September 2, 2014

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. […]

Flexviews – part 3 – improving query performance using materialized views

Combating “data drift” In my first post in this series, I described materialized views (MVs). An MV is essentially a cached result set at one point in time. The contents of the MV will become incorrect (out of sync) when the underlying data changes. This loss of synchronization is sometimes called drift. This is conceptually […]

MySQL 6.0 vs 5.1 in TPC-H queries

Last week I played with queries from TPC-H benchmarks, particularly comparing MySQL 6.0.4-alpha with 5.1. MySQL 6.0 is interesting here, as there is a lot of new changes in optimizer, which should affect execution plan of TPC-H queries. In reality only two queries (from 22) have significantly better execution time (about them in next posts), […]

InnoDB vs MyISAM vs Falcon benchmarks – part 1

Several days ago MySQL AB made new storage engine Falcon available for wide auditory. We cannot miss this event and executed several benchmarks to see how Falcon performs in comparison to InnoDB and MyISAM. The second goal of benchmark was a popular myth that MyISAM is faster than InnoDB in reads, as InnoDB is transactional, […]

MySQL 5.5 and MySQL 5.6 default variable values differences

As the part of analyzing surprising MySQL 5.5 vs MySQL 5.6 performance results I’ve been looking at changes to default variable values. To do that I’ve loaded the values from MySQL 5.5.30 and MySQL 5.6.10 to the different tables and ran the query:

Lets go over to see what are the most important changes […]

Analyzing air traffic performance with InfoBright and MonetDB

Accidentally me and Baron played with InfoBright (see 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 […]

Impact of logging on MySQL’s performance

Introduction When people think about Percona’s microslow patch immediately a question arises how much logging impacts on performance. When we do performance audit often we log every query to find not only slow queries. A query may take less than a second to execute, but a huge number of such queries may significantly load a […]

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 Percona does a MySQL Performance Audit

Our customers or prospective customers often ask us how we do a performance audit (it’s our most popular service). I thought I should write a blog post that will both answer their question, so I can just reply “read all about it at this URL” and share our methodology with readers a little bit. This […]

How multiple disks can benefit for single client workload ?

Let us talk few more about disks. You might have read my previous post and Matt’s Reply and it looks like there are few more things to clarify and explain. Before I get to main topic of the article lets comment on IO vs Disk question. If you look at Disk Based databases all data […]