April 23, 2014

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 […]

PERFORMANCE_SCHEMA vs Slow Query Log

A couple of weeks ago, shortly after Vadim wrote about Percona Cloud Tools and using Slow Query Log to capture the data, Mark Leith asked why don’t we just use Performance Schema instead? This is an interesting question and I think it deserves its own blog post to talk about. First, I would say main […]

Schema changes – what’s new in MySQL 5.6?

Among many of the improvements you can enjoy in MySQL 5.6, there is one that addresses a huge operational problem that most DBAs and System Administrators encounter in their life: schema changes. While it is usually not a problem for small tables or those in early stages of product life cycle, schema changes become a […]

Troubleshooting MySQL Memory Usage

One of the most painful troubleshooting tasks with MySQL is troubleshooting memory usage. The problem usually starts like this – you have configured MySQL to use reasonable global buffers, such as innodb_buffer_size, key_buffer_size etc, you have reasonable amount of connections but yet MySQL takes much more memory than you would expect, causing swapping or other […]

The case for getting rid of duplicate “sets”

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

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 […]

Estimating Replication Capacity

It is easy for MySQL replication to become bottleneck when Master server is not seriously loaded and the more cores and hard drives the get the larger the difference becomes, as long as replication remains single thread process. At the same time it is a lot easier to optimize your system when your replication runs […]

A workaround for the performance problems of TEMPTABLE views

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 […]

How fast is FLUSH TABLES WITH READ LOCK?

A week or so ago at the MySQL conference, I visited one of the backup vendors in the Expo Hall. I started to chat with them about their MySQL backup product. One of the representatives told me that their backup product uses FLUSH TABLES WITH READ LOCK, which he admitted takes a global lock on […]