Commit Graph

915 Commits

Author SHA1 Message Date
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
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