
||||
assert_eq!(column_i64.first(1), Some(12i64));
|
||||
@@ -145,46 +153,6 @@ fn test_dataframe_writer_numerical() {
|
||||
assert_eq!(column_i64.first(6), None); //< we can change the spec for that one.
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_sort_by_full() {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
dataframe_writer.record_numerical(0u32, "value", NumericalValue::U64(1));
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(2));
|
||||
let data = dataframe_writer.sort_order("value", 2, false);
|
||||
assert_eq!(data, vec![0, 1]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_sort_by_opt() {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(3));
|
||||
dataframe_writer.record_numerical(3u32, "value", NumericalValue::U64(2));
|
||||
let data = dataframe_writer.sort_order("value", 5, false);
|
||||
// 0, 2, 4 is 0.0
|
||||
assert_eq!(data, vec![0, 2, 4, 3, 1]);
|
||||
let data = dataframe_writer.sort_order("value", 5, true);
|
||||
assert_eq!(
|
||||
data,
|
||||
vec![4, 2, 0, 3, 1].into_iter().rev().collect::<Vec<_>>()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_sort_by_multi() {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
// valid for sort
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(2));
|
||||
// those are ignored for sort
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(4));
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(4));
|
||||
// valid for sort
|
||||
dataframe_writer.record_numerical(3u32, "value", NumericalValue::U64(3));
|
||||
// ignored, would change sort order
|
||||
dataframe_writer.record_numerical(3u32, "value", NumericalValue::U64(1));
|
||||
let data = dataframe_writer.sort_order("value", 4, false);
|
||||
assert_eq!(data, vec![0, 2, 1, 3]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dictionary_encoded_str() {
|
||||
let mut buffer = Vec::new();
|
||||
@@ -193,12 +161,14 @@ fn test_dictionary_encoded_str() {
|
||||
columnar_writer.record_str(3, "my.column", "c");
|
||||
columnar_writer.record_str(3, "my.column2", "different_column!");
|
||||
columnar_writer.record_str(4, "my.column", "b");
|
||||
columnar_writer.serialize(5, None, &mut buffer).unwrap();
|
||||
columnar_writer.serialize(5, &mut buffer).unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let col_handles = columnar_reader.read_columns("my.column").unwrap();
|
||||
assert_eq!(col_handles.len(), 1);
|
||||
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else { panic!(); };
|
||||
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else {
|
||||
panic!();
|
||||
};
|
||||
let index: Vec<Option<u64>> = (0..5).map(|row_id| str_col.ords().first(row_id)).collect();
|
||||
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
|
||||
assert_eq!(str_col.num_rows(), 5);
|
||||
@@ -225,12 +195,14 @@ fn test_dictionary_encoded_bytes() {
|
||||
columnar_writer.record_bytes(3, "my.column", b"c");
|
||||
columnar_writer.record_bytes(3, "my.column2", b"different_column!");
|
||||
columnar_writer.record_bytes(4, "my.column", b"b");
|
||||
columnar_writer.serialize(5, None, &mut buffer).unwrap();
|
||||
columnar_writer.serialize(5, &mut buffer).unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let col_handles = columnar_reader.read_columns("my.column").unwrap();
|
||||
assert_eq!(col_handles.len(), 1);
|
||||
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else { panic!(); };
|
||||
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else {
|
||||
panic!();
|
||||
};
|
||||
let index: Vec<Option<u64>> = (0..5)
|
||||
.map(|row_id| bytes_col.ords().first(row_id))
|
||||
.collect();
|
||||
@@ -318,9 +290,9 @@ fn bytes_strategy() -> impl Strategy<Value = &'static [u8]> {
|
||||
// A random column value
|
||||
fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
|
||||
prop_oneof![
|
||||
10 => string_strategy().prop_map(|s| ColumnValue::Str(s)),
|
||||
1 => bytes_strategy().prop_map(|b| ColumnValue::Bytes(b)),
|
||||
40 => num_strategy().prop_map(|n| ColumnValue::Numerical(n)),
|
||||
10 => string_strategy().prop_map(ColumnValue::Str),
|
||||
1 => bytes_strategy().prop_map(ColumnValue::Bytes),
|
||||
40 => num_strategy().prop_map(ColumnValue::Numerical),
|
||||
1 => (1u16..3u16).prop_map(|ip_addr_byte| ColumnValue::IpAddr(Ipv6Addr::new(
|
||||
127,
|
||||
0,
|
||||
@@ -331,8 +303,8 @@ fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
|
||||
0,
|
||||
ip_addr_byte
|
||||
))),
|
||||
1 => any::<bool>().prop_map(|b| ColumnValue::Bool(b)),
|
||||
1 => (0_679_723_993i64..1_679_723_995i64)
|
||||
1 => any::<bool>().prop_map(ColumnValue::Bool),
|
||||
1 => (679_723_993i64..1_679_723_995i64)
|
||||
.prop_map(|val| { ColumnValue::DateTime(DateTime::from_timestamp_secs(val)) })
|
||||
]
|
||||
}
|
||||
@@ -357,26 +329,12 @@ fn columnar_docs_strategy() -> impl Strategy<Value = Vec<Vec<(&'static str, Colu
|
||||
.prop_flat_map(|num_docs| proptest::collection::vec(doc_strategy(), num_docs))
|
||||
}
|
||||
|
||||
fn columnar_docs_and_mapping_strategy(
|
||||
) -> impl Strategy<Value = (Vec<Vec<(&'static str, ColumnValue)>>, Vec<RowId>)> {
|
||||
columnar_docs_strategy().prop_flat_map(|docs| {
|
||||
permutation_strategy(docs.len()).prop_map(move |permutation| (docs.clone(), permutation))
|
||||
})
|
||||
}
|
||||
|
||||
fn permutation_strategy(n: usize) -> impl Strategy<Value = Vec<RowId>> {
|
||||
Just((0u32..n as RowId).collect()).prop_shuffle()
|
||||
}
|
||||
|
||||
fn permutation_and_subset_strategy(n: usize) -> impl Strategy<Value = Vec<usize>> {
|
||||
let vals: Vec<usize> = (0..n).collect();
|
||||
subsequence(vals, 0..=n).prop_shuffle()
|
||||
}
|
||||
|
||||
fn build_columnar_with_mapping(
|
||||
docs: &[Vec<(&'static str, ColumnValue)>],
|
||||
old_to_new_row_ids_opt: Option<&[RowId]>,
|
||||
) -> ColumnarReader {
|
||||
fn build_columnar_with_mapping(docs: &[Vec<(&'static str, ColumnValue)>]) -> ColumnarReader {
|
||||
let num_docs = docs.len() as u32;
|
||||
let mut buffer = Vec::new();
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
@@ -404,15 +362,13 @@ fn build_columnar_with_mapping(
|
||||
}
|
||||
}
|
||||
}
|
||||
columnar_writer
|
||||
.serialize(num_docs, old_to_new_row_ids_opt, &mut buffer)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
columnar_reader
|
||||
columnar_writer.serialize(num_docs, &mut buffer).unwrap();
|
||||
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
fn build_columnar(docs: &[Vec<(&'static str, ColumnValue)>]) -> ColumnarReader {
|
||||
build_columnar_with_mapping(docs, None)
|
||||
build_columnar_with_mapping(docs)
|
||||
}
|
||||
|
||||
fn assert_columnar_eq_strict(left: &ColumnarReader, right: &ColumnarReader) {
|
||||
@@ -424,7 +380,7 @@ fn assert_columnar_eq(
|
||||
right: &ColumnarReader,
|
||||
lenient_on_numerical_value: bool,
|
||||
) {
|
||||
assert_eq!(left.num_rows(), right.num_rows());
|
||||
assert_eq!(left.num_docs(), right.num_docs());
|
||||
let left_columns = left.list_columns().unwrap();
|
||||
let right_columns = right.list_columns().unwrap();
|
||||
assert_eq!(left_columns.len(), right_columns.len());
|
||||
@@ -436,6 +392,7 @@ fn assert_columnar_eq(
|
||||
}
|
||||
}
|
||||
|
||||
#[track_caller]
|
||||
fn assert_column_eq<T: Copy + PartialOrd + Debug + Send + Sync + 'static>(
|
||||
left: &Column<T>,
|
||||
right: &Column<T>,
|
||||
@@ -533,28 +490,36 @@ trait AssertEqualToColumnValue {
|
||||
|
||||
impl AssertEqualToColumnValue for bool {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::Bool(val) = column_value else { panic!() };
|
||||
let ColumnValue::Bool(val) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, val);
|
||||
}
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for Ipv6Addr {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::IpAddr(val) = column_value else { panic!() };
|
||||
let ColumnValue::IpAddr(val) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, val);
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: Coerce + PartialEq + Debug + Into<NumericalValue>> AssertEqualToColumnValue for T {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::Numerical(num) = column_value else { panic!() };
|
||||
let ColumnValue::Numerical(num) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, &T::coerce(*num));
|
||||
}
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for DateTime {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::DateTime(dt) = column_value else { panic!() };
|
||||
let ColumnValue::DateTime(dt) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, dt);
|
||||
}
|
||||
}
|
||||
@@ -623,7 +588,7 @@ proptest! {
|
||||
#[test]
|
||||
fn test_single_columnar_builder_proptest(docs in columnar_docs_strategy()) {
|
||||
let columnar = build_columnar(&docs[..]);
|
||||
assert_eq!(columnar.num_rows() as usize, docs.len());
|
||||
assert_eq!(columnar.num_docs() as usize, docs.len());
|
||||
let mut expected_columns: HashMap<(&str, ColumnTypeCategory), HashMap<u32, Vec<&ColumnValue>> > = Default::default();
|
||||
for (doc_id, doc_vals) in docs.iter().enumerate() {
|
||||
for (col_name, col_val) in doc_vals {
|
||||
@@ -663,54 +628,6 @@ proptest! {
|
||||
}
|
||||
}
|
||||
|
||||
// Same as `test_single_columnar_builder_proptest` but with a shuffling mapping.
|
||||
proptest! {
|
||||
#![proptest_config(ProptestConfig::with_cases(500))]
|
||||
#[test]
|
||||
fn test_single_columnar_builder_with_shuffle_proptest((docs, mapping) in columnar_docs_and_mapping_strategy()) {
|
||||
let columnar = build_columnar_with_mapping(&docs[..], Some(&mapping));
|
||||
assert_eq!(columnar.num_rows() as usize, docs.len());
|
||||
let mut expected_columns: HashMap<(&str, ColumnTypeCategory), HashMap<u32, Vec<&ColumnValue>> > = Default::default();
|
||||
for (doc_id, doc_vals) in docs.iter().enumerate() {
|
||||
for (col_name, col_val) in doc_vals {
|
||||
expected_columns
|
||||
.entry((col_name, col_val.column_type_category()))
|
||||
.or_default()
|
||||
.entry(mapping[doc_id])
|
||||
.or_default()
|
||||
.push(col_val);
|
||||
}
|
||||
}
|
||||
let column_list = columnar.list_columns().unwrap();
|
||||
assert_eq!(expected_columns.len(), column_list.len());
|
||||
for (column_name, column) in column_list {
|
||||
let dynamic_column = column.open().unwrap();
|
||||
let col_category: ColumnTypeCategory = dynamic_column.column_type().into();
|
||||
let expected_col_values: &HashMap<u32, Vec<&ColumnValue>> = expected_columns.get(&(column_name.as_str(), col_category)).unwrap();
|
||||
for _doc_id in 0..columnar.num_rows() {
|
||||
match &dynamic_column {
|
||||
DynamicColumn::Bool(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::I64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::U64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::F64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::IpAddr(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::DateTime(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::Bytes(col) =>
|
||||
assert_bytes_column_values(col, expected_col_values, false),
|
||||
DynamicColumn::Str(col) =>
|
||||
assert_bytes_column_values(col, expected_col_values, true),
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// This tests create 2 or 3 random small columnar and attempts to merge them.
|
||||
// It compares the resulting merged dataframe with what would have been obtained by building the
|
||||
// dataframe from the concatenated rows to begin with.
|
||||
@@ -726,7 +643,7 @@ proptest! {
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_readers_arr[..]).into();
|
||||
crate::merge_columnar(&columnar_readers_arr[..], &[], stack_merge_order, &mut output).unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().cloned().flatten().collect();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().flatten().cloned().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
@@ -752,7 +669,7 @@ fn test_columnar_merging_empty_columnar() {
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
|
||||
columnar_docs.iter().cloned().flatten().collect();
|
||||
columnar_docs.iter().flatten().cloned().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
@@ -789,7 +706,7 @@ fn test_columnar_merging_number_columns() {
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
|
||||
columnar_docs.iter().cloned().flatten().collect();
|
||||
columnar_docs.iter().flatten().cloned().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
@@ -798,6 +715,7 @@ fn test_columnar_merging_number_columns() {
|
||||
// TODO test required_columns
|
||||
// TODO document edge case: required_columns incompatible with values.
|
||||
|
||||
#[allow(clippy::type_complexity)]
|
||||
fn columnar_docs_and_remap(
|
||||
) -> impl Strategy<Value = (Vec<Vec<Vec<(&'static str, ColumnValue)>>>, Vec<RowAddr>)> {
|
||||
proptest::collection::vec(columnar_docs_strategy(), 2..=3).prop_flat_map(
|
||||
@@ -824,24 +742,68 @@ fn columnar_docs_and_remap(
|
||||
proptest! {
|
||||
#![proptest_config(ProptestConfig::with_cases(1000))]
|
||||
#[test]
|
||||
fn test_columnar_merge_and_remap_proptest((columnar_docs, shuffle_merge_order) in columnar_docs_and_remap()) {
|
||||
let shuffled_rows: Vec<Vec<(&'static str, ColumnValue)>> = shuffle_merge_order.iter()
|
||||
.map(|row_addr| columnar_docs[row_addr.segment_ord as usize][row_addr.row_id as usize].clone())
|
||||
.collect();
|
||||
let expected_merged_columnar = build_columnar(&shuffled_rows[..]);
|
||||
let columnar_readers: Vec<ColumnarReader> = columnar_docs.iter()
|
||||
.map(|docs| build_columnar(&docs[..]))
|
||||
.collect::<Vec<_>>();
|
||||
let columnar_readers_arr: Vec<&ColumnarReader> = columnar_readers.iter().collect();
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let segment_num_rows: Vec<RowId> = columnar_docs.iter().map(|docs| docs.len() as RowId).collect();
|
||||
let shuffle_merge_order = ShuffleMergeOrder::for_test(&segment_num_rows, shuffle_merge_order);
|
||||
crate::merge_columnar(&columnar_readers_arr[..], &[], shuffle_merge_order.into(), &mut output).unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_columnar_eq(&merged_columnar, &expected_merged_columnar, true);
|
||||
fn test_columnar_merge_and_remap_proptest((columnar_docs, shuffle_merge_order) in
|
||||
columnar_docs_and_remap()) {
|
||||
test_columnar_merge_and_remap(columnar_docs, shuffle_merge_order);
|
||||
}
|
||||
}
|
||||
|
||||
fn test_columnar_merge_and_remap(
|
||||
columnar_docs: Vec<Vec<Vec<(&'static str, ColumnValue)>>>,
|
||||
shuffle_merge_order: Vec<RowAddr>,
|
||||
) {
|
||||
let shuffled_rows: Vec<Vec<(&'static str, ColumnValue)>> = shuffle_merge_order
|
||||
.iter()
|
||||
.map(|row_addr| {
|
||||
columnar_docs[row_addr.segment_ord as usize][row_addr.row_id as usize].clone()
|
||||
})
|
||||
.collect();
|
||||
let expected_merged_columnar = build_columnar(&shuffled_rows[..]);
|
||||
let columnar_readers: Vec<ColumnarReader> = columnar_docs
|
||||
.iter()
|
||||
.map(|docs| build_columnar(&docs[..]))
|
||||
.collect::<Vec<_>>();
|
||||
let columnar_readers_ref: Vec<&ColumnarReader> = columnar_readers.iter().collect();
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let segment_num_rows: Vec<RowId> = columnar_docs
|
||||
.iter()
|
||||
.map(|docs| docs.len() as RowId)
|
||||
.collect();
|
||||
let shuffle_merge_order = ShuffleMergeOrder::for_test(&segment_num_rows, shuffle_merge_order);
|
||||
crate::merge_columnar(
|
||||
&columnar_readers_ref[..],
|
||||
&[],
|
||||
shuffle_merge_order.into(),
|
||||
&mut output,
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_columnar_eq(&merged_columnar, &expected_merged_columnar, true);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_columnar_merge_and_remap_bug_1() {
|
||||
let columnar_docs = vec![vec![
|
||||
vec![
|
||||
("c1", ColumnValue::Numerical(NumericalValue::U64(0))),
|
||||
("c1", ColumnValue::Numerical(NumericalValue::U64(0))),
|
||||
],
|
||||
vec![],
|
||||
]];
|
||||
let shuffle_merge_order: Vec<RowAddr> = vec![
|
||||
RowAddr {
|
||||
segment_ord: 0,
|
||||
row_id: 1,
|
||||
},
|
||||
RowAddr {
|
||||
segment_ord: 0,
|
||||
row_id: 0,
|
||||
},
|
||||
];
|
||||
|
||||
test_columnar_merge_and_remap(columnar_docs, shuffle_merge_order);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_columnar_merge_empty() {
|
||||
let columnar_reader_1 = build_columnar(&[]);
|
||||
@@ -858,7 +820,7 @@ fn test_columnar_merge_empty() {
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_eq!(merged_columnar.num_rows(), 0);
|
||||
assert_eq!(merged_columnar.num_docs(), 0);
|
||||
assert_eq!(merged_columnar.num_columns(), 0);
|
||||
}
|
||||
|
||||
@@ -884,7 +846,7 @@ fn test_columnar_merge_single_str_column() {
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_eq!(merged_columnar.num_rows(), 1);
|
||||
assert_eq!(merged_columnar.num_docs(), 1);
|
||||
assert_eq!(merged_columnar.num_columns(), 1);
|
||||
}
|
||||
|
||||
@@ -916,7 +878,7 @@ fn test_delete_decrease_cardinality() {
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_eq!(merged_columnar.num_rows(), 1);
|
||||
assert_eq!(merged_columnar.num_docs(), 1);
|
||||
assert_eq!(merged_columnar.num_columns(), 1);
|
||||
let cols = merged_columnar.read_columns("c").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
|
||||
@@ -17,6 +17,31 @@ impl NumericalValue {
|
||||
NumericalValue::F64(_) => NumericalType::F64,
|
||||
}
|
||||
}
|
||||
|
||||
/// Tries to normalize the numerical value in the following priorities:
|
||||
/// i64, i64, f64
|
||||
pub fn normalize(self) -> Self {
|
||||
match self {
|
||||
NumericalValue::U64(val) => {
|
||||
if val <= i64::MAX as u64 {
|
||||
NumericalValue::I64(val as i64)
|
||||
} else {
|
||||
NumericalValue::F64(val as f64)
|
||||
}
|
||||
}
|
||||
NumericalValue::I64(val) => NumericalValue::I64(val),
|
||||
NumericalValue::F64(val) => {
|
||||
let fract = val.fract();
|
||||
if fract == 0.0 && val >= i64::MIN as f64 && val <= i64::MAX as f64 {
|
||||
NumericalValue::I64(val as i64)
|
||||
} else if fract == 0.0 && val >= u64::MIN as f64 && val <= u64::MAX as f64 {
|
||||
NumericalValue::U64(val as u64)
|
||||
} else {
|
||||
NumericalValue::F64(val)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl From<u64> for NumericalValue {
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-common"
|
||||
version = "0.5.0"
|
||||
version = "0.9.0"
|
||||
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
|
||||
license = "MIT"
|
||||
edition = "2021"
|
||||
@@ -9,16 +9,17 @@ documentation = "https://docs.rs/tantivy_common/"
|
||||
homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
repository = "https://github.com/quickwit-oss/tantivy"
|
||||
|
||||
|
||||
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
|
||||
|
||||
[dependencies]
|
||||
byteorder = "1.4.3"
|
||||
ownedbytes = { version= "0.5", path="../ownedbytes" }
|
||||
ownedbytes = { version= "0.9", path="../ownedbytes" }
|
||||
async-trait = "0.1"
|
||||
time = { version = "0.3.10", 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"
|
||||
|
||||
|
||||
@@ -1,39 +1,64 @@
|
||||
#![feature(test)]
|
||||
use binggan::{black_box, BenchRunner};
|
||||
use rand::seq::IteratorRandom;
|
||||
use rand::thread_rng;
|
||||
use tantivy_common::{serialize_vint_u32, BitSet, TinySet};
|
||||
|
||||
extern crate test;
|
||||
fn bench_vint() {
|
||||
let mut runner = BenchRunner::new();
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use rand::seq::IteratorRandom;
|
||||
use rand::thread_rng;
|
||||
use tantivy_common::serialize_vint_u32;
|
||||
use test::Bencher;
|
||||
let vals: Vec<u32> = (0..20_000).collect();
|
||||
runner.bench_function("bench_vint", move |_| {
|
||||
let mut out = 0u64;
|
||||
for val in vals.iter().cloned() {
|
||||
let mut buf = [0u8; 8];
|
||||
serialize_vint_u32(val, &mut buf);
|
||||
out += u64::from(buf[0]);
|
||||
}
|
||||
black_box(out);
|
||||
});
|
||||
|
||||
#[bench]
|
||||
fn bench_vint(b: &mut Bencher) {
|
||||
let vals: Vec<u32> = (0..20_000).collect();
|
||||
b.iter(|| {
|
||||
let mut out = 0u64;
|
||||
for val in vals.iter().cloned() {
|
||||
let mut buf = [0u8; 8];
|
||||
serialize_vint_u32(val, &mut buf);
|
||||
out += u64::from(buf[0]);
|
||||
}
|
||||
out
|
||||
});
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_vint_rand(b: &mut Bencher) {
|
||||
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut thread_rng(), 100_000);
|
||||
b.iter(|| {
|
||||
let mut out = 0u64;
|
||||
for val in vals.iter().cloned() {
|
||||
let mut buf = [0u8; 8];
|
||||
serialize_vint_u32(val, &mut buf);
|
||||
out += u64::from(buf[0]);
|
||||
}
|
||||
out
|
||||
});
|
||||
}
|
||||
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut thread_rng(), 100_000);
|
||||
runner.bench_function("bench_vint_rand", move |_| {
|
||||
let mut out = 0u64;
|
||||
for val in vals.iter().cloned() {
|
||||
let mut buf = [0u8; 8];
|
||||
serialize_vint_u32(val, &mut buf);
|
||||
out += u64::from(buf[0]);
|
||||
}
|
||||
black_box(out);
|
||||
});
|
||||
}
|
||||
|
||||
fn bench_bitset() {
|
||||
let mut runner = BenchRunner::new();
|
||||
|
||||
runner.bench_function("bench_tinyset_pop", move |_| {
|
||||
let mut tinyset = TinySet::singleton(black_box(31u32));
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
black_box(tinyset);
|
||||
});
|
||||
|
||||
let tiny_set = TinySet::empty().insert(10u32).insert(14u32).insert(21u32);
|
||||
runner.bench_function("bench_tinyset_sum", move |_| {
|
||||
assert_eq!(black_box(tiny_set).into_iter().sum::<u32>(), 45u32);
|
||||
});
|
||||
|
||||
let v = [10u32, 14u32, 21u32];
|
||||
runner.bench_function("bench_tinyarr_sum", move |_| {
|
||||
black_box(v.iter().cloned().sum::<u32>());
|
||||
});
|
||||
|
||||
runner.bench_function("bench_bitset_initialize", move |_| {
|
||||
black_box(BitSet::with_max_value(1_000_000));
|
||||
});
|
||||
}
|
||||
|
||||
fn main() {
|
||||
bench_vint();
|
||||
bench_bitset();
|
||||
}
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io::Write;
|
||||
use std::{fmt, io, u64};
|
||||
use std::{fmt, io};
|
||||
|
||||
use ownedbytes::OwnedBytes;
|
||||
|
||||
@@ -697,43 +696,3 @@ mod tests {
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(all(test, feature = "unstable"))]
|
||||
mod bench {
|
||||
|
||||
use test;
|
||||
|
||||
use super::{BitSet, TinySet};
|
||||
|
||||
#[bench]
|
||||
fn bench_tinyset_pop(b: &mut test::Bencher) {
|
||||
b.iter(|| {
|
||||
let mut tinyset = TinySet::singleton(test::black_box(31u32));
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
tinyset.pop_lowest();
|
||||
});
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_tinyset_sum(b: &mut test::Bencher) {
|
||||
let tiny_set = TinySet::empty().insert(10u32).insert(14u32).insert(21u32);
|
||||
b.iter(|| {
|
||||
assert_eq!(test::black_box(tiny_set).into_iter().sum::<u32>(), 45u32);
|
||||
});
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_tinyarr_sum(b: &mut test::Bencher) {
|
||||
let v = [10u32, 14u32, 21u32];
|
||||
b.iter(|| test::black_box(v).iter().cloned().sum::<u32>());
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_bitset_initialize(b: &mut test::Bencher) {
|
||||
b.iter(|| BitSet::with_max_value(1_000_000));
|
||||
}
|
||||
}
|
||||
|
||||
130
common/src/bounds.rs
Normal file
130
common/src/bounds.rs
Normal file
@@ -0,0 +1,130 @@
|
||||
use std::io;
|
||||
use std::ops::Bound;
|
||||
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct BoundsRange<T> {
|
||||
pub lower_bound: Bound<T>,
|
||||
pub upper_bound: Bound<T>,
|
||||
}
|
||||
impl<T> BoundsRange<T> {
|
||||
pub fn new(lower_bound: Bound<T>, upper_bound: Bound<T>) -> Self {
|
||||
BoundsRange {
|
||||
lower_bound,
|
||||
upper_bound,
|
||||
}
|
||||
}
|
||||
pub fn is_unbounded(&self) -> bool {
|
||||
matches!(self.lower_bound, Bound::Unbounded) && matches!(self.upper_bound, Bound::Unbounded)
|
||||
}
|
||||
pub fn map_bound<TTo>(&self, transform: impl Fn(&T) -> TTo) -> BoundsRange<TTo> {
|
||||
BoundsRange {
|
||||
lower_bound: map_bound(&self.lower_bound, &transform),
|
||||
upper_bound: map_bound(&self.upper_bound, &transform),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn map_bound_res<TTo, Err>(
|
||||
&self,
|
||||
transform: impl Fn(&T) -> Result<TTo, Err>,
|
||||
) -> Result<BoundsRange<TTo>, Err> {
|
||||
Ok(BoundsRange {
|
||||
lower_bound: map_bound_res(&self.lower_bound, &transform)?,
|
||||
upper_bound: map_bound_res(&self.upper_bound, &transform)?,
|
||||
})
|
||||
}
|
||||
|
||||
pub fn transform_inner<TTo>(
|
||||
&self,
|
||||
transform_lower: impl Fn(&T) -> TransformBound<TTo>,
|
||||
transform_upper: impl Fn(&T) -> TransformBound<TTo>,
|
||||
) -> BoundsRange<TTo> {
|
||||
BoundsRange {
|
||||
lower_bound: transform_bound_inner(&self.lower_bound, &transform_lower),
|
||||
upper_bound: transform_bound_inner(&self.upper_bound, &transform_upper),
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the first set inner value
|
||||
pub fn get_inner(&self) -> Option<&T> {
|
||||
inner_bound(&self.lower_bound).or(inner_bound(&self.upper_bound))
|
||||
}
|
||||
}
|
||||
|
||||
pub enum TransformBound<T> {
|
||||
/// Overwrite the bounds
|
||||
NewBound(Bound<T>),
|
||||
/// Use Existing bounds with new value
|
||||
Existing(T),
|
||||
}
|
||||
|
||||
/// Takes a bound and transforms the inner value into a new bound via a closure.
|
||||
/// The bound variant may change by the value returned value from the closure.
|
||||
pub fn transform_bound_inner_res<TFrom, TTo>(
|
||||
bound: &Bound<TFrom>,
|
||||
transform: impl Fn(&TFrom) -> io::Result<TransformBound<TTo>>,
|
||||
) -> io::Result<Bound<TTo>> {
|
||||
use self::Bound::*;
|
||||
Ok(match bound {
|
||||
Excluded(ref from_val) => match transform(from_val)? {
|
||||
TransformBound::NewBound(new_val) => new_val,
|
||||
TransformBound::Existing(new_val) => Excluded(new_val),
|
||||
},
|
||||
Included(ref from_val) => match transform(from_val)? {
|
||||
TransformBound::NewBound(new_val) => new_val,
|
||||
TransformBound::Existing(new_val) => Included(new_val),
|
||||
},
|
||||
Unbounded => Unbounded,
|
||||
})
|
||||
}
|
||||
|
||||
/// Takes a bound and transforms the inner value into a new bound via a closure.
|
||||
/// The bound variant may change by the value returned value from the closure.
|
||||
pub fn transform_bound_inner<TFrom, TTo>(
|
||||
bound: &Bound<TFrom>,
|
||||
transform: impl Fn(&TFrom) -> TransformBound<TTo>,
|
||||
) -> Bound<TTo> {
|
||||
use self::Bound::*;
|
||||
match bound {
|
||||
Excluded(ref from_val) => match transform(from_val) {
|
||||
TransformBound::NewBound(new_val) => new_val,
|
||||
TransformBound::Existing(new_val) => Excluded(new_val),
|
||||
},
|
||||
Included(ref from_val) => match transform(from_val) {
|
||||
TransformBound::NewBound(new_val) => new_val,
|
||||
TransformBound::Existing(new_val) => Included(new_val),
|
||||
},
|
||||
Unbounded => Unbounded,
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the inner value of a `Bound`
|
||||
pub fn inner_bound<T>(val: &Bound<T>) -> Option<&T> {
|
||||
match val {
|
||||
Bound::Included(term) | Bound::Excluded(term) => Some(term),
|
||||
Bound::Unbounded => None,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn map_bound<TFrom, TTo>(
|
||||
bound: &Bound<TFrom>,
|
||||
transform: impl Fn(&TFrom) -> TTo,
|
||||
) -> Bound<TTo> {
|
||||
use self::Bound::*;
|
||||
match bound {
|
||||
Excluded(ref from_val) => Bound::Excluded(transform(from_val)),
|
||||
Included(ref from_val) => Bound::Included(transform(from_val)),
|
||||
Unbounded => Unbounded,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn map_bound_res<TFrom, TTo, Err>(
|
||||
bound: &Bound<TFrom>,
|
||||
transform: impl Fn(&TFrom) -> Result<TTo, Err>,
|
||||
) -> Result<Bound<TTo>, Err> {
|
||||
use self::Bound::*;
|
||||
Ok(match bound {
|
||||
Excluded(ref from_val) => Excluded(transform(from_val)?),
|
||||
Included(ref from_val) => Included(transform(from_val)?),
|
||||
Unbounded => Unbounded,
|
||||
})
|
||||
}
|
||||
@@ -1,11 +1,12 @@
|
||||
#![allow(deprecated)]
|
||||
|
||||
use std::fmt;
|
||||
use std::io::{Read, Write};
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
use time::format_description::well_known::Rfc3339;
|
||||
use time::{OffsetDateTime, PrimitiveDateTime, UtcOffset};
|
||||
|
||||
use crate::BinarySerializable;
|
||||
|
||||
/// Precision with which datetimes are truncated when stored in fast fields. This setting is only
|
||||
/// relevant for fast fields. In the docstore, datetimes are always saved with nanosecond precision.
|
||||
#[derive(
|
||||
@@ -24,9 +25,6 @@ pub enum DateTimePrecision {
|
||||
Nanoseconds,
|
||||
}
|
||||
|
||||
#[deprecated(since = "0.20.0", note = "Use `DateTimePrecision` instead")]
|
||||
pub type DatePrecision = DateTimePrecision;
|
||||
|
||||
/// A date/time value with nanoseconds precision.
|
||||
///
|
||||
/// This timestamp does not carry any explicit time zone information.
|
||||
@@ -37,7 +35,7 @@ pub type DatePrecision = DateTimePrecision;
|
||||
/// All constructors and conversions are provided as explicit
|
||||
/// functions and not by implementing any `From`/`Into` traits
|
||||
/// to prevent unintended usage.
|
||||
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
|
||||
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
|
||||
pub struct DateTime {
|
||||
// Timestamp in nanoseconds.
|
||||
pub(crate) timestamp_nanos: i64,
|
||||
@@ -164,3 +162,15 @@ impl fmt::Debug for DateTime {
|
||||
f.write_str(&utc_rfc3339)
|
||||
}
|
||||
}
|
||||
|
||||
impl BinarySerializable for DateTime {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
|
||||
let timestamp_micros = self.into_timestamp_micros();
|
||||
<i64 as BinarySerializable>::serialize(×tamp_micros, writer)
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> std::io::Result<Self> {
|
||||
let timestamp_micros = <i64 as BinarySerializable>::deserialize(reader)?;
|
||||
Ok(Self::from_timestamp_micros(timestamp_micros))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,4 +1,6 @@
|
||||
use std::fs::File;
|
||||
use std::ops::{Deref, Range, RangeBounds};
|
||||
use std::path::Path;
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io};
|
||||
|
||||
@@ -32,6 +34,62 @@ pub trait FileHandle: 'static + Send + Sync + HasLen + fmt::Debug {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
/// A File with it's length included.
|
||||
pub struct WrapFile {
|
||||
file: File,
|
||||
len: usize,
|
||||
}
|
||||
impl WrapFile {
|
||||
/// Creates a new WrapFile and stores its length.
|
||||
pub fn new(file: File) -> io::Result<Self> {
|
||||
let len = file.metadata()?.len() as usize;
|
||||
Ok(WrapFile { file, len })
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl FileHandle for WrapFile {
|
||||
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
|
||||
let file_len = self.len();
|
||||
|
||||
// Calculate the actual range to read, ensuring it stays within file boundaries
|
||||
let start = range.start;
|
||||
let end = range.end.min(file_len);
|
||||
|
||||
// Ensure the start is before the end of the range
|
||||
if start >= end {
|
||||
return Err(io::Error::new(io::ErrorKind::InvalidInput, "Invalid range"));
|
||||
}
|
||||
|
||||
let mut buffer = vec![0; end - start];
|
||||
|
||||
#[cfg(unix)]
|
||||
{
|
||||
use std::os::unix::prelude::FileExt;
|
||||
self.file.read_exact_at(&mut buffer, start as u64)?;
|
||||
}
|
||||
|
||||
#[cfg(not(unix))]
|
||||
{
|
||||
use std::io::{Read, Seek};
|
||||
let mut file = self.file.try_clone()?; // Clone the file to read from it separately
|
||||
// Seek to the start position in the file
|
||||
file.seek(io::SeekFrom::Start(start as u64))?;
|
||||
// Read the data into the buffer
|
||||
file.read_exact(&mut buffer)?;
|
||||
}
|
||||
|
||||
Ok(OwnedBytes::new(buffer))
|
||||
}
|
||||
// todo implement async
|
||||
}
|
||||
impl HasLen for WrapFile {
|
||||
fn len(&self) -> usize {
|
||||
self.len
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl FileHandle for &'static [u8] {
|
||||
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
|
||||
@@ -67,6 +125,30 @@ impl fmt::Debug for FileSlice {
|
||||
}
|
||||
}
|
||||
|
||||
impl FileSlice {
|
||||
pub fn stream_file_chunks(&self) -> impl Iterator<Item = io::Result<OwnedBytes>> + '_ {
|
||||
let len = self.range.end;
|
||||
let mut start = self.range.start;
|
||||
std::iter::from_fn(move || {
|
||||
/// Returns chunks of 1MB of data from the FileHandle.
|
||||
const CHUNK_SIZE: usize = 1024 * 1024; // 1MB
|
||||
|
||||
if start < len {
|
||||
let end = (start + CHUNK_SIZE).min(len);
|
||||
let range = start..end;
|
||||
let chunk = self.data.read_bytes(range);
|
||||
start += CHUNK_SIZE;
|
||||
match chunk {
|
||||
Ok(chunk) => Some(Ok(chunk)),
|
||||
Err(e) => Some(Err(e)),
|
||||
}
|
||||
} else {
|
||||
None
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
/// Takes a range, a `RangeBounds` object, and returns
|
||||
/// a `Range` that corresponds to the relative application of the
|
||||
/// `RangeBounds` object to the original `Range`.
|
||||
@@ -96,6 +178,12 @@ fn combine_ranges<R: RangeBounds<usize>>(orig_range: Range<usize>, rel_range: R)
|
||||
}
|
||||
|
||||
impl FileSlice {
|
||||
/// Creates a FileSlice from a path.
|
||||
pub fn open(path: &Path) -> io::Result<FileSlice> {
|
||||
let wrap_file = WrapFile::new(File::open(path)?)?;
|
||||
Ok(FileSlice::new(Arc::new(wrap_file)))
|
||||
}
|
||||
|
||||
/// Wraps a FileHandle.
|
||||
pub fn new(file_handle: Arc<dyn FileHandle>) -> Self {
|
||||
let num_bytes = file_handle.len();
|
||||
|
||||
@@ -27,15 +27,15 @@ pub trait GroupByIteratorExtended: Iterator {
|
||||
where
|
||||
Self: Sized,
|
||||
F: FnMut(&Self::Item) -> K,
|
||||
K: PartialEq + Copy,
|
||||
Self::Item: Copy,
|
||||
K: PartialEq + Clone,
|
||||
Self::Item: Clone,
|
||||
{
|
||||
GroupByIterator::new(self, key)
|
||||
}
|
||||
}
|
||||
impl<I: Iterator> GroupByIteratorExtended for I {}
|
||||
|
||||
pub struct GroupByIterator<I, F, K: Copy>
|
||||
pub struct GroupByIterator<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -50,7 +50,7 @@ where
|
||||
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
|
||||
}
|
||||
|
||||
struct GroupByShared<I, F, K: Copy>
|
||||
struct GroupByShared<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -63,7 +63,7 @@ impl<I, F, K> GroupByIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
K: Copy,
|
||||
K: Clone,
|
||||
{
|
||||
fn new(inner: I, group_by_fn: F) -> Self {
|
||||
let inner = GroupByShared {
|
||||
@@ -80,28 +80,28 @@ where
|
||||
impl<I, F, K> Iterator for GroupByIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
I::Item: Copy,
|
||||
I::Item: Clone,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
K: Copy,
|
||||
K: Clone,
|
||||
{
|
||||
type Item = (K, GroupIterator<I, F, K>);
|
||||
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let mut inner = self.inner.borrow_mut();
|
||||
let value = *inner.iter.peek()?;
|
||||
let value = inner.iter.peek()?.clone();
|
||||
let key = (inner.group_by_fn)(&value);
|
||||
|
||||
let inner = self.inner.clone();
|
||||
|
||||
let group_iter = GroupIterator {
|
||||
inner,
|
||||
group_key: key,
|
||||
group_key: key.clone(),
|
||||
};
|
||||
Some((key, group_iter))
|
||||
}
|
||||
}
|
||||
|
||||
pub struct GroupIterator<I, F, K: Copy>
|
||||
pub struct GroupIterator<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -110,10 +110,10 @@ where
|
||||
group_key: K,
|
||||
}
|
||||
|
||||
impl<I, F, K: PartialEq + Copy> Iterator for GroupIterator<I, F, K>
|
||||
impl<I, F, K: PartialEq + Clone> Iterator for GroupIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
I::Item: Copy,
|
||||
I::Item: Clone,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
{
|
||||
type Item = I::Item;
|
||||
@@ -121,7 +121,7 @@ where
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let mut inner = self.inner.borrow_mut();
|
||||
// peek if next value is in group
|
||||
let peek_val = *inner.iter.peek()?;
|
||||
let peek_val = inner.iter.peek()?.clone();
|
||||
if (inner.group_by_fn)(&peek_val) == self.group_key {
|
||||
inner.iter.next()
|
||||
} else {
|
||||
|
||||
144
common/src/json_path_writer.rs
Normal file
144
common/src/json_path_writer.rs
Normal file
@@ -0,0 +1,144 @@
|
||||
use crate::replace_in_place;
|
||||
|
||||
/// Separates the different segments of a json path.
|
||||
pub const JSON_PATH_SEGMENT_SEP: u8 = 1u8;
|
||||
pub const JSON_PATH_SEGMENT_SEP_STR: &str =
|
||||
unsafe { std::str::from_utf8_unchecked(&[JSON_PATH_SEGMENT_SEP]) };
|
||||
|
||||
/// Separates the json path and the value in
|
||||
/// a JSON term binary representation.
|
||||
pub const JSON_END_OF_PATH: u8 = 0u8;
|
||||
pub const JSON_END_OF_PATH_STR: &str =
|
||||
unsafe { std::str::from_utf8_unchecked(&[JSON_END_OF_PATH]) };
|
||||
|
||||
/// Create a new JsonPathWriter, that creates flattened json paths for tantivy.
|
||||
#[derive(Clone, Debug, Default)]
|
||||
pub struct JsonPathWriter {
|
||||
path: String,
|
||||
indices: Vec<usize>,
|
||||
expand_dots: bool,
|
||||
}
|
||||
|
||||
impl JsonPathWriter {
|
||||
pub fn with_expand_dots(expand_dots: bool) -> Self {
|
||||
JsonPathWriter {
|
||||
path: String::new(),
|
||||
indices: Vec::new(),
|
||||
expand_dots,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn new() -> Self {
|
||||
JsonPathWriter {
|
||||
path: String::new(),
|
||||
indices: Vec::new(),
|
||||
expand_dots: false,
|
||||
}
|
||||
}
|
||||
|
||||
/// When expand_dots is enabled, json object like
|
||||
/// `{"k8s.node.id": 5}` is processed as if it was
|
||||
/// `{"k8s": {"node": {"id": 5}}}`.
|
||||
/// This option has the merit of allowing users to
|
||||
/// write queries like `k8s.node.id:5`.
|
||||
/// On the other, enabling that feature can lead to
|
||||
/// ambiguity.
|
||||
#[inline]
|
||||
pub fn set_expand_dots(&mut self, expand_dots: bool) {
|
||||
self.expand_dots = expand_dots;
|
||||
}
|
||||
|
||||
/// Push a new segment to the path.
|
||||
#[inline]
|
||||
pub fn push(&mut self, segment: &str) {
|
||||
let len_path = self.path.len();
|
||||
self.indices.push(len_path);
|
||||
if self.indices.len() > 1 {
|
||||
self.path.push(JSON_PATH_SEGMENT_SEP as char);
|
||||
}
|
||||
self.path.push_str(segment);
|
||||
if self.expand_dots {
|
||||
// This might include the separation byte, which is ok because it is not a dot.
|
||||
let appended_segment = &mut self.path[len_path..];
|
||||
// The unsafe below is safe as long as b'.' and JSON_PATH_SEGMENT_SEP are
|
||||
// valid single byte ut8 strings.
|
||||
// By utf-8 design, they cannot be part of another codepoint.
|
||||
unsafe {
|
||||
replace_in_place(b'.', JSON_PATH_SEGMENT_SEP, appended_segment.as_bytes_mut())
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
/// Set the end of JSON path marker.
|
||||
#[inline]
|
||||
pub fn set_end(&mut self) {
|
||||
self.path.push_str(JSON_END_OF_PATH_STR);
|
||||
}
|
||||
|
||||
/// Remove the last segment. Does nothing if the path is empty.
|
||||
#[inline]
|
||||
pub fn pop(&mut self) {
|
||||
if let Some(last_idx) = self.indices.pop() {
|
||||
self.path.truncate(last_idx);
|
||||
}
|
||||
}
|
||||
|
||||
/// Clear the path.
|
||||
#[inline]
|
||||
pub fn clear(&mut self) {
|
||||
self.path.clear();
|
||||
self.indices.clear();
|
||||
}
|
||||
|
||||
/// Get the current path.
|
||||
#[inline]
|
||||
pub fn as_str(&self) -> &str {
|
||||
&self.path
|
||||
}
|
||||
}
|
||||
|
||||
impl From<JsonPathWriter> for String {
|
||||
#[inline]
|
||||
fn from(value: JsonPathWriter) -> Self {
|
||||
value.path
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn json_path_writer_test() {
|
||||
let mut writer = JsonPathWriter::new();
|
||||
writer.set_expand_dots(false);
|
||||
|
||||
writer.push("root");
|
||||
assert_eq!(writer.as_str(), "root");
|
||||
|
||||
writer.push("child");
|
||||
assert_eq!(writer.as_str(), "root\u{1}child");
|
||||
|
||||
writer.pop();
|
||||
assert_eq!(writer.as_str(), "root");
|
||||
|
||||
writer.push("k8s.node.id");
|
||||
assert_eq!(writer.as_str(), "root\u{1}k8s.node.id");
|
||||
|
||||
writer.set_expand_dots(true);
|
||||
writer.pop();
|
||||
writer.push("k8s.node.id");
|
||||
assert_eq!(writer.as_str(), "root\u{1}k8s\u{1}node\u{1}id");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_json_path_expand_dots_enabled_pop_segment() {
|
||||
let mut json_writer = JsonPathWriter::with_expand_dots(true);
|
||||
json_writer.push("hello");
|
||||
assert_eq!(json_writer.as_str(), "hello");
|
||||
json_writer.push("color.hue");
|
||||
assert_eq!(json_writer.as_str(), "hello\x01color\x01hue");
|
||||
json_writer.pop();
|
||||
assert_eq!(json_writer.as_str(), "hello");
|
||||
}
|
||||
}
|
||||
@@ -5,19 +5,20 @@ use std::ops::Deref;
|
||||
pub use byteorder::LittleEndian as Endianness;
|
||||
|
||||
mod bitset;
|
||||
pub mod bounds;
|
||||
mod byte_count;
|
||||
mod datetime;
|
||||
pub mod file_slice;
|
||||
mod group_by;
|
||||
pub mod json_path_writer;
|
||||
mod serialize;
|
||||
mod vint;
|
||||
mod writer;
|
||||
pub use bitset::*;
|
||||
pub use byte_count::ByteCount;
|
||||
#[allow(deprecated)]
|
||||
pub use datetime::DatePrecision;
|
||||
pub use datetime::{DateTime, DateTimePrecision};
|
||||
pub use group_by::GroupByIteratorExtended;
|
||||
pub use json_path_writer::JsonPathWriter;
|
||||
pub use ownedbytes::{OwnedBytes, StableDeref};
|
||||
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
|
||||
pub use vint::{
|
||||
@@ -116,6 +117,7 @@ pub fn u64_to_f64(val: u64) -> f64 {
|
||||
///
|
||||
/// This function assumes that the needle is rarely contained in the bytes string
|
||||
/// and offers a fast path if the needle is not present.
|
||||
#[inline]
|
||||
pub fn replace_in_place(needle: u8, replacement: u8, bytes: &mut [u8]) {
|
||||
if !bytes.contains(&needle) {
|
||||
return;
|
||||
@@ -128,11 +130,11 @@ pub fn replace_in_place(needle: u8, replacement: u8, bytes: &mut [u8]) {
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
pub mod test {
|
||||
pub(crate) mod test {
|
||||
|
||||
use proptest::prelude::*;
|
||||
|
||||
use super::{f64_to_u64, i64_to_u64, u64_to_f64, u64_to_i64, BinarySerializable, FixedSize};
|
||||
use super::{f64_to_u64, i64_to_u64, u64_to_f64, u64_to_i64};
|
||||
|
||||
fn test_i64_converter_helper(val: i64) {
|
||||
assert_eq!(u64_to_i64(i64_to_u64(val)), val);
|
||||
@@ -142,12 +144,6 @@ pub mod test {
|
||||
assert_eq!(u64_to_f64(f64_to_u64(val)), val);
|
||||
}
|
||||
|
||||
pub fn fixed_size_test<O: BinarySerializable + FixedSize + Default>() {
|
||||
let mut buffer = Vec::new();
|
||||
O::default().serialize(&mut buffer).unwrap();
|
||||
assert_eq!(buffer.len(), O::SIZE_IN_BYTES);
|
||||
}
|
||||
|
||||
proptest! {
|
||||
#[test]
|
||||
fn test_f64_converter_monotonicity_proptest((left, right) in (proptest::num::f64::NORMAL, proptest::num::f64::NORMAL)) {
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
use std::borrow::Cow;
|
||||
use std::io::{Read, Write};
|
||||
use std::{fmt, io};
|
||||
|
||||
@@ -73,14 +74,14 @@ impl FixedSize for () {
|
||||
|
||||
impl<T: BinarySerializable> BinarySerializable for Vec<T> {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
|
||||
VInt(self.len() as u64).serialize(writer)?;
|
||||
BinarySerializable::serialize(&VInt(self.len() as u64), writer)?;
|
||||
for it in self {
|
||||
it.serialize(writer)?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Vec<T>> {
|
||||
let num_items = VInt::deserialize(reader)?.val();
|
||||
let num_items = <VInt as BinarySerializable>::deserialize(reader)?.val();
|
||||
let mut items: Vec<T> = Vec::with_capacity(num_items as usize);
|
||||
for _ in 0..num_items {
|
||||
let item = T::deserialize(reader)?;
|
||||
@@ -235,12 +236,12 @@ impl FixedSize for bool {
|
||||
impl BinarySerializable for String {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
|
||||
let data: &[u8] = self.as_bytes();
|
||||
VInt(data.len() as u64).serialize(writer)?;
|
||||
BinarySerializable::serialize(&VInt(data.len() as u64), writer)?;
|
||||
writer.write_all(data)
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> io::Result<String> {
|
||||
let string_length = VInt::deserialize(reader)?.val() as usize;
|
||||
let string_length = <VInt as BinarySerializable>::deserialize(reader)?.val() as usize;
|
||||
let mut result = String::with_capacity(string_length);
|
||||
reader
|
||||
.take(string_length as u64)
|
||||
@@ -249,11 +250,47 @@ impl BinarySerializable for String {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> BinarySerializable for Cow<'a, str> {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
|
||||
let data: &[u8] = self.as_bytes();
|
||||
BinarySerializable::serialize(&VInt(data.len() as u64), writer)?;
|
||||
writer.write_all(data)
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Cow<'a, str>> {
|
||||
let string_length = <VInt as BinarySerializable>::deserialize(reader)?.val() as usize;
|
||||
let mut result = String::with_capacity(string_length);
|
||||
reader
|
||||
.take(string_length as u64)
|
||||
.read_to_string(&mut result)?;
|
||||
Ok(Cow::Owned(result))
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> BinarySerializable for Cow<'a, [u8]> {
|
||||
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> io::Result<()> {
|
||||
BinarySerializable::serialize(&VInt(self.len() as u64), writer)?;
|
||||
for it in self.iter() {
|
||||
BinarySerializable::serialize(it, writer)?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn deserialize<R: Read>(reader: &mut R) -> io::Result<Cow<'a, [u8]>> {
|
||||
let num_items = <VInt as BinarySerializable>::deserialize(reader)?.val();
|
||||
let mut items: Vec<u8> = Vec::with_capacity(num_items as usize);
|
||||
for _ in 0..num_items {
|
||||
let item = <u8 as BinarySerializable>::deserialize(reader)?;
|
||||
items.push(item);
|
||||
}
|
||||
Ok(Cow::Owned(items))
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
pub mod test {
|
||||
|
||||
use super::{VInt, *};
|
||||
use crate::serialize::BinarySerializable;
|
||||
use super::*;
|
||||
pub fn fixed_size_test<O: BinarySerializable + FixedSize + Default>() {
|
||||
let mut buffer = Vec::new();
|
||||
O::default().serialize(&mut buffer).unwrap();
|
||||
|
||||
@@ -151,7 +151,7 @@ pub fn read_u32_vint_no_advance(data: &[u8]) -> (u32, usize) {
|
||||
(result, vlen)
|
||||
}
|
||||
/// Write a `u32` as a vint payload.
|
||||
pub fn write_u32_vint<W: io::Write>(val: u32, writer: &mut W) -> io::Result<()> {
|
||||
pub fn write_u32_vint<W: io::Write + ?Sized>(val: u32, writer: &mut W) -> io::Result<()> {
|
||||
let mut buf = [0u8; 8];
|
||||
let data = serialize_vint_u32(val, &mut buf);
|
||||
writer.write_all(data)
|
||||
|
||||
@@ -87,7 +87,7 @@ impl<W: TerminatingWrite> TerminatingWrite for BufWriter<W> {
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a> TerminatingWrite for &'a mut Vec<u8> {
|
||||
impl TerminatingWrite for &mut Vec<u8> {
|
||||
fn terminate_ref(&mut self, _a: AntiCallToken) -> io::Result<()> {
|
||||
self.flush()
|
||||
}
|
||||
|
||||
BIN
doc/assets/images/paradedb.png
Normal file
BIN
doc/assets/images/paradedb.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 30 KiB |
@@ -2,7 +2,7 @@
|
||||
|
||||
> Tantivy is a **search** engine **library** for Rust.
|
||||
|
||||
If you are familiar with Lucene, it's an excellent approximation to consider tantivy as Lucene for rust. tantivy is heavily inspired by Lucene's design and
|
||||
If you are familiar with Lucene, it's an excellent approximation to consider tantivy as Lucene for Rust. Tantivy is heavily inspired by Lucene's design and
|
||||
they both have the same scope and targeted use cases.
|
||||
|
||||
If you are not familiar with Lucene, let's break down our little tagline.
|
||||
@@ -17,7 +17,7 @@ relevancy, collapsing, highlighting, spatial search.
|
||||
experience. But keep in mind this is just a toolbox.
|
||||
Which bring us to the second keyword...
|
||||
|
||||
- **Library** means that you will have to write code. tantivy is not an *all-in-one* server solution like elastic search for instance.
|
||||
- **Library** means that you will have to write code. Tantivy is not an *all-in-one* server solution like Elasticsearch for instance.
|
||||
|
||||
Sometimes a functionality will not be available in tantivy because it is too
|
||||
specific to your use case. By design, tantivy should make it possible to extend
|
||||
@@ -31,4 +31,4 @@ relevancy, collapsing, highlighting, spatial search.
|
||||
index from a different format.
|
||||
|
||||
Tantivy exposes a lot of low level API to do all of these things.
|
||||
|
||||
|
||||
|
||||
@@ -11,7 +11,7 @@ directory shipped with tantivy is the `MmapDirectory`.
|
||||
While this design has some downsides, this greatly simplifies the source code of
|
||||
tantivy. Caching is also entirely delegated to the OS.
|
||||
|
||||
`tantivy` works entirely (or almost) by directly reading the datastructures as they are laid on disk. As a result, the act of opening an indexing does not involve loading different datastructures from the disk into random access memory : starting a process, opening an index, and performing your first query can typically be done in a matter of milliseconds.
|
||||
Tantivy works entirely (or almost) by directly reading the datastructures as they are laid on disk. As a result, the act of opening an indexing does not involve loading different datastructures from the disk into random access memory : starting a process, opening an index, and performing your first query can typically be done in a matter of milliseconds.
|
||||
|
||||
This is an interesting property for a command line search engine, or for some multi-tenant log search engine : spawning a new process for each new query can be a perfectly sensible solution in some use case.
|
||||
|
||||
|
||||
@@ -7,6 +7,11 @@
|
||||
- [Other](#other)
|
||||
- [Usage](#usage)
|
||||
|
||||
# Index Sorting has been removed!
|
||||
More infos here:
|
||||
|
||||
https://github.com/quickwit-oss/tantivy/issues/2352
|
||||
|
||||
# Index Sorting
|
||||
|
||||
Tantivy allows you to sort the index according to a property.
|
||||
@@ -26,13 +31,13 @@ Compression ratio is mainly affected on the fast field of the sorted property, e
|
||||
When data is presorted by a field and search queries request sorting by the same field, we can leverage the natural order of the documents.
|
||||
E.g. if the data is sorted by timestamp and want the top n newest docs containing a term, we can simply leveraging the order of the docids.
|
||||
|
||||
Note: Tantivy 0.16 does not do this optimization yet.
|
||||
Note: tantivy 0.16 does not do this optimization yet.
|
||||
|
||||
### Pruning
|
||||
|
||||
Let's say we want all documents and want to apply the filter `>= 2010-08-11`. When the data is sorted, we could make a lookup in the fast field to find the docid range and use this as the filter.
|
||||
|
||||
Note: Tantivy 0.16 does not do this optimization yet.
|
||||
Note: tantivy 0.16 does not do this optimization yet.
|
||||
|
||||
### Other?
|
||||
|
||||
@@ -40,7 +45,7 @@ In principle there are many algorithms possible that exploit the monotonically i
|
||||
|
||||
## Usage
|
||||
|
||||
The index sorting can be configured setting [`sort_by_field`](https://github.com/quickwit-oss/tantivy/blob/000d76b11a139a84b16b9b95060a1c93e8b9851c/src/core/index_meta.rs#L238) on `IndexSettings` and passing it to a `IndexBuilder`. As of Tantivy 0.16 only fast fields are allowed to be used.
|
||||
The index sorting can be configured setting [`sort_by_field`](https://github.com/quickwit-oss/tantivy/blob/000d76b11a139a84b16b9b95060a1c93e8b9851c/src/core/index_meta.rs#L238) on `IndexSettings` and passing it to a `IndexBuilder`. As of tantivy 0.16 only fast fields are allowed to be used.
|
||||
|
||||
```rust
|
||||
let settings = IndexSettings {
|
||||
|
||||
@@ -39,7 +39,7 @@ Its representation is done by separating segments by a unicode char `\x01`, and
|
||||
- `value`: The value representation is just the regular Value representation.
|
||||
|
||||
This representation is designed to align the natural sort of Terms with the lexicographical sort
|
||||
of their binary representation (Tantivy's dictionary (whether fst or sstable) is sorted and does prefix encoding).
|
||||
of their binary representation (tantivy's dictionary (whether fst or sstable) is sorted and does prefix encoding).
|
||||
|
||||
In the example above, the terms will be sorted as
|
||||
|
||||
|
||||
@@ -12,7 +12,7 @@ use tantivy::aggregation::agg_result::AggregationResults;
|
||||
use tantivy::aggregation::AggregationCollector;
|
||||
use tantivy::query::AllQuery;
|
||||
use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing, FAST};
|
||||
use tantivy::Index;
|
||||
use tantivy::{Index, IndexWriter, TantivyDocument};
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
// # Create Schema
|
||||
@@ -132,10 +132,10 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let stream = Deserializer::from_str(data).into_iter::<Value>();
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
let mut num_indexed = 0;
|
||||
for value in stream {
|
||||
let doc = schema.parse_document(&serde_json::to_string(&value.unwrap())?)?;
|
||||
let doc = TantivyDocument::parse_json(&schema, &serde_json::to_string(&value.unwrap())?)?;
|
||||
index_writer.add_document(doc)?;
|
||||
num_indexed += 1;
|
||||
if num_indexed > 4 {
|
||||
|
||||
@@ -15,7 +15,7 @@
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, ReloadPolicy};
|
||||
use tantivy::{doc, Index, IndexWriter, ReloadPolicy};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn main() -> tantivy::Result<()> {
|
||||
@@ -75,7 +75,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// Here we give tantivy a budget of `50MB`.
|
||||
// Using a bigger memory_arena for the indexer may increase
|
||||
// throughput, but 50 MB is already plenty.
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
let mut index_writer: IndexWriter = index.writer(50_000_000)?;
|
||||
|
||||
// Let's index our documents!
|
||||
// We first need a handle on the title and the body field.
|
||||
@@ -87,7 +87,7 @@ fn main() -> tantivy::Result<()> {
|
||||
let title = schema.get_field("title").unwrap();
|
||||
let body = schema.get_field("body").unwrap();
|
||||
|
||||
let mut old_man_doc = Document::default();
|
||||
let mut old_man_doc = TantivyDocument::default();
|
||||
old_man_doc.add_text(title, "The Old Man and the Sea");
|
||||
old_man_doc.add_text(
|
||||
body,
|
||||
@@ -164,7 +164,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// will reload the index automatically after each commit.
|
||||
let reader = index
|
||||
.reader_builder()
|
||||
.reload_policy(ReloadPolicy::OnCommit)
|
||||
.reload_policy(ReloadPolicy::OnCommitWithDelay)
|
||||
.try_into()?;
|
||||
|
||||
// We now need to acquire a searcher.
|
||||
@@ -217,9 +217,23 @@ fn main() -> tantivy::Result<()> {
|
||||
// the document returned will only contain
|
||||
// a title.
|
||||
for (_score, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
println!("{}", schema.to_json(&retrieved_doc));
|
||||
let retrieved_doc: TantivyDocument = searcher.doc(doc_address)?;
|
||||
println!("{}", retrieved_doc.to_json(&schema));
|
||||
}
|
||||
|
||||
// We can also get an explanation to understand
|
||||
// how a found document got its score.
|
||||
let query = query_parser.parse_query("title:sea^20 body:whale^70")?;
|
||||
|
||||
let (_score, doc_address) = searcher
|
||||
.search(&query, &TopDocs::with_limit(1))?
|
||||
.into_iter()
|
||||
.next()
|
||||
.unwrap();
|
||||
|
||||
let explanation = query.explain(&searcher, doc_address)?;
|
||||
|
||||
println!("{}", explanation.to_pretty_json());
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user