July 30, 2014

MySQL: Followup on UNION for query optimization, Query profiling

Few days ago I wrote an article about using UNION to implement loose index scan. First I should mention double IN also works same way so you do not have to use the union. So changing query to:

So as you see there are really different types of ranges in MySQL. IN range allows […]

Using UNION to implement loose index scan in MySQL

One little known fact about MySQL Indexing, however very important for successfull MySQL Performance Optimization is understanding when exactly MySQL is going to use index and how it is going to do them. So if you have table people with KEY(age,zip) and you will run query something like SELECT name FROM people WHERE age BETWEEN […]

MySQL Query Cache

MySQL has a great feature called “Query Cache” which is quite helpful for MySQL Performance optimization tasks but there are number of things you need to know. First let me clarify what MySQL Query Cache is – I’ve seen number of people being confused, thinking MySQL Query Cache is the same as Oracle Query Cache […]

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 […]

Quickly finding unused indexes (and estimating their size)

I had a customer recently who needed to reduce their database size on disk quickly without a lot of messy schema redesign and application recoding.  They didn’t want to drop any actual data, and their index usage was fairly high, so we decided to look for unused indexes that could be removed. Collecting data It’s […]

Identifying the load with the help of pt-query-digest and Percona Server

Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make […]

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 […]

Moving Subtrees in Closure Table Hierarchies

Many software developers find they need to store hierarchical data, such as threaded comments, personnel org charts, or nested bill-of-materials. Sometimes it’s tricky to do this in SQL and still run efficient queries against the data. I’ll be presenting a webinar for Percona on February 28 at 9am PST. I’ll describe several solutions for storing […]

How is join_buffer_size allocated?

When examining MySQL configuration, we quite often want to know how various buffer sizes are used. This matters because some buffers (sort_buffer_size for example) are allocated to their full size immediately as soon as they are needed, but others are effectively a “max size” and the corresponding buffers are allocated only as big as needed […]