mirror of
https://github.com/meilisearch/MeiliSearch
synced 2024-11-05 04:28:55 +01:00
44 lines
1.5 KiB
Markdown
44 lines
1.5 KiB
Markdown
<p align="center">
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<img alt="the milli logo" src="http-ui/public/logo-black.svg">
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</p>
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<p align="center">a concurrent indexer combined with fast and relevant search algorithms</p>
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## Introduction
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This engine is a prototype, do not use it in production.
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This is one of the most advanced search engine I have worked on.
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It currently only supports the proximity criterion.
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### Compile and Run the server
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You can specify the number of threads to use to index documents and many other settings too.
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```bash
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cd http-ui
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cargo run --release -- serve --db my-database.mdb -vvv --indexing-jobs 8
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```
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### Index your documents
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It can index a massive amount of documents in not much time, I already achieved to index:
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- 115m songs (song and artist name) in ~1h and take 107GB on disk.
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- 12m cities (name, timezone and country ID) in 15min and take 10GB on disk.
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All of that on a 39$/month machine with 4cores.
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You can feed the engine with your CSV (comma-seperated, yes) data like this:
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```bash
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cat "name,age\nhello,32\nkiki,24\n" | http POST 127.0.0.1:9700/documents content-type:text/csv
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```
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Here ids will be automatically generated as UUID v4 if they doesn't exist in some or every documents.
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Note that it also support JSON and JSON streaming, you can send them to the engine by using
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the `content-type:application/json` and `content-type:application/x-ndjson` headers respectively.
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### Querying the engine via the website
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You can query the engine by going to [the HTML page itself](http://127.0.0.1:9700).
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