As part of Percona Remote DBA for MySQL service we recognize that reliable backups are one of the most important things we can bring to the table. In my experience handling emergencies, the single worst thing that can happen is finding out you don’t have backups available when some sort of data loss or catastrophic [...]
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 [...]
MySQL Indexing Best Practices: Webinar Questions Followup
I had a lot of questions on my MySQL Indexing: Best Practices Webinar (both recording and slides are available now) We had lots of questions. I did not have time to answer some and others are better answered in writing anyway. Q: One developer on our team wants to replace longish (25-30) indexed varchars with [...]
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 [...]
InnoDB’s gap locks
One of the most important features of InnoDB is the row level locking. This feature provides better concurrency under heavy write load but needs additional precautions to avoid phantom reads and to get a consistent Statement based replication. To accomplish that, row level locking databases also acquire gap locks. What is a Phantom Read A [...]
Index Condition Pushdown in MySQL 5.6 and MariaDB 5.5 and its performance impact
I have been working with Peter in preparation for the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. We are taking a look at and benchmarking optimizer enhancements one by one. So in the same way this blog post is aimed at a new optimizer enhancement Index Condition Pushdown (ICP). Its available [...]
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 [...]
Distributed Set Processing with Shard-Query
Can Shard-Query scale to 20 nodes? Peter asked this question in comments to to my previous Shard-Query benchmark. Actually he asked if it could scale to 50, but testing 20 was all I could due to to EC2 and time limits. I think the results at 20 nodes are very useful to understand the performance: [...]
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 [...]

