Have you wanted to compress only certain types of columns in a table while leaving other columns uncompressed? While working on a customer case this week I saw an interesting problem where a table had many heavily utilized TEXT fields with some read queries exceeding 500MB (!!), and stored in a 100GB table. In this [...]
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.
When we’re looking at benchmarks we typically run some stable workload and we run it in isolation – nothing else is happening on the system. This is not however how things happen in real world when we have significant variance in the load and many things can be happening concurrently. It is very typical to [...]
Last week I helped 2 different customers with infinite replication loops. I decided to write a blog post about these infinite loop of binary log statements in MySQL Replication. To explain what they are, how to identify them… and how to fix them.
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 [...]
For a long time I’ve wanted to know how MySQL scales as you add more memory to the server. Vadim recently benchmarked the effects of increasing memory and CPU core count. He looked for a balance between utilizing the hardware as much as possible, limiting the system complexity, and lowering the price-to-performance ratio. The outcome [...]
In my previous post I introduced materialized view concepts. This post begins with an introduction to change data capture technology and describes some of the ways in which it can be leveraged for your benefit. This is followed by a description of FlexCDC, the change data capture tool included with Flexviews. It continues with an [...]
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 [...]
Before I begin, a disclaimer. VoltDB is not a customer, and did not pay Percona or me to investigate VoltDB’s scalability or publish this blog post. More disclaimers at the end. Short version: VoltDB is very scalable; it should scale to 120 partitions, 39 servers, and 1.6 million complex transactions per second at over 300 [...]
Mat Keep’s blog post on InnoDB-vs-MyISAM benchmarks that Oracle recently published prompted me to do some mathematical modeling of InnoDB’s scalability as the number of cores in the server increases. Vadim runs lots of benchmarks that measure what happens under increasing concurrency while holding the hardware constant, but not as many with varying numbers of [...]