561: Enriched documents batch reader r=curquiza a=Kerollmops ~This PR is based on #555 and must be rebased on main after it has been merged to ease the review.~ This PR contains the work in #555 and can be merged on main as soon as reviewed and approved. - [x] Create an `EnrichedDocumentsBatchReader` that contains the external documents id. - [x] Extract the primary key name and make it accessible in the `EnrichedDocumentsBatchReader`. - [x] Use the external id from the `EnrichedDocumentsBatchReader` in the `Transform::read_documents`. - [x] Remove the `update_primary_key` from the _transform.rs_ file. - [x] Really generate the auto-generated documents ids. - [x] Insert the (auto-generated) document ids in the document while processing it in `Transform::read_documents`. Co-authored-by: Kerollmops <clement@meilisearch.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
helpers
crate is only used to do operations on the database. - The
http-ui
crate is a simple HTTP dashboard to test the features like for real! - The
infos
crate is used to dump the internal data-structure and ensure correctness. - 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",
"au{hor": "Jane Austin",
"genre": "romance",
"price$": "3.5$",
},
{
"id": 456,
"title": "Le Petit Prince",
"au{hor": "Antoine de Saint-Exupéry",
"genre": "adventure",
"price$": "10.0$",
},
{
"id": 1,
"title": "Wonderland",
"au{hor": "Lewis Carroll",
"genre": "fantasy",
"price$": "25.99$",
},
{
"id": 4,
"title": "Harry Potter ing fantasy\0lood Prince",
"au{hor": "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.