cd2635ccfc
602: Use mimalloc as the default allocator r=Kerollmops a=loiclec ## What does this PR do? Use mimalloc as the global allocator for milli's benchmarks on macOS. ## Why? On Linux, we use jemalloc, which is a very fast allocator. But on macOS, we currently use the system allocator, which is very slow. In practice, this difference in allocator speed means that it is difficult to gain insight into milli's performance by running benchmarks locally on the Mac. By using mimalloc, which is another excellent allocator, we reduce the speed difference between the two platforms. Co-authored-by: Loïc Lecrenier <loic@meilisearch.com> |
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.github | ||
benchmarks | ||
cli | ||
filter-parser | ||
flatten-serde-json | ||
helpers | ||
http-ui | ||
infos | ||
json-depth-checker | ||
milli | ||
script | ||
.gitignore | ||
.rustfmt.toml | ||
bors.toml | ||
Cargo.toml | ||
CONTRIBUTING.md | ||
LICENSE | ||
README.md |
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.