April 16, 2014

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 […]

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 […]

Percona Toolkit 2.0.1 and 1.0.2 released

I’m happy to announce that we’ve released Percona Toolkit 2.0.1, a major new version of our essential DBA toolkit, as well as a minor bugfix update to the old 1.0.x series. You can download it from the project homepage, or install it through our RPM and DEB repositories. Documentation is online (and the 1.0 docs […]

Identifying the load with the help of pt-query-digest and Percona Server

Overview Profiling, analyzing and then fixing queries is likely the most oft-repeated part of a job of a DBA and one that keeps evolving, as new features are added to the application new queries pop up that need to be analyzed and fixed. And there are not too many tools out there that can make […]

Using any general purpose computer as a special purpose SIMD computer

Often times, from a computing perspective, one must run a function on a large amount of input. Often times, the same function must be run on many pieces of input, and this is a very expensive process unless the work can be done in parallel. Shard-Query introduces set based processing, which on the surface appears […]

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: […]

Shard-Query EC2 images available

Infobright and InnoDB AMI images are now available There are now demonstration AMI images for Shard-Query. Each image comes pre-loaded with the data used in the previous Shard-Query blog post. The data in the each image is split into 20 “shards”. This blog post will refer to an EC2 instances as a node from here […]

MySQL caching methods and tips

“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using less computing resources, particularly in the cloud, results in decreased overall operational costs, so caches provide real value by avoiding […]

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 […]

Modeling MySQL Capacity by Measuring Resource Consumptions

There are many angles you can look at the system to predict in performance, the model baron has published for example is good for measuring scalability of the system as concurrency growths. In many cases however we’re facing a need to answer a question how much load a given system can handle when load is […]