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5371: Composite embedders r=irevoire a=dureuill
# Pull Request
## Related issue
Fixes#5343
## What does this PR do?
- Implement [public usage](https://www.notion.so/meilisearch/Composite-embedder-usage-14a4b06b651f81859dc3df21e8cd02a0)
- Refactor the way we check if a parameter is mandatory/allowed/disallowed for a given source
- Take the "nesting context" into account for computer if a parameter is mandatory/allowed/disallowed
- Add tests checking all parameters with all sources, and made sure the results didn't change compared with v1.13
## Dumpless Upgrade
- This adds a new value for an existing parameter => compatible without change
- This adds new optional parameters => compatible without change
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
**Changes:**
The searchable database extraction is now relying on the AttributePatterns and FieldIdMapWithMetadata to match the field to extract.
Remove the SearchableExtractor trait to make the code less complex.
**Impact:**
- Document Addition/modification searchable indexing
- Document deletion searchable indexing
**Changes:**
The Documents changes now take a selector closure instead of a list of field to match the field to extract.
The seek_leaf_values_in_object function now uses a selector closure of a list of field to match the field to extract
The facet database extraction is now relying on the FilterableAttributesRule to match the field to extract.
The facet-search database extraction is now relying on the FieldIdMapWithMetadata to select the field to index.
The facet level database extraction is now relying on the FieldIdMapWithMetadata to select the field to index.
**Important:**
Because the filterable attributes are patterns now,
the fieldIdMap will only register the fields that exists in at least one document.
if a field doesn't exist in any document, it will not be registered even if it has been specified in the filterable fields.
**Impact:**
- Document Addition/modification facet indexing
- Document deletion facet indexing
5147: Batch progress r=dureuill a=irevoire
# Pull Request
## Related issue
Fixes https://github.com/meilisearch/meilisearch/issues/5068
## What does this PR do?
- ...
## PR checklist
Please check if your PR fulfills the following requirements:
- [ ] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
- [ ] Have you read the contributing guidelines?
- [ ] 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: Tamo <tamo@meilisearch.com>
5124: Optimize Prefixes and Merges r=ManyTheFish a=Kerollmops
In this PR, we plan to optimize the read of LMDB to use read the entries in lexicographic order and better use the memory-mapping OS cache:
- Optimize the prefix generation for word position docids (`@manythefish)`
- Optimize the parallel merging of the caches to sort entries before merging the caches (`@kerollmops)`
## Benchmarks on 1cpu 2gb gpo3 (5k IOps)
Before on the tag meilisearch-v1.12.0-rc.3.
```
word_position_docids:merge_and_send_docids: 988s
compute_word_fst: 23.3s
word_pair_proximity_docids:merge_and_send_docids: 428s
compute_word_prefix_fid_docids:recompute_modified_prefixes: 76.3s
compute_word_prefix_position_docids:recompute_modified_prefixes:from_prefixes: 429s
```
After sorting the whole `HashMap`s in a `Vec` on this branch.
```
word_position_docids:merge_and_send_docids: 202s
compute_word_fst: 20.4s
word_pair_proximity_docids:merge_and_send_docids: 427s
compute_word_prefix_fid_docids:recompute_modified_prefixes: 65.5s
compute_word_prefix_position_docids:recompute_modified_prefixes:from_prefixes: 62.5s
```
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
