4713: Speed up facet distribution r=ManyTheFish a=Kerollmops
This PR is akin to #4682, but this time, the same logic is applied to the facets. Bitmaps are not decoded, and we do an intersection on the bytes with the search candidates instead of materializing the RoaringBitmap to destroy it just after the operation.
A prospect raised some slow requests when performing facet searches, and I found out that the disk optimization intersection wasn't performed on the facets.
Co-authored-by: Clément Renault <clement@meilisearch.com>
4693: Introduce distinct attributes at search time r=irevoire a=Kerollmops
This PR fixes#4611.
### To Do
- [x] Remove the `distinguishableAttributes` settings (not even a commit about that).
- [x] Use the `filterableAttributes` to be able to use the `distinct` parameter at search.
- [x] Work on the errors and make tests.
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
4649: Don't store the vectors in the documents database r=dureuill a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/4607
## What does this PR do?
- Ensure that anything falling under `_vectors` is NOT searchable, filterable or sortable
- [x] per embedder, add a roaring bitmap of documents that provide "userProvided" embeddings
- [x] in the indexing process in extract_vector_points, set the bit corresponding to the document depending on the "userProvided" subfield in the _vectors field.
- [x] in the document DB in typed chunks, when writing the _vectors field, remove all keys corresponding to an embedder
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
