October 2, 2014

Should MySQL Extend GROUP BY Syntax ?

Jan has a good article about finding the row matching some value in the group: This is one illustration of group by limitations in SQL language which is not offset by any MySQL specific extensions,yet As you can see if you want to get one row from the group which is sorted some way you […]

More then 1000 columns – get transactional with TokuDB

Recently I encountered a specific situation in which a customer was forced to stay with the MyISAM engine due to a legacy application using tables with over 1000 columns. Unfortunately InnoDB has a limit at this point. I did not expect to hear this argument for MyISAM. It is usually about full text search or […]

What I learned while migrating a customer MySQL installation to Amazon RDS

Hi, I recently had the experience of assisting with a migration of a customer MySQL installation to Amazon RDS (Relational Database Service). Amazon RDS is a great platform for hosting your MySQL installation and offers the following list of pros and cons: You can scale your CPU, IOPS, and storage space separately by using Amazon […]

Managing shards of MySQL databases with MySQL Fabric

This is the fourth post in our MySQL Fabric series. In case you’re joining us now, we started with an introductory post, and then discussed High Availability (HA) using MySQL Fabric here (Part 1) and here (Part 2). Today we will talk about how MySQL Fabric can help you scale out MySQL databases with sharding. Introduction At the […]

Using InfiniDB MySQL server with Hadoop cluster for data analytics

In my previous post about Hadoop and Impala I benchmarked performance of analytical queries in Impala. This time I’ve tried InfiniDB for Hadoop (open-source version) on the modern hardware with an 8-node Hadoop cluster. One of the main advantages (at least for me) of InifiniDB for Hadoop is that it stores the data inside the Hadoop cluster but uses the […]

Using Apache Hadoop and Impala together with MySQL for data analysis

Apache Hadoop is commonly used for data analysis. It is fast for data loads and scalable. In a previous post I showed how to integrate MySQL with Hadoop. In this post I will show how to export a table from  MySQL to Hadoop, load the data to Cloudera Impala (columnar format) and run a reporting […]

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 […]

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 […]

MySQL Query Patterns, Optimized – Webinar questions followup

On Friday I gave a presentation on “MySQL Query Patterns, Optimized” 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 for  during the session, but here […]

More on MySQL transaction descriptors optimization

Since my first post on MySQL transaction descriptors optimization introduced in Percona Server 5.5.30-30.2 and a followup by Dimitri Kravchuk, we have received a large number of questions on why the benchmark results in both posts look rather different. We were curious as well, so we tried to answer that question by retrying benchmarks on […]