mirror of
https://github.com/meilisearch/meilisearch.git
synced 2024-11-30 09:04:59 +08:00
79 lines
5.9 KiB
Markdown
79 lines
5.9 KiB
Markdown
# MeiliDB
|
|
|
|
[](https://dev.azure.com/thomas0884/thomas/_build/latest?definitionId=1&branchName=master)
|
|
[](https://deps.rs/repo/github/meilisearch/MeiliDB)
|
|
[](https://commonsclause.com/)
|
|
|
|
A _full-text search database_ based on the fast [LMDB key-value store](https://en.wikipedia.org/wiki/Lightning_Memory-Mapped_Database).
|
|
|
|
## Features
|
|
|
|
- Provides [6 default ranking criteria](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/criterion/mod.rs#L107-L113) used to [bucket sort](https://en.wikipedia.org/wiki/Bucket_sort) documents
|
|
- Accepts [custom criteria](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/criterion/mod.rs#L24-L33) and can apply them in any custom order
|
|
- Support [ranged queries](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/query_builder.rs#L283), useful for paginating results
|
|
- Can [distinct](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/query_builder.rs#L265-L270) and [filter](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/query_builder.rs#L246-L259) returned documents based on context defined rules
|
|
- Can store complete documents or only [user schema specified fields](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-schema/src/lib.rs#L265-L279)
|
|
- The [default tokenizer](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-tokenizer/src/lib.rs) can index latin and kanji based languages
|
|
- Returns [the matching text areas](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/lib.rs#L66-L88), useful to highlight matched words in results
|
|
- Accepts query time search config like the [searchable attributes](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/query_builder.rs#L272-L275)
|
|
- Supports [runtime incremental indexing](https://github.com/meilisearch/MeiliDB/blob/dc5c42821e1340e96cb90a3da472264624a26326/meilidb-core/src/store/mod.rs#L143-L173)
|
|
|
|
|
|
|
|
It uses [LMDB](https://en.wikipedia.org/wiki/Lightning_Memory-Mapped_Database) 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 `datasets/` 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 HTTP. 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
|
|
|
|
With Rust 1.32 the allocator has been [changed to use the system allocator](https://blog.rust-lang.org/2019/01/17/Rust-1.32.0.html#jemalloc-is-removed-by-default).
|
|
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 the example binary.
|
|
|
|
The _index_ subcommand has been made to create an index and inject documents into it. Using the command line below, the index will be named _movies_ and the _19 700_ movies of the `datasets/` will be injected in MeiliDB.
|
|
|
|
```bash
|
|
cargo run --release --example from_file -- \
|
|
index example.mdb datasets/movies/data.csv \
|
|
--schema datasets/movies/schema.toml
|
|
```
|
|
|
|
Once the first command is done, you can query the freshly created _movies_ index using the _search_ subcomand. In this example we filtered the dataset to only show _non-adult_ movies using the non-definitive `!adult` syntax filter.
|
|
|
|
```bash
|
|
cargo run --release --example from_file -- \
|
|
search example.mdb
|
|
--number 4 \
|
|
--filter '!adult' \
|
|
id popularity adult original_title
|
|
```
|