The Sphinx project just released version 0.9.8, with many enhancements since the previous release. There’s never been a better time to try it out. It’s really cool technology.
What is Sphinx? Glad you asked. It’s fast, efficient, scalable, relevant full-text searching and a heck of a lot more. In fact, Sphinx complements MySQL for a lot of non-search queries that MySQL frankly isn’t very good at, including WHERE clauses on low-selectivity columns, ORDER BY with a LIMIT and OFFSET, and GROUP BY. A lot of you are probably running fairly simple queries with these constructs and getting really bad performance in MySQL. I see it a lot when I’m working with clients, and there’s often not much room for optimization. Sphinx can execute a subset of such queries very efficiently, due to its smart I/O algorithms and the way it uses memory. By “subset” I mean you don’t get the full complexity of SQL, but you get enough functionality for lots of the poorly-performing queries I see in the wild. It’s a 95% solution.
Is Sphinx for you? Good question. You can find answers in Appendix C in High Performance MySQL. And yes, that is why I wrote this blog post—to put in a plug for the book. *grin* But before I go, let me put in another plug for Sphinx: go vote for it on Sourceforge! If it’s voted as one of the Community Choice projects of the year, that will be fantastic.