April 18, 2014

Q&A: Common (but deadly) MySQL Development Mistakes

On Wednesday I gave a presentation on “How to Avoid Common (but Deadly) MySQL Development Mistakes” for Percona MySQL Webinars. If you missed it, you can still register to view the recording and my slides. Thanks to everyone who attended, and especially to folks who asked the great questions. I answered as many as we had time […]

Innotop: A real-time, advanced investigation tool for MySQL

GUI monitoring tools for MySQL are not always suitable for all our needs or situations. Most of them are designed to provide historical views into what happens to our database over time rather then real-time insight into current MySQL server status. Excellent free tools for this include Cacti, Zabbix, Ganglia, Nagios, etc. But each of […]

Schema changes – what’s new in MySQL 5.6?

Among many of the improvements you can enjoy in MySQL 5.6, there is one that addresses a huge operational problem that most DBAs and System Administrators encounter in their life: schema changes. While it is usually not a problem for small tables or those in early stages of product life cycle, schema changes become a […]

10 years of MySQL User Conferences

In preparing for this month’s Percona Live MySQL Conference and Expo, I’ve been reminiscing about the annual MySQL User Conference’s history – the 9 times it previously took place in its various reincarnations – and there are a lot of good things, fun things to remember. 2003 was the year that marked the first MySQL user conference […]

How Percona does a MySQL Performance Audit

Our customers or prospective customers often ask us how we do a performance audit (it’s our most popular service). I thought I should write a blog post that will both answer their question, so I can just reply “read all about it at this URL” and share our methodology with readers a little bit. This […]

How rows_sent can be more than rows_examined?

When looking at queries that are candidates for optimization I often recommend that people look at rows_sent and rows_examined values as available in the slow query log (as well as some other places). If rows_examined is by far larger than rows_sent, say 100 larger, then the query is a great candidate for optimization. Optimization could […]

Increasing slow query performance with the parallel query execution

MySQL and Scaling-up (using more powerful hardware) was always a hot topic. Originally MySQL did not scale well with multiple CPUs; there were times when InnoDB performed poorer with more  CPU cores than with less CPU cores. MySQL 5.6 can scale significantly better; however there is still 1 big limitation: 1 SQL query will eventually use only […]

Improved InnoDB fast index creation

One of the serious limitations in the fast index creation feature introduced in the InnoDB plugin is that it only works when indexes are explicitly created using ALTER TABLE or CREATE INDEX. Peter has already blogged about it before, here I’ll just briefly reiterate other cases that might benefit from that feature: when ALTER TABLE […]

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: […]

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 […]