2f5e61bacb
184: Transfer numbers and strings facets into the appropriate facet databases r=Kerollmops a=Kerollmops
This pull request is related to https://github.com/meilisearch/milli/issues/152 and changes the layout of the facets values, numbers and strings are now in dedicated databases and the user no more needs to define the type of the fields. No more conversion between the two types is done, numbers (floats and integers converted to f64) go to the facet float database and strings go to the strings facet database.
There is one related issue that I found regarding CSVs, the values in a CSV are always considered to be strings, [meilisearch/specifications#28](d916b57d74/text/0028-indexing-csv.md) fixes this issue by allowing the user to define the fields types using `:` in the "CSV Formatting Rules" section.
All previous tests on facets have been modified to pass again and I have also done hand-driven tests with the 115m songs dataset. Everything seems to be good!
Fixes #192.
Co-authored-by: Clément Renault <clement@meilisearch.com>
Co-authored-by: Kerollmops <clement@meilisearch.com>
a concurrent indexer combined with fast and relevant search algorithms
Introduction
This engine is a prototype, do not use it in production. This is one of the most advanced search engine I have worked on. It currently only supports the proximity criterion.
Compile and Run the server
You can specify the number of threads to use to index documents and many other settings too.
cd http-ui
cargo run --release -- --db my-database.mdb -vvv --indexing-jobs 8
Index your documents
It can index a massive amount of documents in not much time, I already achieved to index:
- 115m songs (song and artist name) in ~1h and take 107GB on disk.
- 12m cities (name, timezone and country ID) in 15min and take 10GB on disk.
All of that on a 39$/month machine with 4cores.
You can feed the engine with your CSV (comma-seperated, yes) data like this:
printf "name,age\nhello,32\nkiki,24\n" | http POST 127.0.0.1:9700/documents content-type:text/csv
Here ids will be automatically generated as UUID v4 if they doesn't exist in some or every documents.
Note that it also support JSON and JSON streaming, you can send them to the engine by using
the content-type:application/json and content-type:application/x-ndjson headers respectively.
Querying the engine via the website
You can query the engine by going to the HTML page itself.