May 18, 2013

MySQL 5.6 vs MySQL 5.5 and the Star Schema Benchmark

So far most of the benchmarks posted about MySQL 5.6 use the sysbench OLTP workload.  I wanted to test a set of queries which, unlike sysbench, utilize joins.  I also wanted an easily reproducible set of data which is more rich than the simple sysbench table.  The Star Schema Benchmark (SSB) seems ideal for this. [...]

Quickly finding unused indexes (and estimating their size)

I had a customer recently who needed to reduce their database size on disk quickly without a lot of messy schema redesign and application recoding.  They didn’t want to drop any actual data, and their index usage was fairly high, so we decided to look for unused indexes that could be removed. Collecting data It’s [...]

Aligning IO on a hard disk RAID – the Benchmarks

In the first part of this article I have showed how I align IO, now I want to share results of the benchmark that I have been running to see how much benefit can we get from a proper IO alignment on a 4-disk RAID1+0 with 64k stripe element. I haven’t been running any benchmarks [...]

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: [...]

Using Flexviews – part one, introduction to materialized views

If you know me, then you probably have heard of Flexviews. If not, then it might not be familiar to you. I’m giving a talk on it at the MySQL 2011 CE, and I figured I should blog about it before then. For those unfamiliar, Flexviews enables you to create and maintain incrementally refreshable materialized [...]

MySQL 5.5.8 – in search of stability

A couple of days ago, Dimitri published a blog post, Analyzing Percona’s TPCC-like Workload on MySQL 5.5, which was  a response to my post, MySQL 5.5.8 and Percona Server: being adaptive. I will refer to Dimitri’s article as article [1]. As always, Dimitri has provided a very detailed and thoughtful article, and I strongly recommend reading if [...]

A workaround for the performance problems of TEMPTABLE views

MySQL supports two different algorithms for views: the MERGE algorithm and the TEMPTABLE algorithm. These two algorithms differ greatly. A view which uses the MERGE algorithm can merge filter conditions into the view query itself. This has significant performance advantages over TEMPTABLE views. A view which uses the TEMPTABLE algorithm will have to compute the [...]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see http://www.mysqlperformanceblog.com/2009/09/29/quick-comparison-of-myisam-infobright-and-monetdb/) this week. And following Baron’s example I also run the same load against MonetDB. Reading comments to Baron’s post I tied to load the same data to LucidDB, but I was not successful in this. I tried to analyze a bigger dataset and I took public [...]

Goal driven performance optimization

When your goal is to optimize application performance it is very important to understand what goal do you really have. If you do not have a good understanding of the goal your performance optimization effort may well still bring its results but you may waste a lot of time before you reach same results as [...]

How much overhead is caused by on disk temporary tables

As you might know while running GROUP BY and some other kinds of queries MySQL needs to create temporary tables, which can be created in memory, using MEMORY storage engine or can be created on disk as MYISAM tables. Which one will be used depends on the allowed tmp_table_size and also by the data which [...]