mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-27 04:25:06 +08:00
83 lines
5.6 KiB
Markdown
83 lines
5.6 KiB
Markdown
# MeiliDB
|
|
|
|
[](https://dev.azure.com/thomas0884/thomas/_build/latest?definitionId=1&branchName=master)
|
|
[](https://deps.rs/repo/github/Kerollmops/MeiliDB)
|
|
[](https://github.com/Kerollmops/MeiliDB)
|
|
[](
|
|
https://www.rust-lang.org)
|
|
|
|
A _full-text search database_ using a key-value store internally.
|
|
|
|
## Features
|
|
|
|
- Provides [6 default ranking criteria](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/criterion/mod.rs#L95-L101) used to [bucket sort](https://en.wikipedia.org/wiki/Bucket_sort) documents
|
|
- Accepts [custom criteria](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/criterion/mod.rs#L22-L29) and can apply them in any custom order
|
|
- Support [ranged queries](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/query_builder.rs#L146), useful for paginating results
|
|
- Can [distinct](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/query_builder.rs#L68) and [filter](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/query_builder.rs#L57) returned documents based on context defined rules
|
|
- Can store complete documents or only [user schema specified fields](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/examples/movies/schema-movies.toml)
|
|
- The [default tokenizer](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-tokenizer/src/lib.rs#L99) can index latin and kanji based languages
|
|
- Returns [the matching text areas](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/lib.rs#L117-L120), useful to highlight matched words in results
|
|
- Accepts query time search config like the [searchable fields](https://github.com/meilisearch/MeiliDB/blob/3d85cbf0cfa3a3103cf1e151a75a443719cdd5d7/meilidb-core/src/query_builder.rs#L79)
|
|
- Supports run time indexing (incremental indexing)
|
|
|
|
|
|
|
|
It uses [RocksDB](https://github.com/facebook/rocksdb) as the internal key-value store. The key-value store allows us to handle updates and queries with small memory and CPU overheads. The whole ranking system is [data oriented](https://github.com/meilisearch/MeiliDB/issues/82) and provides great performances.
|
|
|
|
You can [read the deep dive](deep-dive.md) if you want more information on the engine, it describes the whole process of generating updates and handling queries or you can take a look at the [typos and ranking rules](typos-ranking-rules.md) if you want to know the default rules used to sort the documents.
|
|
|
|
We will be proud if you submit issues and pull requests. You can help to grow this project and start contributing by checking [issues tagged "good-first-issue"](https://github.com/meilisearch/MeiliDB/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22). It is a good start!
|
|
|
|
The project is only a library yet. It means that there is no binary provided yet. To get started, you can check the examples wich are made to work with the data located in the `misc/` folder.
|
|
|
|
MeiliDB will be a binary in a near future so you will be able to use it as a database out-of-the-box. We should be able to query it using a [to-be-defined](https://github.com/meilisearch/MeiliDB/issues/38) protocol. This is our current goal, [see the milestones](https://github.com/meilisearch/MeiliDB/milestones). In the end, the binary will be a bunch of network protocols and wrappers around the library - which will also be published on [crates.io](https://crates.io). Both the binary and the library will follow the same update cycle.
|
|
|
|
|
|
|
|
## Performances
|
|
|
|
With a database composed of _100 353_ documents with _352_ attributes each and _3_ of them indexed.
|
|
So more than _300 000_ fields indexed for _35 million_ stored we can handle more than _2.8k req/sec_ with an average response time of _9 ms_ on an Intel i7-7700 (8) @ 4.2GHz.
|
|
|
|
Requests are made using [wrk](https://github.com/wg/wrk) and scripted to simulate real users queries.
|
|
|
|
```
|
|
Running 10s test @ http://localhost:2230
|
|
2 threads and 25 connections
|
|
Thread Stats Avg Stdev Max +/- Stdev
|
|
Latency 9.52ms 7.61ms 99.25ms 84.58%
|
|
Req/Sec 1.41k 119.11 1.78k 64.50%
|
|
28080 requests in 10.01s, 7.42MB read
|
|
Requests/sec: 2806.46
|
|
Transfer/sec: 759.17KB
|
|
```
|
|
|
|
### Notes
|
|
|
|
The default Rust allocator has recently been [changed to use the system allocator](https://github.com/rust-lang/rust/pull/51241/).
|
|
We have seen much better performances when [using jemalloc as the global allocator](https://github.com/alexcrichton/jemallocator#documentation).
|
|
|
|
## Usage and examples
|
|
|
|
Currently MeiliDB do not provide an http server but you can run these two examples to try it out.
|
|
|
|
It creates an index named _movies_ and insert _19 700_ (in batches of _1000_) movies into it.
|
|
|
|
```bash
|
|
cargo run --release --example create-database -- \
|
|
--schema examples/movies/schema-movies.toml \
|
|
--update-group-size 1000 \
|
|
movies.mdb \
|
|
examples/movies/movies.csv
|
|
```
|
|
|
|
Once this is done, you can query this database using the second binary example.
|
|
|
|
```bash
|
|
cargo run --release --example query-database -- \
|
|
movies.mdb \
|
|
--fetch-timeout-ms 50 \
|
|
-n 4 \
|
|
id title overview release_date poster
|
|
```
|