I talk with lot of people who are really interested in Percona XtraDB Cluster (PXC) and mostly they are interested in PXC as a high-availability solution. But, what they tend not to think too much about is if moving from async to synchronous replication is right for their application or not. Facts about Galera replication [...]
Comparing Percona XtraDB Cluster with Semi-Sync replication Cross-WAN
June 14, 2012 By 7 Comments
I have a customer who is considering Percona XtraDB Cluster (PXC) in a two colo WAN environment. They wanted me to do a test comparing PXC against semi-synchronous replication to see how they stack up against each other. Test Environment The test environment included AWS EC2 nodes in US-East and US-West (Oregon). The ping RTT latency [...]
Optimizing InnoDB for creating 30,000 tables (and nothing else)
December 22, 2011 By 5 Comments
Once upon a time, it would have been considered madness to even attempt to create 30,000 tables in InnoDB. That time is now a memory. We have customers with a lot more tables than a mere 30,000. There have historically been no tests for anything near this many tables in the MySQL test suite. So, [...]
Preprocessing Data
August 8, 2011 By 3 Comments
There are many ways of improving response times for users. There are some people that spend a lot of time, energy and money on trying to have the application respond as fast as possible at the time when the users made the request. Those people may miss out on an opportunity to do some or [...]
The case for getting rid of duplicate “sets”
May 17, 2011 By 2 Comments
The most useful feature of the relational database is that it allows us to easily process data in sets, which can be much faster than processing it serially. When the relational database was first implemented, write-ahead-logging and other technologies did not exist. This made it difficult to implement the database in a way that matched [...]
Distributed Set Processing with Shard-Query
May 14, 2011 By 27 Comments
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: [...]
Flexviews – part 3 – improving query performance using materialized views
April 4, 2011 By 20 Comments
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 [...]
Data mart or data warehouse?
July 15, 2010 By 13 Comments
This is part two in my six part series on business intelligence, with a focus on OLAP analysis. Part 1 – Intro to OLAP Identifying the differences between a data warehouse and a data mart. (this post) Introduction to MDX and the kind of SQL which a ROLAP tool must generate to answer those queries. [...]
A workaround for the performance problems of TEMPTABLE views
May 19, 2010 By 7 Comments
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 [...]
High-Performance Click Analysis with MySQL
December 22, 2008 By 13 Comments
We have a lot of customers who do click analysis, site analytics, search engine marketing, online advertising, user behavior analysis, and many similar types of work. The first thing these have in common is that they’re generally some kind of loggable event. The next characteristic of a lot of these systems (real or planned) is [...]
