mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-23 05:14:27 +01:00
189 lines
9.0 KiB
Markdown
189 lines
9.0 KiB
Markdown
# MeiliSearch
|
|
|
|
[](https://github.com/meilisearch/MeiliSearch/actions)
|
|
[](https://deps.rs/repo/github/meilisearch/MeiliSearch)
|
|
[](https://github.com/meilisearch/MeiliSearch/blob/master/LICENSE)
|
|
|
|
⚡ Ultra relevant and instant full-text search API 🔍
|
|
|
|
MeiliSearch is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.
|
|
For more [details about those features, go to our documentation](https://docs.meilisearch.com/).
|
|
|
|
[](https://crates.meilisearch.com)
|
|
> Meili helps the Rust community find crates on [crates.meilisearch.com](https://crates.meilisearch.com)
|
|
|
|
## Features
|
|
* Search as-you-type experience (answers < 50ms)
|
|
* Full-text search
|
|
* Typo tolerant (understands typos and spelling mistakes)
|
|
* Supports Kanji
|
|
* Supports Synonym
|
|
* Easy to install, deploy, and maintain
|
|
* Whole documents returned
|
|
* Highly customizable
|
|
* RESTfull API
|
|
|
|
## Quick Start
|
|
|
|
### Deploy the Server
|
|
|
|
#### Run it using Docker
|
|
|
|
```bash
|
|
docker run -it -p 7700:7700 --rm getmeili/meilisearch
|
|
```
|
|
|
|
#### Installation using APT
|
|
|
|
```bash
|
|
echo "deb [trusted=yes] https://apt.fury.io/meilisearch/ /" > /etc/apt/sources.list.d/fury.list
|
|
apt update && apt install meilisearch-http
|
|
meilisearch
|
|
```
|
|
|
|
#### Download the binary
|
|
|
|
```bash
|
|
curl -L https://install.meilisearch.com | sh
|
|
./meilisearch
|
|
```
|
|
|
|
#### Run it on heroku
|
|
|
|
[](https://heroku.com/deploy?template=https://github.com/meilisearch/MeiliSearch)
|
|
|
|
#### Compile and run it from sources
|
|
|
|
If you have the Rust toolchain already installed, you can compile from the source
|
|
|
|
```bash
|
|
git clone https://github.com/meilisearch/MeiliSearch.git
|
|
cd MeiliSearch
|
|
cargo run --release
|
|
```
|
|
|
|
### Create an Index and Upload Some Documents
|
|
|
|
We provide a movie dataset that you can use for testing purposes.
|
|
|
|
```bash
|
|
curl -L 'https://bit.ly/2PAcw9l' -o movies.json
|
|
```
|
|
|
|
MeiliSearch can serve multiple indexes, with different kinds of documents,
|
|
therefore, it is required to create the index before sending documents to it.
|
|
|
|
```bash
|
|
curl -i -X POST 'http://127.0.0.1:7700/indexes' --data '{ "name": "Movies", "uid": "movies" }'
|
|
```
|
|
|
|
Now that the server knows about our brand new index, we can send it data.
|
|
We provided you a small dataset that is available in the `datasets/` directory.
|
|
|
|
```bash
|
|
curl -i -X POST 'http://127.0.0.1:7700/indexes/movies/documents' \
|
|
--header 'content-type: application/json' \
|
|
--data-binary @movies.json
|
|
```
|
|
|
|
### Search for Documents
|
|
|
|
#### In command line
|
|
|
|
The search engine is now aware of our documents and can serve those via our HTTP server again.
|
|
The [`jq` command-line tool](https://stedolan.github.io/jq/) can significantly help you read the server responses.
|
|
|
|
```bash
|
|
curl 'http://127.0.0.1:7700/indexes/movies/search?q=botman+robin&limit=2' | jq
|
|
```
|
|
|
|
```json
|
|
{
|
|
"hits": [
|
|
{
|
|
"id": "415",
|
|
"title": "Batman & Robin",
|
|
"poster": "https://image.tmdb.org/t/p/w1280/79AYCcxw3kSKbhGpx1LiqaCAbwo.jpg",
|
|
"overview": "Along with crime-fighting partner Robin and new recruit Batgirl...",
|
|
"release_date": "1997-06-20",
|
|
},
|
|
{
|
|
"id": "411736",
|
|
"title": "Batman: Return of the Caped Crusaders",
|
|
"poster": "https://image.tmdb.org/t/p/w1280/GW3IyMW5Xgl0cgCN8wu96IlNpD.jpg",
|
|
"overview": "Adam West and Burt Ward returns to their iconic roles of Batman and Robin...",
|
|
"release_date": "2016-10-08",
|
|
}
|
|
],
|
|
"offset": 0,
|
|
"limit": 2,
|
|
"processingTimeMs": 1,
|
|
"query": "botman robin"
|
|
}
|
|
```
|
|
|
|
#### With the Web Interface
|
|
|
|
MeiliSearch provides a simple web interface containing a search bar in order to quickly test the instant search experience with a given set of documents.
|
|
|
|
This web interface is available in your browser at the root of the server. The default URL is [http://127.0.0.1:7700](http://127.0.0.1:7700).
|
|
|
|
### Documentation
|
|
|
|
Now, that you have a running MeiliSearch, you can learn more and tune your search engine using [the documentation](https://docs.meilisearch.com).
|
|
|
|
## How it works
|
|
|
|
MeiliSearch 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/MeiliSearch/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. Also, 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.
|
|
|
|
### Technical features
|
|
|
|
- Provides [6 default ranking criteria](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/criterion/mod.rs#L106-L111) used to [bucket sort](https://en.wikipedia.org/wiki/Bucket_sort) documents
|
|
- Accepts [custom criteria](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/criterion/mod.rs#L20-L29) and can apply them in any custom order
|
|
- Support [ranged queries](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/query_builder.rs#L342), useful for paginating results
|
|
- Can [distinct](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/query_builder.rs#L324-L329) and [filter](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/query_builder.rs#L313-L318) returned documents based on context defined rules
|
|
- Searches for [concatenated](https://github.com/meilisearch/MeiliSearch/pull/164) and [splitted query words](https://github.com/meilisearch/MeiliSearch/pull/232) to improve the search quality.
|
|
- Can store complete documents or only [user schema specified fields](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/datasets/movies/schema.toml)
|
|
- The [default tokenizer](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-tokenizer/src/lib.rs) can index latin and kanji based languages
|
|
- Returns [the matching text areas](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-types/src/lib.rs#L49-L65), useful to highlight matched words in results
|
|
- Accepts query time search config like the [searchable attributes](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/query_builder.rs#L331-L336)
|
|
- Supports [runtime incremental indexing](https://github.com/meilisearch/MeiliSearch/blob/3ea5aa18a209b6973b921542d46a79e1c753c163/meilisearch-core/src/store/mod.rs#L143-L212)
|
|
|
|
## Performances
|
|
|
|
With a dataset 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
|
|
```
|
|
|
|
We also indexed a dataset containing something like _12 millions_ cities names in _24 minutes_ on a machine with _8 cores_, _64 GB of RAM_, and a _300 GB NMVe_ SSD.<br/>
|
|
The resulting database was _16 GB_ and search results were between _30 ms_ and _4 seconds_ for short prefix queries.
|
|
|
|
### 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).
|
|
|
|
## Contributing
|
|
|
|
We will be glad 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/MeiliSearch/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22). It is a good start!
|
|
|
|
### Analytic Events
|
|
|
|
We send events to our Amplitude instance to be aware of the number of people who use MeiliSearch.<br/>
|
|
We only send the platform on which the server runs once by day. No other information is sent.<br/>
|
|
If you do not want us to send events, you can disable these analytics by using the `MEILI_NO_ANALYTICS` env variable.
|