April 16, 2014

The story of one MySQL Upgrade

I recently worked on upgrading MySQL from one of very early MySQL 5.0 versions to Percona Server 5.1. This was a classical upgrade scenario which can cause surprises. Master and few slaves need to be upgraded. It is a shared database used by tons of applications written by many people over more than 5 years […]

MySQL Quality of old and new features

Recent couple of days our team was pointed to number of bugs in MySQL 5.0 which again seriously shakes the confidence in both MySQL Quality Control and bug fix promptness. Let me just take couple of bugs as examples: Triggers broken with auto-increment columns for Innodb tables (bug 26316). As you can see this bug […]

Engineer duo from Google, LinkedIn join again for InnoDB talks

Google senior systems engineer Jeremy Cole is once again teaming with LinkedIn senior software engineer Davi Arnaut for two InnoDB-focused sessions at the upcoming Percona Live MySQL Conference and Expo 2014 this April 1-4 in Santa Clara, California. The duo will present “InnoDB: A journey to the core II” on April 2 and “InnoDB: A […]

thread_concurrency doesn’t do what you expect

Over the last months I’ve seen lots of customers trying to tune the thread concurrency inside MySQL with the variable thread_concurrency. Our advice is: stop wasting your time, it does nothing on GNU/Linux Some of the biggest GNU/Linux distributions includes the variable thread_concurrency in their my.cnf file by default. One example is Debian and its […]

kernel_mutex problem. Or double throughput with single variable

Problem with kernel_mutex in MySQL 5.1 and MySQL 5.5 is known: Bug report. In fact in MySQL 5.6 there are some fixes that suppose to provide a solution, but MySQL 5.6 yet has long way ahead before production, and it is also not clear if the problem is really fixed. Meantime the problem with kernel_mutex […]

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 […]