diff --git a/README.md b/README.md index 181dd0d13..1c9652d31 100644 --- a/README.md +++ b/README.md @@ -7,8 +7,12 @@ ⚡ 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/). -## What MeiliSearch has to offer +[![crates.io demo gif](misc/crates-io-demo.gif)](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) @@ -17,50 +21,34 @@ MeiliSearch is a powerful, fast, open-source, easy to use, and deploy search eng * Easy to install, deploy, and maintain * Whole documents returned * Highly customizable -* RESTfull API - -For more [details about those features, go to our documentation](https://docs.meilisearch.com/introduction/features.html). - -[![crates.io demo gif](misc/crates-io-demo.gif)](https://crates.meilisearch.com) - -> Meili helps the Rust community find crates on [crates.meilisearch.com](https://crates.meilisearch.com) - -### In-depth 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) - +* RESTfull API ## Quick Start -You can deploy your instant, relevant, and typo-tolerant MeiliSearch search engine by yourself too. -Something similar to the demo above can be achieved by following these little three steps first. -You still need to create your front-end to make it pretty, though. - ### Deploy the Server -If you have not yet installed Rust and its package manager `cargo`, go to [the installation page](https://www.rust-lang.org/tools/install).
-You can deploy the server on your machine; it listens to HTTP requests on the 7700 port by default. - ```bash +# If you have the Rust toolchain already installed, you can compile from the source +git clone https://github.com/meilisearch/MeiliSearch.git +cd MeiliSearch cargo run --release -``` -For more logs during the execution, run: -```bash -RUST_LOG=info cargo run --release +# You can also use Docker +docker run -it -p 7700:7700 --rm getmeili/MeiliSearch + +# You can also download the binary +curl -L https://install.meilisearch.com | sh +./meilisearch ``` ### 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/33MKvk4' -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. @@ -74,7 +62,7 @@ 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 @datasets/movies/movies.json + --data-binary @movies.json ``` ### Search for Documents @@ -83,34 +71,57 @@ The search engine is now aware of our documents and can serve those via our HTTP 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' +curl 'http://127.0.0.1:7700/indexes/movies/search?q=botman+robin&limit=2' | jq ``` ```json { "hits": [ { - "id": "29751", - "title": "Batman Unmasked: The Psychology of the Dark Knight", - "poster": "https://image.tmdb.org/t/p/w1280/jjHu128XLARc2k4cJrblAvZe0HE.jpg", - "overview": "Delve into the world of Batman and the vigilante justice tha", - "release_date": "2008-07-15" + "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": "471474", - "title": "Batman: Gotham by Gaslight", - "poster": "https://image.tmdb.org/t/p/w1280/7souLi5zqQCnpZVghaXv0Wowi0y.jpg", - "overview": "ve Victorian Age Gotham City, Batman begins his war on crime", - "release_date": "2018-01-12" + "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" + "query": "botman robin" } ``` +### 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. @@ -137,12 +148,6 @@ The resulting database was _16 GB_ and search results were between _30 ms_ and _ 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). -## 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. - ## 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!