August 1, 2014

How fast can MySQL Process Data

Reading Barons post about Kickfire Appliance and of course talking to them directly I learned a lot in their product is about beating data processing limitations of current systems. This raises valid question how fast can MySQL process (filter) data using it current architecture ? I decided to test the most simple case – what […]

10+ Ways to Crash or Overload MySQL

People are sometimes contacting me and asking about bugs like this which provide a trivial way to crash MySQL to the user with basic privileges and asking me what to do. My answer to them is – there is nothing new to it and they just sit should back and relax Really – there are […]

Filtered MySQL Replication

To get this straight – I’m not a big fan of filtered or partial MySQL Replication (as of version MySQL 5.0) – there is enough gotchas with replication itself and getting things right with filtering can get quite bumpy road. In some applications however it is very helpful so lets see what one should do […]

MySQL Query Cache

MySQL has a great feature called “Query Cache” which is quite helpful for MySQL Performance optimization tasks but there are number of things you need to know. First let me clarify what MySQL Query Cache is – I’ve seen number of people being confused, thinking MySQL Query Cache is the same as Oracle Query Cache […]

Faster Point In Time Recovery with LVM2 Snaphots and Binary Logs

LVM snapshots is one powerful way of taking a consistent backup of your MySQL databases – but did you know that you can now restore directly from a snapshot (and binary logs for point in time recovery) in case of that ‘Oops’ moment? Let me show you quickly how. This howto assumes that you already […]

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 […]