August 1, 2014

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 MySQL 5.6 Performance Schema in multi-tenant environments

Hosting a shared MySQL instance for your internal or external clients (“multi-tenant”) was always a challenge. Multi-tenants approach or a “schema-per-customer” approach is pretty common nowadays to host multiple clients on the same MySQL sever. One of issues of this approach, however, is the lack of visibility: it is hard to tell how many resources (queries, disk, […]

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 […]

Parallel Query for MySQL with Shard-Query

While Shard-Query can work over multiple nodes, this blog post focuses on using Shard-Query with a single node.  Shard-Query can add parallelism to queries which use partitioned tables.  Very large tables can often be partitioned fairly easily. Shard-Query can leverage partitioning to add paralellism, because each partition can be queried independently. Because MySQL 5.6 supports 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 […]

The power of MySQL’s GROUP_CONCAT

In the very early days of Percona Vadim wrote very nice post about GROUP_CONCAT. But I want to show you a bit more about it. When is GROUP_CONCAT useful? Usually while working with Support customers I recommend it when you have aggregation of many-to-many info. It makes the view simpler and more beautiful and it […]

Designing one to many relations – MongoDB vs MySQL

We already discussed one to one relations in MongoDB, and the main conclusion was that you should design your collections according to the most frequent access pattern. With one to many relations, this is still valid, but other factors may come into play. Let’s look at a simple problem: we are a shop and we […]

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 […]