April 20, 2014

How to find bugs in MySQL

Finding bugs in MySQL is not only fun, it’s also something I have been doing the last four years of my life. Whether you want to become the next Shane Bester (who is generally considered the most skilled MySQL bug hunter worldwide), or just want to prove you can outsmart some of the world’s best […]

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 […]

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 […]

Shard-Query adds parallelism to queries

Preamble: On performance, workload and scalability: MySQL has always been focused on OLTP workloads. In fact, both Percona Server and MySQL 5.5.7rc have numerous performance improvements which benefit workloads that have high concurrency. Typical OLTP workloads feature numerous clients (perhaps hundreds or thousands) each reading and writing small chunks of data. The recent improvements to […]

3 ways MySQL uses indexes

I often see people confuse different ways MySQL can use indexing, getting wrong ideas on what query performance they should expect. There are 3 main ways how MySQL can use the indexes for query execution, which are not mutually exclusive, in fact some queries will use indexes for all 3 purposes listed here.

Is it query which needs to be optimized ?

Last few days I had a lot of a lot of questions at MySQL Performance Forum as well as from our customers regarding query optimization… which had one thing in common – It is not query which needed to be optimized. Way too frequently people design schema first and then think how the queries they […]

Using Sphinx as MySQL data retrieval accelerator

I’ve run into the following thread couple of days ago: Basically someone is using sphinx to perform search simply on attributes (date, group etc) and get sorted result set and claiming it is way faster than getting it with MySQL. Honestly I can well believe it for cases when you want to know number of […]

Descending indexing and loose index scan

Comments to my previous posts, especially this one by Gokhan inspired me to write a bit about descending indexes and about loose index scan, or what Gokhan calls “better range” support. None of these are actially related to Innodb tables in general – these are features MySQL should get for all storage engines at some […]