May 20, 2013

MySQL 5.5 and MySQL 5.6 default variable values differences

As the part of analyzing surprising MySQL 5.5 vs MySQL 5.6 performance results I’ve been looking at changes to default variable values. To do that I’ve loaded the values from MySQL 5.5.30 and MySQL 5.6.10 to the different tables and ran the query:

Lets go over to see what are the most important changes [...]

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 [...]

Join Optimizations in MySQL 5.6 and MariaDB 5.5

This is the third blog post in the series of blog posts leading up to the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. This blog post is targeted at the join related optimizations introduced in the optimizer. These optimizations are available in both MySQL 5.6 and MariaDB 5.5, and MariaDB 5.5 [...]

Multi Range Read (MRR) in MySQL 5.6 and MariaDB 5.5

This is the second blog post in the series of blog posts leading up to the talk comparing the optimizer enhancements in MySQL 5.6 and MariaDB 5.5. This blog post is aimed at the optimizer enhancement Multi Range Read (MRR). Its available in both MySQL 5.6 and MariaDB 5.5 Now let’s take a look at [...]

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: [...]

MySQL caching methods and tips

“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding [...]

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 [...]

How adding another table to JOIN can improve performance ?

JOINs are expensive and it most typical the fewer tables (for the same database) you join the better performance you will get. As for any rules there are however exceptions The one I’m speaking about comes from the issue with MySQL optimizer stopping using further index key parts as soon as there is a range [...]