October 31, 2014

Q&A: Even More Deadly Mistakes of MySQL Development

On Wednesday I gave a presentation on “How to Avoid Even More Common (but Deadly) MySQL Development Mistakes” for Percona MySQL Webinars.  If you missed it, you can still register to view the recording and my slides. Thanks to everyone who attended, and especially to folks who asked the great questions.  I answered as many as we had […]

Q&A: Common (but deadly) MySQL Development Mistakes

On Wednesday I gave a presentation on “How to Avoid Common (but Deadly) MySQL Development Mistakes” for Percona MySQL Webinars. If you missed it, you can still register to view the recording and my slides. Thanks to everyone who attended, and especially to folks who asked the great questions. I answered as many as we had time […]

Innotop: A real-time, advanced investigation tool for MySQL

GUI monitoring tools for MySQL are not always suitable for all our needs or situations. Most of them are designed to provide historical views into what happens to our database over time rather then real-time insight into current MySQL server status. Excellent free tools for this include Cacti, Zabbix, Ganglia, Nagios, etc. But each of […]

How can we bring query to the data?

Baron recently wrote about sending the query to the data looking at distributed systems like Cassandra. I want to take a look at more simple systems like MySQL and see how we’re doing in this space. It is obvious getting computations as closer to the data as possible is the most efficient as we will […]

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 […]

What is exec_time in binary logs?

If you’ve used MySQL’s mysqlbinlog tool, you’ve probably seen something like the following in the output: “exec_time=0″ What is the exec_time? It seems to be the query’s execution time, but it is not.

Slow Query Log analyzes tools

(There is an updated version of this post here). MySQL has simple but quite handy feature – slow query log, which allows you to log all queries which took over define number of seconds to execute. There is also an option to enable logging queries which do not use indexes even if they take less […]

MySQL compression: Compressed and Uncompressed data size

MySQL has information_schema.tables that contain information such as “data_length” or “avg_row_length.” Documentation on this table however is quite poor, making an assumption that those fields are self explanatory – they are not when it comes to tables that employ compression. And this is where inconsistency is born. Lets take a look at the same table […]

Getting to know TokuDB for MySQL

During last April’s Percona Live MySQL Conference and Expo, TokuDB celebrated it’s first full-year as an open source storage engine. I still remember reading the official announcement and the expectations it created one year ago. The premises were very interesting as it had the potential of helping MySQL manage “big data” in a way InnoDB just […]