1afde4fea5
3542: Refactor of the search algorithms r=dureuill a=loiclec This PR refactors a large part of the search logic (related to https://github.com/meilisearch/meilisearch/issues/3547) - The "query tree" is replaced by a "query graph", which describes the different ways in which the search query can be interpreted and precomputes the word derivations for each query term. Example: <img width="1162" alt="Screenshot 2023-02-27 at 10 26 50" src="https://user-images.githubusercontent.com/6040237/221525270-87917cc0-60d1-473f-847f-2c5a7de9e370.png"> - The control flow between the ~criterions~ ranking rules is managed in a single place instead of being independently implemented by each ranking rule. - The set of document candidates is determined greedily from the beginning. It is often referred as the "universe" in the code. - The ranking rules `proximity`, `attribute`, `typo`, and (maybe) `exactness` are or will be implemented using a K-shortest path graph algorithm. This minimises the number of database and bitmap operations we need to do to compute each ranking rule bucket. It also simplifies the code a lot since a lot of ranking rules will share a large part of their implementation. - Pointers to database values are stored in a cache to avoid searching in the LMDB databases needlessly. - The result of some roaring bitmap operations are also stored in a cache, although we'll need to measure the memory pressure this puts on the system and maybe deactivate this cache later on. - Search requests can be visually logged and debugged in tests. TODO: - [ ] Reintroduce search benchmarks - [x] Implement `disableOnWords` and `disableOnAttributes` settings of typo tolerance - [x] Implement "exhaustive number of hits - [x] Implement `attribute` ranking rule - [x] Indexing changes: split into `word_fid_docids` and `word_position_docids` (with bucketed position) - [x] Ranking rule implementations - [ ] Implement `exactness` ranking rule - [x] Initial implementation - [ ] Correct implementation when followed by `Words` - [ ] Implement `geosort` ranking rule - [ ] Add tests - [x] Typo tolerance `disableOnWords`/`disableOnAttributes` - [ ] Geosort - [x] Exactness - [ ] Attribute/Position - [ ] Interactions between ranking rules: - [x] Typo/Proximity/Attribute not preceded by Words - [x] Exactness not preceded by Words - [x] Exactness -> Words (+ check universe correctness) - [x] Exactness -> Typo, etc. - [ ] Sort -> Words (performance tests) - [ ] Attribute/Position -> Typo - [ ] Attribute/Position -> Proximity - [x] Typo -> Exactness - [x] Typo -> Proximity - [x] Proximity -> Typo - [x] Words - [x] Typo - [x] Proximity - [x] Sort - [x] Ngrams - [x] Split words - [x] Ngram + Split Words - [x] Term matching strategy - [x] Distinct attribute - [x] Phrase Search - [x] Placeholder search - [x] Highlighter - [x] Limit the number of word derivations in a search query - [x] Compute the initial universe correctly according to the terms matching strategy - [x] Implement placeholder search - [x] Get the list of ranking rules from the settings - [x] Implement `distinct` - [x] Determine what to do when one of `attribute`, `proximity`, `typo`, or `exactness` is placed before `words` - [x] Make sure the correct number of allowed typos is used for each word, including the prefix one - [x] Make sure stop words are treated correctly (e.g. correct position in query graph), including in phrases - [x] Support phrases correctly - [x] Support synonyms - [x] Support split words - [x] Support combination of ngram + split-words (e.g. `whiteh orse` -> `"white horse"`) - [x] Implement `typo` ranking rule - [x] Implement `sort` ranking rule - [x] Use existing `Search` interface to use the new search algorithms - [x] Remove old code Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com> |
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⚡ A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow 🔍
Meilisearch helps you shape a delightful search experience in a snap, offering features that work out-of-the-box to speed up your workflow.
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✨ Features
- Search-as-you-type: find search results in less than 50 milliseconds
- Typo tolerance: get relevant matches even when queries contain typos and misspellings
- Filtering and faceted search: enhance your user's search experience with custom filters and build a faceted search interface in a few lines of code
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- Synonym support: configure synonyms to include more relevant content in your search results
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