It is no secret that bugs related to multithreading–deadlocks, data races, starvations etc–have a big impact on application’s stability and are at the same time hard to find due to their nondeterministic nature. Any tool that makes finding such bugs easier, preferably before anybody is aware of their existence, is very welcome.
Helgrinding MySQL with InnoDB for Synchronisation Errors, Fun and Profit
November 24, 2011 By 2 Comments
The case for getting rid of duplicate “sets”
May 17, 2011 By 2 Comments
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 [...]
Using any general purpose computer as a special purpose SIMD computer
May 16, 2011 By 5 Comments
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
May 14, 2011 By 27 Comments
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
April 4, 2011 By 20 Comments
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
March 8, 2011 By 1 Comment
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 [...]
Moving from MyISAM to Innodb or XtraDB. Basics
November 22, 2010 By 2 Comments
I do not know if it is because we’re hosting a free webinar on migrating MyISAM to Innodb or some other reason but recently I see a lot of questions about migration from MyISAM to Innodb. Webinar will cover the process in a lot more details though I would like to go over basics in [...]
Shard-Query adds parallelism to queries
November 15, 2010 By 18 Comments
Preamble: On performance, workload and scalability: MySQL has always been focused on OLTP workloads. In fact, both Percona Server and MySQL 5.5.7rc have numerous performance improvements which benefit workloads that have high concurrency. Typical OLTP workloads feature numerous clients (perhaps hundreds or thousands) each reading and writing small chunks of data. The recent improvements to [...]
UDF -vs- MySQL Stored Function
September 6, 2010 By 8 Comments
Few days ago I was working on a case where we needed to modify a lot of data before pushing it to sphinx – MySQL did not have a function to do the thing so I thought I’ll write MySQL Stored Function and we’ll be good to go. It worked! But not so well really [...]
Estimating Replication Capacity
July 20, 2010 By 4 Comments
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 [...]
