723: Fix bug in handling of soft deleted documents when updating settings r=Kerollmops a=loiclec # Pull Request ## Related issue Fixes (partially, until merged into meilisearch) https://github.com/meilisearch/meilisearch/issues/3021 ## What does this PR do? This PR fixes the bug where a `missing key in documents database` internal error message could appear when indexing documents. When updating the settings, before clearing the database and before creating the transform output, we now modify the `ExternalDocumentsIds` structure to get rid of all references to soft deleted document ids in its FSTs. It used to be that updating the settings would clear the soft-deleted document ids, but keep the original `ExternalDocumentsIds` structure. As a consequence of this, when processing a future document addition, we could wrongly believe that a document was being replaced when, in fact, it was a completely new document. See the tests `bug_3021_first`, `bug_3021_second`, and `bug_3021` for a minimal test case that would have reproduced the issue. We need to take special care to: - evaluate how users should update to v0.30.1 (containing this fix): dump? reimporting all documents from scratch? - understand IF/HOW this bug could have caused duplicate documents to be returned - and evaluate the correctness of the fix, of course :) Co-authored-by: Loïc Lecrenier <loic.lecrenier@me.com>
a concurrent indexer combined with fast and relevant search algorithms
Introduction
This repository contains the core engine used in Meilisearch.
It contains a library that can manage one and only one index. Meilisearch manages the multi-index itself. Milli is unable to store updates in a store: it is the job of something else above and this is why it is only able to process one update at a time.
This repository contains crates to quickly debug the engine:
- There are benchmarks located in the
benchmarks
crate. - The
cli
crate is a simple command-line interface that helps run flamegraph on top of it. - The
filter-parser
crate contains the parser for the Meilisearch filter syntax. - The
flatten-serde-json
crate contains the library that flattens serde-jsonValue
objects like Elasticsearch does. - The
json-depth-checker
crate is used to indicate if a JSON must be flattened.
How to use it?
Milli is a library that does search things, it must be embedded in a program.
You can compute the documentation of it by using cargo doc --open
.
Here is an example usage of the library where we insert documents into the engine and search for one of them right after.
let path = tempfile::tempdir().unwrap();
let mut options = EnvOpenOptions::new();
options.map_size(10 * 1024 * 1024); // 10 MB
let index = Index::new(options, &path).unwrap();
let mut wtxn = index.write_txn().unwrap();
let content = documents!([
{
"id": 2,
"title": "Prideand Prejudice",
"author": "Jane Austin",
"genre": "romance",
"price$": "3.5$",
},
{
"id": 456,
"title": "Le Petit Prince",
"author": "Antoine de Saint-Exupéry",
"genre": "adventure",
"price$": "10.0$",
},
{
"id": 1,
"title": "Wonderland",
"author": "Lewis Carroll",
"genre": "fantasy",
"price$": "25.99$",
},
{
"id": 4,
"title": "Harry Potter ing fantasy\0lood Prince",
"author": "J. K. Rowling",
"genre": "fantasy\0",
},
]);
let config = IndexerConfig::default();
let indexing_config = IndexDocumentsConfig::default();
let mut builder =
IndexDocuments::new(&mut wtxn, &index, &config, indexing_config.clone(), |_| ())
.unwrap();
builder.add_documents(content).unwrap();
builder.execute().unwrap();
wtxn.commit().unwrap();
// You can search in the index now!
let mut rtxn = index.read_txn().unwrap();
let mut search = Search::new(&rtxn, &index);
search.query("horry");
search.limit(10);
let result = search.execute().unwrap();
assert_eq!(result.documents_ids.len(), 1);
Contributing
We're glad you're thinking about contributing to this repository! Feel free to pick an issue, and to ask any question you need. Some points might not be clear and we are available to help you!
Also, we recommend following the CONTRIBUTING.md to create your PR.