September 1, 2014

Sysbench Benchmarking of Tesora’s Database Virtualization Engine

Tesora, previously called Parelastic, asked Percona to do a sysbench benchmark evaluation of its Database Virtualization Engine on specific architectures on Amazon EC2. The focus of Tesora is to provide a scalable Database As A Service platform for OpenStack. The Database Virtualization Engine (DVE) plays a part in this as it aims at allowing databases […]

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 […]

Percona Server on the Raspberry Pi: Your own MySQL Database Server for Under $80

There are many reasons for wanting a small MySQL database server: You’re a uni student who wants to learn the SQL language better and needs a mini-testbox You’re a Windows user who wants to play around with Percona Server on Linux You’re a corporate application developer who wants a small SQL development & test box […]

Data compression in InnoDB for text and blob fields

Have you wanted to compress only certain types of columns in a table while leaving other columns uncompressed? While working on a customer case this week I saw an interesting problem where a table had many heavily utilized TEXT fields with some read queries exceeding 500MB (!!), and stored in a 100GB table. In this […]

Sample datasets for benchmarking and testing

Sometimes you just need some data to test and stress things. But randomly generated data is awful — it doesn’t have realistic distributions, and it isn’t easy to understand whether your results are meaningful and correct. Real or quasi-real data is best. Whether you’re looking for a couple of megabytes or many terabytes, the following […]

Checking for a live database connection considered harmful

It is very common for me to look at a customer’s database and notice a lot of overhead from checking whether a database connection is active before sending a query to it. This comes from the following design pattern, written in pseudo-code:

Many of the popular development platforms do something similar to this. Two […]

When should you store serialized objects in the database?

A while back Friendfeed posted a blog post explaining how they changed from storing data in MySQL columns to serializing data and just storing it inside TEXT/BLOB columns. It seems that since then, the technique has gotten more popular with Ruby gems now around to do this for you automatically.