For a very long time – since when multiple CPU cores were commonly available – I dreamed about MySQL having the ability to execute queries in parallel. This feature was lacking from MySQL, and I wrote a lots of posts on how to emulate parallel queries in MySQL using different methods: from simple parallel bash script to using Apache Spark to using ClickHouse together with MySQL. I have watched parallelism coming to PostgreSQL, to new databases like TiDB, to …

Parallel query execution is my favorite, non-existent, feature in MySQL. In all versions of MySQL – at least at the time of writing – when you run a single query it will run in one thread, effectively utilizing one CPU core only. Multiple queries run at the same time will be using different threads and will utilize more than one CPU core.

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. With faster disks (i.e. SSD) we can’t utilize the full potential of IOPS with just one thread.

AWS Aurora (based on MySQL 5.6) now has a version which will support parallelism for SELECT queries (utilizing the read capacity of storage nodes underneath the Aurora cluster). In this article, we will look at how this can improve the reporting/analytical query performance in MySQL. I will compare AWS Aurora with MySQL …

In this blog post, we’ll look at pipelining versus parallel query execution when using X Plugin for MySQL 5.7.

In my previous blog post, I showed how to use X Plugin for MySQL 5.7 for parallel query execution. The tricks I used to make it work:

• Partitioning by hash
• Open N connections to MySQL, where N = number of CPU cores

I had to do it manually (as well as to sort the result at the end) as X Plugin only supports “pipelining” (which only saves the round trip time) and does not “multiplex” connections …