2e49d6aec1
3768: Fix bugs in graph-based ranking rules + make `words` a graph-based ranking rule r=dureuill a=loiclec This PR contains three changes: ## 1. Don't call the `words` ranking rule if the term matching strategy is `All` This is because the purpose of `words` is only to remove nodes from the query graph. It would never do any useful work when the matching strategy was `All`. Remember that the universe was already computed before by computing all the docids corresponding to the "maximally reduced" query graph, which, in the case of `All`, is equal to the original graph. ## 2. The `words` ranking rule is replaced by a graph-based ranking rule. This is for three reasons: 1. **performance**: graph-based ranking rules benefit from a lot of optimisations by default, which ensures that they are never too slow. The previous implementation of `words` could call `compute_query_graph_docids` many times if some words had to be removed from the query, which would be quite expensive. I was especially worried about its performance in cases where it is placed right after the `sort` ranking rule. Furthermore, `compute_query_graph_docids` would clone a lot of bitmaps many times unnecessarily. 2. **consistency**: every other ranking rule (except `sort`) is graph-based. It makes sense to implement `words` like that as well. It will automatically benefit from all the features, optimisations, and bug fixes that all the other ranking rules get. 3. **surfacing bugs**: as the first ranking rule to be called (most of the time), I'd like `words` to behave the same as the other ranking rules so that we can quickly detect bugs in our graph algorithms. This actually already happened, which is why this PR also contains a bug fix. ## 3. Fix the `update_all_costs_before_nodes` function It is a bit difficult to explain what was wrong, but I'll try. The bug happened when we had graphs like: <img width="730" alt="Screenshot 2023-05-16 at 10 58 57" src="https://github.com/meilisearch/meilisearch/assets/6040237/40db1a68-d852-4e89-99d5-0d65757242a7"> and we gave the node `is` as argument. Then, we'd walk backwards from the node breadth-first. We'd update the costs of: 1. `sun` 2. `thesun` 3. `start` 4. `the` which is an incorrect order. The correct order is: 1. `sun` 2. `thesun` 3. `the` 4. `start` That is, we can only update the cost of a node when all of its successors have either already been visited or were not affected by the update to the node passed as argument. To solve this bug, I factored out the graph-traversal logic into a `traverse_breadth_first_backward` function. Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com> Co-authored-by: Louis Dureuil <louis@meilisearch.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
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Take a look at the complete Meilisearch integration list.
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Experienced users will want to keep our API Reference close at hand.
We also offer a wide range of dedicated guides to all Meilisearch features, such as filtering, sorting, geosearch, API keys, and tenant tokens.
Finally, for more in-depth information, refer to our articles explaining fundamental Meilisearch concepts such as documents and indexes.
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