467: optimize prefix database r=Kerollmops a=MarinPostma
This pr introduces two optimizations that greatly improve the speed of computing prefix databases.
- The time that it takes to create the prefix FST has been divided by 5 by inverting the way we iterated over the words FST.
- We unconditionally and needlessly checked for documents to remove in `word_prefix_pair`, which caused an iteration over the whole database.
Co-authored-by: ad hoc <postma.marin@protonmail.com>
> "Attribute `{}` is not sortable. This index doesn't have configured sortable attributes."
> "Attribute `{}` is not sortable. Available sortable attributes are: `{}`."
coexist in the error handling
436: Speed up the word prefix databases computation time r=Kerollmops a=Kerollmops
This PR depends on the fixes done in #431 and must be merged after it.
In this PR we will bring the `WordPrefixPairProximityDocids`, `WordPrefixDocids` and, `WordPrefixPositionDocids` update structures to a new era, a better era, where computing the word prefix pair proximities costs much fewer CPU cycles, an era where this update structure can use the, previously computed, set of new word docids from the newly indexed batch of documents.
---
The `WordPrefixPairProximityDocids` is an update structure, which means that it is an object that we feed with some parameters and which modifies the LMDB database of an index when asked for. This structure specifically computes the list of word prefix pair proximities, which correspond to a list of pairs of words associated with a proximity (the distance between both words) where the second word is not a word but a prefix e.g. `s`, `se`, `a`. This word prefix pair proximity is associated with the list of documents ids which contains the pair of words and prefix at the given proximity.
The origin of the performances issue that this struct brings is related to the fact that it starts its job from the beginning, it clears the LMDB database before rewriting everything from scratch, using the other LMDB databases to achieve that. I hope you understand that this is absolutely not an optimized way of doing things.
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
442: fix phrase search r=curquiza a=MarinPostma
Run the exact match search on 7 words windows instead of only two. This makes false positive very very unlikely, and impossible on phrase query that are less than seven words.
Co-authored-by: ad hoc <postma.marin@protonmail.com>
433: fix(filter): Fix two bugs. r=Kerollmops a=irevoire
- Stop lowercasing the field when looking in the field id map
- When a field id does not exist it means there is currently zero
documents containing this field thus we return an empty RoaringBitmap
instead of throwing an internal error
Will fix https://github.com/meilisearch/MeiliSearch/issues/2082 once meilisearch is released
Co-authored-by: Tamo <tamo@meilisearch.com>
- Stop lowercasing the field when looking in the field id map
- When a field id does not exist it means there is currently zero
documents containing this field thus we returns an empty RoaringBitmap
instead of throwing an internal error
The `matching_bytes` function takes a `&Token` now and:
- gets the number of bytes to highlight (unchanged).
- uses `Token.num_graphemes_from_bytes` to get the number of grapheme
clusters to highlight.
In essence, the `matching_bytes` function returns the number of matching
grapheme clusters instead of bytes. Should this function be renamed
then?
Added proper highlighting in the HTTP UI:
- requires dependency on `unicode-segmentation` to extract grapheme
clusters from tokens
- `<mark>` tag is put around only the matched part
- before this change, the entire word was highlighted even if only a
part of it matched
returned metaimprove document addition returned metaimprove document
addition returned metaimprove document addition returned metaimprove
document addition returned metaimprove document addition returned
metaimprove document addition returned meta
402: Optimize document transform r=MarinPostma a=MarinPostma
This pr optimizes the transform of documents additions in the obkv format. Instead on accepting any serializable objects, we instead treat json and CSV specifically:
- For json, we build a serde `Visitor`, that transform the json straight into obkv without intermediate representation.
- For csv, we directly write the lines in the obkv, applying other optimization as well.
Co-authored-by: marin postma <postma.marin@protonmail.com>
390: Add helper methods on the settings r=Kerollmops a=irevoire
This would be a good addition to look at the content of a setting without consuming it.
It’s useful for analytics.
Co-authored-by: Irevoire <tamo@meilisearch.com>
384: Replace memmap with memmap2 r=Kerollmops a=palfrey
[memmap is unmaintained](https://rustsec.org/advisories/RUSTSEC-2020-0077.html) and needs replacing. memmap2 is a drop-in replacement fork that's well maintained. Note that the version numbers got reset on fork, hence the lower values.
Co-authored-by: Tom Parker-Shemilt <palfrey@tevp.net>
388: fix primary key inference r=MarinPostma a=MarinPostma
The primary key is was infered from a hashtable index of the field. For this reason the order in which the fields were interated upon was not deterministic, and the primary key was chosed ffrom the first field containing "id".
This fix sorts the the index by field_id when infering the primary key.
Co-authored-by: mpostma <postma.marin@protonmail.com>
Instead of using an arbitrary limit we encode the absolute position in a u32
using one strong u16 for the field id and a weak u16 for the relative position in the attribute.
Latitude are not supposed to go beyound 90 degrees or below -90.
The same goes for longitude with 180 or -180.
This was badly implemented in the filters, and was not implemented for the AscDesc rules.
379: Revert "Change chunk size to 4MiB to fit more the end user usage" r=curquiza a=ManyTheFish
Reverts meilisearch/milli#370
Co-authored-by: Many <legendre.maxime.isn@gmail.com>
373: Improve error message for bad sort syntax with geosearch r=Kerollmops a=irevoire
`@Kerollmops` This should be the last PR for the geosearch and error handling, sorry for doing it in so many steps 😬
Co-authored-by: Tamo <tamo@meilisearch.com>
372: Fix Meilisearch 1714 r=Kerollmops a=ManyTheFish
The bug comes from the typo tolerance, to know how many typos are accepted we were counting bytes instead of characters in a word.
On Chinese Script characters, we were allowing 2 typos on 3 characters words.
We are now counting the number of char instead of counting bytes to assign the typo tolerance.
Related to [Meilisearch#1714](https://github.com/meilisearch/MeiliSearch/issues/1714)
Co-authored-by: many <maxime@meilisearch.com>
322: Geosearch r=ManyTheFish a=irevoire
This PR introduces [basic geo-search functionalities](https://github.com/meilisearch/specifications/pull/59), it makes the engine able to index, filter and, sort by geo-point. We decided to use [the rstar library](https://docs.rs/rstar) and to save the points in [an RTree](https://docs.rs/rstar/0.9.1/rstar/struct.RTree.html) that we de/serialize in the index database [by using serde](https://serde.rs/) with [bincode](https://docs.rs/bincode). This is not an efficient way to query this tree as it will consume a lot of CPU and memory when a search is made, but at least it is an easy first way to do so.
### What we will have to do on the indexing part:
- [x] Index the `_geo` fields from the documents.
- [x] Create a new module with an extractor in the `extract` module that takes the `obkv_documents` and retrieves the latitude and longitude coordinates, outputting them in a `grenad::Reader` for further process.
- [x] Call the extractor in the `extract::extract_documents_data` function and send the result to the `TypedChunk` module.
- [x] Get the `grenad::Reader` in the `typed_chunk::write_typed_chunk_into_index` function and store all the points in the `rtree`
- [x] Delete the documents from the `RTree` when deleting documents from the database. All this can be done in the `delete_documents.rs` file by getting the data structure and removing the points from it, inserting it back after the modification.
- [x] Clearing the `RTree` entirely when we clear the documents from the database, everything happens in the `clear_documents.rs` file.
- [x] save a Roaring bitmap of all documents containing the `_geo` field
### What we will have to do on the query part:
- [x] Filter the documents at a certain distance around a point, this is done by [collecting the documents from the searched point](https://docs.rs/rstar/0.9.1/rstar/struct.RTree.html#method.nearest_neighbor_iter) while they are in range.
- [x] We must introduce new `geoLowerThan` and `geoGreaterThan` variants to the `Operator` filter enum.
- [x] Implement the `negative` method on both variants where the `geoGreaterThan` variant is implemented by executing the `geoLowerThan` and removing the results found from the whole list of geo faceted documents.
- [x] Add the `_geoRadius` function in the pest parser.
- [x] Introduce a `_geo` ascending ranking function that takes a point in parameter, ~~this function must keep the iterator on the `RTree` and make it peekable~~ This was not possible for now, we had to collect the whole iterator. Only the documents that are part of the candidates must be sent too!
- [x] This ascending ranking rule will only be active if the search is set up with the `_geoPoint` parameter that indicates the center point of the ascending ranking rule.
-----------
- On Meilisearch part: We must introduce a new concept, returning the documents with a new `_geoDistance` field when it passed by the `_geo` ranking rule, this has never been done before. We could maybe just do it afterward when the documents have been retrieved from the database, computing the distance from the `_geoPoint` and all of the documents to be returned.
Co-authored-by: Irevoire <tamo@meilisearch.com>
Co-authored-by: cvermand <33010418+bidoubiwa@users.noreply.github.com>
Co-authored-by: Tamo <tamo@meilisearch.com>
