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Author SHA1 Message Date
bors[bot]
f1d848bb9a
Merge #552 
552: Fix escaped quotes in filter r=Kerollmops a=irevoire

Will fix https://github.com/meilisearch/meilisearch/issues/2380

The issue was that in the evaluation of the filter, I was using the deref implementation instead of calling the `value` method of my token.

To avoid the problem happening again, I removed the deref implementation; now, you need to either call the `lexeme` or the `value` methods but can't rely on a « default » implementation to get a string out of a token.

Co-authored-by: Tamo <tamo@meilisearch.com>
 2022-06-09 14:56:44 +00:00
Tamo
676187ba43
bump milli version 2022-06-09 16:53:32 +02:00
Tamo
90afde435b
fix escaped quotes in filter 2022-06-09 16:03:49 +02:00
Kerollmops
445d5474cc
Add the pagination_limited_to setting to the database 2022-06-08 18:14:27 +02:00
Kerollmops
69931e50d2
Add the max_values_by_facet setting to the database 2022-06-08 17:54:56 +02:00
Kerollmops
52a494bd3b
Add the new pagination.limited_to and faceting.max_values_per_facet settings 2022-06-08 17:15:36 +02:00
bors[bot]
9580b9de79
Merge #549 
549: Bump the version to 0.29.2 r=curquiza a=Kerollmops



Co-authored-by: Kerollmops <clement@meilisearch.com>
 2022-06-08 14:29:47 +00:00
Kerollmops
56ee9cc21f
Bump the version to 0.29.2 2022-06-08 16:00:06 +02:00
Kerollmops
2a505503b3
Change the number of facet values returned by default to 100 2022-06-08 15:58:57 +02:00
Kerollmops
bae4007447
Remove the hard limit on the number of facet values returned 2022-06-08 15:58:57 +02:00
bors[bot]
7313d6c533
Merge #547 
547: Update version for next release (v0.29.1) r=Kerollmops a=curquiza

A new milli version will be released once this PR is merged https://github.com/meilisearch/milli/pull/543

Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
 2022-06-08 10:20:24 +00:00
Clémentine Urquizar
478dbfa45a
Update version for next release (v0.29.1) 2022-06-07 18:59:33 +02:00
Tamo
d0aaa7ff00
Fix wrong internal ids assignments 2022-06-07 15:49:33 +02:00
ad hoc
31776fdc3f
add failing test 2022-06-07 15:49:33 +02:00
bors[bot]
05ae6dbfa4
Merge #541 
541: Update version for next release (v0.29.0) r=ManyTheFish a=curquiza

Need to update the version since #540 was merged and breaking

Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
 2022-06-02 16:53:28 +00:00
ManyTheFish
d212dc6b8b Remove useless newline 2022-06-02 18:22:56 +02:00
Clémentine Urquizar
6ce1c6487a
Update version for next release (v0.29.0) 2022-06-02 18:07:55 +02:00
ManyTheFish
7aabe42ae0 Refactor matching words 2022-06-02 17:59:04 +02:00
ManyTheFish
86ac8568e6 Use Charabia in milli 2022-06-02 16:59:11 +02:00
ManyTheFish
192e024ada Add Charabia in Cargo.toml 2022-06-02 16:59:07 +02:00
Clémentine Urquizar
c19c17eddb
Update version to v0.28.1 2022-06-01 18:31:02 +02:00
bors[bot]
74d1914a64
Merge #535 
535: Reintroduce the max values by facet limit r=ManyTheFish a=Kerollmops

This PR reintroduces the max values by facet limit this is related to https://github.com/meilisearch/meilisearch/issues/2349.

~I would like some help in deciding on whether I keep the default 100 max values in milli and set up the `FacetDistribution` settings in Meilisearch to use 1000 as the new value, I expose the `max_values_by_facet` for this purpose.~

I changed the default value to 1000 and the max to 10000, thank you `@ManyTheFish` for the help!

Co-authored-by: Kerollmops <clement@meilisearch.com>
 2022-06-01 14:30:50 +00:00
bors[bot]
582930dbbb
Merge #538 
538: speedup exact words r=Kerollmops a=MarinPostma

This PR make `exact_words` return an `Option` instead of an empty set, since set creation is costly, as noticed by `@kerollmops.`

I was not convinces that this was the cause for all of the performance drop we measured, and then realized that methods that initialized it were called recursively which caused initialization times to add up. While the first fix solves the issue when not using exact words, using exact word remained way more expensive that it should be. To address this issue, the exact words are cached into the `Context`, so they are only initialized once.


Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-05-30 08:20:34 +00:00
ad hoc
25fc576696
review changes 2022-05-24 14:15:33 +02:00
ad hoc
69dc4de80f
change &Option<Set> to Option<&Set> 2022-05-24 12:14:55 +02:00
ad hoc
ac975cc747
cache context's exact words 2022-05-24 09:43:17 +02:00
ad hoc
8993fec8a3
return optional exact words 2022-05-24 09:15:49 +02:00
Matthias Wright
754f48a4fb Improves ranking rules error message 2022-05-20 21:25:43 +02:00
Kerollmops
cd7c6e19ed
Reintroduce the max values by facet limit 2022-05-18 15:57:57 +02:00
ManyTheFish
895f5d8a26 Bump milli version 2022-05-18 10:37:12 +02:00
ManyTheFish
137434a1c8 Add some implementation on MatchBounds 2022-05-17 15:57:09 +02:00
bors[bot]
08c6d50cd1
Merge #531 
531: fix the mixed dataset geosearch indexing bug r=Kerollmops a=irevoire

port #529 to main

Co-authored-by: Tamo <tamo@meilisearch.com>
 2022-05-16 16:06:36 +00:00
bors[bot]
cf3e574cb4
Merge #530 
530: fix the searchable fields bug when a field is nested r=Kerollmops a=irevoire

port #528 to main

Co-authored-by: Tamo <tamo@meilisearch.com>
 2022-05-16 15:52:30 +00:00
Tamo
0af399a6d7
fix the mixed dataset geosearch indexing bug 2022-05-16 17:37:45 +02:00
Tamo
f586028f9a
fix the searchable fields bug when a field is nested 
Update milli/src/index.rs

Co-authored-by: Clément Renault <clement@meilisearch.com>
 2022-05-16 17:24:36 +02:00
bors[bot]
e1e85267fd
Merge #526 
526: remove useless comment r=irevoire a=MarinPostma



Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-05-16 10:01:43 +00:00
bors[bot]
51809eb260
Merge #525 
525: Simplify the error creation with thiserror r=irevoire a=irevoire

I introduced [`thiserror`](https://docs.rs/thiserror/latest/thiserror/) to implements all the `Display` trait and most of the `impl From<xxx> for yyy` in way less lines.
And then I introduced a cute macro to implements the `impl<X, Y, Z> From<X> for Z where Y: From<X>, Z: From<X>` more easily.

Co-authored-by: Tamo <tamo@meilisearch.com>
 2022-05-04 15:47:32 +00:00
Tamo
484a9ddb27
Simplify the error creation with thiserror and a smol friendly macro 2022-05-04 17:24:00 +02:00
bors[bot]
65e6aa0de2
Merge #523 
523: Improve geosearch error messages r=irevoire a=irevoire

Improve the geosearch error messages (#488).
And try to parse the string as specified in https://github.com/meilisearch/meilisearch/issues/2354

Co-authored-by: Tamo <tamo@meilisearch.com>
 2022-05-04 13:36:11 +00:00
Tamo
c55368ddd4
apply code suggestion 
Co-authored-by: Kerollmops <kero@meilisearch.com>
 2022-05-04 14:11:03 +02:00
ad hoc
5ad5d56f7e
remove useless comment 2022-05-04 10:43:54 +02:00
bors[bot]
0c2c8af44e
Merge #520 
520: fix mistake in Settings initialization r=irevoire a=MarinPostma

fix settings not being correctly initialized and add a test to make sure that they are in the future.

fix https://github.com/meilisearch/meilisearch/issues/2358


Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-05-03 15:32:18 +00:00
Kerollmops
211c8763b9
Make sure that we do not generate too long keys 2022-05-03 10:03:15 +02:00
Kerollmops
7e47031bdc
Add a test for long keys in LMDB 2022-05-03 10:03:13 +02:00
Tamo
3cb1f6d0a1
improve geosearch error messages 2022-05-02 19:20:47 +02:00
ad hoc
1ee3d6ae33
fix mistake in Settings initialization 2022-04-29 16:24:25 +02:00
bors[bot]
9db86aac51
Merge #518 
518: Return facets even when there is no value associated to it r=Kerollmops a=Kerollmops

This PR is related to https://github.com/meilisearch/meilisearch/issues/2352 and should fix the issue when Meilisearch is up-to-date with this PR.

Co-authored-by: Kerollmops <clement@meilisearch.com>
 2022-04-28 09:04:36 +00:00
Kerollmops
a4d343aade
Add a test to check for the returned facet distribution 2022-04-26 18:12:58 +02:00
bors[bot]
c2bd94c871
Merge #511 
511: Update version in every workspace r=curquiza a=curquiza

Checked with `@Kerollmops` 

- Update the version into every workspace (the current version is v0.27.0, but I forgot to update it for the previous release)
- add `publish = false` except in `milli` workspace.


Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
 2022-04-26 16:06:47 +00:00
Kerollmops
7d1c2d97bf
Return facets even when there is no values associated to it 2022-04-26 17:59:53 +02:00
bors[bot]
d388ea0f9d
Merge #506 
506: fix cargo warnings r=Kerollmops a=MarinPostma

fix cargo warnings


Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-04-26 15:45:20 +00:00
ad hoc
5c29258e8e
fix cargo warnings 2022-04-26 17:33:11 +02:00
bors[bot]
2fdf520271
Merge #514 
514: Stop flattening every field r=Kerollmops a=irevoire

When we need to flatten a document:
* The primary key contains a `.`.
* Some fields need to be flattened

Instead of flattening the whole object and thus creating a lot of allocations with the `serde_json_flatten_crate`, we instead generate a minimal sub-object containing only the fields that need to be flattened.
That should create fewer allocations and thus index faster.

---------

```
group                                                             indexing_main_e1e362fa                 indexing_stop-flattening-every-field_40d1bd6b
-----                                                             ----------------------                 ---------------------------------------------
indexing/Indexing geo_point                                       1.99      23.7±0.23s        ? ?/sec    1.00      11.9±0.21s        ? ?/sec
indexing/Indexing movies in three batches                         1.00      18.2±0.24s        ? ?/sec    1.01      18.3±0.29s        ? ?/sec
indexing/Indexing movies with default settings                    1.00      17.5±0.09s        ? ?/sec    1.01      17.7±0.26s        ? ?/sec
indexing/Indexing songs in three batches with default settings    1.00      64.8±0.47s        ? ?/sec    1.00      65.1±0.49s        ? ?/sec
indexing/Indexing songs with default settings                     1.00      54.9±0.99s        ? ?/sec    1.01      55.7±1.34s        ? ?/sec
indexing/Indexing songs without any facets                        1.00      50.6±0.62s        ? ?/sec    1.01      50.9±1.05s        ? ?/sec
indexing/Indexing songs without faceted numbers                   1.00      54.0±1.14s        ? ?/sec    1.01      54.7±1.13s        ? ?/sec
indexing/Indexing wiki                                            1.00     996.2±8.54s        ? ?/sec    1.02   1021.1±30.63s        ? ?/sec
indexing/Indexing wiki in three batches                           1.00    1136.8±9.72s        ? ?/sec    1.00    1138.6±6.59s        ? ?/sec
```

So basically everything slowed down a liiiiiittle bit except the dataset with a nested field which got twice faster

Co-authored-by: Tamo <tamo@meilisearch.com>
 2022-04-26 11:50:33 +00:00
Tamo
f19d2dc548
Only flatten the required fields 
apply review comments

Co-authored-by: Kerollmops <kero@meilisearch.com>
 2022-04-26 12:33:46 +02:00
Clémentine Urquizar
d138b3c704
Update version 2022-04-25 18:43:46 +02:00
Tamo
fa6f495662
fix the indexing fuzzer 2022-04-25 18:32:06 +02:00
bors[bot]
8010eca9c7
Merge #505 
505: normalize exact words r=curquiza a=MarinPostma

Normalize the exact words, as specified in the specification.


Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-04-25 09:35:32 +00:00
ad hoc
2e0089d5ff
normalize exact words 2022-04-21 15:38:40 +02:00
ad hoc
3a2451fcba
add test normalize exact words 2022-04-21 13:52:09 +02:00
Clément Renault
eb5830aa40
Add a test to make sure that long words are handled 2022-04-21 13:45:28 +02:00
ad hoc
8b14090927
fix min-word-len-for-typo not reset properly 2022-04-19 15:20:16 +02:00
bors[bot]
ea4bb9402f
Merge #483 
483: Enhance matching words r=Kerollmops a=ManyTheFish

# Summary

Enhance milli word-matcher making it handle match computing and cropping.

# Implementation

## Computing best matches for cropping

Before we were considering that the first match of the attribute was the best one, this was accurate when only one word was searched but was missing the target when more than one word was searched.

Now we are searching for the best matches interval to crop around, the chosen interval is the one:
1) that have the highest count of unique matches
> for example, if we have a query `split the world`, then the interval `the split the split the` has 5 matches but only 2 unique matches (1 for `split` and 1 for `the`) where the interval `split of the world` has 3 matches and 3 unique matches. So the interval `split of the world` is considered better.
2) that have the minimum distance between matches
> for example, if we have a query `split the world`, then the interval `split of the world` has a distance of 3 (2 between `split` and `the`, and 1 between `the` and `world`) where the interval `split the world` has a distance of 2. So the interval `split the world` is considered better.
3) that have the highest count of ordered matches
> for example, if we have a query `split the world`, then the interval `the world split` has 2 ordered words where the interval `split the world` has 3. So the interval `split the world` is considered better.

## Cropping around the best matches interval

Before we were cropping around the interval without checking the context.

Now we are cropping around words in the same context as matching words.
This means that we will keep words that are farther from the matching words but are in the same phrase, than words that are nearer but separated by a dot.

> For instance, for the matching word `Split` the text:
`Natalie risk her future. Split The World is a book written by Emily Henry. I never read it.`
will be cropped like:
`…. Split The World is a book written by Emily Henry. …`
and  not like:
`Natalie risk her future. Split The World is a book …`


Co-authored-by: ManyTheFish <many@meilisearch.com>
 2022-04-19 11:42:32 +00:00
ManyTheFish
f1115e274f Use Copy impl of FormatOption instead of clonning 2022-04-19 10:35:50 +02:00
Clémentine Urquizar
8d630a6f62
Update version for the next release (v0.26.1) 2022-04-14 11:44:06 +02:00
Tamo
00f78d6b5a
Apply code suggestions 
Co-authored-by: Clément Renault <clement@meilisearch.com>
 2022-04-14 11:14:08 +02:00
Tamo
399fba16bb
only flatten an object if it's nested 2022-04-14 11:14:08 +02:00
Tamo
ee64f4a936
Use smartstring to store the external id in our hashmap 
We need to store all the external id (primary key) in a hashmap
associated to their internal id during.
The smartstring remove heap allocation / memory usage and should
improve the cache locality.
 2022-04-13 21:22:07 +02:00
ad hoc
dda28d7415
exclude excluded canditates from search result candidates 2022-04-13 12:10:35 +02:00
ad hoc
cd83014fff
add test for disctinct nb hits 2022-04-13 12:10:35 +02:00
ad hoc
bbb6728d2f
add distinct attributes to cli 2022-04-13 12:10:35 +02:00
ManyTheFish
5809d3ae0d Add first benchmarks on formatting 2022-04-12 16:31:58 +02:00
ManyTheFish
827cedcd15 Add format option structure 2022-04-12 13:42:14 +02:00
ManyTheFish
011f8210ed Make compute_matches more rust idiomatic 2022-04-12 10:19:02 +02:00
ManyTheFish
a16de5de84 Symplify format and remove intermediate function 2022-04-08 11:20:41 +02:00
ManyTheFish
a769e09dfa Make token_crop_bounds more rust idiomatic 2022-04-07 20:15:14 +02:00
bors[bot]
9ac2fd1c37
Merge #487 
487: Update version (v0.26.0) r=Kerollmops a=curquiza

breaking because of #458 

Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
 2022-04-07 17:10:24 +00:00
Tamo
bab898ce86
move the flatten-serde-json crate inside of milli 2022-04-07 18:20:44 +02:00
ManyTheFish
c8ed1675a7 Add some documentation 2022-04-07 17:32:13 +02:00
ManyTheFish
b1905dfa24 Make split_best_frequency returns references instead of owned data 2022-04-07 17:05:44 +02:00
Tamo
ab458d8840
fix tests after rebase 2022-04-07 17:00:00 +02:00
Irevoire
4f3ce6d9cd
nested fields 2022-04-07 16:58:46 +02:00
Clémentine Urquizar
ee1d627803
Update version (v0.26.0) 2022-04-07 15:56:10 +02:00
bors[bot]
4ae7aea3b2
Merge #486 
486: Update version (v0.25.0) r=curquiza a=curquiza

v0.25.0 will be released once #478 is merged

Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
 2022-04-06 11:40:41 +00:00
ad hoc
b799f3326b
rename merge_nothing to merge_ignore_values 2022-04-05 18:44:35 +02:00
ManyTheFish
fa7d3a37c0 Make some cleaning and add comments 2022-04-05 17:48:56 +02:00
ManyTheFish
3bb1e35ada Fix match count 2022-04-05 17:48:45 +02:00
ManyTheFish
56e0edd621 Put crop markers direclty around words 2022-04-05 17:41:32 +02:00
ManyTheFish
a93cd8c61c Fix prefix highlight with special chars 2022-04-05 17:41:32 +02:00
ManyTheFish
b3f0f39106 Make some cleaning 2022-04-05 17:41:32 +02:00
ManyTheFish
6dc345bc53 Test and Fix prefix highlight 2022-04-05 17:41:32 +02:00
ManyTheFish
bd30ee97b8 Keep separators at start of the croped string 2022-04-05 17:41:32 +02:00
ManyTheFish
29c5f76d7f Use new matcher in http-ui 2022-04-05 17:41:32 +02:00
ManyTheFish
734d0899d3 Publish Matcher 2022-04-05 17:41:32 +02:00
ManyTheFish
4428cb5909 Add some tests and fix some corner cases 2022-04-05 17:41:32 +02:00
ManyTheFish
844f546a8b Add matches algorithm V1 2022-04-05 17:41:32 +02:00
ManyTheFish
3be1790803 Add crop algorithm with naive match algorithm 2022-04-05 17:41:32 +02:00
ManyTheFish
d96e72e5dc Create formater with some tests 2022-04-05 17:41:32 +02:00
ad hoc
201fea0fda
limit extract_word_docids memory usage 2022-04-05 14:14:15 +02:00
ad hoc
5cfd3d8407
add exact attributes documentation 2022-04-05 14:10:22 +02:00
Clémentine Urquizar
9eec44dd98
Update version (v0.25.0) 2022-04-05 12:06:42 +02:00
ad hoc
b85cd4983e
remove field_id_from_position 2022-04-05 09:50:34 +02:00
ad hoc
ab185a59b5
fix infos 2022-04-05 09:46:56 +02:00
ad hoc
59e41d98e3
add comments to integration test 2022-04-04 21:17:06 +02:00
ad hoc
1810927dbd
rephrase exact_attributes doc 2022-04-04 21:04:49 +02:00
ad hoc
b7694c34f5
remove println 2022-04-04 21:00:07 +02:00
ad hoc
6cabd47c32
fix typo in comment 2022-04-04 20:59:20 +02:00
ad hoc
c8d3a09af8
add integration test for disabel typo on attributes 2022-04-04 20:54:03 +02:00
ad hoc
6b2c2509b2
fix bug in exact search 2022-04-04 20:54:03 +02:00
ad hoc
56b4f5dce2
add exact prefix to query_docids 2022-04-04 20:54:03 +02:00
ad hoc
21ae4143b1
add exact_word_prefix to Context 2022-04-04 20:54:03 +02:00
ad hoc
e8f06f6c06
extract exact_word_prefix_docids 2022-04-04 20:54:03 +02:00
ad hoc
6dd2e4ffbd
introduce exact_word_prefix database in index 2022-04-04 20:54:03 +02:00
ad hoc
ba0bb29cd8
refactor WordPrefixDocids to take dbs instead of indexes 2022-04-04 20:54:02 +02:00
ad hoc
c4c6e35352
query exact_word_docids in resolve_query_tree 2022-04-04 20:54:02 +02:00
ad hoc
8d46a5b0b5
extract exact word docids 2022-04-04 20:54:02 +02:00
ad hoc
5451c64d5d
increase criteria asc desc test map size 2022-04-04 20:54:02 +02:00
ad hoc
0a77be4ec0
introduce exact_word_docids db 2022-04-04 20:54:02 +02:00
ad hoc
5f9f82757d
refactor spawn_extraction_task 2022-04-04 20:54:02 +02:00
ad hoc
f82d4b36eb
introduce exact attribute setting 2022-04-04 20:54:02 +02:00
ad hoc
c882d8daf0
add test for exact words 2022-04-04 20:54:01 +02:00
ad hoc
7e9d56a9e7
disable typos on exact words 2022-04-04 20:54:01 +02:00
ad hoc
3e67d8818c
fix typo in test comment 2022-04-04 20:34:23 +02:00
ad hoc
284d8a24e0
add intergration test for disabled typon on word 2022-04-04 20:15:51 +02:00
ad hoc
30a2711bac
rename serde module to serde_impl module 
needed because of issues with rustfmt
 2022-04-04 20:10:55 +02:00
ad hoc
0fd55db21c
fmt 2022-04-04 20:10:55 +02:00
ad hoc
559e46be5e
fix bad rebase bug 2022-04-04 20:10:55 +02:00
ad hoc
8b1e5d9c6d
add test for exact words 2022-04-04 20:10:55 +02:00
ad hoc
774fa8f065
disable typos on exact words 2022-04-04 20:10:55 +02:00
ad hoc
9bbffb8fee
add exact words setting 2022-04-04 20:10:54 +02:00
ad hoc
853b4a520f
fmt 2022-04-04 10:41:46 +02:00
ad hoc
2cb71dff4a
add typo integration tests 2022-04-04 10:41:46 +02:00
ad hoc
1941072bb2
implement Copy on Setting 2022-04-04 10:41:46 +02:00
ad hoc
fdaf45aab2
replace hardcoded value with constant in TestContext 2022-04-04 10:41:46 +02:00
ad hoc
950a740bd4
refactor typos for readability 2022-04-04 10:41:46 +02:00
ad hoc
66020cd923
rename min_word_len* to use plain letter numbers 2022-04-04 10:41:46 +02:00
ad hoc
4c4b336ecb
rename min word len for typo error 2022-04-01 11:17:03 +02:00
ad hoc
286dd7b2e4
rename min_word_len_2_typo 2022-04-01 11:17:03 +02:00
ad hoc
55af85db3c
add tests for min_word_len_for_typo 2022-04-01 11:17:02 +02:00
ad hoc
9102de5500
fix error message 2022-04-01 11:17:02 +02:00
ad hoc
a1a3a49bc9
dynamic minimum word len for typos in query tree builder 2022-04-01 11:17:02 +02:00
ad hoc
5a24e60572
introduce word len for typo setting 2022-04-01 11:17:02 +02:00
ad hoc
9fe40df960
add word derivations tests 2022-04-01 11:05:18 +02:00
ad hoc
d5ddc6b080
fix 2 typos word derivation bug 2022-04-01 10:51:22 +02:00
ad hoc
3e34981d9b
add test for authorize_typos in update 2022-03-31 14:12:00 +02:00
ad hoc
6ef3bb9d83
fmt 2022-03-31 14:06:23 +02:00
ad hoc
f782fe2062
add authorize_typo_test 2022-03-31 10:08:39 +02:00
ad hoc
c4653347fd
add authorize typo setting 2022-03-31 10:05:44 +02:00
Clémentine Urquizar
ddf78a735b
Update version (v0.24.1) 2022-03-24 16:39:45 +01:00
Irevoire
86dd88698d
bump tokenizer 2022-03-23 14:25:58 +01:00
Irevoire
5dc464b9a7
rollback meilisearch-tokenizer version 2022-03-21 17:29:10 +01:00
bors[bot]
90276d9a2d
Merge #472 
472: Remove useless variables in proximity r=Kerollmops a=ManyTheFish

Was passing by plane sweep algorithm to find some inspiration, and I discover that we have useless variables that were not detected because of the recursive function.

Co-authored-by: ManyTheFish <many@meilisearch.com>
 2022-03-16 15:33:11 +00:00
ManyTheFish
49d59d88c2 Remove useless variables in proximity 2022-03-16 16:12:52 +01:00
Bruno Casali
adc71742c8 Move string concat to the struct instead of in the calling 2022-03-16 10:26:12 -03:00
Bruno Casali
4822fe1beb Add a better error message when the filterable attrs are empty 
Fixes https://github.com/meilisearch/meilisearch/issues/2140
 2022-03-15 18:13:59 -03:00
bors[bot]
f04ab67083
Merge #466 
466: Bump version to 0.23.1 r=curquiza a=Kerollmops

This PR bumps the crate versions to 0.23.1. Nothing seems to be breaking in the next release.

Co-authored-by: Kerollmops <clement@meilisearch.com>
 2022-03-15 17:19:05 +00:00
bors[bot]
ad4c982c68
Merge #439 
439: Optimize typo criterion r=Kerollmops a=MarinPostma

This pr implements a couple of optimization for the typo criterion:

- clamp max typo on concatenated query words to 1: By considering that a concatenated query word is a typo, we clamp the max number of typos allowed o it to 1. This is useful because we noticed that concatenated query words often introduced words with 2 typos in queries that otherwise didn't allow for 2 typo words.

- Make typos on the first letter count for 2. This change is a big performance gain: by considering the typos on the first letter to count as 2 typos, we drastically restrict the search space for 1 typo, and if we reach 2 typos, the search space is reduced as well, as we only consider: (2 typos ∩ correct first letter) ∪ (wrong first letter ∩ 1 typo) instead of 2 typos anywhere in the word.

## benches
```
group                                                                                                    main                                   typo
-----                                                                                                    ----                                   ----
smol-songs.csv: asc + default/Notstandskomitee                                                           2.51      5.8±0.01ms        ? ?/sec    1.00      2.3±0.01ms        ? ?/sec
smol-songs.csv: asc + default/charles                                                                    2.48      3.0±0.01ms        ? ?/sec    1.00   1190.9±1.29µs        ? ?/sec
smol-songs.csv: asc + default/charles mingus                                                             5.56     10.8±0.01ms        ? ?/sec    1.00   1935.3±1.00µs        ? ?/sec
smol-songs.csv: asc + default/david                                                                      1.65      3.9±0.00ms        ? ?/sec    1.00      2.4±0.01ms        ? ?/sec
smol-songs.csv: asc + default/david bowie                                                                3.34     12.5±0.02ms        ? ?/sec    1.00      3.7±0.00ms        ? ?/sec
smol-songs.csv: asc + default/john                                                                       1.00   1849.7±3.74µs        ? ?/sec    1.01   1875.1±4.65µs        ? ?/sec
smol-songs.csv: asc + default/marcus miller                                                              4.32     15.7±0.01ms        ? ?/sec    1.00      3.6±0.01ms        ? ?/sec
smol-songs.csv: asc + default/michael jackson                                                            3.31     12.5±0.01ms        ? ?/sec    1.00      3.8±0.00ms        ? ?/sec
smol-songs.csv: asc + default/tamo                                                                       1.05    565.4±0.86µs        ? ?/sec    1.00    539.3±1.22µs        ? ?/sec
smol-songs.csv: asc + default/thelonious monk                                                            3.49     11.5±0.01ms        ? ?/sec    1.00      3.3±0.00ms        ? ?/sec
smol-songs.csv: asc/Notstandskomitee                                                                     2.59      5.6±0.02ms        ? ?/sec    1.00      2.2±0.01ms        ? ?/sec
smol-songs.csv: asc/charles                                                                              6.05      2.1±0.00ms        ? ?/sec    1.00    347.8±0.60µs        ? ?/sec
smol-songs.csv: asc/charles mingus                                                                       14.46     9.4±0.01ms        ? ?/sec    1.00    649.2±0.97µs        ? ?/sec
smol-songs.csv: asc/david                                                                                3.87      2.4±0.00ms        ? ?/sec    1.00    618.2±0.69µs        ? ?/sec
smol-songs.csv: asc/david bowie                                                                          10.14     9.8±0.01ms        ? ?/sec    1.00    970.8±1.55µs        ? ?/sec
smol-songs.csv: asc/john                                                                                 1.00    546.5±1.10µs        ? ?/sec    1.00    547.1±2.11µs        ? ?/sec
smol-songs.csv: asc/marcus miller                                                                        11.45    10.4±0.06ms        ? ?/sec    1.00    907.9±1.37µs        ? ?/sec
smol-songs.csv: asc/michael jackson                                                                      10.56     9.7±0.01ms        ? ?/sec    1.00    919.6±1.03µs        ? ?/sec
smol-songs.csv: asc/tamo                                                                                 1.03     43.3±0.18µs        ? ?/sec    1.00     42.2±0.23µs        ? ?/sec
smol-songs.csv: asc/thelonious monk                                                                      4.16     10.7±0.02ms        ? ?/sec    1.00      2.6±0.00ms        ? ?/sec
smol-songs.csv: basic filter: <=/Notstandskomitee                                                        1.00     95.7±0.20µs        ? ?/sec    1.15   109.6±10.40µs        ? ?/sec
smol-songs.csv: basic filter: <=/charles                                                                 1.00     27.8±0.15µs        ? ?/sec    1.01     27.9±0.18µs        ? ?/sec
smol-songs.csv: basic filter: <=/charles mingus                                                          1.72    119.2±0.67µs        ? ?/sec    1.00     69.1±0.13µs        ? ?/sec
smol-songs.csv: basic filter: <=/david                                                                   1.00     22.3±0.33µs        ? ?/sec    1.05     23.4±0.19µs        ? ?/sec
smol-songs.csv: basic filter: <=/david bowie                                                             1.59     86.9±0.79µs        ? ?/sec    1.00     54.5±0.31µs        ? ?/sec
smol-songs.csv: basic filter: <=/john                                                                    1.00     17.9±0.06µs        ? ?/sec    1.06     18.9±0.15µs        ? ?/sec
smol-songs.csv: basic filter: <=/marcus miller                                                           1.65    102.7±1.63µs        ? ?/sec    1.00     62.3±0.18µs        ? ?/sec
smol-songs.csv: basic filter: <=/michael jackson                                                         1.76    128.2±1.85µs        ? ?/sec    1.00     72.9±0.19µs        ? ?/sec
smol-songs.csv: basic filter: <=/tamo                                                                    1.00     17.9±0.13µs        ? ?/sec    1.05     18.7±0.20µs        ? ?/sec
smol-songs.csv: basic filter: <=/thelonious monk                                                         1.53    157.5±2.38µs        ? ?/sec    1.00    102.8±0.88µs        ? ?/sec
smol-songs.csv: basic filter: TO/Notstandskomitee                                                        1.00    100.9±4.36µs        ? ?/sec    1.04    105.0±8.25µs        ? ?/sec
smol-songs.csv: basic filter: TO/charles                                                                 1.00     28.4±0.36µs        ? ?/sec    1.03     29.4±0.33µs        ? ?/sec
smol-songs.csv: basic filter: TO/charles mingus                                                          1.71    118.1±1.08µs        ? ?/sec    1.00     68.9±0.26µs        ? ?/sec
smol-songs.csv: basic filter: TO/david                                                                   1.00     24.0±0.26µs        ? ?/sec    1.03     24.6±0.43µs        ? ?/sec
smol-songs.csv: basic filter: TO/david bowie                                                             1.72     95.2±0.30µs        ? ?/sec    1.00     55.2±0.14µs        ? ?/sec
smol-songs.csv: basic filter: TO/john                                                                    1.00     18.8±0.09µs        ? ?/sec    1.06     19.8±0.17µs        ? ?/sec
smol-songs.csv: basic filter: TO/marcus miller                                                           1.61    102.4±1.65µs        ? ?/sec    1.00     63.4±0.24µs        ? ?/sec
smol-songs.csv: basic filter: TO/michael jackson                                                         1.77    132.1±1.41µs        ? ?/sec    1.00     74.5±0.59µs        ? ?/sec
smol-songs.csv: basic filter: TO/tamo                                                                    1.00     18.2±0.14µs        ? ?/sec    1.05     19.2±0.46µs        ? ?/sec
smol-songs.csv: basic filter: TO/thelonious monk                                                         1.49    150.8±1.92µs        ? ?/sec    1.00    101.3±0.44µs        ? ?/sec
smol-songs.csv: basic placeholder/                                                                       1.00     27.3±0.07µs        ? ?/sec    1.03     28.0±0.05µs        ? ?/sec
smol-songs.csv: basic with quote/"Notstandskomitee"                                                      1.00    122.4±0.17µs        ? ?/sec    1.03    125.6±0.16µs        ? ?/sec
smol-songs.csv: basic with quote/"charles"                                                               1.00     88.8±0.30µs        ? ?/sec    1.00     88.4±0.15µs        ? ?/sec
smol-songs.csv: basic with quote/"charles" "mingus"                                                      1.00    685.2±0.74µs        ? ?/sec    1.01    689.4±6.07µs        ? ?/sec
smol-songs.csv: basic with quote/"david"                                                                 1.00    161.6±0.42µs        ? ?/sec    1.01    162.6±0.17µs        ? ?/sec
smol-songs.csv: basic with quote/"david" "bowie"                                                         1.00    731.7±0.73µs        ? ?/sec    1.02    743.1±0.77µs        ? ?/sec
smol-songs.csv: basic with quote/"john"                                                                  1.00    267.1±0.33µs        ? ?/sec    1.01    270.9±0.33µs        ? ?/sec
smol-songs.csv: basic with quote/"marcus" "miller"                                                       1.00    138.7±0.31µs        ? ?/sec    1.02    140.9±0.13µs        ? ?/sec
smol-songs.csv: basic with quote/"michael" "jackson"                                                     1.01    841.4±0.72µs        ? ?/sec    1.00    833.8±0.92µs        ? ?/sec
smol-songs.csv: basic with quote/"tamo"                                                                  1.01    189.2±0.26µs        ? ?/sec    1.00    188.2±0.71µs        ? ?/sec
smol-songs.csv: basic with quote/"thelonious" "monk"                                                     1.00   1100.5±1.36µs        ? ?/sec    1.01   1111.7±2.17µs        ? ?/sec
smol-songs.csv: basic without quote/Notstandskomitee                                                     3.40      7.9±0.02ms        ? ?/sec    1.00      2.3±0.02ms        ? ?/sec
smol-songs.csv: basic without quote/charles                                                              2.57    494.4±0.89µs        ? ?/sec    1.00    192.5±0.18µs        ? ?/sec
smol-songs.csv: basic without quote/charles mingus                                                       1.29      2.8±0.02ms        ? ?/sec    1.00      2.1±0.01ms        ? ?/sec
smol-songs.csv: basic without quote/david                                                                1.95    623.8±0.90µs        ? ?/sec    1.00    319.2±1.22µs        ? ?/sec
smol-songs.csv: basic without quote/david bowie                                                          1.12      5.9±0.00ms        ? ?/sec    1.00      5.2±0.00ms        ? ?/sec
smol-songs.csv: basic without quote/john                                                                 1.24   1340.9±2.25µs        ? ?/sec    1.00   1084.7±7.76µs        ? ?/sec
smol-songs.csv: basic without quote/marcus miller                                                        7.97     14.6±0.01ms        ? ?/sec    1.00   1826.0±6.84µs        ? ?/sec
smol-songs.csv: basic without quote/michael jackson                                                      1.19      3.9±0.00ms        ? ?/sec    1.00      3.3±0.00ms        ? ?/sec
smol-songs.csv: basic without quote/tamo                                                                 1.65    737.7±3.58µs        ? ?/sec    1.00    446.7±0.51µs        ? ?/sec
smol-songs.csv: basic without quote/thelonious monk                                                      1.16      4.5±0.02ms        ? ?/sec    1.00      3.9±0.04ms        ? ?/sec
smol-songs.csv: big filter/Notstandskomitee                                                              3.27      7.6±0.02ms        ? ?/sec    1.00      2.3±0.01ms        ? ?/sec
smol-songs.csv: big filter/charles                                                                       8.26   1957.5±1.37µs        ? ?/sec    1.00    236.8±0.34µs        ? ?/sec
smol-songs.csv: big filter/charles mingus                                                                18.49    11.2±0.06ms        ? ?/sec    1.00    607.7±3.03µs        ? ?/sec
smol-songs.csv: big filter/david                                                                         3.78      2.4±0.00ms        ? ?/sec    1.00    622.8±0.80µs        ? ?/sec
smol-songs.csv: big filter/david bowie                                                                   9.00     12.0±0.01ms        ? ?/sec    1.00   1336.0±3.17µs        ? ?/sec
smol-songs.csv: big filter/john                                                                          1.00    554.2±0.95µs        ? ?/sec    1.01    560.4±0.79µs        ? ?/sec
smol-songs.csv: big filter/marcus miller                                                                 18.09    12.0±0.01ms        ? ?/sec    1.00    664.7±0.60µs        ? ?/sec
smol-songs.csv: big filter/michael jackson                                                               8.43     12.0±0.01ms        ? ?/sec    1.00   1421.6±1.37µs        ? ?/sec
smol-songs.csv: big filter/tamo                                                                          1.00     86.3±0.14µs        ? ?/sec    1.01     87.3±0.21µs        ? ?/sec
smol-songs.csv: big filter/thelonious monk                                                               5.55     14.3±0.02ms        ? ?/sec    1.00      2.6±0.01ms        ? ?/sec
smol-songs.csv: desc + default/Notstandskomitee                                                          2.52      5.8±0.01ms        ? ?/sec    1.00      2.3±0.01ms        ? ?/sec
smol-songs.csv: desc + default/charles                                                                   3.04      2.7±0.01ms        ? ?/sec    1.00    893.4±1.08µs        ? ?/sec
smol-songs.csv: desc + default/charles mingus                                                            6.77     10.3±0.01ms        ? ?/sec    1.00   1520.8±1.90µs        ? ?/sec
smol-songs.csv: desc + default/david                                                                     1.39      5.7±0.00ms        ? ?/sec    1.00      4.1±0.00ms        ? ?/sec
smol-songs.csv: desc + default/david bowie                                                               2.34     15.8±0.02ms        ? ?/sec    1.00      6.7±0.01ms        ? ?/sec
smol-songs.csv: desc + default/john                                                                      1.00      2.5±0.00ms        ? ?/sec    1.02      2.6±0.01ms        ? ?/sec
smol-songs.csv: desc + default/marcus miller                                                             5.06     14.5±0.02ms        ? ?/sec    1.00      2.9±0.01ms        ? ?/sec
smol-songs.csv: desc + default/michael jackson                                                           2.64     14.1±0.05ms        ? ?/sec    1.00      5.4±0.00ms        ? ?/sec
smol-songs.csv: desc + default/tamo                                                                      1.00    567.0±0.65µs        ? ?/sec    1.00    565.7±0.97µs        ? ?/sec
smol-songs.csv: desc + default/thelonious monk                                                           3.55     11.6±0.02ms        ? ?/sec    1.00      3.3±0.00ms        ? ?/sec
smol-songs.csv: desc/Notstandskomitee                                                                    2.58      5.6±0.02ms        ? ?/sec    1.00      2.2±0.02ms        ? ?/sec
smol-songs.csv: desc/charles                                                                             6.04      2.1±0.00ms        ? ?/sec    1.00    348.1±0.57µs        ? ?/sec
smol-songs.csv: desc/charles mingus                                                                      14.51     9.4±0.01ms        ? ?/sec    1.00    646.7±0.99µs        ? ?/sec
smol-songs.csv: desc/david                                                                               3.86      2.4±0.00ms        ? ?/sec    1.00    620.7±2.46µs        ? ?/sec
smol-songs.csv: desc/david bowie                                                                         10.10     9.8±0.01ms        ? ?/sec    1.00    973.9±3.31µs        ? ?/sec
smol-songs.csv: desc/john                                                                                1.00    545.5±0.78µs        ? ?/sec    1.00    547.2±0.48µs        ? ?/sec
smol-songs.csv: desc/marcus miller                                                                       11.39    10.3±0.01ms        ? ?/sec    1.00    903.7±0.95µs        ? ?/sec
smol-songs.csv: desc/michael jackson                                                                     10.51     9.7±0.01ms        ? ?/sec    1.00    924.7±2.02µs        ? ?/sec
smol-songs.csv: desc/tamo                                                                                1.01     43.2±0.33µs        ? ?/sec    1.00     42.6±0.35µs        ? ?/sec
smol-songs.csv: desc/thelonious monk                                                                     4.19     10.8±0.03ms        ? ?/sec    1.00      2.6±0.00ms        ? ?/sec
smol-songs.csv: prefix search/a                                                                          1.00   1008.7±1.00µs        ? ?/sec    1.00   1005.5±0.91µs        ? ?/sec
smol-songs.csv: prefix search/b                                                                          1.00    885.0±0.70µs        ? ?/sec    1.01    890.6±1.11µs        ? ?/sec
smol-songs.csv: prefix search/i                                                                          1.00   1051.8±1.25µs        ? ?/sec    1.00   1056.6±4.12µs        ? ?/sec
smol-songs.csv: prefix search/s                                                                          1.00    724.7±1.77µs        ? ?/sec    1.00    721.6±0.59µs        ? ?/sec
smol-songs.csv: prefix search/x                                                                          1.01    212.4±0.21µs        ? ?/sec    1.00    210.9±0.38µs        ? ?/sec
smol-songs.csv: proximity/7000 Danses Un Jour Dans Notre Vie                                             18.55    48.5±0.09ms        ? ?/sec    1.00      2.6±0.03ms        ? ?/sec
smol-songs.csv: proximity/The Disneyland Sing-Along Chorus                                               8.41     56.7±0.45ms        ? ?/sec    1.00      6.7±0.05ms        ? ?/sec
smol-songs.csv: proximity/Under Great Northern Lights                                                    15.74    38.9±0.14ms        ? ?/sec    1.00      2.5±0.00ms        ? ?/sec
smol-songs.csv: proximity/black saint sinner lady                                                        11.82    40.1±0.13ms        ? ?/sec    1.00      3.4±0.02ms        ? ?/sec
smol-songs.csv: proximity/les dangeureuses 1960                                                          6.90     26.1±0.13ms        ? ?/sec    1.00      3.8±0.04ms        ? ?/sec
smol-songs.csv: typo/Arethla Franklin                                                                    14.93     5.8±0.01ms        ? ?/sec    1.00    390.1±1.89µs        ? ?/sec
smol-songs.csv: typo/Disnaylande                                                                         3.18      7.3±0.01ms        ? ?/sec    1.00      2.3±0.00ms        ? ?/sec
smol-songs.csv: typo/dire straights                                                                      5.55     15.2±0.02ms        ? ?/sec    1.00      2.7±0.00ms        ? ?/sec
smol-songs.csv: typo/fear of the duck                                                                    28.03    20.0±0.03ms        ? ?/sec    1.00    713.3±1.54µs        ? ?/sec
smol-songs.csv: typo/indochie                                                                            19.25  1851.4±2.38µs        ? ?/sec    1.00     96.2±0.13µs        ? ?/sec
smol-songs.csv: typo/indochien                                                                           14.66  1887.7±3.18µs        ? ?/sec    1.00    128.8±0.18µs        ? ?/sec
smol-songs.csv: typo/klub des loopers                                                                    37.73    18.0±0.02ms        ? ?/sec    1.00    476.7±0.73µs        ? ?/sec
smol-songs.csv: typo/michel depech                                                                       10.17     5.8±0.01ms        ? ?/sec    1.00    565.8±1.16µs        ? ?/sec
smol-songs.csv: typo/mongus                                                                              15.33  1897.4±3.44µs        ? ?/sec    1.00    123.8±0.13µs        ? ?/sec
smol-songs.csv: typo/stromal                                                                             14.63  1859.3±2.40µs        ? ?/sec    1.00    127.1±0.29µs        ? ?/sec
smol-songs.csv: typo/the white striper                                                                   10.83     9.4±0.01ms        ? ?/sec    1.00    866.0±0.98µs        ? ?/sec
smol-songs.csv: typo/thelonius monk                                                                      14.40     3.8±0.00ms        ? ?/sec    1.00    261.5±1.30µs        ? ?/sec
smol-songs.csv: words/7000 Danses / Le Baiser / je me trompe de mots                                     5.54     70.8±0.09ms        ? ?/sec    1.00     12.8±0.03ms        ? ?/sec
smol-songs.csv: words/Bring Your Daughter To The Slaughter but now this is not part of the title         3.48    119.8±0.14ms        ? ?/sec    1.00     34.4±0.04ms        ? ?/sec
smol-songs.csv: words/The Disneyland Children's Sing-Alone song                                          8.98     71.9±0.12ms        ? ?/sec    1.00      8.0±0.01ms        ? ?/sec
smol-songs.csv: words/les liaisons dangeureuses 1793                                                     11.88    37.4±0.07ms        ? ?/sec    1.00      3.1±0.01ms        ? ?/sec
smol-songs.csv: words/seven nation mummy                                                                 22.86    23.4±0.04ms        ? ?/sec    1.00   1024.8±1.57µs        ? ?/sec
smol-songs.csv: words/the black saint and the sinner lady and the good doggo                             2.76    124.4±0.15ms        ? ?/sec    1.00     45.1±0.09ms        ? ?/sec
smol-songs.csv: words/whathavenotnsuchforth and a good amount of words to pop to match the first one     2.52    107.0±0.23ms        ? ?/sec    1.00     42.4±0.66ms        ? ?/sec

group                                                                                    main-wiki                              typo-wiki
-----                                                                                    ---------                              ---------
smol-wiki-articles.csv: basic placeholder/                                               1.02     13.7±0.02µs        ? ?/sec    1.00     13.4±0.03µs        ? ?/sec
smol-wiki-articles.csv: basic with quote/"film"                                          1.02    409.8±0.67µs        ? ?/sec    1.00    402.6±0.48µs        ? ?/sec
smol-wiki-articles.csv: basic with quote/"france"                                        1.00    325.9±0.91µs        ? ?/sec    1.00    326.4±0.49µs        ? ?/sec
smol-wiki-articles.csv: basic with quote/"japan"                                         1.00    218.4±0.26µs        ? ?/sec    1.01    220.5±0.20µs        ? ?/sec
smol-wiki-articles.csv: basic with quote/"machine"                                       1.00    143.0±0.12µs        ? ?/sec    1.04    148.8±0.21µs        ? ?/sec
smol-wiki-articles.csv: basic with quote/"miles" "davis"                                 1.00     11.7±0.06ms        ? ?/sec    1.00     11.8±0.01ms        ? ?/sec
smol-wiki-articles.csv: basic with quote/"mingus"                                        1.00      4.4±0.03ms        ? ?/sec    1.00      4.4±0.00ms        ? ?/sec
smol-wiki-articles.csv: basic with quote/"rock" "and" "roll"                             1.00     43.5±0.08ms        ? ?/sec    1.01     43.8±0.06ms        ? ?/sec
smol-wiki-articles.csv: basic with quote/"spain"                                         1.00    137.3±0.35µs        ? ?/sec    1.05    144.4±0.23µs        ? ?/sec
smol-wiki-articles.csv: basic without quote/film                                         1.00    125.3±0.30µs        ? ?/sec    1.06    133.1±0.37µs        ? ?/sec
smol-wiki-articles.csv: basic without quote/france                                       1.21   1782.6±1.65µs        ? ?/sec    1.00   1477.0±1.39µs        ? ?/sec
smol-wiki-articles.csv: basic without quote/japan                                        1.28   1363.9±0.80µs        ? ?/sec    1.00   1064.3±1.79µs        ? ?/sec
smol-wiki-articles.csv: basic without quote/machine                                      1.73    760.3±0.81µs        ? ?/sec    1.00    439.6±0.75µs        ? ?/sec
smol-wiki-articles.csv: basic without quote/miles davis                                  1.03     17.0±0.03ms        ? ?/sec    1.00     16.5±0.02ms        ? ?/sec
smol-wiki-articles.csv: basic without quote/mingus                                       1.07      5.3±0.01ms        ? ?/sec    1.00      5.0±0.00ms        ? ?/sec
smol-wiki-articles.csv: basic without quote/rock and roll                                1.01     63.9±0.18ms        ? ?/sec    1.00     63.0±0.07ms        ? ?/sec
smol-wiki-articles.csv: basic without quote/spain                                        2.07    667.4±0.93µs        ? ?/sec    1.00    322.8±0.29µs        ? ?/sec
smol-wiki-articles.csv: prefix search/c                                                  1.00    343.1±0.47µs        ? ?/sec    1.00    344.0±0.34µs        ? ?/sec
smol-wiki-articles.csv: prefix search/g                                                  1.00    374.4±3.42µs        ? ?/sec    1.00    374.1±0.44µs        ? ?/sec
smol-wiki-articles.csv: prefix search/j                                                  1.00    359.9±0.31µs        ? ?/sec    1.00    361.2±0.79µs        ? ?/sec
smol-wiki-articles.csv: prefix search/q                                                  1.01    102.0±0.12µs        ? ?/sec    1.00    101.4±0.32µs        ? ?/sec
smol-wiki-articles.csv: prefix search/t                                                  1.00    536.7±1.39µs        ? ?/sec    1.00    534.3±0.84µs        ? ?/sec
smol-wiki-articles.csv: prefix search/x                                                  1.00    400.9±1.00µs        ? ?/sec    1.00    399.5±0.45µs        ? ?/sec
smol-wiki-articles.csv: proximity/april paris                                            3.86     14.4±0.01ms        ? ?/sec    1.00      3.7±0.01ms        ? ?/sec
smol-wiki-articles.csv: proximity/diesel engine                                          12.98    10.4±0.01ms        ? ?/sec    1.00    803.5±1.13µs        ? ?/sec
smol-wiki-articles.csv: proximity/herald sings                                           1.00     12.7±0.06ms        ? ?/sec    5.29     67.1±0.09ms        ? ?/sec
smol-wiki-articles.csv: proximity/tea two                                                6.48   1452.1±2.78µs        ? ?/sec    1.00    224.1±0.38µs        ? ?/sec
smol-wiki-articles.csv: typo/Disnaylande                                                 3.89      8.5±0.01ms        ? ?/sec    1.00      2.2±0.01ms        ? ?/sec
smol-wiki-articles.csv: typo/aritmetric                                                  3.78     10.3±0.01ms        ? ?/sec    1.00      2.7±0.00ms        ? ?/sec
smol-wiki-articles.csv: typo/linax                                                       8.91   1426.7±0.97µs        ? ?/sec    1.00    160.1±0.18µs        ? ?/sec
smol-wiki-articles.csv: typo/migrosoft                                                   7.48   1417.3±5.84µs        ? ?/sec    1.00    189.5±0.88µs        ? ?/sec
smol-wiki-articles.csv: typo/nympalidea                                                  3.96      7.2±0.01ms        ? ?/sec    1.00   1810.1±2.03µs        ? ?/sec
smol-wiki-articles.csv: typo/phytogropher                                                3.71      7.2±0.01ms        ? ?/sec    1.00   1934.3±6.51µs        ? ?/sec
smol-wiki-articles.csv: typo/sisan                                                       6.44   1497.2±1.38µs        ? ?/sec    1.00    232.7±0.94µs        ? ?/sec
smol-wiki-articles.csv: typo/the fronce                                                  6.92      2.9±0.00ms        ? ?/sec    1.00    418.0±1.76µs        ? ?/sec
smol-wiki-articles.csv: words/Abraham machin                                             16.63    10.8±0.01ms        ? ?/sec    1.00    649.7±1.08µs        ? ?/sec
smol-wiki-articles.csv: words/Idaho Bellevue pizza                                       27.15    25.6±0.03ms        ? ?/sec    1.00    944.2±5.07µs        ? ?/sec
smol-wiki-articles.csv: words/Kameya Tokujirō mingus monk                                26.87    40.7±0.05ms        ? ?/sec    1.00   1515.3±2.73µs        ? ?/sec
smol-wiki-articles.csv: words/Ulrich Hensel meilisearch milli                            11.99    48.8±0.10ms        ? ?/sec    1.00      4.1±0.02ms        ? ?/sec
smol-wiki-articles.csv: words/the black saint and the sinner lady and the good doggo     4.90    110.0±0.15ms        ? ?/sec    1.00     22.4±0.03ms        ? ?/sec

```

Co-authored-by: mpostma <postma.marin@protonmail.com>
Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-03-15 16:43:36 +00:00
ad hoc
3f24555c3d
custom fst automatons 2022-03-15 17:38:35 +01:00
ad hoc
628c835a22
fix tests 2022-03-15 17:38:34 +01:00
bors[bot]
8efac33b53
Merge #467 
467: optimize prefix database r=Kerollmops a=MarinPostma

This pr introduces two optimizations that greatly improve the speed of computing prefix databases.

- The time that it takes to create the prefix FST has been divided by 5 by inverting the way we iterated over the words FST.
- We unconditionally and needlessly checked for documents to remove in  `word_prefix_pair`, which caused an iteration over the whole database.

Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-03-15 16:14:35 +00:00
ad hoc
d127c57f2d
review edits 2022-03-15 17:12:48 +01:00
ad hoc
d633ac5b9d
optimize word prefix pair 2022-03-15 16:37:22 +01:00
ad hoc
d68fe2b3c7
optimize word prefix fst 2022-03-15 16:36:48 +01:00
Kerollmops
08a06b49f0
Bump version to 0.23.1 2022-03-15 15:50:28 +01:00
Clément Renault
0c5f4ed7de
Apply suggestions 
Co-authored-by: Many <many@meilisearch.com>
 2022-03-15 14:18:29 +01:00
Kerollmops
21ec334dcc
Fix the compilation error of the dependency versions 2022-03-15 11:17:45 +01:00
Kerollmops
63682c2c9a
Upgrade the dependencies 2022-03-15 11:17:44 +01:00
Kerollmops
288a879411
Remove three useless dependencies 2022-03-15 11:17:44 +01:00
psvnl sai kumar
5e08fac729 fixes for rustfmt pass 2022-03-14 19:22:41 +05:30
psvnl sai kumar
92e2e09434 exporting heed to avoid having different versions of Heed in Meilisearch 2022-03-14 01:01:58 +05:30
Kerollmops
1ae13c1374
Avoid iterating on big databases when useless 2022-03-09 15:43:54 +01:00
Bruno Casali
66c6d5e1ef Add a new error message when the valid_fields is empty 
> "Attribute `{}` is not sortable. This index doesn't have configured sortable attributes."
> "Attribute `{}` is not sortable. Available sortable attributes are: `{}`."

coexist in the error handling
 2022-03-05 10:38:18 -03:00
Clémentine Urquizar
d9ed9de2b0
Update heed link in cargo toml 2022-03-01 19:45:29 +01:00
Kerollmops
d5b8b5a2f8
Replace the ugly unwraps by clean if let Somes 2022-02-28 16:31:33 +01:00
Kerollmops
8d26f3040c
Remove a useless grenad file merging 2022-02-28 16:31:33 +01:00
Clément Renault
04b1bbf932
Reintroduce appending sorted entries when possible 2022-02-24 14:50:45 +01:00
bors[bot]
25123af3b8
Merge #436 
436: Speed up the word prefix databases computation time r=Kerollmops a=Kerollmops

This PR depends on the fixes done in #431 and must be merged after it.

In this PR we will bring the `WordPrefixPairProximityDocids`, `WordPrefixDocids` and, `WordPrefixPositionDocids` update structures to a new era, a better era, where computing the word prefix pair proximities costs much fewer CPU cycles, an era where this update structure can use the, previously computed, set of new word docids from the newly indexed batch of documents.

---

The `WordPrefixPairProximityDocids` is an update structure, which means that it is an object that we feed with some parameters and which modifies the LMDB database of an index when asked for. This structure specifically computes the list of word prefix pair proximities, which correspond to a list of pairs of words associated with a proximity (the distance between both words) where the second word is not a word but a prefix e.g. `s`, `se`, `a`. This word prefix pair proximity is associated with the list of documents ids which contains the pair of words and prefix at the given proximity.

The origin of the performances issue that this struct brings is related to the fact that it starts its job from the beginning, it clears the LMDB database before rewriting everything from scratch, using the other LMDB databases to achieve that. I hope you understand that this is absolutely not an optimized way of doing things.

Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
 2022-02-16 15:41:14 +00:00
Clément Renault
ff8d7a810d
Change the behavior of the as_cloneable_grenad by taking a ref 2022-02-16 15:40:08 +01:00
Clément Renault
f367cc2e75
Finally bump grenad to v0.4.1 2022-02-16 15:28:48 +01:00
Irevoire
0defeb268c
bump milli 2022-02-16 13:27:41 +01:00
Irevoire
48542ac8fd
get rid of chrono in favor of time 2022-02-15 11:41:55 +01:00
Clémentine Urquizar
d03b3ceb58
Update version for the next release (v0.22.1) 2022-02-07 18:39:29 +01:00
bors[bot]
5d58cb7449
Merge #442 
442: fix phrase search r=curquiza a=MarinPostma

Run the exact match search on 7 words windows instead of only two. This makes false positive very very unlikely, and impossible on phrase query that are less than seven words.


Co-authored-by: ad hoc <postma.marin@protonmail.com>
 2022-02-07 16:18:20 +00:00
ad hoc
bd2262ceea
allow null values in csv 2022-02-03 16:03:01 +01:00
ad hoc
13de251047
rewrite word pair distance gathering 2022-02-03 15:57:20 +01:00
Many
d59bcea749 Revert "Revert "Change chunk size to 4MiB to fit more the end user usage"" 2022-02-02 17:01:13 +01:00
mpostma
7541ab99cd
review changes 2022-02-02 12:59:01 +01:00
mpostma
d0aabde502
optimize 2 typos case 2022-02-02 12:56:09 +01:00
mpostma
55e6cb9c7b
typos on first letter counts as 2 2022-02-02 12:56:09 +01:00
mpostma
642c01d0dc
set max typos on ngram to 1 2022-02-02 12:56:08 +01:00
ad hoc
d852dc0d2b
fix phrase search 2022-02-01 20:21:33 +01:00
Kerollmops
fb79c32430
Compute the new, common and, deleted prefix words fst once 2022-01-27 11:00:18 +01:00
Clément Renault
51d1e64b23
Remove, now useless, the WriteMethod enum 2022-01-27 10:08:35 +01:00
Clément Renault
e9c02173cf
Rework the WordsPrefixPositionDocids update to compute a subset of the database 2022-01-27 10:08:35 +01:00
Clément Renault
dbba5fd461
Create a function to simplify the word prefix pair proximity docids compute 2022-01-27 10:08:35 +01:00
Clément Renault
e760e02737
Fix the computation of the newly added and common prefix pair proximity words 2022-01-27 10:08:35 +01:00
Clément Renault
d59e559317
Fix the computation of the newly added and common prefix words 2022-01-27 10:08:34 +01:00
Clément Renault
2ec8542105
Rework the WordPrefixDocids update to compute a subset of the database 2022-01-27 10:08:34 +01:00
Clément Renault
28692f65be
Rework the WordPrefixDocids update to compute a subset of the database 2022-01-27 10:08:34 +01:00
Clément Renault
5404bc02dd
Move the fst_stream_into_hashset method in the helper methods 2022-01-27 10:06:00 +01:00
Clément Renault
c90fa95f93
Only compute the word prefix pairs on the created word pair proximities 2022-01-27 10:06:00 +01:00