November 23, 2014

The Optimization That (Often) Isn’t: Index Merge Intersection

Prior to version 5.0, MySQL could only use one index per table in a given query without any exceptions; folks that didn’t understand this limitation would often have tables with lots of single-column indexes on columns which commonly appeared in their WHERE clauses, and they’d wonder why the EXPLAIN plan for a given SELECT would […]

Tools and Techniques for Index Design Webinar Questions Followup

I presented a webinar this week to give an overview of Tools and Techniques for Index Design. Even if you missed the webinar, you can register for it, and you’ll be emailed a link to the recording. I’d like to invite folks who are interested in tools for query optimization to attend the new Percona […]

A case for MariaDB’s Hash Joins

MariaDB 5.3/5.5 has introduced a new join type “Hash Joins” which is an implementation of a Classic Block-based Hash Join Algorithm. In this post we will see what the Hash Join is, how it works and for what types of queries would it be the right choice. I will show the results of executing benchmarks […]

Using any general purpose computer as a special purpose SIMD computer

Often times, from a computing perspective, one must run a function on a large amount of input. Often times, the same function must be run on many pieces of input, and this is a very expensive process unless the work can be done in parallel. Shard-Query introduces set based processing, which on the surface appears […]

Shard-Query turbo charges Infobright community edition (ICE)

Shard-Query is an open source tool kit which helps improve the performance of queries against a MySQL database by distributing the work over multiple machines and/or multiple cores. This is similar to the divide and conquer approach that Hive takes in combination with Hadoop. Shard-Query applies a clever approach to parallelism which allows it to […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]

A workaround for the performance problems of TEMPTABLE views

MySQL supports two different algorithms for views: the MERGE algorithm and the TEMPTABLE algorithm. These two algorithms differ greatly. A view which uses the MERGE algorithm can merge filter conditions into the view query itself. This has significant performance advantages over TEMPTABLE views. A view which uses the TEMPTABLE algorithm will have to compute the […]

Debugging problems with row based replication

MySQL 5.1 introduces row based binary logging. In fact, the default binary logging format in GA versions of MySQL 5.1 is ‘MIXED’ STATEMENT*;   The binlog_format  variable can still be changed per sessions which means it is possible that some of your binary log entries will be written in a row-based fashion instead of the […]

Tuning for heavy writing workloads

For the my previous post, there was comment to suggest to test db_STRESS benchmark on XtraDB by Dimitri. And I tested and tuned for the benchmark. I will show you the tunings. It should be also tuning procedure for general heavy writing workloads. At first, <tuning peak performance>. The next, <tuning purge operation> to stabilize […]

Multi Column indexes vs Index Merge

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 […]