4254: Bring back v1.5.1 changes into main r=ManyTheFish a=Kerollmops
This pull request brings back changes from the _release-v1.5.1_ branch into _main_.
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: curquiza <curquiza@users.noreply.github.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
4250: Update version for the next release (v1.5.1) in Cargo.toml r=dureuill a=meili-bot
⚠️ This PR is automatically generated. Check the new version is the expected one and Cargo.lock has been updated before merging.
Co-authored-by: curquiza <curquiza@users.noreply.github.com>
4239: Remove the actix-web dependency from milli r=dureuill a=Kerollmops
Just remove actix-web from milli.
Co-authored-by: Clément Renault <clement@meilisearch.com>
4233: Add test reproducing #4232 r=dureuill a=ManyTheFish
- add a test reproducing the bug
- fix the bug by creating 2 different restricting lists of attributes, one for the exact attributes, and the other for the tolerant attributes
## Related issue
Fixes#4232
Co-authored-by: ManyTheFish <many@meilisearch.com>
4223: Update to heed 0.20 r=dureuill a=Kerollmops
This PR brings the v0.20-alpha.9 version of heed into Meilisearch 🎉 The main goal is to test it in a real environment to make the necessary changes if needed. We also want to merge it as soon as possible during the pre-release phase to ensure we catch bugs before the release.
Most of the calls to heed are the same as before, except:
- The `PolyDatabase` has been replaced with a `Database<Unspecified, Unspecified>`. We replaced the `get<T, U>()` by a `remap<T, U>().get()` calls.
- The `Database` `append(...)` method has been replaced with a `put_with_flags(PutFlags::APPEND, ...)`.
- The `RwTxn<'e, 'p>` has been simplified into a `RwTxn<'e>`.
- The `BytesEncode/Decode` traits return a `Result<_, BoxedError>` instead of an `Option<_>`.
- We no longer need to wrap and unwrap the `BEU32` integer when storing/getting them from heed.
### TODO
- [x] Create actual, simple error types instead of using strings in the codecs.
### Follow-up work
- Move the codecs into another member crate (we depend on the uuid one in the meilitool crate).
- Display the internal decoding error in the `SerializationError` internal error variant.
Co-authored-by: Clément Renault <clement@meilisearch.com>
4234: Fix puffin in the index scheduler r=dureuill a=irevoire
Currently, we can't compile the index scheduler without this feature.
It could be cool to specify the dependencies in the main workspace cargo toml like quickwit does to avoid this kind of error in the future; https://github.com/quickwit-oss/quickwit/blob/main/quickwit/Cargo.toml#L41
Co-authored-by: Tamo <tamo@meilisearch.com>
4231: Fixed payload limit setting being ignored for delete documents by batch r=Kerollmops a=Karribalu
# Pull Request
## Related issue
Fixes#4224
## What does this PR do?
- Added http_payload_size_limit to JsonConfig to allow deleting documents in batches with a payload size greater than 2MB, which is the default limit set in the JsonConfig crate.
## PR checklist
Please check if your PR fulfills the following requirements:
- [Y] Does this PR fix an existing issue, or have you listed the changes applied in the PR description (and why they are needed)?
- [Y] Have you read the contributing guidelines?
- [Y] 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: karribalu <karri.balu123456@gmail.com>
4220: Bring back changes from v1.5.0 into main r=dureuill a=Kerollmops
This will bring the fixes from v1.5.0 into main. By [following this guide](https://github.com/meilisearch/engine-team/blob/main/resources/meilisearch-release.md#after-the-release) I decided to create a temporary branch to fix the git conflicts and merge into main afterward.
Co-authored-by: curquiza <curquiza@users.noreply.github.com>
Co-authored-by: Vivek Kumar <vivek.26@outlook.com>
Co-authored-by: Louis Dureuil <louis.dureuil@gmail.com>
Co-authored-by: meili-bors[bot] <89034592+meili-bors[bot]@users.noreply.github.com>
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Louis Dureuil <louis.dureuil@xinra.net>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
4090: Diff indexing r=ManyTheFish a=ManyTheFish
This pull request aims to reduce the indexing time by computing a difference between the data added to the index and the data removed from the index before writing in LMDB.
## Why focus on reducing the writings in LMDB?
The indexing in Meilisearch is split into 3 main phases:
1) The computing or the extraction of the data (Multi-threaded)
2) The writing of the data in LMDB (Mono-threaded)
3) The processing of the prefix databases (Mono-threaded)
see below:
Because the writing is mono-threaded, it represents a bottleneck in the indexing, reducing the number of writes in LMDB will reduce the pressure on the main thread and should reduce the global time spent on the indexing.
## Give Feedback
We created [a dedicated discussion](https://github.com/meilisearch/meilisearch/discussions/4196) for users to try this new feature and to give feedback on bugs or performance issues.
## Technical approach
### Part 1: merge the addition and the deletion process
This part:
a) Aims to reduce the time spent on indexing only the filterable/sortable fields of documents, for example:
- Updating the number of "likes" or "stars" of a song or a movie
- Updating the "stock count" or the "price" of a product
b) Aims to reduce the time spent on writing in LMDB which should reduce the global indexing time for the highly multi-threaded machines by reducing the writing bottleneck.
c) Aims to reduce the average time spent to delete documents without having to keep the soft-deleted documents implementation
- [x] Create a preprocessing function that creates the diff-based documents chuck (`OBKV<fid, OBKV<AddDel, value>>`)
- [x] and clearly separate the faceted fields and the searchable fields in two different chunks
- Change the parameters of the input extractor by taking an `OBKV<fid, OBKV<AddDel, value>>` instead of `OBKV<fid, value>`.
- [x] extract_docid_word_positions
- [x] extract_geo_points
- [x] extract_vector_points
- [x] extract_fid_docid_facet_values
- Adapt the searchable extractors to the new diff-chucks
- [x] extract_fid_word_count_docids
- [x] extract_word_pair_proximity_docids
- [x] extract_word_position_docids
- [x] extract_word_docids
- Adapt the facet extractors to the new diff-chucks
- [x] extract_facet_number_docids
- [x] extract_facet_string_docids
- [x] extract_fid_docid_facet_values
- [x] FacetsUpdate
- [x] Adapt the prefix database extractors ⚠️⚠️
- [x] Make the LMDB writer remove the document_ids to delete at the same time the new document_ids are added
- [x] Remove document deletion pipeline
- [x] remove `new_documents_ids` entirely and `replaced_documents_ids`
- [x] reuse extracted external id from transform instead of re-extracting in `TypedChunks::Documents`
- [x] Remove deletion pipeline after autobatcher
- [x] remove autobatcher deletion pipeline
- [x] everything uses `IndexOperation::DocumentOperation`
- [x] repair deletion by internal id for filter by delete
- [x] Improve the deletion via internal ids by avoiding iterating over the whole set of external document ids.
- [x] Remove soft-deleted documents
#### FIXME
- [x] field distribution is not correctly updated after deletion
- [x] missing documents in the tests of tokenizer_customization
### Part 2: Only compute the documents field by field
This part aims to reduce the global indexing time for any kind of partial document modification on any size of machine from the mono-threaded one to the highly multi-threaded one.
- [ ] Make the preprocessing function only send the fields that changed to the extractors
- [ ] remove the `word_docids` and `exact_word_docids` database and adapt the search (⚠️ could impact the search performances)
- [ ] replace the `word_pair_proximity_docids` database with a `word_pair_proximity_fid_docids` database and adapt the search (⚠️ could impact the search performances)
- [ ] Adapt the prefix database extractors ⚠️⚠️
## Technical Concerns
- The part 1 implementation could increase the indexing time for the smallest machines (with few threads) by increasing the extracting time (multi-threaded) more than the writing time (mono-threaded)
- The part 2 implementation needs to change the databases which could have a significant impact on the search performances
- The prefix databases are a bit special to process and may be a pain to adapt to the difference-based indexing
Co-authored-by: ManyTheFish <many@meilisearch.com>
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Louis Dureuil <louis@meilisearch.com>
