Commit Graph

983 Commits

Author SHA1 Message Date
Tamo
e7244aa485 fix warnings 2023-10-30 11:00:46 +01:00
Louis Dureuil
2bae9550c8
Add explanatory comment 2023-10-23 12:06:28 +02:00
Vivek Kumar
5fe7c4545a
compute all candidates correctly when skipping 2023-10-23 12:02:45 +02:00
meili-bors[bot]
5e0485d8dd
Merge #4131
4131: Reduce proximity range from 7 to 3 r=Kerollmops a=ManyTheFish

## Summary
This PR aims to reduce the impact of the proximity databases on the indexing time and on the database size by reducing the maximum distance between two words to be indexed in the proximity database.

## Stats

### Impact on database size and indexing time
![Impact on datasets](https://github.com/meilisearch/meilisearch/assets/6482087/28ed3d96-bdde-41c1-bdac-e90c1b1dbb23)

### Impact on search relevancy

<details>

| dataset_name | host_name        | Relevancy rate (Precision) | completion_rate  25.00% | completion_rate 50.00% | completion_rate 75.00% | completion_rate 100.00% |
|--------------|------------------|------------------------------------|-----------------|-----------------|-----------------|-----------------|
| FBIS         | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | 1_4_0            | percentile-50 |           0.00% |           0.00% |           5.00% |           5.56% |
| FBIS         | 1_4_0            | percentile-75 |           0.00% |          12.50% |          35.00% |          45.00% |
| FBIS         | 1_4_0            | percentile-90 |          20.00% |          40.00% |                 |         100.00% |
| FBIS         | 1_4_0            | average       |           5.78% |          11.16% |          21.90% |          26.29% |
| FBIS         | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FBIS         | reduce_proximity | percentile-50 |           0.00% |           0.00% |           5.00% |           5.56% |
| FBIS         | reduce_proximity | percentile-75 |           0.00% |          15.00% |          35.00% |          40.00% |
| FBIS         | reduce_proximity | percentile-90 |          20.00% |          40.00% |          85.00% |         100.00% |
| FBIS         | reduce_proximity | average       |           5.55% |          11.34% |          21.75% |          26.14% |
| FR94         | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | 1_4_0            | percentile-50 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | 1_4_0            | percentile-75 |           0.00% |           5.00% |          15.00% |          42.11% |
| FR94         | 1_4_0            | percentile-90 |          15.00% |          54.55% |         100.00% |         100.00% |
| FR94         | 1_4_0            | average       |           5.95% |          12.07% |          18.70% |          25.57% |
| FR94         | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | reduce_proximity | percentile-50 |           0.00% |           0.00% |           0.00% |           0.00% |
| FR94         | reduce_proximity | percentile-75 |           0.00% |           5.00% |          15.00% |          42.11% |
| FR94         | reduce_proximity | percentile-90 |          15.00% |          54.55% |         100.00% |         100.00% |
| FR94         | reduce_proximity | average       |           5.79% |          12.00% |          18.70% |          25.53% |
| FT           | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | 1_4_0            | percentile-50 |           0.00% |           0.00% |           5.00% |          10.00% |
| FT           | 1_4_0            | percentile-75 |           0.00% |          15.00% |          30.00% |          40.00% |
| FT           | 1_4_0            | percentile-90 |          20.00% |          50.00% |          65.00% |         100.00% |
| FT           | 1_4_0            | average       |           5.08% |          12.58% |          20.00% |          25.49% |
| FT           | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| FT           | reduce_proximity | percentile-50 |           0.00% |           0.00% |           5.00% |          10.00% |
| FT           | reduce_proximity | percentile-75 |           0.00% |          15.00% |          30.00% |          40.00% |
| FT           | reduce_proximity | percentile-90 |          10.00% |          45.00% |          60.00% |         100.00% |
| FT           | reduce_proximity | average       |           5.01% |          12.64% |          20.10% |          25.53% |
| LAT          | 1_4_0            | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | 1_4_0            | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | 1_4_0            | percentile-50 |           0.00% |           0.00% |           5.00% |           5.00% |
| LAT          | 1_4_0            | percentile-75 |           5.00% |          15.00% |          30.00% |          30.00% |
| LAT          | 1_4_0            | percentile-90 |          15.00% |          45.00% |          60.00% |          80.00% |
| LAT          | 1_4_0            | average       |           4.80% |          11.80% |          17.88% |          21.62% |
| LAT          | reduce_proximity | percentile-10 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | reduce_proximity | percentile-25 |           0.00% |           0.00% |           0.00% |           0.00% |
| LAT          | reduce_proximity | percentile-50 |           0.00% |           0.00% |           5.00% |           5.00% |
| LAT          | reduce_proximity | percentile-75 |           0.00% |          11.11% |          25.00% |          35.00% |
| LAT          | reduce_proximity | percentile-90 |          15.00% |          45.00% |          55.00% |          80.00% |
| LAT          | reduce_proximity | average       |           4.43% |          11.23% |          17.32% |          21.45% |

</details>

### Impact on Search time

| dataset_name | host_name        |      25.00% |      50.00% |      75.00% |     100.00% | Average     |
|--------------|------------------|------------:|------------:|------------:|------------:|-------------|
| FBIS         | 1_4_0            |        3.45 | 7.446666667 | 9.773489933 | 9.620300752 | 7.572614338 |
| FBIS         | reduce_proximity | 2.983333333 | 5.316666667 | 6.911073826 | 7.637218045 | 5.712072968 |
| FR94         | 1_4_0            | 2.236666667 |        4.45 | 5.523489933 | 4.560150376 | 4.192576744 |
| FR94         | reduce_proximity |        2.09 | 3.991666667 | 4.981543624 | 4.266917293 | 3.832531896 |
| FT           | 1_4_0            | 5.956666667 | 9.656666667 | 13.86912752 | 10.83270677 |  10.0787919 |
| FT           | reduce_proximity |        4.51 | 5.981666667 | 7.701342282 | 6.766917293 |  6.23998156 |
| LAT          | 1_4_0            | 5.856666667 | 9.233333333 | 12.98322148 | 10.78759398 | 9.715203865 |
| LAT          | reduce_proximity |        6.91 | 6.706666667 | 8.463087248 | 8.265037594 | 7.586197877 |

## Technical approach

- Ensure the MAX_DISTANCE constant is used everywhere needed
- Reduce the MAX_DISTANCE from 8 to 4

## Related

TBD

Co-authored-by: ManyTheFish <many@meilisearch.com>
2023-10-18 14:56:08 +00:00
ManyTheFish
27eec21415 Fix tests 2023-10-18 16:03:22 +02:00
Vivek Kumar
d4da06ff47
fix bug where distinct search with no ranking returns offset+limit hits 2023-10-11 19:02:16 +05:30
ManyTheFish
43989fe2e4 Reduce porximity range from 7 to 3 2023-10-03 12:16:48 +02:00
Vivek Kumar
abfa7ded25
use a new temp index in the test 2023-09-08 12:32:47 +05:30
Vivek Kumar
f2837aaec2
add another test case 2023-09-08 11:39:54 +05:30
Vivek Kumar
11df155598
fix highlighting bug when searching for a phrase with cropping 2023-09-08 11:39:52 +05:30
meili-bors[bot]
ccf3ba3f32
Merge #4019
4019: Bringing back changes from `v1.3.2` onto `main` r=irevoire a=Kerollmops



Co-authored-by: Kerollmops <clement@meilisearch.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: irevoire <irevoire@users.noreply.github.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
2023-08-28 12:14:11 +00:00
Clément Renault
8c0ebd1331
Update milli/src/search/new/bucket_sort.rs
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2023-08-23 16:40:39 +02:00
Kerollmops
5130e06b41
Temporarily disable an assert in the ranking rules 2023-08-23 16:11:54 +02:00
meili-bors[bot]
914b125c5f
Merge #3945
3945: Do not leak field information on error r=Kerollmops a=vivek-26

# Pull Request

## Related issue
Fixes #3865

## What does this PR do?
This PR ensures that `InvalidSortableAttribute`and `InvalidFacetSearchFacetName` errors do not leak field information i.e. fields which are not part of `displayedAttributes` in the settings are hidden from the error message.

## PR checklist
Please check if your PR fulfills the following requirements:
- [x] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
- [x] Have you read the contributing guidelines?
- [x] Have you made sure that the title is accurate and descriptive of the changes?

Thank you so much for contributing to Meilisearch!


Co-authored-by: Vivek Kumar <vivek.26@outlook.com>
2023-08-22 18:55:27 +00:00
ManyTheFish
4a21fecf67 Merge branch 'main' into settings-customizing-tokenization 2023-08-08 16:08:16 +02:00
Vivek Kumar
dd57873f8e
hide fields not in the displayedAttributes list from errors 2023-08-05 16:03:10 +05:30
ManyTheFish
b0c1a9504a ensure the synonyms are updated when the tokenizer settings are changed 2023-07-26 09:33:42 +02:00
meili-bors[bot]
be72be7c0d
Merge #3942
3942: Normalize for the search the facets values r=ManyTheFish a=Kerollmops

This PR improves and fixes the search for facet values feature. Searching for _bre_ wasn't returning facet values like _brévent_ or _brô_.

The issue was related to the fact that facets are normalized but not in the same way as the `searchableAttributes` are. We decided to normalize them further and add another intermediate database where the key is the normalized facet value, and the value is a set of the non-normalized facets. We then use these non-normalized ones to get the correct counts by fetching the associated databases.

### What's missing in this PR?
 - [x] Apply the change to the whole set of `SearchForFacetValue::execute` conditions.
 - [x] Factorize the code that does an intermediate normalized value fetch in a function.
 - [x] Add or modify the search for facet value test.

Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
2023-07-25 14:37:17 +00:00
Kerollmops
29ab54b259
Replace the hnsw crate by the instant-distance one 2023-07-25 12:37:35 +02:00
ManyTheFish
9c485f8563 Make the search and the indexing work 2023-07-24 18:35:20 +02:00
Kerollmops
691a536893
Implement the facet search with the normalized index 2023-07-24 17:56:17 +02:00
Clément Renault
df528b41d8
Normalize for the search the facets values 2023-07-20 17:57:07 +02:00
Kerollmops
d383afc82b
Fix the geo sort when lat and lng are strings 2023-07-17 18:28:04 +02:00
Louis Dureuil
4310928803
Fixes #3912 2023-07-12 10:08:56 +02:00
Louis Dureuil
74315b4ea8
Fixes #3911 2023-07-12 10:08:29 +02:00
Louis Dureuil
55cd7738b9
Update snapshots 2023-07-04 16:31:01 +02:00
Louis Dureuil
48409c9183
Add missing exactness.matchingWords, exactness.maxMatchingWords 2023-07-04 16:31:01 +02:00
Louis Dureuil
324d448236
Format let-else ❤️ 🎉 2023-07-03 10:20:28 +02:00
meili-bors[bot]
661d1f90dc
Merge #3866
3866: Update charabia v0.8.0 r=dureuill a=ManyTheFish

# Pull Request

Update Charabia:
- enhance Japanese segmentation
- enhance Latin Tokenization
  - words containing `_` are now properly segmented into several words
  - brackets `{([])}` are no more considered as context separators so word separated by brackets are now considered near together for the proximity ranking rule
- fixes #3815
- fixes #3778
- fixes [product#151](https://github.com/meilisearch/product/discussions/151)

> Important note: now the float numbers are segmented around the `.` so `3.22` is segmented as [`3`, `.`, `22`] but the middle dot isn't considered as a hard separator, which means that if we search `3.22` we find documents containing `3.22`

Co-authored-by: ManyTheFish <many@meilisearch.com>
2023-06-29 15:24:36 +00:00
ManyTheFish
6ec7541026 Update inta snapshots 2023-06-29 17:18:39 +02:00
ManyTheFish
84845de9ef Update Charabia 2023-06-29 15:56:32 +02:00
Clément Renault
7c157fc442
Document that the LevelEntry fields order is important 2023-06-29 14:33:32 +02:00
Clément Renault
0b97596c93
Replace unwraps with ? 2023-06-29 14:33:32 +02:00
Clément Renault
a0e0fce677
Simplify a Rust lifetime trick 2023-06-29 14:33:32 +02:00
Clément Renault
b951830461
Add more tests 2023-06-29 14:33:32 +02:00
Kerollmops
b132e859f7
Make clippy happy 2023-06-29 14:33:31 +02:00
Kerollmops
9917bf046a
Move the sortFacetValuesBy in the faceting settings 2023-06-29 14:33:31 +02:00
Kerollmops
d9fea0143f
Make Clippy happy 2023-06-29 14:33:31 +02:00
Kerollmops
a385642ec3
Replace the BTreeMap by an IndexMap to return values in order 2023-06-29 14:33:31 +02:00
Kerollmops
34b2e98fe9
Expose a sortFacetValuesBy parameter to the user 2023-06-29 14:33:00 +02:00
Kerollmops
80bbd4b6f3
Clean and make the facet order configurable internally 2023-06-29 14:31:17 +02:00
Kerollmops
f42bef2f66
Make the search to always return the facets ordered by count 2023-06-29 14:31:17 +02:00
Kerollmops
bd3c026406
First to-test version of the algorithm 2023-06-29 14:31:17 +02:00
Kerollmops
84f8938f33
Rename facet distribution to be explicit on the order to find them 2023-06-29 14:31:15 +02:00
Kerollmops
60ddd53439
Return one of the original facet values when doing a facet search 2023-06-28 15:06:09 +02:00
Kerollmops
2bcd8d2983
Make sure the facet queries are normalized 2023-06-28 15:06:09 +02:00
Kerollmops
41760a9306
Introduce a new invalid_facet_search_facet_name error code 2023-06-28 15:06:07 +02:00
Kerollmops
ed0ff47551
Return an empty list of results if attribute is set as filterable 2023-06-28 15:01:51 +02:00
Clément Renault
e1b8fb48ee
Use the minWordSizeForTypos index settings 2023-06-28 15:01:51 +02:00
Clément Renault
87e22e436a
Fix compilation issues 2023-06-28 15:01:51 +02:00
Clément Renault
0252cfe8b6
Simplify the placeholder search of the facet-search route 2023-06-28 15:01:50 +02:00
Clément Renault
f35ad96afa
Use the disableOnAttributes parameter on the facet-search route 2023-06-28 15:01:50 +02:00
Clément Renault
2ceb781c73
Use the disableOnWords parameter on the facet-search route 2023-06-28 15:01:50 +02:00
Clément Renault
7bd67543dd
Support the typoTolerant.enabled parameter 2023-06-28 15:01:50 +02:00
Clément Renault
8e86eb91bb
Log an error when a facet value is missing from the database 2023-06-28 15:01:50 +02:00
Clément Renault
55c17aa38b
Rename the SearchForFacetValues struct 2023-06-28 15:01:50 +02:00
Clément Renault
aadbe88048
Return an internal error when a field id is missing 2023-06-28 15:01:50 +02:00
Clément Renault
702041b7e1
Improve the returned errors from the facet-search route 2023-06-28 15:01:48 +02:00
Clément Renault
a05074e675
Fix the max number of facets to be returned to 100 2023-06-28 14:58:42 +02:00
Clément Renault
93f30e65a9
Return the correct response JSON object from the facet-search route 2023-06-28 14:58:42 +02:00
Clément Renault
e81809aae7
Make the search for facet work 2023-06-28 14:58:41 +02:00
Kerollmops
ce7e7f12c8
Introduce the facet search route 2023-06-28 14:58:41 +02:00
Kerollmops
addb21f110
Restrict the number of facet search results to 1000 2023-06-28 14:58:41 +02:00
Kerollmops
c34de05106
Introduce the SearchForFacetValue struct 2023-06-28 14:58:41 +02:00
meili-bors[bot]
d4f10800f2
Merge #3834
3834: Define searchable fields at runtime r=Kerollmops a=ManyTheFish

## Summary
This feature allows the end-user to search in one or multiple attributes using the search parameter `attributesToSearchOn`:

```json
{
  "q": "Captain Marvel",
  "attributesToSearchOn": ["title"]
}
```

This feature act like a filter, forcing Meilisearch to only return the documents containing the requested words in the attributes-to-search-on. Note that, with the matching strategy `last`, Meilisearch will only ensure that the first word is in the attributes-to-search-on, but, the retrieved documents will be ordered taking into account the word contained in the attributes-to-search-on. 

## Trying the prototype

A dedicated docker image has been released for this feature:

#### last prototype version:

```bash
docker pull getmeili/meilisearch:prototype-define-searchable-fields-at-search-time-1
```

#### others prototype versions:

```bash
docker pull getmeili/meilisearch:prototype-define-searchable-fields-at-search-time-0
```

## Technical Detail

The attributes-to-search-on list is given to the search context, then, the search context uses the `fid_word_docids`database using only the allowed field ids instead of the global `word_docids` database. This is the same for the prefix databases.
The database cache is updated with the merged values, meaning that the union of the field-id-database values is only made if the requested key is missing from the cache.

### Relevancy limits

Almost all ranking rules behave as expected when ordering the documents.
Only `proximity` could miss-order documents if all the searched words are in the restricted attribute but a better proximity is found in an ignored attribute in a document that should be ranked lower. I put below a failing test showing it:
```rust
#[actix_rt::test]
async fn proximity_ranking_rule_order() {
    let server = Server::new().await;
    let index = index_with_documents(
        &server,
        &json!([
        {
            "title": "Captain super mega cool. A Marvel story",
            // Perfect distance between words in an ignored attribute
            "desc": "Captain Marvel",
            "id": "1",
        },
        {
            "title": "Captain America from Marvel",
            "desc": "a Shazam ersatz",
            "id": "2",
        }]),
    )
    .await;

    // Document 2 should appear before document 1.
    index
        .search(json!({"q": "Captain Marvel", "attributesToSearchOn": ["title"], "attributesToRetrieve": ["id"]}), |response, code| {
            assert_eq!(code, 200, "{}", response);
            assert_eq!(
                response["hits"],
                json!([
                    {"id": "2"},
                    {"id": "1"},
                ])
            );
        })
        .await;
}
```

Fixing this would force us to create a `fid_word_pair_proximity_docids` and a `fid_word_prefix_pair_proximity_docids` databases which may multiply the keys of `word_pair_proximity_docids` and `word_prefix_pair_proximity_docids` by the number of attributes in the searchable_attributes list. If we think we should fix this test, I'll suggest doing it in another PR.

## Related

Fixes #3772

Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: ManyTheFish <many@meilisearch.com>
2023-06-28 08:19:23 +00:00
Clément Renault
29d8268c94
Fix the vector query part by using the correct universe 2023-06-27 12:32:43 +02:00
Kerollmops
ab9f2269aa
Normalize the vectors during indexation and search 2023-06-27 12:32:41 +02:00
Kerollmops
3b560ef7d0
Make clippy happy 2023-06-27 12:32:40 +02:00
Kerollmops
3c31e1cdd1
Support more pages but in an ugly way 2023-06-27 12:32:39 +02:00
Kerollmops
c79e82c62a
Move back to the hnsw crate
This reverts commit 7a4b6c065482f988b01298642f4c18775503f92f.
2023-06-27 12:32:39 +02:00
Kerollmops
268a9ef416
Move to the hgg crate 2023-06-27 12:32:38 +02:00
Clément Renault
642b0f3a1b
Expose a new vector field on the search route 2023-06-27 12:32:38 +02:00
ManyTheFish
63ca25290b Take into account small Review requests 2023-06-26 14:56:19 +02:00
ManyTheFish
59f64a5256 Return an error when an attribute is not searchable 2023-06-26 14:56:19 +02:00
ManyTheFish
42709ea9a5 Fix clippy warnings 2023-06-26 14:55:57 +02:00
ManyTheFish
fb8fa07169 Restrict field ids in search context 2023-06-26 14:55:57 +02:00
ManyTheFish
0ccf1e2e40 Allow the search cache to store owned values 2023-06-26 14:55:57 +02:00
ManyTheFish
461b5118bd Add API search setting 2023-06-26 14:55:14 +02:00
Tamo
a3716c5678 add the new parameter to the search builder of milli 2023-06-26 14:55:14 +02:00
Louis Dureuil
d26e9a96ec
Add score details to new search tests 2023-06-22 12:39:14 +02:00
Louis Dureuil
49c8bc4de6
Fix tests 2023-06-22 12:39:14 +02:00
Louis Dureuil
da833eb095
Expose the scores and detailed scores in the API 2023-06-22 12:39:14 +02:00
Louis Dureuil
701d44bd91
Store the scores for each bucket
Remove optimization where ranking rules are not executed on buckets of a single document
when the score needs to be computed
2023-06-22 12:39:14 +02:00
Louis Dureuil
c621a250a7
Score for graph based ranking rules
Count phrases in matchingWords and maxMatchingWords
2023-06-22 12:39:14 +02:00
Louis Dureuil
8939e85f60
Add rank_to_score for graph based ranking rules 2023-06-22 12:39:14 +02:00
Louis Dureuil
fa41d2489e
Score for sort 2023-06-22 12:39:14 +02:00
Louis Dureuil
59c5b992c2
Score for geosort 2023-06-22 12:39:14 +02:00
Louis Dureuil
2ea8194c18
Score for exact_attributes 2023-06-22 12:39:14 +02:00
Louis Dureuil
421df64602
RankingRuleOutput now contains a Score 2023-06-22 12:39:14 +02:00
Louis Dureuil
f050634b1e
add virtual conditions to fid and position to always have the max cost 2023-06-20 10:07:18 +02:00
Louis Dureuil
becf1f066a
Change how the cost of removing words is computed 2023-06-20 09:45:43 +02:00
Louis Dureuil
701d299369
Remove out-of-date comment 2023-06-20 09:45:42 +02:00
Louis Dureuil
a20e4d447c
Position now takes into account the distance to the position of the word in the query
it used to be based on the distance to the position 0
2023-06-20 09:45:42 +02:00
Louis Dureuil
af57c3c577
Proximity costs 0 for documents that are perfectly matching 2023-06-20 09:45:42 +02:00
Louis Dureuil
0c40ef6911
Fix sort id 2023-06-20 09:45:42 +02:00
Loïc Lecrenier
2da86b31a6 Remove comments and add documentation 2023-06-14 12:39:42 +02:00
Louis Dureuil
a2a3b8c973
Fix offset difference between query and indexing for hard separators 2023-06-08 12:07:12 +02:00
Louis Dureuil
1dfc4038ab
Add test that fails before PR and passes now 2023-05-29 11:58:26 +02:00
Louis Dureuil
73198179f1
Consistently use wrapping add to avoid overflow in debug when query starts with a separator 2023-05-29 11:54:12 +02:00
meili-bors[bot]
2e49d6aec1
Merge #3768
3768: Fix bugs in graph-based ranking rules + make `words` a graph-based ranking rule r=dureuill a=loiclec

This PR contains three changes:

## 1. Don't call the `words` ranking rule if the term matching strategy is `All`

This is because the purpose of `words` is only to remove nodes from the query graph. It would never do any useful work when the matching strategy was `All`. Remember that the universe was already computed before by computing all the docids corresponding to the "maximally reduced" query graph, which, in the case of `All`, is equal to the original graph.

## 2. The `words` ranking rule is replaced by a graph-based ranking rule. 

This is for three reasons:

1. **performance**: graph-based ranking rules benefit from a lot of optimisations by default, which ensures that they are never too slow. The previous implementation of `words` could call `compute_query_graph_docids` many times if some words had to be removed from the query, which would be quite expensive. I was especially worried about its performance in cases where it is placed right after the `sort` ranking rule. Furthermore, `compute_query_graph_docids` would clone a lot of bitmaps many times unnecessarily.

2. **consistency**: every other ranking rule (except `sort`) is graph-based. It makes sense to implement `words` like that as well. It will automatically benefit from all the features, optimisations, and bug fixes that all the other ranking rules get.

3. **surfacing bugs**: as the first ranking rule to be called (most of the time), I'd like `words` to behave the same as the other ranking rules so that we can quickly detect bugs in our graph algorithms. This actually already happened, which is why this PR also contains a bug fix.

## 3. Fix the `update_all_costs_before_nodes` function

It is a bit difficult to explain what was wrong, but I'll try. The bug happened when we had graphs like:
<img width="730" alt="Screenshot 2023-05-16 at 10 58 57" src="https://github.com/meilisearch/meilisearch/assets/6040237/40db1a68-d852-4e89-99d5-0d65757242a7">
and we gave the node `is` as argument.

Then, we'd walk backwards from the node breadth-first. We'd update the costs of:
1. `sun`
2. `thesun`
3. `start`
4. `the`

which is an incorrect order. The correct order is:

1. `sun`
2. `thesun`
3. `the`
4. `start`

That is, we can only update the cost of a node when all of its successors have either already been visited or were not affected by the update to the node passed as argument. To solve this bug, I factored out the graph-traversal logic into a `traverse_breadth_first_backward` function.


Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
2023-05-23 13:28:08 +00:00