snowykami/meilisearch
1
0
Fork 0
mirror of https://github.com/meilisearch/meilisearch.git synced 2024-11-22 18:17:39 +08:00
Code Issues Actions 9 Packages Projects Releases Wiki Activity

Update the README

Browse Source
This commit is contained in:
Clément Renault 2019-10-16 18:03:56 +02:00
parent dc5c42821e
commit 925a22b644
No known key found for this signature in database
GPG Key ID: 92ADA4E935E71FA4
1 changed files with 18 additions and 21 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

39
README.md
View File

@ -1,24 +1,22 @@
# MeiliDB
[![Build Status](https://dev.azure.com/thomas0884/thomas/_apis/build/status/meilisearch.MeiliDB?branchName=master)](https://dev.azure.com/thomas0884/thomas/_build/latest?definitionId=1&branchName=master)
[![dependency status](https://deps.rs/repo/github/Kerollmops/MeiliDB/status.svg)](https://deps.rs/repo/github/Kerollmops/MeiliDB)
[![License](https://img.shields.io/github/license/Kerollmops/MeiliDB.svg)](https://github.com/Kerollmops/MeiliDB)
[![Rust 1.31+](https://img.shields.io/badge/rust-1.31+-lightgray.svg)](
https://www.rust-lang.org)
[![dependency status](https://deps.rs/repo/github/meilisearch/MeiliDB/status.svg)](https://deps.rs/repo/github/meilisearch/MeiliDB)
[![License](https://img.shields.io/badge/license-commons%20clause-lightgrey)](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/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-core/src/criterion/mod.rs#L14-L19) used to [bucket sort](https://en.wikipedia.org/wiki/Bucket_sort) documents
- Accepts [custom criteria](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-core/src/criterion/mod.rs#L24-L33) and can apply them in any custom order
- Support [ranged queries](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-core/src/query_builder.rs#L255-L260), useful for paginating results
- Can [distinct](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-core/src/query_builder.rs#L241-L246) and [filter](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-core/src/query_builder.rs#L223-L235) returned documents based on context defined rules
- Can store complete documents or only [user schema specified fields](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-schema/src/lib.rs#L265-L279)
- The [default tokenizer](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-tokenizer/src/lib.rs) can index latin and kanji based languages
- Returns [the matching text areas](https://github.com/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/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/Kerollmops/new-meilidb/blob/dea7e28a45dde897f97742bdd33fcf75d5673502/meilidb-core/src/query_builder.rs#L248-L252)
- Supports run time indexing (incremental indexing)
- 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)
@ -28,9 +26,9 @@ You can [read the deep dive](deep-dive.md) if you want more information on the e
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.
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 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.
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.
@ -54,23 +52,22 @@ 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/).
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 these two examples to try it out.
Currently MeiliDB do not provide an http server but you can run the example binary.
It creates an index named _movies_ and insert _19 700_ (in batches of _1000_) movies into it.
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 \
--update-group-size 1000
--schema datasets/movies/schema.toml
```
Once this is done, you can query this database using the second binary example.
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 -- \