Queries in MySQL, Sphinx and many other database or search engines are typically single-threaded. That is when you issue a single query on your brand new r910 with 32 CPU cores and 16 disks, the maximum that is going to be used to process this query at any given point is 1 CPU core and […]
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One of the most common causes of a poor Sphinx search performance I find our customers face is misuse of search filters. In this article I will cover how Sphinx attributes (which are normally used for filtering) work, when they are a good idea to use and what to do when they are not, but […]
Today I was looking at the ALTER TABLE performance with fast index creation and without it with different buffer pool sizes. Results are pretty interesting. I used modified Sysbench table for these tests because original table as initially created only has index on column K which initially contains only zeros, which means index is very […]
A while back Friendfeed posted a blog post explaining how they changed from storing data in MySQL columns to serializing data and just storing it inside TEXT/BLOB columns. It seems that since then, the technique has gotten more popular with Ruby gems now around to do this for you automatically.
The mistake I commonly see among MySQL users is how indexes are created. Quite commonly people just index individual columns as they are referenced in where clause thinking this is the optimal indexing strategy. For example if I would have something like AGE=18 AND STATE=’CA’ they would create 2 separate indexes on AGE and STATE […]
Suboptimal ORDER BY implementation, especially together with LIMIT is often the cause of MySQL Performance problems. Here is what you need to know about ORDER BY … LIMIT optimization to avoid these problems ORDER BY with LIMIT is most common use of ORDER BY in interactive applications with large data sets being sorted. On many […]