Full-text search: from scratch to a HA cluster
Getting started with search is very easy. Just how hard can a LIKE '%query%' be, right? Or better yet, a CREATE FULLTEXT INDEX and then MATCH AGAINST? And to extent, that works. But these days, it's surprisingly easy to grow beyond the point where that simplistic approach does not really work any more, and you find yourself struggling to scale the performance, tweak the matching, or improve relevance.
Proper search at a decent scale is tough. Whatever technology you choose. Getting it right will require time and effort. There's no silver bullet. We give you a lead bullet though: Sphinx. And it comes with a silver lining: this tutorial. In which we shall go through several different topics and demos:
- Getting started with Sphinx. Using SphinxQL and SphinxAPI. And a 20-minute integration demo.
- Managing indexes. Disk indexes, delta scheme. Realtime indexes.
- Search quality. What is relevance. Judgments, metrics, formulas, experiments. What else is there to search quality.
- Cluster setups. Distributed indexes. Capacity planning. HA tools in Sphinx.
So come drop by if you're interested in improving your search. We know a few tricks to make it better and we want to share.