May 26, 2013

Is Synchronous Replication right for your app?

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 [...]

Is your MySQL buffer pool warm? Make it sweat!

Today’s blog post diving into the waters of the MySQL buffer pool is a cross-post from Groupon’s engineering blog, and is Part 1 of 2. Thank you to Kyle Oppenheim at Groupon for contributing to this project and post. We’ll be posting Part 2 on Thursday. I’ll be at the Percona Live MySQL Conference and [...]

InnoDB Full-text Search in MySQL 5.6 (part 1)

I’ve never been a very big fan of MyISAM; I would argue that in most situations, any possible advantages to using MyISAM are far outweighed by the potential disadvantages and the strengths of InnoDB. However, up until MySQL 5.6, MyISAM was the only storage engine with support for full-text search (FTS). And I’ve encountered many [...]

Recovery after DROP & CREATE

In a very popular data loss scenario a table is dropped and empty one is created with the same name. This is because  mysqldump in many cases generates the “DROP TABLE” instruction before the “CREATE TABLE”:

If there were no subsequent CREATE TABLE the recovery would be trivial. Index_id of the PRIMARY index of [...]

MySQL Indexing Best Practices: Webinar Questions Followup

I had a lot of questions on my MySQL Indexing: Best Practices Webinar (both recording and slides are available now) We had lots of questions. I did not have time to answer some and others are better answered in writing anyway. Q: One developer on our team wants to replace longish (25-30) indexed varchars with [...]

How FLUSH TABLES WITH READ LOCK works with Innodb Tables

Many backup tools including Percona Xtrabackup, MyLVMBackup and others use FLUSH TABLES WITH READ LOCK to temporary make MySQL read only. In many cases the period for which server has to be made read only is very short, just few seconds, yet the impact of FLUSH TABLES WITH READ LOCK can be quite large because [...]

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: [...]

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 [...]

Using Flexviews – part two, change data capture

In my previous post I introduced materialized view concepts. This post begins with an introduction to change data capture technology and describes some of the ways in which it can be leveraged for your benefit. This is followed by a description of FlexCDC, the change data capture tool included with Flexviews. It continues with an [...]