Sphinx Search - Lessons LearnedHere are a few things I've learned while working on a project that uses Sphinx search:
- It's important to know the difference between fields and attributes. Attributes are basically unindexed columns and you should try to avoid filtering only on these columns. Fields support full text search.
- It supports its own custom binary protocol and the MySQL protocol (recently they also added a HTTP API). When you see "listen = localhost:9306:mysql41" in the config, that means it's listening for MySQL protocol traffic on port 9306.
- https://github.com/a1tus/sphinxapi-py3 appears to be the best Python client for the binary api at the moment. This doesn't support INSERTing things into the index (you'll need to use the MySQL protocol for that).
- The version of sphinxapi-py3 on pypi is a fork with just a few minor fixes and appears to be safe.
- It does not match partial words by default. Turning on partial matching can also increase the size of your index dramatically. You can also limit the fields that support partial matching with the "infix_fields" and "prefix_fields" setting.
- Stemmers aren't turned on by default. So, searching for "dog" will not match "dogs".
- Most special characters ($, @, &, etc) are ignored by default. You will need to add them to charset_table if you want them to be searchable.
- Ruby's thinking-sphinx looks much more battle tested than all of the Python binary api clients: https://github.com/pat/thinking-sphinx
- You will need to use a real-time index if you want to INSERT/DELETE records immediately.
- If you're using a real-time index, you will probably need to increase the "rt_mem_limit" from its default of 128mb. If this limit is too low, you'll see a high number of "disk chunks" when you run the "SHOW INDEX rtindex STATUS" query. More info: http://sphinxsearch.com/blog/2014/02/12/rt_performance_basics/
- You have to use a special dialect if you want to use SQLAlchemy with sphinx: https://github.com/conversant/sqlalchemy-sphinx
- This appears to be the best Dockerfile for sphinx: https://github.com/leodido/dockerfiles
I probably won't be using Sphinx search for any new projects. Elasticsearch seems preferable these days.