523: Improve geosearch error messages r=irevoire a=irevoire
Improve the geosearch error messages (#488).
And try to parse the string as specified in https://github.com/meilisearch/meilisearch/issues/2354
Co-authored-by: Tamo <tamo@meilisearch.com>
527: Remove the wip section part of the contributing file r=curquiza a=Kerollmops
Everything was good in the _Development Workflow_ section so I removed the _WIP Section_ part, now this PR fixes https://github.com/meilisearch/milli/issues/513.
Co-authored-by: Kerollmops <clement@meilisearch.com>
520: fix mistake in Settings initialization r=irevoire a=MarinPostma
fix settings not being correctly initialized and add a test to make sure that they are in the future.
fix https://github.com/meilisearch/meilisearch/issues/2358
Co-authored-by: ad hoc <postma.marin@protonmail.com>
522: Do not generate keys that are too long for LMDB r=Kerollmops a=Kerollmops
This PR fixes https://github.com/meilisearch/meilisearch/issues/2338 by making sure that we do not generate keys that are too long for LMDB especially when we are creating our prefix and proximity pairs keys.
Co-authored-by: Kerollmops <clement@meilisearch.com>
507: deny warnings in CI r=Kerollmops a=MarinPostma
Add `RUSTFLAGS= -D warnings` to the CI so all warnings are treated as hard errors.
Co-authored-by: ad hoc <postma.marin@protonmail.com>
518: Return facets even when there is no value associated to it r=Kerollmops a=Kerollmops
This PR is related to https://github.com/meilisearch/meilisearch/issues/2352 and should fix the issue when Meilisearch is up-to-date with this PR.
Co-authored-by: Kerollmops <clement@meilisearch.com>
511: Update version in every workspace r=curquiza a=curquiza
Checked with `@Kerollmops`
- Update the version into every workspace (the current version is v0.27.0, but I forgot to update it for the previous release)
- add `publish = false` except in `milli` workspace.
Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
514: Stop flattening every field r=Kerollmops a=irevoire
When we need to flatten a document:
* The primary key contains a `.`.
* Some fields need to be flattened
Instead of flattening the whole object and thus creating a lot of allocations with the `serde_json_flatten_crate`, we instead generate a minimal sub-object containing only the fields that need to be flattened.
That should create fewer allocations and thus index faster.
---------
```
group indexing_main_e1e362fa indexing_stop-flattening-every-field_40d1bd6b
----- ---------------------- ---------------------------------------------
indexing/Indexing geo_point 1.99 23.7±0.23s ? ?/sec 1.00 11.9±0.21s ? ?/sec
indexing/Indexing movies in three batches 1.00 18.2±0.24s ? ?/sec 1.01 18.3±0.29s ? ?/sec
indexing/Indexing movies with default settings 1.00 17.5±0.09s ? ?/sec 1.01 17.7±0.26s ? ?/sec
indexing/Indexing songs in three batches with default settings 1.00 64.8±0.47s ? ?/sec 1.00 65.1±0.49s ? ?/sec
indexing/Indexing songs with default settings 1.00 54.9±0.99s ? ?/sec 1.01 55.7±1.34s ? ?/sec
indexing/Indexing songs without any facets 1.00 50.6±0.62s ? ?/sec 1.01 50.9±1.05s ? ?/sec
indexing/Indexing songs without faceted numbers 1.00 54.0±1.14s ? ?/sec 1.01 54.7±1.13s ? ?/sec
indexing/Indexing wiki 1.00 996.2±8.54s ? ?/sec 1.02 1021.1±30.63s ? ?/sec
indexing/Indexing wiki in three batches 1.00 1136.8±9.72s ? ?/sec 1.00 1138.6±6.59s ? ?/sec
```
So basically everything slowed down a liiiiiittle bit except the dataset with a nested field which got twice faster
Co-authored-by: Tamo <tamo@meilisearch.com>
515: Improve the README r=curquiza a=Kerollmops
This PR closes#512 by adding more content to the README. We listed all of the subcrates of the repository, changed the descriptions of the subcrates, and added a simple example usage in the README.
Co-authored-by: Kerollmops <clement@meilisearch.com>
Co-authored-by: Clémentine Urquizar - curqui <clementine@meilisearch.com>
509: Remove pr_status from bors settings r=Kerollmops a=curquiza
Because of multiple issue we had with bors.
https://github.com/bors-ng/bors-ng/issues/1492
Co-authored-by: Clémentine Urquizar <clementine@meilisearch.com>
505: normalize exact words r=curquiza a=MarinPostma
Normalize the exact words, as specified in the specification.
Co-authored-by: ad hoc <postma.marin@protonmail.com>
499: fix min-word-len-for-typo not reset properly r=Kerollmops a=MarinPostma
fix min word len for typo not resettign properly, as reported in https://github.com/meilisearch/meilisearch/issues/2330
Co-authored-by: ad hoc <postma.marin@protonmail.com>
483: Enhance matching words r=Kerollmops a=ManyTheFish
# Summary
Enhance milli word-matcher making it handle match computing and cropping.
# Implementation
## Computing best matches for cropping
Before we were considering that the first match of the attribute was the best one, this was accurate when only one word was searched but was missing the target when more than one word was searched.
Now we are searching for the best matches interval to crop around, the chosen interval is the one:
1) that have the highest count of unique matches
> for example, if we have a query `split the world`, then the interval `the split the split the` has 5 matches but only 2 unique matches (1 for `split` and 1 for `the`) where the interval `split of the world` has 3 matches and 3 unique matches. So the interval `split of the world` is considered better.
2) that have the minimum distance between matches
> for example, if we have a query `split the world`, then the interval `split of the world` has a distance of 3 (2 between `split` and `the`, and 1 between `the` and `world`) where the interval `split the world` has a distance of 2. So the interval `split the world` is considered better.
3) that have the highest count of ordered matches
> for example, if we have a query `split the world`, then the interval `the world split` has 2 ordered words where the interval `split the world` has 3. So the interval `split the world` is considered better.
## Cropping around the best matches interval
Before we were cropping around the interval without checking the context.
Now we are cropping around words in the same context as matching words.
This means that we will keep words that are farther from the matching words but are in the same phrase, than words that are nearer but separated by a dot.
> For instance, for the matching word `Split` the text:
`Natalie risk her future. Split The World is a book written by Emily Henry. I never read it.`
will be cropped like:
`…. Split The World is a book written by Emily Henry. …`
and not like:
`Natalie risk her future. Split The World is a book …`
Co-authored-by: ManyTheFish <many@meilisearch.com>
